diff --git a/.gitignore b/.gitignore index 815e97851..f0378dfc6 100644 --- a/.gitignore +++ b/.gitignore @@ -26,6 +26,7 @@ examples/python/**/*.xml docs/build docs/source/_images/*.pdf docs/source/_images/*.aux +docs/source/pythonapi/generated/ # Source build build diff --git a/.travis.yml b/.travis.yml index acec278ed..b99ce540b 100644 --- a/.travis.yml +++ b/.travis.yml @@ -27,7 +27,7 @@ before_install: - conda config --set always_yes yes --set changeps1 no - conda update -q conda - conda info -a - - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy h5py pandas + - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy h5py=2.5 pandas - source activate test-environment # Install GCC, MPICH, HDF5, PHDF5 diff --git a/docs/source/_templates/myclass.rst b/docs/source/_templates/myclass.rst new file mode 100644 index 000000000..a0560f93a --- /dev/null +++ b/docs/source/_templates/myclass.rst @@ -0,0 +1,7 @@ +{{ fullname }} +{{ underline }} + +.. currentmodule:: {{ module }} + +.. autoclass:: {{ objname }} + :members: diff --git a/docs/source/_templates/myclassinherit.rst b/docs/source/_templates/myclassinherit.rst new file mode 100644 index 000000000..ed93a2966 --- /dev/null +++ b/docs/source/_templates/myclassinherit.rst @@ -0,0 +1,8 @@ +{{ fullname }} +{{ underline }} + +.. currentmodule:: {{ module }} + +.. autoclass:: {{ objname }} + :members: + :inherited-members: diff --git a/docs/source/_templates/myfunction.rst b/docs/source/_templates/myfunction.rst new file mode 100644 index 000000000..4d7ea38a1 --- /dev/null +++ b/docs/source/_templates/myfunction.rst @@ -0,0 +1,6 @@ +{{ fullname }} +{{ underline }} + +.. currentmodule:: {{ module }} + +.. autofunction:: {{ objname }} diff --git a/docs/source/conf.py b/docs/source/conf.py index 6ca551a43..38661cdb3 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -24,13 +24,8 @@ except ImportError: from mock import Mock as MagicMock -class Mock(MagicMock): - @classmethod - def __getattr__(cls, name): - return Mock() - MOCK_MODULES = ['numpy', 'h5py', 'pandas', 'opencg'] -sys.modules.update((mod_name, Mock()) for mod_name in MOCK_MODULES) +sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES) # If extensions (or modules to document with autodoc) are in another directory, @@ -48,6 +43,8 @@ extensions = ['sphinx.ext.autodoc', 'sphinx.ext.napoleon', 'sphinx.ext.mathjax', 'sphinx.ext.autosummary', + 'sphinx.ext.intersphinx', + 'sphinx.ext.viewcode', 'sphinx_numfig', 'notebook_sphinxext'] @@ -65,7 +62,7 @@ master_doc = 'index' # General information about the project. project = u'OpenMC' -copyright = u'2011-2015, Massachusetts Institute of Technology' +copyright = u'2011-2016, Massachusetts Institute of Technology' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the @@ -122,20 +119,13 @@ pygments_style = 'tango' # -- Options for HTML output --------------------------------------------------- -# The theme to use for HTML and HTML Help pages. Major themes that come with -# Sphinx are currently 'default' and 'sphinxdoc'. -if on_rtd: - html_theme = 'default' - html_logo = '_images/openmc200px.png' -else: - html_theme = 'haiku' - html_theme_options = {'full_logo': True, - 'linkcolor': '#0c3762', - 'visitedlinkcolor': '#0c3762'} - html_logo = '_images/openmc.png' +# The theme to use for HTML and HTML Help pages +if not on_rtd: + import sphinx_rtd_theme + html_theme = 'sphinx_rtd_theme' + html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] -# Add any paths that contain custom themes here, relative to this directory. -#html_theme_path = ["_theme"] +html_logo = '_images/openmc200px.png' # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". @@ -248,4 +238,12 @@ latex_elements = { #Autodocumentation Flags #autodoc_member_order = "groupwise" #autoclass_content = "both" -#autosummary_generate = [] +autosummary_generate = True + +napoleon_use_ivar = True + +intersphinx_mapping = { + 'python': ('https://docs.python.org/3', None), + 'numpy': ('http://docs.scipy.org/doc/numpy/', None), + 'pandas': ('http://pandas.pydata.org/pandas-docs/stable/', None) +} diff --git a/docs/source/index.rst b/docs/source/index.rst index 54ba825e5..a79a10de1 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -13,11 +13,14 @@ OpenMC was originally developed by members of the `Computational Reactor Physics Group`_ at the `Massachusetts Institute of Technology`_ starting in 2011. Various universities, laboratories, and other organizations now contribute to the development of OpenMC. For more information on OpenMC, feel -free to send a message to the User's Group `mailing list`_. +free to send a message to the User's Group `mailing list`_. Documentation for +the latest developmental version of the develop branch can be found on +`Read the Docs`_. .. _Computational Reactor Physics Group: http://crpg.mit.edu .. _Massachusetts Institute of Technology: http://web.mit.edu .. _mailing list: https://groups.google.com/forum/?fromgroups=#!forum/openmc-users +.. _Read the Docs: http://openmc.readthedocs.io/en/latest/ .. only:: html diff --git a/docs/source/license.rst b/docs/source/license.rst index 73e329617..c51902d6f 100644 --- a/docs/source/license.rst +++ b/docs/source/license.rst @@ -4,7 +4,7 @@ License Agreement ================= -Copyright © 2011-2015 Massachusetts Institute of Technology +Copyright © 2011-2016 Massachusetts Institute of Technology Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in diff --git a/docs/source/methods/geometry.rst b/docs/source/methods/geometry.rst index f642cca10..bcd568ca3 100644 --- a/docs/source/methods/geometry.rst +++ b/docs/source/methods/geometry.rst @@ -437,6 +437,8 @@ where :math:`(x_0, y_0, z_0)` are the coordinates to the lower-left-bottom corner of the lattice, and :math:`p_0, p_1, p_2` are the pitches along the :math:`x`, :math:`y`, and :math:`z` axes, respectively. +.. _hexagonal_indexing: + Hexagonal Lattice Indexing -------------------------- diff --git a/docs/source/pythonapi/ace.rst b/docs/source/pythonapi/ace.rst deleted file mode 100644 index 4810ec4bb..000000000 --- a/docs/source/pythonapi/ace.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_ace: - -========== -ACE Format -========== - -.. automodule:: openmc.ace - :members: diff --git a/docs/source/pythonapi/cmfd.rst b/docs/source/pythonapi/cmfd.rst deleted file mode 100644 index 51470069f..000000000 --- a/docs/source/pythonapi/cmfd.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_cmfd: - -==== -CMFD -==== - -.. automodule:: openmc.cmfd - :members: diff --git a/docs/source/pythonapi/element.rst b/docs/source/pythonapi/element.rst deleted file mode 100644 index 473cbba45..000000000 --- a/docs/source/pythonapi/element.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_element: - -======= -Element -======= - -.. automodule:: openmc.element - :members: diff --git a/docs/source/pythonapi/energy_groups.rst b/docs/source/pythonapi/energy_groups.rst deleted file mode 100644 index 28ca6f3fe..000000000 --- a/docs/source/pythonapi/energy_groups.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_energy_groups: - -============= -Energy Groups -============= - -.. automodule:: openmc.mgxs.groups - :members: diff --git a/docs/source/pythonapi/examples/mgxs-part-i.ipynb b/docs/source/pythonapi/examples/mgxs-part-i.ipynb index 6b78e9d53..ea75bec72 100644 --- a/docs/source/pythonapi/examples/mgxs-part-i.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-i.ipynb @@ -141,15 +141,12 @@ }, "outputs": [], "source": [ + "%matplotlib inline\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "import openmc\n", - "import openmc.mgxs as mgxs\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", - "\n", - "%matplotlib inline" + "import openmc.mgxs as mgxs" ] }, { @@ -204,7 +201,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With our material, we can now create a `MaterialsFile` object that can be exported to an actual XML file." + "With our material, we can now create a `Materials` object that can be exported to an actual XML file." ] }, { @@ -215,10 +212,9 @@ }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, register all Materials, and export to XML\n", - "materials_file = openmc.MaterialsFile()\n", + "# Instantiate a Materials collection and export to XML\n", + "materials_file = openmc.Materials([inf_medium])\n", "materials_file.default_xs = '71c'\n", - "materials_file.add_material(inf_medium)\n", "materials_file.export_to_xml()" ] }, @@ -293,7 +289,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We now must create a geometry that is assigned a root universe, put the geometry into a `GeometryFile` object, and export it to XML." + "We now must create a geometry that is assigned a root universe and export it to XML." ] }, { @@ -308,12 +304,8 @@ "openmc_geometry = openmc.Geometry()\n", "openmc_geometry.root_universe = root_universe\n", "\n", - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = openmc_geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "openmc_geometry.export_to_xml()" ] }, { @@ -336,15 +328,17 @@ "inactive = 10\n", "particles = 2500\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "settings_file.output = {'tallies': True}\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", "bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", - "settings_file.source = Source(space=Box(\n", - " bounds[:3], bounds[3:], only_fissionable=True))\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Export to \"settings.xml\"\n", "settings_file.export_to_xml()" @@ -378,10 +372,12 @@ "\n", "* `TotalXS`\n", "* `TransportXS`\n", + "* `NuTransportXS`\n", "* `AbsorptionXS`\n", "* `CaptureXS`\n", "* `FissionXS`\n", "* `NuFissionXS`\n", + "* `KappaFissionXS`\n", "* `ScatterXS`\n", "* `NuScatterXS`\n", "* `ScatterMatrixXS`\n", @@ -400,9 +396,9 @@ "outputs": [], "source": [ "# Instantiate a few different sections\n", - "total = mgxs.TotalXS(domain=cell, domain_type='cell', groups=groups)\n", - "absorption = mgxs.AbsorptionXS(domain=cell, domain_type='cell', groups=groups)\n", - "scattering = mgxs.ScatterXS(domain=cell, domain_type='cell', groups=groups)" + "total = mgxs.TotalXS(domain=cell, groups=groups)\n", + "absorption = mgxs.AbsorptionXS(domain=cell, groups=groups)\n", + "scattering = mgxs.ScatterXS(domain=cell, groups=groups)" ] }, { @@ -423,22 +419,24 @@ "data": { "text/plain": [ "OrderedDict([('flux', Tally\n", - " \tID =\t10000\n", - " \tName =\t\n", - " \tFilters =\t\n", - " \t\tcell\t[1]\n", - " \t\tenergy\t[ 0.00000000e+00 6.25000000e-07 2.00000000e+01]\n", - " \tNuclides =\ttotal \n", - " \tScores =\t['flux']\n", - " \tEstimator =\ttracklength), ('absorption', Tally\n", - " \tID =\t10001\n", - " \tName =\t\n", - " \tFilters =\t\n", - " \t\tcell\t[1]\n", - " \t\tenergy\t[ 0.00000000e+00 6.25000000e-07 2.00000000e+01]\n", - " \tNuclides =\ttotal \n", - " \tScores =\t['absorption']\n", - " \tEstimator =\ttracklength)])" + "\tID =\t10000\n", + "\tName =\t\n", + "\tFilters =\t\n", + " \t\tcell\t[1]\n", + " \t\tenergy\t[ 0.00000000e+00 6.25000000e-07 2.00000000e+01]\n", + "\tNuclides =\ttotal \n", + "\tScores =\t['flux']\n", + "\tEstimator =\ttracklength\n", + "), ('absorption', Tally\n", + "\tID =\t10001\n", + "\tName =\t\n", + "\tFilters =\t\n", + " \t\tcell\t[1]\n", + " \t\tenergy\t[ 0.00000000e+00 6.25000000e-07 2.00000000e+01]\n", + "\tNuclides =\ttotal \n", + "\tScores =\t['absorption']\n", + "\tEstimator =\ttracklength\n", + ")])" ] }, "execution_count": 13, @@ -454,7 +452,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The `Absorption` object includes tracklength tallies for the 'absorption' and 'flux' scores in the 2-group structure in cell 1. Now that each `MGXS` object contains the tallies that it needs, we must add these tallies to a `TalliesFile` object to generate the \"tallies.xml\" input file for OpenMC." + "The `Absorption` object includes tracklength tallies for the 'absorption' and 'flux' scores in the 2-group structure in cell 1. Now that each `MGXS` object contains the tallies that it needs, we must add these tallies to a `Tallies` object to generate the \"tallies.xml\" input file for OpenMC." ] }, { @@ -465,21 +463,18 @@ }, "outputs": [], "source": [ - "# Instantiate an empty TalliesFile\n", - "tallies_file = openmc.TalliesFile()\n", + "# Instantiate an empty Tallies object\n", + "tallies_file = openmc.Tallies()\n", "\n", "# Add total tallies to the tallies file\n", - "for tally in total.tallies.values():\n", - " tallies_file.add_tally(tally)\n", + "tallies_file += total.tallies.values()\n", "\n", "# Add absorption tallies to the tallies file\n", - "for tally in absorption.tallies.values():\n", - " tallies_file.add_tally(tally)\n", + "tallies_file += absorption.tallies.values()\n", "\n", "# Add scattering tallies to the tallies file\n", - "for tally in scattering.tallies.values():\n", - " tallies_file.add_tally(tally)\n", - " \n", + "tallies_file += scattering.tallies.values()\n", + "\n", "# Export to \"tallies.xml\"\n", "tallies_file.export_to_xml()" ] @@ -515,11 +510,11 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: 34381b40a9445a727e360873aaa6ef892af1cb6a\n", - " Date/Time: 2016-02-07 15:58:16\n", + " Git SHA1: 19feb55e6d5e8350398627f39fb55ee8e2e63011\n", + " Date/Time: 2016-05-13 10:19:16\n", " MPI Processes: 1\n", "\n", " ===========================================================================\n", @@ -546,56 +541,56 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 1.19804 \n", - " 2/1 1.12945 \n", - " 3/1 1.15573 \n", - " 4/1 1.13929 \n", - " 5/1 1.16300 \n", - " 6/1 1.22117 \n", - " 7/1 1.19012 \n", - " 8/1 1.11299 \n", - " 9/1 1.16066 \n", - " 10/1 1.12566 \n", - " 11/1 1.20854 \n", - " 12/1 1.14691 1.17773 +/- 0.03082\n", - " 13/1 1.17204 1.17583 +/- 0.01789\n", - " 14/1 1.14148 1.16724 +/- 0.01529\n", - " 15/1 1.17272 1.16834 +/- 0.01189\n", - " 16/1 1.18575 1.17124 +/- 0.01014\n", - " 17/1 1.20498 1.17606 +/- 0.00983\n", - " 18/1 1.14754 1.17249 +/- 0.00923\n", - " 19/1 1.18141 1.17348 +/- 0.00820\n", - " 20/1 1.15074 1.17121 +/- 0.00768\n", - " 21/1 1.15914 1.17011 +/- 0.00703\n", - " 22/1 1.14586 1.16809 +/- 0.00673\n", - " 23/1 1.18999 1.16978 +/- 0.00642\n", - " 24/1 1.15101 1.16844 +/- 0.00609\n", - " 25/1 1.13791 1.16640 +/- 0.00602\n", - " 26/1 1.19791 1.16837 +/- 0.00597\n", - " 27/1 1.19818 1.17012 +/- 0.00587\n", - " 28/1 1.14160 1.16854 +/- 0.00576\n", - " 29/1 1.11487 1.16571 +/- 0.00614\n", - " 30/1 1.17538 1.16620 +/- 0.00584\n", - " 31/1 1.20210 1.16791 +/- 0.00581\n", - " 32/1 1.20078 1.16940 +/- 0.00574\n", - " 33/1 1.14624 1.16839 +/- 0.00558\n", - " 34/1 1.14618 1.16747 +/- 0.00542\n", - " 35/1 1.16866 1.16752 +/- 0.00520\n", - " 36/1 1.18565 1.16821 +/- 0.00504\n", - " 37/1 1.16824 1.16821 +/- 0.00485\n", - " 38/1 1.18299 1.16874 +/- 0.00471\n", - " 39/1 1.21418 1.17031 +/- 0.00480\n", - " 40/1 1.11167 1.16835 +/- 0.00504\n", - " 41/1 1.11545 1.16665 +/- 0.00516\n", - " 42/1 1.11114 1.16491 +/- 0.00529\n", - " 43/1 1.14227 1.16423 +/- 0.00517\n", - " 44/1 1.14104 1.16355 +/- 0.00506\n", - " 45/1 1.16756 1.16366 +/- 0.00492\n", - " 46/1 1.13065 1.16274 +/- 0.00487\n", - " 47/1 1.11251 1.16139 +/- 0.00492\n", - " 48/1 1.14731 1.16101 +/- 0.00481\n", - " 49/1 1.16691 1.16117 +/- 0.00469\n", - " 50/1 1.19679 1.16206 +/- 0.00465\n", + " 1/1 1.11184 \n", + " 2/1 1.15820 \n", + " 3/1 1.18468 \n", + " 4/1 1.17492 \n", + " 5/1 1.19645 \n", + " 6/1 1.18436 \n", + " 7/1 1.14070 \n", + " 8/1 1.15150 \n", + " 9/1 1.19202 \n", + " 10/1 1.17677 \n", + " 11/1 1.20272 \n", + " 12/1 1.21366 1.20819 +/- 0.00547\n", + " 13/1 1.15906 1.19181 +/- 0.01668\n", + " 14/1 1.14687 1.18058 +/- 0.01629\n", + " 15/1 1.14570 1.17360 +/- 0.01442\n", + " 16/1 1.13480 1.16713 +/- 0.01343\n", + " 17/1 1.17680 1.16852 +/- 0.01144\n", + " 18/1 1.16866 1.16853 +/- 0.00990\n", + " 19/1 1.19253 1.17120 +/- 0.00913\n", + " 20/1 1.18124 1.17220 +/- 0.00823\n", + " 21/1 1.19206 1.17401 +/- 0.00766\n", + " 22/1 1.17681 1.17424 +/- 0.00700\n", + " 23/1 1.17634 1.17440 +/- 0.00644\n", + " 24/1 1.13659 1.17170 +/- 0.00654\n", + " 25/1 1.17144 1.17169 +/- 0.00609\n", + " 26/1 1.20649 1.17386 +/- 0.00610\n", + " 27/1 1.11238 1.17024 +/- 0.00678\n", + " 28/1 1.18911 1.17129 +/- 0.00647\n", + " 29/1 1.14681 1.17000 +/- 0.00626\n", + " 30/1 1.12152 1.16758 +/- 0.00641\n", + " 31/1 1.12729 1.16566 +/- 0.00639\n", + " 32/1 1.15399 1.16513 +/- 0.00612\n", + " 33/1 1.13547 1.16384 +/- 0.00599\n", + " 34/1 1.17723 1.16440 +/- 0.00576\n", + " 35/1 1.09296 1.16154 +/- 0.00622\n", + " 36/1 1.19621 1.16287 +/- 0.00612\n", + " 37/1 1.12560 1.16149 +/- 0.00605\n", + " 38/1 1.17872 1.16211 +/- 0.00586\n", + " 39/1 1.17721 1.16263 +/- 0.00568\n", + " 40/1 1.13724 1.16178 +/- 0.00555\n", + " 41/1 1.18526 1.16254 +/- 0.00542\n", + " 42/1 1.13779 1.16177 +/- 0.00531\n", + " 43/1 1.15066 1.16143 +/- 0.00516\n", + " 44/1 1.12174 1.16026 +/- 0.00514\n", + " 45/1 1.17479 1.16068 +/- 0.00501\n", + " 46/1 1.14146 1.16014 +/- 0.00489\n", + " 47/1 1.20464 1.16135 +/- 0.00491\n", + " 48/1 1.15119 1.16108 +/- 0.00479\n", + " 49/1 1.17938 1.16155 +/- 0.00468\n", + " 50/1 1.15798 1.16146 +/- 0.00457\n", " Creating state point statepoint.50.h5...\n", "\n", " ===========================================================================\n", @@ -605,27 +600,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.2100E-01 seconds\n", - " Reading cross sections = 7.4000E-02 seconds\n", - " Total time in simulation = 8.3830E+00 seconds\n", - " Time in transport only = 8.3670E+00 seconds\n", - " Time in inactive batches = 1.0330E+00 seconds\n", - " Time in active batches = 7.3500E+00 seconds\n", - " Time synchronizing fission bank = 4.0000E-03 seconds\n", - " Sampling source sites = 1.0000E-03 seconds\n", - " SEND/RECV source sites = 3.0000E-03 seconds\n", + " Total time for initialization = 4.2300E-01 seconds\n", + " Reading cross sections = 9.3000E-02 seconds\n", + " Total time in simulation = 1.6549E+01 seconds\n", + " Time in transport only = 1.6535E+01 seconds\n", + " Time in inactive batches = 2.3650E+00 seconds\n", + " Time in active batches = 1.4184E+01 seconds\n", + " Time synchronizing fission bank = 5.0000E-03 seconds\n", + " Sampling source sites = 3.0000E-03 seconds\n", + " SEND/RECV source sites = 0.0000E+00 seconds\n", " Time accumulating tallies = 0.0000E+00 seconds\n", - " Total time for finalization = 1.0000E-03 seconds\n", - " Total time elapsed = 8.7140E+00 seconds\n", - " Calculation Rate (inactive) = 24201.4 neutrons/second\n", - " Calculation Rate (active) = 13605.4 neutrons/second\n", + " Total time for finalization = 0.0000E+00 seconds\n", + " Total time elapsed = 1.6981E+01 seconds\n", + " Calculation Rate (inactive) = 10570.8 neutrons/second\n", + " Calculation Rate (active) = 7050.20 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.16131 +/- 0.00453\n", - " k-effective (Track-length) = 1.16206 +/- 0.00465\n", - " k-effective (Absorption) = 1.16096 +/- 0.00364\n", - " Combined k-effective = 1.16120 +/- 0.00325\n", + " k-effective (Collision) = 1.15984 +/- 0.00411\n", + " k-effective (Track-length) = 1.16146 +/- 0.00457\n", + " k-effective (Absorption) = 1.16177 +/- 0.00380\n", + " Combined k-effective = 1.16105 +/- 0.00364\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -643,8 +638,7 @@ ], "source": [ "# Run OpenMC\n", - "executor = openmc.Executor()\n", - "executor.run_simulation()" + "openmc.run()" ] }, { @@ -677,20 +671,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. This is necessary for the `openmc.mgxs` module to properly process the tally data. We first create a `Summary` object and link it with the statepoint." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "# Load the summary file and link it with the statepoint\n", - "su = openmc.Summary('summary.h5')\n", - "sp.link_with_summary(su)" + "In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. By default, a `Summary` object is automatically linked when a `StatePoint` is loaded. This is necessary for the `openmc.mgxs` module to properly process the tally data." ] }, { @@ -702,7 +683,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -737,7 +718,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -751,8 +732,8 @@ "\tDomain Type =\tcell\n", "\tDomain ID =\t1\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t6.81e-01 +/- 1.88e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t1.40e+00 +/- 5.91e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t6.81e-01 +/- 2.69e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t1.40e+00 +/- 5.93e-01%\n", "\n", "\n", "\n" @@ -772,7 +753,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -780,7 +761,7 @@ { "data": { "text/html": [ - "
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\n", @@ -1166,11 +1147,11 @@ "1 1 6.25e-07 2.00e+01 total \n", "\n", " score mean std. dev. \n", - "0 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 7.74e-03 \n", - "1 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 2.62e-03 " + "0 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 7.76e-03 \n", + "1 (((absorption / flux) / (total / flux)) + ((sc... 1.00e+00 3.74e-03 " ] }, - "execution_count": 26, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1200,7 +1181,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", - "version": "2.7.10" + "version": "2.7.6" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb index 0a8d7230e..b882e949c 100644 --- a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb @@ -13,7 +13,7 @@ "* The use of **[PyNE](http://pyne.io/) to plot** continuous-energy vs. multi-group cross sections\n", "* **Validation** of multi-group cross sections with **[OpenMOC](https://mit-crpg.github.io/OpenMOC/)**\n", "\n", - "**Note:** This Notebook was created using [OpenMOC](https://mit-crpg.github.io/OpenMOC/) to verify the multi-group cross-sections generated by OpenMC. In order to run this Notebook in its entirety, you must have [OpenMOC](https://mit-crpg.github.io/OpenMOC/) installed on your system, along with OpenCG to convert the OpenMC geometries into OpenMOC geometries. In addition, this Notebook illustrates the use of [Pandas](http://pandas.pydata.org/) `DataFrames` to containerize multi-group cross section data. We recommend using [Pandas](http://pandas.pydata.org/) >v0.15.0 or later since OpenMC's Python API leverages the multi-indexing feature included in the most recent releases of [Pandas](http://pandas.pydata.org/)." + "**Note:** This Notebook was created using [OpenMOC](https://mit-crpg.github.io/OpenMOC/) to verify the multi-group cross-sections generated by OpenMC. In order to run this Notebook in its entirety, you must have [OpenMOC](https://mit-crpg.github.io/OpenMOC/) installed on your system, along with OpenCG to convert the OpenMC geometries into OpenMOC geometries. In addition, this Notebook illustrates the use of [Pandas](http://pandas.pydata.org/) `DataFrames` to containerize multi-group cross section data." ] }, { @@ -34,14 +34,16 @@ "name": "stderr", "output_type": "stream", "text": [ - "/usr/lib/pymodules/python2.7/matplotlib/__init__.py:1173: UserWarning: This call to matplotlib.use() has no effect\n", + "/usr/local/lib/python2.7/dist-packages/matplotlib-1.5.1+1178.ga40c9ec-py2.7-linux-x86_64.egg/matplotlib/__init__.py:884: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n", + " warnings.warn(self.msg_depr % (key, alt_key))\n", + "/usr/local/lib/python2.7/dist-packages/matplotlib-1.5.1+1178.ga40c9ec-py2.7-linux-x86_64.egg/matplotlib/__init__.py:1362: UserWarning: This call to matplotlib.use() has no effect\n", "because the backend has already been chosen;\n", "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", "or matplotlib.backends is imported for the first time.\n", "\n", " warnings.warn(_use_error_msg)\n", - "/usr/local/lib/python2.7/dist-packages/IPython/kernel/__main__.py:11: QAWarning: pyne.rxname is not yet QA compliant.\n", - "/usr/local/lib/python2.7/dist-packages/IPython/kernel/__main__.py:11: QAWarning: pyne.ace is not yet QA compliant.\n" + "/usr/local/lib/python2.7/dist-packages/IPython/kernel/__main__.py:9: QAWarning: pyne.rxname is not yet QA compliant.\n", + "/usr/local/lib/python2.7/dist-packages/IPython/kernel/__main__.py:9: QAWarning: pyne.ace is not yet QA compliant.\n" ] } ], @@ -52,10 +54,8 @@ "\n", "import openmc\n", "import openmc.mgxs as mgxs\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", "import openmoc\n", - "from openmoc.compatible import get_openmoc_geometry\n", + "from openmoc.opencg_compatible import get_openmoc_geometry\n", "import pyne.ace\n", "\n", "%matplotlib inline" @@ -122,7 +122,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With our materials, we can now create a `MaterialsFile` object that can be exported to an actual XML file." + "With our materials, we can now create a `Materials` object that can be exported to an actual XML file." ] }, { @@ -133,11 +133,8 @@ }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, add Materials\n", - "materials_file = openmc.MaterialsFile()\n", - "materials_file.add_material(fuel)\n", - "materials_file.add_material(water)\n", - "materials_file.add_material(zircaloy)\n", + "# Instantiate a Materials collection\n", + "materials_file = openmc.Materials((fuel, water, zircaloy))\n", "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", @@ -238,7 +235,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We now must create a geometry that is assigned a root universe, put the geometry into a `GeometryFile` object, and export it to XML." + "We now must create a geometry that is assigned a root universe and export it to XML." ] }, { @@ -253,12 +250,8 @@ "openmc_geometry = openmc.Geometry()\n", "openmc_geometry.root_universe = root_universe\n", "\n", - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = openmc_geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "openmc_geometry.export_to_xml()" ] }, { @@ -281,15 +274,17 @@ "inactive = 10\n", "particles = 10000\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "settings_file.output = {'tallies': True}\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", "bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", - "settings_file.source = Source(space=Box(\n", - " bounds[:3], bounds[3:], only_fissionable=True))\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Activate tally precision triggers\n", "settings_file.trigger_active = True\n", @@ -394,23 +389,22 @@ }, "outputs": [], "source": [ - "# Instantiate an empty TalliesFile\n", - "tallies_file = openmc.TalliesFile()\n", + "# Instantiate an empty Tallies object\n", + "tallies_file = openmc.Tallies()\n", "\n", "# Iterate over all cells and cross section types\n", "for cell in openmc_cells:\n", " for rxn_type in xs_library[cell.id]:\n", "\n", - " # Set the cross sections domain type to the cell\n", + " # Set the cross sections domain to the cell\n", " xs_library[cell.id][rxn_type].domain = cell\n", - " xs_library[cell.id][rxn_type].domain_type = 'cell'\n", " \n", " # Tally cross sections by nuclide\n", " xs_library[cell.id][rxn_type].by_nuclide = True\n", " \n", " # Add OpenMC tallies to the tallies file for XML generation\n", " for tally in xs_library[cell.id][rxn_type].tallies.values():\n", - " tallies_file.add_tally(tally, merge=True)\n", + " tallies_file.append(tally, merge=True)\n", "\n", "# Export to \"tallies.xml\"\n", "tallies_file.export_to_xml()" @@ -447,11 +441,11 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: 263266f4f8807fd38c6ac282fae259ae73fa1eee\n", - " Date/Time: 2016-01-20 18:12:40\n", + " Git SHA1: 19feb55e6d5e8350398627f39fb55ee8e2e63011\n", + " Date/Time: 2016-05-13 10:13:48\n", " MPI Processes: 1\n", "\n", " ===========================================================================\n", @@ -478,91 +472,87 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 1.22593 \n", - " 2/1 1.24245 \n", - " 3/1 1.24545 \n", - " 4/1 1.21868 \n", - " 5/1 1.22429 \n", - " 6/1 1.22607 \n", - " 7/1 1.21456 \n", - " 8/1 1.23816 \n", - " 9/1 1.25060 \n", - " 10/1 1.22806 \n", - " 11/1 1.19821 \n", - " 12/1 1.19897 1.19859 +/- 0.00038\n", - " 13/1 1.22119 1.20612 +/- 0.00754\n", - " 14/1 1.20701 1.20634 +/- 0.00533\n", - " 15/1 1.24784 1.21464 +/- 0.00927\n", - " 16/1 1.22413 1.21622 +/- 0.00773\n", - " 17/1 1.25050 1.22112 +/- 0.00817\n", - " 18/1 1.22006 1.22099 +/- 0.00707\n", - " 19/1 1.22813 1.22178 +/- 0.00629\n", - " 20/1 1.22791 1.22239 +/- 0.00566\n", - " 21/1 1.22729 1.22284 +/- 0.00514\n", - " 22/1 1.19867 1.22083 +/- 0.00510\n", - " 23/1 1.23796 1.22214 +/- 0.00488\n", - " 24/1 1.22412 1.22228 +/- 0.00452\n", - " 25/1 1.22638 1.22256 +/- 0.00421\n", - " 26/1 1.22181 1.22251 +/- 0.00394\n", - " 27/1 1.19055 1.22063 +/- 0.00415\n", - " 28/1 1.20683 1.21986 +/- 0.00399\n", - " 29/1 1.21689 1.21971 +/- 0.00378\n", - " 30/1 1.23670 1.22056 +/- 0.00368\n", - " 31/1 1.21396 1.22024 +/- 0.00352\n", - " 32/1 1.21389 1.21995 +/- 0.00337\n", - " 33/1 1.24649 1.22111 +/- 0.00342\n", - " 34/1 1.23204 1.22156 +/- 0.00330\n", - " 35/1 1.20768 1.22101 +/- 0.00322\n", - " 36/1 1.22271 1.22107 +/- 0.00309\n", - " 37/1 1.21796 1.22096 +/- 0.00298\n", - " 38/1 1.23842 1.22158 +/- 0.00293\n", - " 39/1 1.23080 1.22190 +/- 0.00285\n", - " 40/1 1.23572 1.22236 +/- 0.00279\n", - " 41/1 1.21691 1.22218 +/- 0.00271\n", - " 42/1 1.24616 1.22293 +/- 0.00272\n", - " 43/1 1.21903 1.22282 +/- 0.00264\n", - " 44/1 1.22967 1.22302 +/- 0.00257\n", - " 45/1 1.22053 1.22295 +/- 0.00250\n", - " 46/1 1.24087 1.22344 +/- 0.00248\n", - " 47/1 1.20251 1.22288 +/- 0.00248\n", - " 48/1 1.20331 1.22236 +/- 0.00246\n", - " 49/1 1.22724 1.22249 +/- 0.00240\n", - " 50/1 1.24798 1.22313 +/- 0.00243\n", - " Triggers unsatisfied, max unc./thresh. is 1.32110 for scatter-p1 in tally 10054\n", - " The estimated number of batches is 80\n", + " 1/1 1.20332 \n", + " 2/1 1.22209 \n", + " 3/1 1.24309 \n", + " 4/1 1.22833 \n", + " 5/1 1.21786 \n", + " 6/1 1.22005 \n", + " 7/1 1.20894 \n", + " 8/1 1.22071 \n", + " 9/1 1.21279 \n", + " 10/1 1.22198 \n", + " 11/1 1.22287 \n", + " 12/1 1.25490 1.23888 +/- 0.01602\n", + " 13/1 1.20224 1.22667 +/- 0.01532\n", + " 14/1 1.23375 1.22844 +/- 0.01098\n", + " 15/1 1.23068 1.22889 +/- 0.00851\n", + " 16/1 1.23073 1.22920 +/- 0.00696\n", + " 17/1 1.25364 1.23269 +/- 0.00684\n", + " 18/1 1.20820 1.22963 +/- 0.00667\n", + " 19/1 1.23138 1.22982 +/- 0.00588\n", + " 20/1 1.20682 1.22752 +/- 0.00574\n", + " 21/1 1.23580 1.22827 +/- 0.00525\n", + " 22/1 1.24190 1.22941 +/- 0.00492\n", + " 23/1 1.23125 1.22955 +/- 0.00453\n", + " 24/1 1.21606 1.22859 +/- 0.00430\n", + " 25/1 1.23653 1.22912 +/- 0.00404\n", + " 26/1 1.23850 1.22970 +/- 0.00383\n", + " 27/1 1.20986 1.22853 +/- 0.00378\n", + " 28/1 1.25277 1.22988 +/- 0.00381\n", + " 29/1 1.23334 1.23006 +/- 0.00361\n", + " 30/1 1.24345 1.23073 +/- 0.00349\n", + " 31/1 1.21565 1.23001 +/- 0.00339\n", + " 32/1 1.20555 1.22890 +/- 0.00342\n", + " 33/1 1.22995 1.22895 +/- 0.00327\n", + " 34/1 1.19763 1.22764 +/- 0.00339\n", + " 35/1 1.22645 1.22760 +/- 0.00325\n", + " 36/1 1.23900 1.22803 +/- 0.00316\n", + " 37/1 1.24305 1.22859 +/- 0.00309\n", + " 38/1 1.22484 1.22846 +/- 0.00298\n", + " 39/1 1.20986 1.22782 +/- 0.00294\n", + " 40/1 1.23764 1.22814 +/- 0.00286\n", + " 41/1 1.20476 1.22739 +/- 0.00287\n", + " 42/1 1.21652 1.22705 +/- 0.00280\n", + " 43/1 1.21279 1.22662 +/- 0.00275\n", + " 44/1 1.20210 1.22590 +/- 0.00276\n", + " 45/1 1.22644 1.22591 +/- 0.00268\n", + " 46/1 1.22907 1.22600 +/- 0.00261\n", + " 47/1 1.24057 1.22639 +/- 0.00257\n", + " 48/1 1.21610 1.22612 +/- 0.00251\n", + " 49/1 1.22199 1.22602 +/- 0.00245\n", + " 50/1 1.20860 1.22558 +/- 0.00243\n", + " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10051\n", + " The estimated number of batches is 73\n", " Creating state point statepoint.050.h5...\n", - " 51/1 1.22253 1.22311 +/- 0.00237\n", - " 52/1 1.24330 1.22359 +/- 0.00236\n", - " 53/1 1.23251 1.22380 +/- 0.00231\n", - " 54/1 1.21133 1.22352 +/- 0.00228\n", - " 55/1 1.24503 1.22399 +/- 0.00228\n", - " 56/1 1.22013 1.22391 +/- 0.00223\n", - " 57/1 1.23877 1.22423 +/- 0.00220\n", - " 58/1 1.23793 1.22451 +/- 0.00218\n", - " 59/1 1.21018 1.22422 +/- 0.00215\n", - " 60/1 1.22417 1.22422 +/- 0.00211\n", - " 61/1 1.23094 1.22435 +/- 0.00207\n", - " 62/1 1.23310 1.22452 +/- 0.00204\n", - " 63/1 1.22488 1.22453 +/- 0.00200\n", - " 64/1 1.22702 1.22457 +/- 0.00196\n", - " 65/1 1.18834 1.22391 +/- 0.00204\n", - " 66/1 1.23112 1.22404 +/- 0.00200\n", - " 67/1 1.21611 1.22390 +/- 0.00197\n", - " 68/1 1.22513 1.22392 +/- 0.00194\n", - " 69/1 1.21741 1.22381 +/- 0.00191\n", - " 70/1 1.22484 1.22383 +/- 0.00188\n", - " 71/1 1.19662 1.22338 +/- 0.00190\n", - " 72/1 1.23315 1.22354 +/- 0.00187\n", - " 73/1 1.22796 1.22361 +/- 0.00185\n", - " 74/1 1.21417 1.22346 +/- 0.00182\n", - " 75/1 1.21020 1.22326 +/- 0.00181\n", - " 76/1 1.23413 1.22343 +/- 0.00179\n", - " 77/1 1.22184 1.22340 +/- 0.00176\n", - " 78/1 1.20309 1.22310 +/- 0.00176\n", - " 79/1 1.23458 1.22327 +/- 0.00174\n", - " 80/1 1.20724 1.22304 +/- 0.00173\n", - " Triggers satisfied for batch 80\n", - " Creating state point statepoint.080.h5...\n", + " 51/1 1.21850 1.22541 +/- 0.00237\n", + " 52/1 1.22833 1.22548 +/- 0.00232\n", + " 53/1 1.20239 1.22494 +/- 0.00233\n", + " 54/1 1.24876 1.22548 +/- 0.00234\n", + " 55/1 1.20670 1.22506 +/- 0.00232\n", + " 56/1 1.24260 1.22545 +/- 0.00230\n", + " 57/1 1.21039 1.22512 +/- 0.00228\n", + " 58/1 1.23929 1.22542 +/- 0.00225\n", + " 59/1 1.21357 1.22518 +/- 0.00221\n", + " 60/1 1.23456 1.22537 +/- 0.00218\n", + " 61/1 1.23963 1.22565 +/- 0.00215\n", + " 62/1 1.24020 1.22593 +/- 0.00213\n", + " 63/1 1.22325 1.22587 +/- 0.00209\n", + " 64/1 1.22070 1.22578 +/- 0.00205\n", + " 65/1 1.22423 1.22575 +/- 0.00201\n", + " 66/1 1.22973 1.22582 +/- 0.00198\n", + " 67/1 1.21842 1.22569 +/- 0.00195\n", + " 68/1 1.19552 1.22517 +/- 0.00198\n", + " 69/1 1.21475 1.22500 +/- 0.00196\n", + " 70/1 1.21888 1.22489 +/- 0.00193\n", + " 71/1 1.19720 1.22444 +/- 0.00195\n", + " 72/1 1.23770 1.22465 +/- 0.00193\n", + " 73/1 1.23894 1.22488 +/- 0.00191\n", + " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10051\n", + " The estimated number of batches is 74\n", + " 74/1 1.22437 1.22487 +/- 0.00188\n", + " Triggers satisfied for batch 74\n", + " Creating state point statepoint.074.h5...\n", "\n", " ===========================================================================\n", " ======================> SIMULATION FINISHED <======================\n", @@ -571,27 +561,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.3200E-01 seconds\n", - " Reading cross sections = 9.1000E-02 seconds\n", - " Total time in simulation = 2.2239E+02 seconds\n", - " Time in transport only = 2.2234E+02 seconds\n", - " Time in inactive batches = 1.3715E+01 seconds\n", - " Time in active batches = 2.0867E+02 seconds\n", - " Time synchronizing fission bank = 2.3000E-02 seconds\n", - " Sampling source sites = 1.7000E-02 seconds\n", - " SEND/RECV source sites = 6.0000E-03 seconds\n", - " Time accumulating tallies = 2.0000E-03 seconds\n", - " Total time for finalization = 9.0000E-03 seconds\n", - " Total time elapsed = 2.2288E+02 seconds\n", - " Calculation Rate (inactive) = 7291.29 neutrons/second\n", - " Calculation Rate (active) = 1916.88 neutrons/second\n", + " Total time for initialization = 5.7400E-01 seconds\n", + " Reading cross sections = 1.2600E-01 seconds\n", + " Total time in simulation = 2.6256E+02 seconds\n", + " Time in transport only = 2.6250E+02 seconds\n", + " Time in inactive batches = 2.2890E+01 seconds\n", + " Time in active batches = 2.3967E+02 seconds\n", + " Time synchronizing fission bank = 3.4000E-02 seconds\n", + " Sampling source sites = 2.1000E-02 seconds\n", + " SEND/RECV source sites = 1.3000E-02 seconds\n", + " Time accumulating tallies = 0.0000E+00 seconds\n", + " Total time for finalization = 1.3000E-02 seconds\n", + " Total time elapsed = 2.6320E+02 seconds\n", + " Calculation Rate (inactive) = 4368.72 neutrons/second\n", + " Calculation Rate (active) = 1668.93 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.22327 +/- 0.00148\n", - " k-effective (Track-length) = 1.22304 +/- 0.00173\n", - " k-effective (Absorption) = 1.22407 +/- 0.00129\n", - " Combined k-effective = 1.22373 +/- 0.00113\n", + " k-effective (Collision) = 1.22358 +/- 0.00179\n", + " k-effective (Track-length) = 1.22487 +/- 0.00188\n", + " k-effective (Absorption) = 1.22300 +/- 0.00114\n", + " Combined k-effective = 1.22347 +/- 0.00106\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -609,8 +599,7 @@ ], "source": [ "# Run OpenMC\n", - "executor = openmc.Executor()\n", - "executor.run_simulation(output=True)" + "openmc.run(output=True)" ] }, { @@ -636,27 +625,7 @@ "outputs": [], "source": [ "# Load the last statepoint file\n", - "sp = openmc.StatePoint('statepoint.080.h5')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. This is necessary for the `openmc.mgxs` module to properly process the tally data. We first create a `Summary` object and link it with the statepoint." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Load the summary file and link it with the statepoint\n", - "su = openmc.Summary('summary.h5')\n", - "sp.link_with_summary(su)" + "sp = openmc.StatePoint('statepoint.074.h5')" ] }, { @@ -668,7 +637,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -703,7 +672,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -718,25 +687,25 @@ "\tDomain ID =\t10000\n", "\tNuclide =\tU-235\n", "\tCross Sections [barns]:\n", - " Group 1 [0.821 - 20.0 MeV]:\t3.31e+00 +/- 1.88e-01%\n", - " Group 2 [0.00553 - 0.821 MeV]:\t3.97e+00 +/- 1.24e-01%\n", - " Group 3 [4e-06 - 0.00553 MeV]:\t5.50e+01 +/- 2.02e-01%\n", - " Group 4 [6.25e-07 - 4e-06 MeV]:\t8.83e+01 +/- 3.56e-01%\n", - " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t2.90e+02 +/- 4.54e-01%\n", - " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t4.49e+02 +/- 4.10e-01%\n", - " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t6.87e+02 +/- 2.56e-01%\n", - " Group 8 [0.0 - 5.8e-08 MeV]:\t1.44e+03 +/- 2.82e-01%\n", + " Group 1 [0.821 - 20.0 MeV]:\t3.30e+00 +/- 2.19e-01%\n", + " Group 2 [0.00553 - 0.821 MeV]:\t3.96e+00 +/- 1.32e-01%\n", + " Group 3 [4e-06 - 0.00553 MeV]:\t5.52e+01 +/- 2.31e-01%\n", + " Group 4 [6.25e-07 - 4e-06 MeV]:\t8.83e+01 +/- 2.96e-01%\n", + " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t2.90e+02 +/- 4.64e-01%\n", + " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t4.49e+02 +/- 4.22e-01%\n", + " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t6.87e+02 +/- 2.97e-01%\n", + " Group 8 [0.0 - 5.8e-08 MeV]:\t1.44e+03 +/- 2.91e-01%\n", "\n", "\tNuclide =\tU-238\n", "\tCross Sections [barns]:\n", - " Group 1 [0.821 - 20.0 MeV]:\t1.06e+00 +/- 2.30e-01%\n", - " Group 2 [0.00553 - 0.821 MeV]:\t1.21e-03 +/- 2.25e-01%\n", - " Group 3 [4e-06 - 0.00553 MeV]:\t5.82e-04 +/- 3.09e+00%\n", - " Group 4 [6.25e-07 - 4e-06 MeV]:\t6.54e-06 +/- 3.27e-01%\n", - " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t1.07e-05 +/- 4.39e-01%\n", - " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t1.55e-05 +/- 4.12e-01%\n", - " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t2.30e-05 +/- 2.57e-01%\n", - " Group 8 [0.0 - 5.8e-08 MeV]:\t4.24e-05 +/- 2.81e-01%\n", + " Group 1 [0.821 - 20.0 MeV]:\t1.06e+00 +/- 2.56e-01%\n", + " Group 2 [0.00553 - 0.821 MeV]:\t1.21e-03 +/- 2.55e-01%\n", + " Group 3 [4e-06 - 0.00553 MeV]:\t5.77e-04 +/- 3.67e+00%\n", + " Group 4 [6.25e-07 - 4e-06 MeV]:\t6.54e-06 +/- 2.74e-01%\n", + " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t1.07e-05 +/- 4.55e-01%\n", + " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t1.55e-05 +/- 4.25e-01%\n", + " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t2.30e-05 +/- 2.97e-01%\n", + " Group 8 [0.0 - 5.8e-08 MeV]:\t4.24e-05 +/- 2.90e-01%\n", "\n", "\n", "\n" @@ -757,7 +726,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -771,14 +740,14 @@ "\tDomain Type =\tcell\n", "\tDomain ID =\t10000\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [0.821 - 20.0 MeV]:\t2.52e-02 +/- 2.19e-01%\n", - " Group 2 [0.00553 - 0.821 MeV]:\t1.51e-03 +/- 1.22e-01%\n", - " Group 3 [4e-06 - 0.00553 MeV]:\t2.06e-02 +/- 2.02e-01%\n", - " Group 4 [6.25e-07 - 4e-06 MeV]:\t3.31e-02 +/- 3.56e-01%\n", - " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t1.09e-01 +/- 4.54e-01%\n", - " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t1.69e-01 +/- 4.10e-01%\n", - " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t2.58e-01 +/- 2.56e-01%\n", - " Group 8 [0.0 - 5.8e-08 MeV]:\t5.40e-01 +/- 2.82e-01%\n", + " Group 1 [0.821 - 20.0 MeV]:\t2.52e-02 +/- 2.44e-01%\n", + " Group 2 [0.00553 - 0.821 MeV]:\t1.51e-03 +/- 1.30e-01%\n", + " Group 3 [4e-06 - 0.00553 MeV]:\t2.07e-02 +/- 2.31e-01%\n", + " Group 4 [6.25e-07 - 4e-06 MeV]:\t3.31e-02 +/- 2.96e-01%\n", + " Group 5 [2.8e-07 - 6.25e-07 MeV]:\t1.09e-01 +/- 4.64e-01%\n", + " Group 6 [1.4e-07 - 2.8e-07 MeV]:\t1.69e-01 +/- 4.22e-01%\n", + " Group 7 [5.8e-08 - 1.4e-07 MeV]:\t2.58e-01 +/- 2.97e-01%\n", + " Group 8 [0.0 - 5.8e-08 MeV]:\t5.40e-01 +/- 2.91e-01%\n", "\n", "\n", "\n" @@ -799,22 +768,11 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n", - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n", - "/usr/local/lib/python2.7/dist-packages/openmc-0.7.1-py2.7.egg/openmc/mgxs/mgxs.py:1303: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n" - ] - }, { "data": { "text/html": [ @@ -838,8 +796,8 @@ " 1\n", " 1\n", " H-1\n", - " 0.234022\n", - " 0.003645\n", + " 0.234115\n", + " 0.003568\n", " \n", " \n", " 127\n", @@ -847,8 +805,8 @@ " 1\n", " 1\n", " O-16\n", - " 1.560305\n", - " 0.006280\n", + " 1.563707\n", + " 0.005953\n", " \n", " \n", " 124\n", @@ -856,8 +814,8 @@ " 1\n", " 2\n", " H-1\n", - " 1.588025\n", - " 0.002815\n", + " 1.594129\n", + " 0.002369\n", " \n", " \n", " 125\n", @@ -865,8 +823,8 @@ " 1\n", " 2\n", " O-16\n", - " 0.285147\n", - " 0.001392\n", + " 0.285761\n", + " 0.001676\n", " \n", " \n", " 122\n", @@ -874,8 +832,8 @@ " 1\n", " 3\n", " H-1\n", - " 0.010776\n", - " 0.000186\n", + " 0.011089\n", + " 0.000248\n", " \n", " \n", " 123\n", @@ -892,8 +850,8 @@ " 1\n", " 4\n", " H-1\n", - " 0.000023\n", - " 0.000010\n", + " 0.000000\n", + " 0.000000\n", " \n", " \n", " 121\n", @@ -928,19 +886,19 @@ ], "text/plain": [ " cell group in group out nuclide mean std. dev.\n", - "126 10002 1 1 H-1 0.234022 0.003645\n", - "127 10002 1 1 O-16 1.560305 0.006280\n", - "124 10002 1 2 H-1 1.588025 0.002815\n", - "125 10002 1 2 O-16 0.285147 0.001392\n", - "122 10002 1 3 H-1 0.010776 0.000186\n", + "126 10002 1 1 H-1 0.234115 0.003568\n", + "127 10002 1 1 O-16 1.563707 0.005953\n", + "124 10002 1 2 H-1 1.594129 0.002369\n", + "125 10002 1 2 O-16 0.285761 0.001676\n", + "122 10002 1 3 H-1 0.011089 0.000248\n", "123 10002 1 3 O-16 0.000000 0.000000\n", - "120 10002 1 4 H-1 0.000023 0.000010\n", + "120 10002 1 4 H-1 0.000000 0.000000\n", "121 10002 1 4 O-16 0.000000 0.000000\n", "118 10002 1 5 H-1 0.000000 0.000000\n", "119 10002 1 5 O-16 0.000000 0.000000" ] }, - "execution_count": 20, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -960,7 +918,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "collapsed": true }, @@ -982,7 +940,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { "collapsed": false }, @@ -997,18 +955,18 @@ "\tDomain ID =\t10000\n", "\tNuclide =\tU-235\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t7.81e-03 +/- 4.75e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t1.82e-01 +/- 1.89e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t7.73e-03 +/- 5.06e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t1.82e-01 +/- 2.05e-01%\n", "\n", "\tNuclide =\tU-238\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t2.17e-01 +/- 1.31e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t2.53e-01 +/- 2.08e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t2.17e-01 +/- 1.44e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t2.53e-01 +/- 2.57e-01%\n", "\n", "\tNuclide =\tO-16\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t1.45e-01 +/- 1.50e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t1.74e-01 +/- 2.66e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t1.46e-01 +/- 1.60e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t1.75e-01 +/- 2.94e-01%\n", "\n", "\n", "\n" @@ -1021,21 +979,11 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n", - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n" - ] - }, { "data": { "text/html": [ @@ -1057,48 +1005,48 @@ " 10000\n", " 1\n", " U-235\n", - " 20.828127\n", - " 0.098842\n", + " 20.611692\n", + " 0.104237\n", " \n", " \n", " 4\n", " 10000\n", " 1\n", " U-238\n", - " 9.582295\n", - " 0.012550\n", + " 9.585358\n", + " 0.013808\n", " \n", " \n", " 5\n", " 10000\n", " 1\n", " O-16\n", - " 3.157358\n", - " 0.004725\n", + " 3.164190\n", + " 0.005049\n", " \n", " \n", " 0\n", " 10000\n", " 2\n", " U-235\n", - " 485.217649\n", - " 0.916465\n", + " 485.413426\n", + " 0.996410\n", " \n", " \n", " 1\n", " 10000\n", " 2\n", " U-238\n", - " 11.176081\n", - " 0.023196\n", + " 11.190386\n", + " 0.028731\n", " \n", " \n", " 2\n", " 10000\n", " 2\n", " O-16\n", - " 3.788167\n", - " 0.010090\n", + " 3.794859\n", + " 0.011139\n", " \n", " \n", "\n", @@ -1106,15 +1054,15 @@ ], "text/plain": [ " cell group in nuclide mean std. dev.\n", - "3 10000 1 U-235 20.828127 0.098842\n", - "4 10000 1 U-238 9.582295 0.012550\n", - "5 10000 1 O-16 3.157358 0.004725\n", - "0 10000 2 U-235 485.217649 0.916465\n", - "1 10000 2 U-238 11.176081 0.023196\n", - "2 10000 2 O-16 3.788167 0.010090" + "3 10000 1 U-235 20.611692 0.104237\n", + "4 10000 1 U-238 9.585358 0.013808\n", + "5 10000 1 O-16 3.164190 0.005049\n", + "0 10000 2 U-235 485.413426 0.996410\n", + "1 10000 2 U-238 11.190386 0.028731\n", + "2 10000 2 O-16 3.794859 0.011139" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1140,14 +1088,14 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Create an OpenMOC Geometry from the OpenCG Geometry\n", - "openmoc_geometry = get_openmoc_geometry(su.opencg_geometry)" + "openmoc_geometry = get_openmoc_geometry(sp.summary.opencg_geometry)" ] }, { @@ -1159,7 +1107,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -1204,7 +1152,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "collapsed": false }, @@ -1215,174 +1163,175 @@ "text": [ "[ NORMAL ] Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.574633\tres = 5.948E-317\n", - "[ NORMAL ] Iteration 1:\tk_eff = 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openmoc.TrackGenerator(openmoc_geometry, num_azim=128, spacing=0.1)\n", + "track_generator = openmoc.TrackGenerator(openmoc_geometry, num_azim=128, azim_spacing=0.1)\n", "track_generator.generateTracks()\n", "\n", "# Run OpenMOC\n", @@ -1399,7 +1348,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "collapsed": false }, @@ -1408,9 +1357,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "openmc keff = 1.223729\n", - "openmoc keff = 1.219868\n", - "bias [pcm]: -386.1\n" + "openmc keff = 1.223474\n", + "openmoc keff = 1.220892\n", + "bias [pcm]: -258.1\n" ] } ], @@ -1434,13 +1383,13 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "openmoc_geometry = get_openmoc_geometry(su.opencg_geometry)\n", + "openmoc_geometry = get_openmoc_geometry(sp.summary.opencg_geometry)\n", "openmoc_cells = openmoc_geometry.getRootUniverse().getAllCells()\n", "\n", "# Inject multi-group cross sections into OpenMOC Materials\n", @@ -1474,7 +1423,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -1485,243 +1434,243 @@ "text": [ "[ NORMAL ] Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.495594\tres = 5.948E-317\n", - "[ NORMAL ] Iteration 1:\tk_eff = 0.557312\tres = 5.044E-01\n", - "[ NORMAL ] Iteration 2:\tk_eff = 0.518115\tres = 1.245E-01\n", - "[ NORMAL ] Iteration 3:\tk_eff = 0.509016\tres = 7.033E-02\n", - "[ NORMAL ] Iteration 4:\tk_eff = 0.496279\tres = 1.756E-02\n", - "[ NORMAL ] Iteration 5:\tk_eff = 0.488357\tres = 2.502E-02\n", - "[ NORMAL ] Iteration 6:\tk_eff = 0.482659\tres = 1.596E-02\n", - "[ NORMAL ] Iteration 7:\tk_eff = 0.479523\tres = 1.167E-02\n", - "[ NORMAL ] Iteration 8:\tk_eff = 0.478568\tres = 6.497E-03\n", - "[ NORMAL ] Iteration 9:\tk_eff = 0.479590\tres = 1.991E-03\n", 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NORMAL ] Iteration 221:\tk_eff = 1.223101\tres = 1.437E-05\n", + "[ NORMAL ] Iteration 222:\tk_eff = 1.223117\tres = 1.382E-05\n", + "[ NORMAL ] Iteration 223:\tk_eff = 1.223133\tres = 1.329E-05\n", + "[ NORMAL ] Iteration 224:\tk_eff = 1.223148\tres = 1.279E-05\n", + "[ NORMAL ] Iteration 225:\tk_eff = 1.223162\tres = 1.230E-05\n", + "[ NORMAL ] Iteration 226:\tk_eff = 1.223176\tres = 1.183E-05\n", + "[ NORMAL ] Iteration 227:\tk_eff = 1.223190\tres = 1.137E-05\n", + "[ NORMAL ] Iteration 228:\tk_eff = 1.223203\tres = 1.094E-05\n", + "[ NORMAL ] Iteration 229:\tk_eff = 1.223215\tres = 1.052E-05\n", + "[ NORMAL ] Iteration 230:\tk_eff = 1.223227\tres = 1.012E-05\n" ] } ], "source": [ "# Generate tracks for OpenMOC\n", - "track_generator = openmoc.TrackGenerator(openmoc_geometry, num_azim=128, spacing=0.1)\n", + "track_generator = openmoc.TrackGenerator(openmoc_geometry, num_azim=128, azim_spacing=0.1)\n", "track_generator.generateTracks()\n", "\n", "# Run OpenMOC\n", @@ -1731,7 +1680,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -1740,9 +1689,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "openmc keff = 1.223729\n", - "openmoc keff = 1.222447\n", - "bias [pcm]: -128.2\n" + "openmc keff = 1.223474\n", + "openmoc keff = 1.223227\n", + "bias [pcm]: -24.7\n" ] } ], @@ -1788,7 +1737,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -1814,7 +1763,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, @@ -1825,15 +1774,15 @@ "(9.9999999999999994e-12, 20.0)" ] }, - "execution_count": 32, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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NiQo+A2zbVhpS7/HHs7juuuDB588+s3PyyQURB6bT7T6mu1ai9ZoTfG5s5bMg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\nnYz04Ol8fel6baJlPT25tggrTElUAlN2J1IrGZq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N73Q6ue++BxgzZhyPPfZos+WNVcYlBxEpFZGPReSUVMdu397DrFm1dO7s5uSTS1izRjuq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\n+KP1PP8hsU6nNWku3KqsyVy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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1875,22 +1824,11 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n", - "/usr/local/lib/python2.7/dist-packages/numpy/lib/shape_base.py:872: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n" - ] - } - ], + "outputs": [], "source": [ "# Construct a Pandas DataFrame for the microscopic nu-scattering matrix\n", "nuscatter = xs_library[moderator_cell.id]['nu-scatter']\n", @@ -1918,16 +1856,16 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, diff --git a/docs/source/pythonapi/examples/mgxs-part-iii.ipynb b/docs/source/pythonapi/examples/mgxs-part-iii.ipynb index dcb496160..5f0acde3f 100644 --- a/docs/source/pythonapi/examples/mgxs-part-iii.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-iii.ipynb @@ -11,7 +11,7 @@ "* **Validation** of multi-group cross sections with **[OpenMOC](https://mit-crpg.github.io/OpenMOC/)**\n", "* Steady-state pin-by-pin **fission rates comparison** between OpenMC and [OpenMOC](https://mit-crpg.github.io/OpenMOC/)\n", "\n", - "**Note:** This Notebook was created using [OpenMOC](https://mit-crpg.github.io/OpenMOC/) to verify the multi-group cross-sections generated by OpenMC. In order to run this Notebook in its entirety, you must have [OpenMOC](https://mit-crpg.github.io/OpenMOC/) installed on your system, along with OpenCG to convert the OpenMC geometries into OpenMOC geometries. In addition, this Notebook illustrates the use of [Pandas](http://pandas.pydata.org/) `DataFrames` to containerize multi-group cross section data. We recommend using [Pandas](http://pandas.pydata.org/) >v0.15.0 or later since OpenMC's Python API leverages the multi-indexing feature included in the most recent releases of [Pandas](http://pandas.pydata.org/)." + "**Note:** This Notebook was created using [OpenMOC](https://mit-crpg.github.io/OpenMOC/) to verify the multi-group cross-sections generated by OpenMC. In order to run this Notebook in its entirety, you must have [OpenMOC](https://mit-crpg.github.io/OpenMOC/) installed on your system, along with OpenCG to convert the OpenMC geometries into OpenMOC geometries. In addition, this Notebook illustrates the use of [Pandas](http://pandas.pydata.org/) `DataFrames` to containerize multi-group cross section data." ] }, { @@ -32,7 +32,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/usr/local/lib/python2.7/dist-packages/matplotlib/__init__.py:1318: UserWarning: This call to matplotlib.use() has no effect\n", + "/home/wboyd/anaconda2/lib/python2.7/site-packages/matplotlib/__init__.py:1350: UserWarning: This call to matplotlib.use() has no effect\n", "because the backend has already been chosen;\n", "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", "or matplotlib.backends is imported for the first time.\n", @@ -44,20 +44,16 @@ "source": [ "import math\n", "import pickle\n", + "\n", "from IPython.display import Image\n", - "import matplotlib.pylab as pylab\n", + "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "import openmc\n", "import openmc.mgxs\n", - "from openmc.statepoint import StatePoint\n", - "from openmc.summary import Summary\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", - "\n", "import openmoc\n", "import openmoc.process\n", - "from openmoc.compatible import get_openmoc_geometry\n", + "from openmoc.opencg_compatible import get_openmoc_geometry\n", "from openmoc.materialize import load_openmc_mgxs_lib\n", "\n", "%matplotlib inline" @@ -126,7 +122,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With our three materials, we can now create a `MaterialsFile` object that can be exported to an actual XML file." + "With our three materials, we can now create a `Materials` object that can be exported to an actual XML file." ] }, { @@ -137,11 +133,8 @@ }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, add Materials\n", - "materials_file = openmc.MaterialsFile()\n", - "materials_file.add_material(fuel)\n", - "materials_file.add_material(water)\n", - "materials_file.add_material(zircaloy)\n", + "# Instantiate a Materials object\n", + "materials_file = openmc.Materials((fuel, water, zircaloy))\n", "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", @@ -267,7 +260,6 @@ "source": [ "# Create fuel assembly Lattice\n", "assembly = openmc.RectLattice(name='1.6% Fuel Assembly')\n", - "assembly.dimension = (17, 17)\n", "assembly.pitch = (1.26, 1.26)\n", "assembly.lower_left = [-1.26 * 17. / 2.0] * 2" ] @@ -335,7 +327,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We now must create a geometry that is assigned a root universe, put the geometry into a `GeometryFile` object, and export it to XML." + "We now must create a geometry that is assigned a root universe and export it to XML." ] }, { @@ -359,12 +351,8 @@ }, "outputs": [], "source": [ - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "geometry.export_to_xml()" ] }, { @@ -387,15 +375,17 @@ "inactive = 10\n", "particles = 2500\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "settings_file.output = {'tallies': False}\n", - "source_bounds = [-10.71, -10.71, -10, 10.71, 10.71, 10.]\n", - "settings_file.source = Source(Box(\n", - " source_bounds[:3], source_bounds[3:], only_fissionable=True))\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", + "bounds = [-10.71, -10.71, -10, 10.71, 10.71, 10.]\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Export to \"settings.xml\"\n", "settings_file.export_to_xml()" @@ -405,7 +395,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Let us also create a `PlotsFile` that we can use to verify that our fuel assembly geometry was created successfully." + "Let us also create a `Plots` file that we can use to verify that our fuel assembly geometry was created successfully." ] }, { @@ -420,13 +410,12 @@ "plot = openmc.Plot(plot_id=1)\n", "plot.filename = 'materials-xy'\n", "plot.origin = [0, 0, 0]\n", - "plot.width = [21.5, 21.5]\n", "plot.pixels = [250, 250]\n", + "plot.width = [-10.71*2, -10.71*2]\n", "plot.color = 'mat'\n", "\n", - "# Instantiate a PlotsFile, add Plot, and export to \"plots.xml\"\n", - "plot_file = openmc.PlotsFile()\n", - "plot_file.add_plot(plot)\n", + "# Instantiate a Plots object, add Plot, and export to \"plots.xml\"\n", + "plot_file = openmc.Plots([plot])\n", "plot_file.export_to_xml()" ] }, @@ -457,8 +446,7 @@ ], "source": [ "# Run openmc in plotting mode\n", - "executor = openmc.Executor()\n", - "executor.plot_geometry(output=False)" + "openmc.plot_geometry(output=False)" ] }, { @@ -470,7 +458,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -550,17 +538,19 @@ "\n", "* `TotalXS` (`\"total\"`)\n", "* `TransportXS` (`\"transport\"`)\n", + "* `NuTransportXS` (`\"nu-transport\"`)\n", "* `AbsorptionXS` (`\"absorption\"`)\n", "* `CaptureXS` (`\"capture\"`)\n", "* `FissionXS` (`\"fission\"`)\n", "* `NuFissionXS` (`\"nu-fission\"`)\n", + "* `KappaFissionXS` (`\"kappa-fission\"`)\n", "* `ScatterXS` (`\"scatter\"`)\n", "* `NuScatterXS` (`\"nu-scatter\"`)\n", "* `ScatterMatrixXS` (`\"scatter matrix\"`)\n", "* `NuScatterMatrixXS` (`\"nu-scatter matrix\"`)\n", "* `Chi` (`\"chi\"`)\n", "\n", - "In this case, let's create the multi-group cross sections needed to run an OpenMOC simulation to verify the accuracy of our cross sections. In particular, we will define `\"transport\"`, `\"nu-fission\"`, `\"nu-scatter matrix\"` and `\"chi\"` cross sections for our `Library`.\n", + "In this case, let's create the multi-group cross sections needed to run an OpenMOC simulation to verify the accuracy of our cross sections. In particular, we will define `\"transport\"`, `\"nu-fission\"`, `'\"fission\"`, `\"nu-scatter matrix\"` and `\"chi\"` cross sections for our `Library`.\n", "\n", "**Note**: A variety of different approximate transport-corrected total multi-group cross sections (and corresponding scattering matrices) can be found in the literature. At the present time, the `openmc.mgxs` module only supports the `\"P0\"` transport correction. This correction can be turned on and off through the boolean `Library.correction` property which may take values of `\"P0\"` (default) or `None`." ] @@ -569,12 +559,12 @@ "cell_type": "code", "execution_count": 19, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ "# Specify multi-group cross section types to compute\n", - "mgxs_lib.mgxs_types = ['transport', 'nu-fission', 'nu-scatter matrix', 'chi']" + "mgxs_lib.mgxs_types = ['transport', 'nu-fission', 'fission', 'nu-scatter matrix', 'chi']" ] }, { @@ -595,7 +585,7 @@ "outputs": [], "source": [ "# Specify a \"cell\" domain type for the cross section tally filters\n", - "mgxs_lib.domain_type = \"cell\"\n", + "mgxs_lib.domain_type = 'cell'\n", "\n", "# Specify the cell domains over which to compute multi-group cross sections\n", "mgxs_lib.domains = geometry.get_all_material_cells()" @@ -645,7 +635,7 @@ "source": [ "The tallies can now be export to a \"tallies.xml\" input file for OpenMC. \n", "\n", - "**NOTE**: At this point the `Library` has constructed nearly 100 distinct `Tally` objects. The overhead to tally in OpenMC scales as $O(N)$ for $N$ tallies, which can become a bottleneck for large tally datasets. To compensate for this, the Python API's `Tally`, `Filter` and `TalliesFile` classes allow for the smart *merging* of tallies when possible. The `Library` class supports this runtime optimization with the use of the optional `merge` paramter (`False` by default) for the `Library.add_to_tallies_file(...)` method, as shown below." + "**NOTE**: At this point the `Library` has constructed nearly 100 distinct `Tally` objects. The overhead to tally in OpenMC scales as $O(N)$ for $N$ tallies, which can become a bottleneck for large tally datasets. To compensate for this, the Python API's `Tally`, `Filter` and `Tallies` classes allow for the smart *merging* of tallies when possible. The `Library` class supports this runtime optimization with the use of the optional `merge` paramter (`False` by default) for the `Library.add_to_tallies_file(...)` method, as shown below." ] }, { @@ -657,7 +647,7 @@ "outputs": [], "source": [ "# Create a \"tallies.xml\" file for the MGXS Library\n", - "tallies_file = openmc.TalliesFile()\n", + "tallies_file = openmc.Tallies()\n", "mgxs_lib.add_to_tallies_file(tallies_file, merge=True)" ] }, @@ -681,7 +671,7 @@ "mesh.type = 'regular'\n", "mesh.dimension = [17, 17]\n", "mesh.lower_left = [-10.71, -10.71]\n", - "mesh.width = [1.26, 1.26]\n", + "mesh.upper_right = [+10.71, +10.71]\n", "\n", "# Instantiate tally Filter\n", "mesh_filter = openmc.Filter()\n", @@ -689,13 +679,11 @@ "\n", "# Instantiate the Tally\n", "tally = openmc.Tally(name='mesh tally')\n", - "tally.add_filter(mesh_filter)\n", - "tally.add_score('fission')\n", - "tally.add_score('nu-fission')\n", + "tally.filters = [mesh_filter]\n", + "tally.scores = ['fission', 'nu-fission']\n", "\n", - "# Add mesh and Tally to TalliesFile\n", - "tallies_file.add_mesh(mesh)\n", - "tallies_file.add_tally(tally)" + "# Add tally to collection\n", + "tallies_file.append(tally)" ] }, { @@ -734,11 +722,12 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: ea9fb637f63f9374c7436456141afa850b84acf9\n", - " Date/Time: 2016-01-14 08:12:09\n", + " Git SHA1: 47ef320ad517612376e181ec6a6bc42ca0db98ce\n", + " Date/Time: 2016-05-14 12:29:07\n", + " MPI Processes: 1\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -765,56 +754,56 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 1.02650 \n", - " 2/1 1.01386 \n", - " 3/1 1.01045 \n", - " 4/1 1.05511 \n", - " 5/1 1.04873 \n", - " 6/1 1.04558 \n", - " 7/1 1.03840 \n", - " 8/1 1.02086 \n", - " 9/1 1.08845 \n", - " 10/1 1.03932 \n", - " 11/1 1.01271 \n", - " 12/1 1.03448 1.02360 +/- 0.01088\n", - " 13/1 1.04395 1.03038 +/- 0.00925\n", - " 14/1 1.05477 1.03648 +/- 0.00894\n", - " 15/1 1.00485 1.03015 +/- 0.00938\n", - " 16/1 1.04523 1.03267 +/- 0.00806\n", - " 17/1 1.01328 1.02990 +/- 0.00735\n", - " 18/1 1.01476 1.02800 +/- 0.00664\n", - " 19/1 1.01490 1.02655 +/- 0.00604\n", - " 20/1 1.00926 1.02482 +/- 0.00567\n", - " 21/1 0.98504 1.02120 +/- 0.00627\n", - " 22/1 1.00397 1.01977 +/- 0.00591\n", - " 23/1 1.02556 1.02021 +/- 0.00545\n", - " 24/1 0.99808 1.01863 +/- 0.00529\n", - " 25/1 0.99638 1.01715 +/- 0.00514\n", - " 26/1 0.99615 1.01584 +/- 0.00499\n", - " 27/1 1.01843 1.01599 +/- 0.00469\n", - " 28/1 1.00315 1.01528 +/- 0.00447\n", - " 29/1 1.00633 1.01480 +/- 0.00426\n", - " 30/1 1.02159 1.01514 +/- 0.00405\n", - " 31/1 1.03395 1.01604 +/- 0.00396\n", - " 32/1 1.02672 1.01652 +/- 0.00381\n", - " 33/1 1.03778 1.01745 +/- 0.00375\n", - " 34/1 1.03807 1.01831 +/- 0.00369\n", - " 35/1 1.07854 1.02072 +/- 0.00428\n", - " 36/1 1.03524 1.02128 +/- 0.00415\n", - " 37/1 1.03100 1.02164 +/- 0.00401\n", - " 38/1 1.03853 1.02224 +/- 0.00391\n", - " 39/1 1.04089 1.02288 +/- 0.00383\n", - " 40/1 1.02150 1.02284 +/- 0.00370\n", - " 41/1 0.98470 1.02161 +/- 0.00379\n", - " 42/1 1.00658 1.02114 +/- 0.00370\n", - " 43/1 0.98652 1.02009 +/- 0.00373\n", - " 44/1 1.02787 1.02032 +/- 0.00363\n", - " 45/1 0.98800 1.01939 +/- 0.00364\n", - " 46/1 1.00286 1.01893 +/- 0.00357\n", - " 47/1 1.02559 1.01911 +/- 0.00348\n", - " 48/1 1.03729 1.01959 +/- 0.00342\n", - " 49/1 1.02538 1.01974 +/- 0.00333\n", - " 50/1 1.01478 1.01962 +/- 0.00325\n", + " 1/1 1.03852 \n", + " 2/1 0.99743 \n", + " 3/1 1.02987 \n", + " 4/1 1.04472 \n", + " 5/1 1.02183 \n", + " 6/1 1.05263 \n", + " 7/1 0.99048 \n", + " 8/1 1.02753 \n", + " 9/1 1.03159 \n", + " 10/1 1.04005 \n", + " 11/1 1.05278 \n", + " 12/1 1.02555 1.03917 +/- 0.01362\n", + " 13/1 0.99400 1.02411 +/- 0.01699\n", + " 14/1 1.03508 1.02685 +/- 0.01232\n", + " 15/1 1.00055 1.02159 +/- 0.01090\n", + " 16/1 1.01334 1.02022 +/- 0.00900\n", + " 17/1 0.99822 1.01707 +/- 0.00823\n", + " 18/1 1.01767 1.01715 +/- 0.00713\n", + " 19/1 1.05052 1.02086 +/- 0.00730\n", + " 20/1 1.03133 1.02190 +/- 0.00661\n", + " 21/1 1.04112 1.02365 +/- 0.00623\n", + " 22/1 1.04175 1.02516 +/- 0.00588\n", + " 23/1 1.01909 1.02469 +/- 0.00543\n", + " 24/1 1.07119 1.02801 +/- 0.00603\n", + " 25/1 0.97445 1.02444 +/- 0.00665\n", + " 26/1 1.04737 1.02588 +/- 0.00638\n", + " 27/1 1.04656 1.02709 +/- 0.00612\n", + " 28/1 1.03464 1.02751 +/- 0.00578\n", + " 29/1 1.02528 1.02739 +/- 0.00547\n", + " 30/1 1.02799 1.02742 +/- 0.00519\n", + " 31/1 1.05846 1.02890 +/- 0.00516\n", + " 32/1 1.03811 1.02932 +/- 0.00493\n", + " 33/1 1.00894 1.02843 +/- 0.00480\n", + " 34/1 1.02049 1.02810 +/- 0.00460\n", + " 35/1 1.00690 1.02726 +/- 0.00450\n", + " 36/1 1.03129 1.02741 +/- 0.00432\n", + " 37/1 0.98864 1.02597 +/- 0.00440\n", + " 38/1 1.00017 1.02505 +/- 0.00434\n", + " 39/1 1.03635 1.02544 +/- 0.00421\n", + " 40/1 1.07090 1.02696 +/- 0.00434\n", + " 41/1 1.03141 1.02710 +/- 0.00420\n", + " 42/1 1.02624 1.02707 +/- 0.00406\n", + " 43/1 1.02668 1.02706 +/- 0.00394\n", + " 44/1 1.05940 1.02801 +/- 0.00394\n", + " 45/1 1.01149 1.02754 +/- 0.00385\n", + " 46/1 1.06958 1.02871 +/- 0.00392\n", + " 47/1 1.02674 1.02866 +/- 0.00381\n", + " 48/1 1.02542 1.02857 +/- 0.00371\n", + " 49/1 1.03516 1.02874 +/- 0.00362\n", + " 50/1 1.06818 1.02973 +/- 0.00366\n", " Creating state point statepoint.50.h5...\n", "\n", " ===========================================================================\n", @@ -824,27 +813,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.1800E-01 seconds\n", - " Reading cross sections = 1.4300E-01 seconds\n", - " Total time in simulation = 4.1206E+01 seconds\n", - " Time in transport only = 4.1193E+01 seconds\n", - " Time in inactive batches = 4.1760E+00 seconds\n", - " Time in active batches = 3.7030E+01 seconds\n", - " Time synchronizing fission bank = 3.0000E-03 seconds\n", + " Total time for initialization = 5.7700E-01 seconds\n", + " Reading cross sections = 1.3400E-01 seconds\n", + " Total time in simulation = 8.0461E+01 seconds\n", + " Time in transport only = 8.0422E+01 seconds\n", + " Time in inactive batches = 6.4060E+00 seconds\n", + " Time in active batches = 7.4055E+01 seconds\n", + " Time synchronizing fission bank = 6.0000E-03 seconds\n", " Sampling source sites = 2.0000E-03 seconds\n", - " SEND/RECV source sites = 1.0000E-03 seconds\n", + " SEND/RECV source sites = 3.0000E-03 seconds\n", " Time accumulating tallies = 0.0000E+00 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 4.1648E+01 seconds\n", - " Calculation Rate (inactive) = 5986.59 neutrons/second\n", - " Calculation Rate (active) = 2700.51 neutrons/second\n", + " Total time elapsed = 8.1067E+01 seconds\n", + " Calculation Rate (inactive) = 3902.59 neutrons/second\n", + " Calculation Rate (active) = 1350.35 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.01805 +/- 0.00261\n", - " k-effective (Track-length) = 1.01962 +/- 0.00325\n", - " k-effective (Absorption) = 1.01554 +/- 0.00339\n", - " Combined k-effective = 1.01711 +/- 0.00235\n", + " k-effective (Collision) = 1.02763 +/- 0.00343\n", + " k-effective (Track-length) = 1.02973 +/- 0.00366\n", + " k-effective (Absorption) = 1.02732 +/- 0.00319\n", + " Combined k-effective = 1.02826 +/- 0.00259\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -862,7 +851,7 @@ ], "source": [ "# Run OpenMC\n", - "executor.run_simulation()" + "openmc.run()" ] }, { @@ -891,25 +880,6 @@ "sp = openmc.StatePoint('statepoint.50.h5')" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. This is necessary for the `openmc.mgxs` module to properly process the tally data. We first create a `Summary` object and link it with the statepoint." - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "su = openmc.Summary('summary.h5')\n", - "sp.link_with_summary(su)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -919,7 +889,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -954,7 +924,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -968,12 +938,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The `NuFissionXS` object supports all of the methods described previously the `openmc.mgxs` tutorials, such as [Pandas](http://pandas.pydata.org/) `DataFrames`:" + "The `NuFissionXS` object supports all of the methods described previously in the `openmc.mgxs` tutorials, such as [Pandas](http://pandas.pydata.org/) `DataFrames`:\n", + "Note that since so few histories were simulated, we should expect a few division-by-error errors as some tallies have not yet scored any results." ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -982,14 +953,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/romano/openmc/openmc/tallies.py:1642: RuntimeWarning: invalid value encountered in true_divide\n", + "/home/wboyd/Documents/NSE-CRPG-Codes/openmc/openmc/tallies.py:1988: RuntimeWarning: invalid value encountered in true_divide\n", " self_rel_err = data['self']['std. dev.'] / data['self']['mean']\n" ] }, { "data": { "text/html": [ - "
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true @@ -1327,132 +1298,132 @@ "name": "stdout", "output_type": "stream", "text": [ - "[ NORMAL ] Ray tracing for track segmentation...\n", - "[ NORMAL ] Dumping tracks to file...\n", + "[ NORMAL ] Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.854316\tres = 0.000E+00\n", - "[ NORMAL ] Iteration 1:\tk_eff = 0.801593\tres = 1.522E-01\n", - "[ NORMAL ] Iteration 2:\tk_eff = 0.761131\tres = 6.380E-02\n", - "[ NORMAL ] Iteration 3:\tk_eff = 0.731467\tres = 5.066E-02\n", - "[ NORMAL ] Iteration 4:\tk_eff = 0.709897\tres = 3.910E-02\n", - "[ NORMAL ] Iteration 5:\tk_eff = 0.695111\tres = 2.954E-02\n", - "[ NORMAL ] Iteration 6:\tk_eff = 0.685967\tres = 2.085E-02\n", - "[ NORMAL ] Iteration 7:\tk_eff = 0.681511\tres = 1.317E-02\n", - "[ NORMAL ] Iteration 8:\tk_eff = 0.680926\tres = 6.520E-03\n", - "[ NORMAL ] Iteration 9:\tk_eff = 0.683509\tres = 1.046E-03\n", - "[ NORMAL ] Iteration 10:\tk_eff = 0.688659\tres = 3.848E-03\n", - "[ NORMAL ] Iteration 11:\tk_eff = 0.695861\tres = 7.565E-03\n", - "[ NORMAL ] Iteration 12:\tk_eff = 0.704674\tres = 1.048E-02\n", - "[ NORMAL ] Iteration 13:\tk_eff = 0.714726\tres = 1.269E-02\n", - "[ NORMAL ] Iteration 14:\tk_eff = 0.725701\tres = 1.428E-02\n", - "[ NORMAL ] Iteration 15:\tk_eff = 0.737329\tres = 1.537E-02\n", - "[ NORMAL ] Iteration 16:\tk_eff = 0.749388\tres = 1.604E-02\n", - "[ NORMAL ] Iteration 17:\tk_eff = 0.761691\tres = 1.637E-02\n", - "[ NORMAL ] Iteration 18:\tk_eff = 0.774081\tres = 1.643E-02\n", - "[ NORMAL ] Iteration 19:\tk_eff = 0.786431\tres = 1.628E-02\n", - "[ NORMAL ] Iteration 20:\tk_eff = 0.798638\tres = 1.597E-02\n", - "[ NORMAL ] Iteration 21:\tk_eff = 0.810618\tres = 1.553E-02\n", - "[ NORMAL ] Iteration 22:\tk_eff = 0.822303\tres = 1.501E-02\n", - "[ NORMAL ] Iteration 23:\tk_eff = 0.833643\tres = 1.443E-02\n", - "[ NORMAL ] Iteration 24:\tk_eff = 0.844598\tres = 1.380E-02\n", - "[ NORMAL ] Iteration 25:\tk_eff = 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NORMAL ] Iteration 116:\tk_eff = 1.028481\tres = 1.106E-05\n", + "[ NORMAL ] Iteration 117:\tk_eff = 1.028491\tres = 1.016E-05\n" ] } ], "source": [ "# Generate tracks for OpenMOC\n", - "track_generator = openmoc.TrackGenerator(openmoc_geometry, num_azim=32, spacing=0.1)\n", + "track_generator = openmoc.TrackGenerator(openmoc_geometry, num_azim=32, azim_spacing=0.1)\n", "track_generator.generateTracks()\n", "\n", "# Run OpenMOC\n", @@ -1469,7 +1440,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "metadata": { "collapsed": false }, @@ -1478,9 +1449,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "openmc keff = 1.017105\n", - "openmoc keff = 1.020704\n", - "bias [pcm]: 359.8\n" + "openmc keff = 1.028263\n", + "openmoc keff = 1.028491\n", + "bias [pcm]: 22.8\n" ] } ], @@ -1522,7 +1493,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": { "collapsed": false }, @@ -1548,26 +1519,24 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Export OpenMOC's fission rates for each pin cell instance in the fuel assembly\n", - "openmoc.process.compute_fission_rates(solver)\n", + "# Create OpenMOC Mesh on which to tally fission rates\n", + "openmoc_mesh = openmoc.process.Mesh()\n", + "openmoc_mesh.dimension = np.array(mesh.dimension)\n", + "openmoc_mesh.lower_left = np.array(mesh.lower_left)\n", + "openmoc_mesh.upper_right = np.array(mesh.upper_right)\n", + "openmoc_mesh.width = openmoc_mesh.upper_right - openmoc_mesh.lower_left\n", + "openmoc_mesh.width /= openmoc_mesh.dimension\n", "\n", - "# Open the pickle file with the fission rates\n", - "fission_rates = pickle.load(open('fission-rates/fission-rates.pkl', 'rb' ))\n", - "\n", - "# Allocate array for fission rates in each fuel pin\n", - "openmoc_fission_rates = np.zeros((17, 17))\n", - "\n", - "# Extract fission rates for each fuel pin\n", - "for key, value in fission_rates.items():\n", - " lat_x = int(key.split(':')[1].split()[3][1:-1])\n", - " lat_y = int(key.split(':')[1].split()[4][:-1]) \n", - " openmoc_fission_rates[lat_x, lat_y] = value\n", + "# Tally OpenMOC fission rates on the Mesh\n", + "openmoc_fission_rates = openmoc_mesh.tally_fission_rates(solver)\n", + "openmoc_fission_rates = np.squeeze(openmoc_fission_rates)\n", + "openmoc_fission_rates = np.fliplr(openmoc_fission_rates)\n", "\n", "# Normalize to the average pin fission rate\n", "openmoc_fission_rates /= np.mean(openmoc_fission_rates)" @@ -1582,7 +1551,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 43, "metadata": { "collapsed": false }, @@ -1590,18 +1559,18 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 44, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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C1AQ5bCGEqAly2EIIURPksIUQoibIYQshRE1o78SZ8tJsG0t5iQkdADyaFhl9aFpmVJNF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\nhKgJA06cMbPLgdc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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1609,35 +1578,39 @@ } ], "source": [ + "# Ignore zero fission rates in guide tubes with Matplotlib color scheme\n", + "openmc_fission_rates[openmc_fission_rates == 0] = np.nan\n", + "openmoc_fission_rates[openmoc_fission_rates == 0] = np.nan\n", + "\n", "# Plot OpenMC's fission rates in the left subplot\n", - "fig = pylab.subplot(121)\n", - "pylab.imshow(openmc_fission_rates, interpolation='none', cmap='jet')\n", - "pylab.title('OpenMC Fission Rates')\n", + "fig = plt.subplot(121)\n", + "plt.imshow(openmc_fission_rates, interpolation='none', cmap='jet')\n", + "plt.title('OpenMC Fission Rates')\n", "\n", "# Plot OpenMOC's fission rates in the right subplot\n", - "fig2 = pylab.subplot(122)\n", - "pylab.imshow(openmoc_fission_rates, interpolation='none', cmap='jet')\n", - "pylab.title('OpenMOC Fission Rates')" + "fig2 = plt.subplot(122)\n", + "plt.imshow(openmoc_fission_rates, interpolation='none', cmap='jet')\n", + "plt.title('OpenMOC Fission Rates')" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.5.1" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/mgxs-part-iv.ipynb b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb new file mode 100644 index 000000000..b845636e2 --- /dev/null +++ b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb @@ -0,0 +1,1461 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This Notebook illustrates the use of the openmc.mgxs.Library class specifically for application in OpenMC's multi-group mode. This example notebook follows the same process as was done in MGXS Part III, but instead uses OpenMC as the multi-group solver. During this process, this notebook will illustrate the following features:\n", + "\n", + " - Calculation of multi-group cross sections for a fuel assembly\n", + " - Automated creation and storage of MGXS with openmc.mgxs.Library\n", + " - Steady-state pin-by-pin fission rates comparison between continuous-energy and multi-group OpenMC.\n", + "\n", + "Note: This Notebook illustrates the use of Pandas DataFrames to containerize multi-group cross section data. We recommend using Pandas >v0.15.0 or later since OpenMC's Python API leverages the multi-indexing feature included in the most recent releases of Pandas.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Generate Input Files" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import math\n", + "import pickle\n", + "\n", + "from IPython.display import Image\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os\n", + "\n", + "import openmc\n", + "import openmc.mgxs\n", + "\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "First we need to define materials that will be used in the problem. Before defining a material, we must create nuclides that are used in the material." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Instantiate some Nuclides\n", + "h1 = openmc.Nuclide('H-1')\n", + "b10 = openmc.Nuclide('B-10')\n", + "o16 = openmc.Nuclide('O-16')\n", + "u235 = openmc.Nuclide('U-235')\n", + "u238 = openmc.Nuclide('U-238')\n", + "zr90 = openmc.Nuclide('Zr-90')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With the nuclides we defined, we will now create three materials for the fuel, water, and cladding of the fuel pins." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# 1.6 enriched fuel\n", + "fuel = openmc.Material(name='1.6% Fuel')\n", + "fuel.set_density('g/cm3', 10.31341)\n", + "fuel.add_nuclide(u235, 3.7503e-4)\n", + "fuel.add_nuclide(u238, 2.2625e-2)\n", + "fuel.add_nuclide(o16, 4.6007e-2)\n", + "\n", + "# zircaloy\n", + "zircaloy = openmc.Material(name='Zircaloy')\n", + "zircaloy.set_density('g/cm3', 6.55)\n", + "zircaloy.add_nuclide(zr90, 7.2758e-3)\n", + "\n", + "# borated water\n", + "water = openmc.Material(name='Borated Water')\n", + "water.set_density('g/cm3', 0.740582)\n", + "water.add_nuclide(h1, 4.9457e-2)\n", + "water.add_nuclide(o16, 2.4732e-2)\n", + "water.add_nuclide(b10, 8.0042e-6)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With our three materials, we can now create a Materials object that can be exported to an actual XML file." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Instantiate a Materials object\n", + "materials_file = openmc.Materials((fuel, zircaloy, water))\n", + "materials_file.default_xs = '71c'\n", + "\n", + "# Export to \"materials.xml\"\n", + "materials_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now let's move on to the geometry. This problem will be a square array of fuel pins and control rod guide tubes for which we can use OpenMC's lattice/universe feature. The basic universe will have three regions for the fuel, the clad, and the surrounding coolant. The first step is to create the bounding surfaces for fuel and clad, as well as the outer bounding surfaces of the problem." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create cylinders for the fuel and clad\n", + "fuel_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.39218)\n", + "clad_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.45720)\n", + "\n", + "# Create boundary planes to surround the geometry\n", + "min_x = openmc.XPlane(x0=-10.71, boundary_type='reflective')\n", + "max_x = openmc.XPlane(x0=+10.71, boundary_type='reflective')\n", + "min_y = openmc.YPlane(y0=-10.71, boundary_type='reflective')\n", + "max_y = openmc.YPlane(y0=+10.71, boundary_type='reflective')\n", + "min_z = openmc.ZPlane(z0=-10., boundary_type='reflective')\n", + "max_z = openmc.ZPlane(z0=+10., boundary_type='reflective')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With the surfaces defined, we can now construct a fuel pin cell from cells that are defined by intersections of half-spaces created by the surfaces." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Create a Universe to encapsulate a fuel pin\n", + "fuel_pin_universe = openmc.Universe(name='1.6% Fuel Pin')\n", + "\n", + "# Create fuel Cell\n", + "fuel_cell = openmc.Cell(name='1.6% Fuel')\n", + "fuel_cell.fill = fuel\n", + "fuel_cell.region = -fuel_outer_radius\n", + "fuel_pin_universe.add_cell(fuel_cell)\n", + "\n", + "# Create a clad Cell\n", + "clad_cell = openmc.Cell(name='1.6% Clad')\n", + "clad_cell.fill = zircaloy\n", + "clad_cell.region = +fuel_outer_radius & -clad_outer_radius\n", + "fuel_pin_universe.add_cell(clad_cell)\n", + "\n", + "# Create a moderator Cell\n", + "moderator_cell = openmc.Cell(name='1.6% Moderator')\n", + "moderator_cell.fill = water\n", + "moderator_cell.region = +clad_outer_radius\n", + "fuel_pin_universe.add_cell(moderator_cell)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Likewise, we can construct a control rod guide tube with the same surfaces." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Create a Universe to encapsulate a control rod guide tube\n", + "guide_tube_universe = openmc.Universe(name='Guide Tube')\n", + "\n", + "# Create guide tube Cell\n", + "guide_tube_cell = openmc.Cell(name='Guide Tube Water')\n", + "guide_tube_cell.fill = water\n", + "guide_tube_cell.region = -fuel_outer_radius\n", + "guide_tube_universe.add_cell(guide_tube_cell)\n", + "\n", + "# Create a clad Cell\n", + "clad_cell = openmc.Cell(name='Guide Clad')\n", + "clad_cell.fill = zircaloy\n", + "clad_cell.region = +fuel_outer_radius & -clad_outer_radius\n", + "guide_tube_universe.add_cell(clad_cell)\n", + "\n", + "# Create a moderator Cell\n", + "moderator_cell = openmc.Cell(name='Guide Tube Moderator')\n", + "moderator_cell.fill = water\n", + "moderator_cell.region = +clad_outer_radius\n", + "guide_tube_universe.add_cell(moderator_cell)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the pin cell universe, we can construct a 17x17 rectangular lattice with a 1.26 cm pitch." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Create fuel assembly Lattice\n", + "assembly = openmc.RectLattice(name='1.6% Fuel Assembly')\n", + "assembly.pitch = (1.26, 1.26)\n", + "assembly.lower_left = [-1.26 * 17. / 2.0] * 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we create a NumPy array of fuel pin and guide tube universes for the lattice." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create array indices for guide tube locations in lattice\n", + "template_x = np.array([5, 8, 11, 3, 13, 2, 5, 8, 11, 14, 2, 5, 8,\n", + " 11, 14, 2, 5, 8, 11, 14, 3, 13, 5, 8, 11])\n", + "template_y = np.array([2, 2, 2, 3, 3, 5, 5, 5, 5, 5, 8, 8, 8, 8,\n", + " 8, 11, 11, 11, 11, 11, 13, 13, 14, 14, 14])\n", + "\n", + "# Initialize an empty 17x17 array of the lattice universes\n", + "universes = np.empty((17, 17), dtype=openmc.Universe)\n", + "\n", + "# Fill the array with the fuel pin and guide tube universes\n", + "universes[:,:] = fuel_pin_universe\n", + "universes[template_x, template_y] = guide_tube_universe\n", + "\n", + "# Store the array of universes in the lattice\n", + "assembly.universes = universes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "OpenMC requires that there is a \"root\" universe. Let us create a root cell that is filled by the pin cell universe and then assign it to the root universe." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Create root Cell\n", + "root_cell = openmc.Cell(name='root cell')\n", + "root_cell.fill = assembly\n", + "\n", + "# Add boundary planes\n", + "root_cell.region = +min_x & -max_x & +min_y & -max_y & +min_z & -max_z\n", + "\n", + "# Create root Universe\n", + "root_universe = openmc.Universe(name='root universe', universe_id=0)\n", + "root_universe.add_cell(root_cell)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We now must create a geometry that is assigned a root universe and export it to XML." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Create Geometry and set root Universe\n", + "geometry = openmc.Geometry()\n", + "geometry.root_universe = root_universe\n", + "# Export to \"geometry.xml\"\n", + "geometry.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With the geometry and materials finished, we now just need to define simulation parameters. In this case, we will use 10 inactive batches and 40 active batches each with 5000 particles." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# OpenMC simulation parameters\n", + "batches = 50\n", + "inactive = 10\n", + "particles = 5000\n", + "\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", + "settings_file.batches = batches\n", + "settings_file.inactive = inactive\n", + "settings_file.particles = particles\n", + "settings_file.output = {'tallies': False}\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", + "bounds = [-10.71, -10.71, -10, 10.71, 10.71, 10.]\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", + "\n", + "# Export to \"settings.xml\"\n", + "settings_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let us also create a Plots file that we can use to verify that our fuel assembly geometry was created successfully." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Instantiate a Plot\n", + "plot = openmc.Plot()\n", + "plot.filename = 'materials-xy'\n", + "plot.origin = [0, 0, 0]\n", + "plot.pixels = [250, 250]\n", + "plot.width = [-10.71*2, -10.71*2]\n", + "plot.color = 'mat'\n", + "\n", + "# Instantiate a Plots object, add Plot, and export to \"plots.xml\"\n", + "plot_file = openmc.Plots([plot])\n", + "plot_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With the plots.xml file, we can now generate and view the plot. OpenMC outputs plots in .ppm format, which can be converted into a compressed format like .png with the convert utility." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Run openmc in plotting mode\n", + "openmc.plot_geometry(output=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nVDE0OjIwOjUzLTA0OjAwMSw5XwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Convert OpenMC's funky ppm to png\n", + "!convert materials-xy.ppm materials-xy.png\n", + "\n", + "# Display the materials plot inline\n", + "Image(filename='materials-xy.png')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see from the plot, we have a nice array of fuel and guide tube pin cells with fuel, cladding, and water!\n", + "\n", + "# Create an MGXS Library\n", + "\n", + "Now we are ready to generate multi-group cross sections! First, let's define a 2-group structure using the built-in EnergyGroups class." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Instantiate a 2-group EnergyGroups object\n", + "groups = openmc.mgxs.EnergyGroups()\n", + "groups.group_edges = np.array([0., 0.625e-6, 20.])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we will instantiate an openmc.mgxs.Library for the energy groups with our the fuel assembly geometry." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Initialize an 2-group MGXS Library for OpenMOC\n", + "mgxs_lib = openmc.mgxs.Library(geometry)\n", + "mgxs_lib.energy_groups = groups" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we must specify to the Library which types of cross sections to compute. OpenMC's multi-group mode can accept isotropic flux-weighted cross sections or angle-dependent cross sections, as well as supporting anisotropic scattering represented by either Legendre polynomials, histogram, or tabular angular distributions. At this time the MGXS Library class only supports the generation of isotropic flux-weighted cross sections and P0 scattering, so that is what will be used for this example. Therefore, we will create the following multi-group cross sections needed to run an OpenMC simulation to verify the accuracy of our cross sections: \"total\", \"absorption\", \"nu-fission\", '\"fission\", \"nu-scatter matrix\", \"multiplicity matrix\", and \"chi\".\n", + "\"multiplicity matrix\" is needed to provide OpenMC's multi-group mode with additional information needed to accurately treat scattering multiplication (i.e., (n,xn) reactions)) explicitly." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Specify multi-group cross section types to compute\n", + "mgxs_lib.mgxs_types = ['total', 'absorption', 'nu-fission', 'fission',\n", + " 'nu-scatter matrix', 'multiplicity matrix', 'chi']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we must specify the type of domain over which we would like the `Library` to compute multi-group cross sections. The domain type corresponds to the type of tally filter to be used in the tallies created to compute multi-group cross sections. At the present time, the `Library` supports \"material,\" \"cell,\" and \"universe\" domain types. In this simple example, we wish to compute multi-group cross sections only for each material andtherefore will use a \"material\" domain type.\n", + "\n", + "**Note:** By default, the `Library` class will instantiate `MGXS` objects for each and every domain (material, cell or universe) in the geometry of interest. However, one may specify a subset of these domains to the `Library.domains` property." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Specify a \"cell\" domain type for the cross section tally filters\n", + "mgxs_lib.domain_type = \"material\"\n", + "\n", + "# Specify the cell domains over which to compute multi-group cross sections\n", + "mgxs_lib.domains = geometry.get_all_materials()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will instruct the library to not compute cross sections on a nuclide-by-nuclide basis, and instead to focus on generating material-specific macroscopic cross sections.\n", + "\n", + "**NOTE:** The default value of the `by_nuclide` parameter is `False`, so the following step is not necessary but is included for illustrative purposes." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Do not compute cross sections on a nuclide-by-nuclide basis\n", + "mgxs_lib.by_nuclide = False" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we will set the scattering order that we wish to use. For this problem we will use P3 scattering. A warning is expected telling us that the default behavior (a P0 correction on the scattering data) is over-ridden by our choice of using a Legendre expansion to treat anisotropic scattering." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/nelsonag/git/openmc/openmc/mgxs/library.py:320: RuntimeWarning: The P0 correction will be ignored since the scattering order 0 is greater than zero\n", + " warnings.warn(msg, RuntimeWarning)\n" + ] + } + ], + "source": [ + "# Set the Legendre order to 3 for P3 scattering\n", + "mgxs_lib.legendre_order = 3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that the `Library` has been setup, lets make sure it contains the types of cross sections which meet the needs of OpenMC's multi-group solver. Note that this step is done automatically when writing the Multi-Group Library file later in the process (as part of the `mgxs_lib.write_mg_library()`), but it is a good practice to also run this before spending all the time running OpenMC to generate the cross sections." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Check the library - if no errors are raised, then the library is satisfactory.\n", + "mgxs_lib.check_library_for_openmc_mgxs()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lastly, we use the `Library` to construct the tallies needed to compute all of the requested multi-group cross sections in each domain and nuclide." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Construct all tallies needed for the multi-group cross section library\n", + "mgxs_lib.build_library()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The tallies can now be export to a \"tallies.xml\" input file for OpenMC.\n", + "\n", + "**NOTE:** At this point the `Library` has constructed nearly 100 distinct Tally objects. The overhead to tally in OpenMC scales as O(N) for N tallies, which can become a bottleneck for large tally datasets. To compensate for this, the Python API's `Tally`, `Filter` and `Tallies` classes allow for the smart merging of tallies when possible. The `Library` class supports this runtime optimization with the use of the optional `merge` parameter (`False` by default) for the `Library.add_to_tallies_file(...)` method, as shown below." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Create a \"tallies.xml\" file for the MGXS Library\n", + "tallies_file = openmc.Tallies()\n", + "mgxs_lib.add_to_tallies_file(tallies_file, merge=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition, we instantiate a fission rate mesh tally to compare with the multi-group result." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Instantiate a tally Mesh\n", + "mesh = openmc.Mesh()\n", + "mesh.type = 'regular'\n", + "mesh.dimension = [17, 17]\n", + "mesh.lower_left = [-10.71, -10.71]\n", + "mesh.upper_right = [+10.71, +10.71]\n", + "\n", + "# Instantiate tally Filter\n", + "mesh_filter = openmc.Filter()\n", + "mesh_filter.mesh = mesh\n", + "\n", + "# Instantiate the Tally\n", + "tally = openmc.Tally(name='mesh tally')\n", + "tally.filters = [mesh_filter]\n", + "tally.scores = ['fission']\n", + "\n", + "# Add tally to collection\n", + "tallies_file.append(tally, merge=True)\n", + "\n", + "# Export all tallies to a \"tallies.xml\" file\n", + "tallies_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "Time to run the calculation and get our results!" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " .d88888b. 888b d888 .d8888b.\n", + " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", + " 888 888 88888b.d88888 888 888\n", + " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", + " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", + " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", + " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", + " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", + "__________________888______________________________________________________\n", + " 888\n", + " 888\n", + "\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", + " Version: 0.7.1\n", + " Git SHA1: d20322f22d4850bd640b4accf34e2551550d17fb\n", + " Date/Time: 2016-05-30 14:20:53\n", + " OpenMP Threads: 4\n", + "\n", + " ===========================================================================\n", + " ========================> INITIALIZATION <=========================\n", + " ===========================================================================\n", + "\n", + " Reading settings XML file...\n", + " Reading cross sections XML file...\n", + " Reading geometry XML file...\n", + " Reading materials XML file...\n", + " Reading tallies XML file...\n", + " Building neighboring cells lists for each surface...\n", + " Loading ACE cross section table: 92235.71c\n", + " Loading ACE cross section table: 92238.71c\n", + " Loading ACE cross section table: 8016.71c\n", + " Loading ACE cross section table: 40090.71c\n", + " Loading ACE cross section table: 1001.71c\n", + " Loading ACE cross section table: 5010.71c\n", + " Maximum neutron transport energy: 20.0000 MeV for 92235.71c\n", + " Initializing source particles...\n", + "\n", + " ===========================================================================\n", + " ====================> K EIGENVALUE SIMULATION <====================\n", + " ===========================================================================\n", + "\n", + " Bat./Gen. k Average k \n", + " ========= ======== ==================== \n", + " 1/1 1.05201 \n", + " 2/1 1.02017 \n", + " 3/1 1.02398 \n", + " 4/1 1.02677 \n", + " 5/1 1.01070 \n", + " 6/1 1.02964 \n", + " 7/1 1.02163 \n", + " 8/1 1.04524 \n", + " 9/1 1.00773 \n", + " 10/1 1.01536 \n", + " 11/1 1.02992 \n", + " 12/1 1.03248 1.03120 +/- 0.00128\n", + " 13/1 0.99044 1.01761 +/- 0.01361\n", + " 14/1 1.01484 1.01692 +/- 0.00965\n", + " 15/1 1.01491 1.01652 +/- 0.00748\n", + " 16/1 1.03809 1.02011 +/- 0.00709\n", + " 17/1 1.02536 1.02086 +/- 0.00604\n", + " 18/1 1.03663 1.02283 +/- 0.00559\n", + " 19/1 1.03902 1.02463 +/- 0.00525\n", + " 20/1 1.01557 1.02373 +/- 0.00478\n", + " 21/1 1.01286 1.02274 +/- 0.00443\n", + " 22/1 1.01392 1.02200 +/- 0.00411\n", + " 23/1 1.04439 1.02372 +/- 0.00416\n", + " 24/1 1.04034 1.02491 +/- 0.00403\n", + " 25/1 0.99433 1.02287 +/- 0.00427\n", + " 26/1 1.02720 1.02314 +/- 0.00400\n", + " 27/1 1.03545 1.02387 +/- 0.00383\n", + " 28/1 1.03853 1.02468 +/- 0.00370\n", + " 29/1 1.02735 1.02482 +/- 0.00350\n", + " 30/1 1.02429 1.02480 +/- 0.00332\n", + " 31/1 1.02901 1.02500 +/- 0.00317\n", + " 32/1 1.03296 1.02536 +/- 0.00304\n", + " 33/1 1.03605 1.02582 +/- 0.00294\n", + " 34/1 1.04247 1.02652 +/- 0.00290\n", + " 35/1 1.02088 1.02629 +/- 0.00279\n", + " 36/1 1.03017 1.02644 +/- 0.00269\n", + " 37/1 1.03216 1.02665 +/- 0.00259\n", + " 38/1 1.01459 1.02622 +/- 0.00254\n", + " 39/1 1.03706 1.02659 +/- 0.00248\n", + " 40/1 1.01383 1.02617 +/- 0.00243\n", + " 41/1 0.99043 1.02502 +/- 0.00262\n", + " 42/1 1.02891 1.02514 +/- 0.00254\n", + " 43/1 1.02100 1.02501 +/- 0.00246\n", + " 44/1 0.99546 1.02414 +/- 0.00254\n", + " 45/1 1.01562 1.02390 +/- 0.00248\n", + " 46/1 1.03025 1.02408 +/- 0.00242\n", + " 47/1 0.99409 1.02327 +/- 0.00249\n", + " 48/1 1.04355 1.02380 +/- 0.00248\n", + " 49/1 1.02763 1.02390 +/- 0.00242\n", + " 50/1 0.99426 1.02316 +/- 0.00247\n", + " Creating state point statepoint.50.h5...\n", + "\n", + " ===========================================================================\n", + " ======================> SIMULATION FINISHED <======================\n", + " ===========================================================================\n", + "\n", + "\n", + " =======================> TIMING STATISTICS <=======================\n", + "\n", + " Total time for initialization = 1.4260E+00 seconds\n", + " Reading cross sections = 1.1340E+00 seconds\n", + " Total time in simulation = 1.6739E+01 seconds\n", + " Time in transport only = 1.6650E+01 seconds\n", + " Time in inactive batches = 2.1540E+00 seconds\n", + " Time in active batches = 1.4585E+01 seconds\n", + " Time synchronizing fission bank = 1.0000E-02 seconds\n", + " Sampling source sites = 9.0000E-03 seconds\n", + " SEND/RECV source sites = 1.0000E-03 seconds\n", + " Time accumulating tallies = 0.0000E+00 seconds\n", + " Total time for finalization = 0.0000E+00 seconds\n", + " Total time elapsed = 1.8174E+01 seconds\n", + " Calculation Rate (inactive) = 23212.6 neutrons/second\n", + " Calculation Rate (active) = 13712.7 neutrons/second\n", + "\n", + " ============================> RESULTS <============================\n", + "\n", + " k-effective (Collision) = 1.02389 +/- 0.00235\n", + " k-effective (Track-length) = 1.02316 +/- 0.00247\n", + " k-effective (Absorption) = 1.02494 +/- 0.00180\n", + " Combined k-effective = 1.02429 +/- 0.00140\n", + " Leakage Fraction = 0.00000 +/- 0.00000\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Run OpenMC\n", + "openmc.run()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To make the files available and not be over-written when running the multi-group calculation, we will now rename the statepoint and summary files." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Move the StatePoint File\n", + "ce_spfile = './ce_statepoint.h5'\n", + "os.rename('statepoint.' + str(batches) + '.h5', ce_spfile)\n", + "# Move the Summary file\n", + "ce_sumfile = './ce_summary.h5'\n", + "os.rename('summary.h5', ce_sumfile)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tally Data Processing\n", + "\n", + "Our simulation ran successfully and created statepoint and summary output files. Let's begin by loading the StatePoint file, but not automatically linking the summary file." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Load the statepoint file, but not the summary file, as it is a different filename than expected.\n", + "sp = openmc.StatePoint(ce_spfile, autolink=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition to the statepoint file, our simulation also created a summary file which encapsulates information about the materials and geometry. This is necessary for the `openmc.mgxs` module to properly process the tally data. We first create a `Summary` object and link it with the statepoint. Normally this would not need to be performed, but since we have renamed our summary file to avoid conflicts with the Multi-Group calculation's summary file, we will load this in explicitly." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "su = openmc.Summary(ce_sumfile)\n", + "sp.link_with_summary(su)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The statepoint is now ready to be analyzed by the `Library`. We simply have to load the tallies from the statepoint into the `Library` and our `MGXS` objects will compute the cross sections for us under-the-hood." + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Initialize MGXS Library with OpenMC statepoint data\n", + "mgxs_lib.load_from_statepoint(sp)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The next step will be to prepare the input for OpenMC to use our newly created multi-group data." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Multi-Group OpenMC Calculation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will now use the `Library` to produce a multi-group cross section data set for use by the OpenMC multi-group solver. \n", + "Note that since this simulation included so few histories, it is reasonable to expect some divisions by zero errors. This will show up as a runtime warning in the following step." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/nelsonag/git/openmc/openmc/tallies.py:1986: RuntimeWarning: invalid value encountered in true_divide\n", + " self_rel_err = data['self']['std. dev.'] / data['self']['mean']\n", + "/home/nelsonag/git/openmc/openmc/tallies.py:1987: RuntimeWarning: invalid value encountered in true_divide\n", + " other_rel_err = data['other']['std. dev.'] / data['other']['mean']\n", + "/home/nelsonag/git/openmc/openmc/tallies.py:1988: RuntimeWarning: invalid value encountered in true_divide\n", + " new_tally._mean = data['self']['mean'] / data['other']['mean']\n" + ] + } + ], + "source": [ + "# Create a MGXS File which can then be written to disk\n", + "mgxs_file = mgxs_lib.create_mg_library(xs_type='macro', xsdata_names=['fuel', 'zircaloy', 'water'],\n", + " xs_ids='2m')\n", + "\n", + "# Write the file to disk using the default filename of `mgxs.xml`\n", + "mgxs_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "OpenMC's multi-group mode uses the same input files as does the continuous-energy mode (materials, geometry, settings, plots ,and tallies file). Differences would include the use of a flag to tell the code to use multi-group transport, a location of the multi-group library file, and any changes needed in the materials.xml and geometry.xml files to re-define materials as necessary (for example, if using a macroscopic cross section library instead of individual microscopic nuclide cross sections as is done in continuous-energy, or if multiple cross sections exist for the same material due to the material existing in varied spectral regions).\n", + "\n", + "Since this example is using material-wise macroscopic cross sections without considering that the neutron energy spectra and thus cross sections may be changing in space, we only need to modify the materials.xml and settings.xml files. If the material names and ids are not otherwise changed, then the geometry.xml file does not need to be modified from its continuous-energy form. The tallies.xml file will be left untouched as it currently contains the tally types that we will need to perform our comparison. \n", + "\n", + "First we will create the new materials.xml file. Continuous-energy cross section nuclidic data sets are named with the nuclide name followed by a cross section identifier. For example, the data for hydrogen is accessed in OpenMC by the name `H-1.71c`. The cross-section identifier (in this case, `71c`) can be used to distinguish between different variants of `H-1` data, such as for different evaluations or temperatures. OpenMC multi-group libraries use the same convention of a name followed by a xs identifier. We will use a cross section identifier here of `2m`. Similar to how continuous-energy cross section libraries are named, the `openmc.Macroscopic` quantities below can either have their `xs_id` included (i.e., `'fuel.2m'`). An alternative is to leave this extension off and simply change the `default_xs` parameter to `.2m`." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Instantiate our Macroscopic Data\n", + "fuel_macro = openmc.Macroscopic('fuel')\n", + "zircaloy_macro = openmc.Macroscopic('zircaloy')\n", + "water_macro = openmc.Macroscopic('water')\n", + "\n", + "# Now re-define our materials to use the Multi-Group macroscopic data\n", + "# instead of the continuous-energy data.\n", + "# 1.6 enriched fuel UO2\n", + "fuel = openmc.Material(name='UO2')\n", + "fuel.add_macroscopic(fuel_macro)\n", + "\n", + "# cladding\n", + "zircaloy = openmc.Material(name='Clad')\n", + "zircaloy.add_macroscopic(zircaloy_macro)\n", + "\n", + "# moderator\n", + "water = openmc.Material(name='Water')\n", + "water.add_macroscopic(water_macro)\n", + "\n", + "# Finally, instantiate our Materials object\n", + "materials_file = openmc.Materials((fuel, zircaloy, water))\n", + "materials_file.default_xs = '2m'\n", + "\n", + "# Export to \"materials.xml\"\n", + "materials_file.export_to_xml()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "No geometry file neeeds to be written as the continuous-energy file is correctly defined for the multi-group case as well." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we can make the changes we need to the settings file.\n", + "These changes are limited to telling OpenMC we will be running a multi-group calculation and pointing to the location of our multi-group cross section file." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Set the location of the cross sections file\n", + "settings_file.cross_sections = './mgxs.xml'\n", + "settings_file.energy_mode = 'multi-group'\n", + "\n", + "# Export to \"settings.xml\"\n", + "settings_file.export_to_xml()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, since we want similar tally data in the end, we will leave our pre-existing `tallies.xml` file for this calculation.\n", + "\n", + "At this point, the problem is set up and we can run the multi-group calculation." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " .d88888b. 888b d888 .d8888b.\n", + " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", + " 888 888 88888b.d88888 888 888\n", + " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", + " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", + " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", + " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", + " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", + "__________________888______________________________________________________\n", + " 888\n", + " 888\n", + "\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", + " Version: 0.7.1\n", + " Git SHA1: d20322f22d4850bd640b4accf34e2551550d17fb\n", + " Date/Time: 2016-05-30 14:21:12\n", + " OpenMP Threads: 4\n", + "\n", + " ===========================================================================\n", + " ========================> INITIALIZATION <=========================\n", + " ===========================================================================\n", + "\n", + " Reading settings XML file...\n", + " Reading cross sections XML file...\n", + " Reading geometry XML file...\n", + " Reading materials XML file...\n", + " Reading tallies XML file...\n", + " Building neighboring cells lists for each surface...\n", + " Loading Cross Section Data...\n", + " Loading fuel.2m Data...\n", + " Loading zircaloy.2m Data...\n", + " Loading water.2m Data...\n", + " Initializing source particles...\n", + "\n", + " ===========================================================================\n", + " ====================> K EIGENVALUE SIMULATION <====================\n", + " ===========================================================================\n", + "\n", + " Bat./Gen. k Average k \n", + " ========= ======== ==================== \n", + " 1/1 1.06913 \n", + " 2/1 1.04067 \n", + " 3/1 1.01854 \n", + " 4/1 1.00203 \n", + " 5/1 1.03243 \n", + " 6/1 1.02688 \n", + " 7/1 1.06855 \n", + " 8/1 1.03420 \n", + " 9/1 1.01657 \n", + " 10/1 1.02795 \n", + " 11/1 1.01796 \n", + " 12/1 1.03372 1.02584 +/- 0.00788\n", + " 13/1 1.02433 1.02534 +/- 0.00458\n", + " 14/1 1.01147 1.02187 +/- 0.00474\n", + " 15/1 1.01215 1.01993 +/- 0.00416\n", + " 16/1 1.04088 1.02342 +/- 0.00487\n", + " 17/1 1.04033 1.02583 +/- 0.00477\n", + " 18/1 1.04483 1.02821 +/- 0.00477\n", + " 19/1 1.02870 1.02826 +/- 0.00420\n", + " 20/1 1.01339 1.02678 +/- 0.00404\n", + " 21/1 1.03389 1.02742 +/- 0.00371\n", + " 22/1 1.02535 1.02725 +/- 0.00340\n", + " 23/1 1.00225 1.02533 +/- 0.00367\n", + " 24/1 0.99938 1.02347 +/- 0.00387\n", + " 25/1 1.01620 1.02299 +/- 0.00363\n", + " 26/1 1.03393 1.02367 +/- 0.00347\n", + " 27/1 1.01875 1.02338 +/- 0.00327\n", + " 28/1 1.00305 1.02225 +/- 0.00328\n", + " 29/1 1.01453 1.02185 +/- 0.00313\n", + " 30/1 1.02891 1.02220 +/- 0.00299\n", + " 31/1 0.99612 1.02096 +/- 0.00311\n", + " 32/1 1.04911 1.02224 +/- 0.00323\n", + " 33/1 1.01410 1.02188 +/- 0.00310\n", + " 34/1 0.98979 1.02055 +/- 0.00326\n", + " 35/1 1.00938 1.02010 +/- 0.00316\n", + " 36/1 1.02857 1.02043 +/- 0.00305\n", + " 37/1 1.04095 1.02119 +/- 0.00303\n", + " 38/1 1.02033 1.02115 +/- 0.00292\n", + " 39/1 1.02104 1.02115 +/- 0.00282\n", + " 40/1 1.00854 1.02073 +/- 0.00276\n", + " 41/1 1.00932 1.02036 +/- 0.00269\n", + " 42/1 1.00284 1.01982 +/- 0.00266\n", + " 43/1 1.02489 1.01997 +/- 0.00258\n", + " 44/1 1.03981 1.02055 +/- 0.00257\n", + " 45/1 1.02630 1.02072 +/- 0.00251\n", + " 46/1 1.00133 1.02018 +/- 0.00249\n", + " 47/1 1.02409 1.02028 +/- 0.00243\n", + " 48/1 1.03928 1.02078 +/- 0.00241\n", + " 49/1 1.01226 1.02057 +/- 0.00236\n", + " 50/1 1.03536 1.02094 +/- 0.00233\n", + " Creating state point statepoint.50.h5...\n", + "\n", + " ===========================================================================\n", + " ======================> SIMULATION FINISHED <======================\n", + " ===========================================================================\n", + "\n", + "\n", + " =======================> TIMING STATISTICS <=======================\n", + "\n", + " Total time for initialization = 2.8000E-02 seconds\n", + " Reading cross sections = 4.0000E-03 seconds\n", + " Total time in simulation = 1.2816E+01 seconds\n", + " Time in transport only = 1.2770E+01 seconds\n", + " Time in inactive batches = 1.3130E+00 seconds\n", + " Time in active batches = 1.1503E+01 seconds\n", + " Time synchronizing fission bank = 9.0000E-03 seconds\n", + " Sampling source sites = 3.0000E-03 seconds\n", + " SEND/RECV source sites = 6.0000E-03 seconds\n", + " Time accumulating tallies = 0.0000E+00 seconds\n", + " Total time for finalization = 0.0000E+00 seconds\n", + " Total time elapsed = 1.2854E+01 seconds\n", + " Calculation Rate (inactive) = 38080.7 neutrons/second\n", + " Calculation Rate (active) = 17386.8 neutrons/second\n", + "\n", + " ============================> RESULTS <============================\n", + "\n", + " k-effective (Collision) = 1.02358 +/- 0.00231\n", + " k-effective (Track-length) = 1.02094 +/- 0.00233\n", + " k-effective (Absorption) = 1.02682 +/- 0.00152\n", + " Combined k-effective = 1.02527 +/- 0.00153\n", + " Leakage Fraction = 0.00000 +/- 0.00000\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Run the Multi-Group OpenMC Simulation\n", + "openmc.run()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Results Comparison\n", + "Now we can compare the multi-group and continuous-energy results.\n", + "\n", + "We will begin by loading the multi-group statepoint file we just finished writing and extracting the calculated keff.\n", + "Since we did not rename the summary file, we do not need to load it separately this time." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Load the last statepoint file and keff value\n", + "mgsp = openmc.StatePoint('statepoint.' + str(batches) + '.h5')\n", + "mg_keff = mgsp.k_combined" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we can load the continuous-energy eigenvalue for comparison." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ce_keff = sp.k_combined" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lets compare the two eigenvalues, including their bias" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Continuous-Energy keff = 1.024295\n", + "Multi-Group keff = 1.025274\n", + "bias [pcm]: -97.9\n" + ] + } + ], + "source": [ + "bias = 1.0E5 * (ce_keff[0] - mg_keff[0])\n", + "\n", + "print('Continuous-Energy keff = {0:1.6f}'.format(ce_keff[0]))\n", + "print('Multi-Group keff = {0:1.6f}'.format(mg_keff[0]))\n", + "print('bias [pcm]: {0:1.1f}'.format(bias))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This shows a small but nontrivial pcm bias between the two methods. Some degree of mismatch is expected simply to the very few histories being used in these example problems. An additional mismatch is always inherent in the practical application of multi-group theory due to the high degree of approximations inherent in that method." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Flux and Pin Power Visualizations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next we will visualize the mesh tally results obtained from both the Continuous-Energy and Multi-Group OpenMC calculations.\n", + "\n", + "First, we extract volume-integrated fission rates from the Multi-Group calculation's mesh fission rate tally for each pin cell in the fuel assembly." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Get the OpenMC fission rate mesh tally data\n", + "mg_mesh_tally = mgsp.get_tally(name='mesh tally')\n", + "mg_fission_rates = mg_mesh_tally.get_values(scores=['fission'])\n", + "\n", + "# Reshape array to 2D for plotting\n", + "mg_fission_rates.shape = (17,17)\n", + "\n", + "# Normalize to the average pin power\n", + "mg_fission_rates /= np.mean(mg_fission_rates)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can do the same for the Continuous-Energy results." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Get the OpenMC fission rate mesh tally data\n", + "ce_mesh_tally = sp.get_tally(name='mesh tally')\n", + "ce_fission_rates = ce_mesh_tally.get_values(scores=['fission'])\n", + "\n", + "# Reshape array to 2D for plotting\n", + "ce_fission_rates.shape = (17,17)\n", + "\n", + "# Normalize to the average pin power\n", + "ce_fission_rates /= np.mean(ce_fission_rates)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can easily use Matplotlib to visualize the two fission rates side-by-side." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Force zeros to be NaNs so their values are not included when matplotlib calculates\n", + "# the color scale\n", + "ce_fission_rates[ce_fission_rates == 0.] = np.nan\n", + "mg_fission_rates[mg_fission_rates == 0.] = np.nan\n", + "\n", + "# Plot the CE fission rates in the left subplot\n", + "fig = plt.subplot(121)\n", + "plt.imshow(ce_fission_rates, interpolation='none', cmap='jet')\n", + "plt.title('Continuous-Energy Fission Rates')\n", + "\n", + "# Plot the MG fission rates in the right subplot\n", + "fig2 = plt.subplot(122)\n", + "plt.imshow(mg_fission_rates, interpolation='none', cmap='jet')\n", + "plt.title('Multi-Group Fission Rates')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "We also see very good agreement between the fission rate distributions, though these should converge closer together with an increasing number of particle histories in both the continuous-energy run to generate the multi-group cross sections, and in the multi-group calculation itself." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.1" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/docs/source/pythonapi/examples/mgxs-part-iv.rst b/docs/source/pythonapi/examples/mgxs-part-iv.rst new file mode 100644 index 000000000..e24325521 --- /dev/null +++ b/docs/source/pythonapi/examples/mgxs-part-iv.rst @@ -0,0 +1,13 @@ +.. _notebook_mgxs_part_iv: + +==================================================== +MGXS Part IV: Multi-Group Mode Cross-Section Library +==================================================== + +.. only:: html + + .. notebook:: mgxs-part-iv.ipynb + +.. only:: latex + + IPython notebooks must be viewed in the online HTML documentation. diff --git a/docs/source/pythonapi/examples/pandas-dataframes.ipynb b/docs/source/pythonapi/examples/pandas-dataframes.ipynb index ac5d4e410..2c222ad6e 100644 --- a/docs/source/pythonapi/examples/pandas-dataframes.ipynb +++ b/docs/source/pythonapi/examples/pandas-dataframes.ipynb @@ -17,19 +17,14 @@ }, "outputs": [], "source": [ + "%matplotlib inline\n", "import glob\n", "from IPython.display import Image\n", - "import matplotlib.pylab as pylab\n", + "import matplotlib.pyplot as plt\n", "import scipy.stats\n", "import numpy as np\n", "\n", - "import openmc\n", - "from openmc.statepoint import StatePoint\n", - "from openmc.summary import Summary\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", - "\n", - "%matplotlib inline" + "import openmc" ] }, { @@ -113,11 +108,8 @@ }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, add Materials\n", - "materials_file = openmc.MaterialsFile()\n", - "materials_file.add_material(fuel)\n", - "materials_file.add_material(water)\n", - "materials_file.add_material(zircaloy)\n", + "# Instantiate a Materials collection\n", + "materials_file = openmc.Materials((fuel, water, zircaloy))\n", "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", @@ -207,7 +199,6 @@ "source": [ "# Create fuel assembly Lattice\n", "assembly = openmc.RectLattice(name='1.6% Fuel - 0BA')\n", - "assembly.dimension = (17, 17)\n", "assembly.pitch = (1.26, 1.26)\n", "assembly.lower_left = [-1.26 * 17. / 2.0] * 2\n", "assembly.universes = [[pin_cell_universe] * 17] * 17" @@ -244,7 +235,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We now must create a geometry that is assigned a root universe, put the geometry into a `GeometryFile` object, and export it to XML." + "We now must create a geometry that is assigned a root universe and export it to XML." ] }, { @@ -268,12 +259,8 @@ }, "outputs": [], "source": [ - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "geometry.export_to_xml()" ] }, { @@ -297,17 +284,19 @@ "inactive = 5\n", "particles = 2500\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = min_batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "settings_file.output = {'tallies': False}\n", "settings_file.trigger_active = True\n", "settings_file.trigger_max_batches = max_batches\n", - "source_bounds = [-10.71, -10.71, -10, 10.71, 10.71, 10.]\n", - "settings_file.source = Source(space=Box(\n", - " source_bounds[:3], source_bounds[3:]))\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", + "bounds = [-10.71, -10.71, -10, 10.71, 10.71, 10.]\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Export to \"settings.xml\"\n", "settings_file.export_to_xml()" @@ -336,9 +325,8 @@ "plot.pixels = [250, 250]\n", "plot.color = 'mat'\n", "\n", - "# Instantiate a PlotsFile, add Plot, and export to \"plots.xml\"\n", - "plot_file = openmc.PlotsFile()\n", - "plot_file.add_plot(plot)\n", + "# Instantiate a Plots collection and export to \"plots.xml\"\n", + "plot_file = openmc.Plots([plot])\n", "plot_file.export_to_xml()" ] }, @@ -369,8 +357,7 @@ ], "source": [ "# Run openmc in plotting mode\n", - "executor = openmc.Executor()\n", - "executor.plot_geometry(output=False)" + "openmc.plot_geometry(output=False)" ] }, { @@ -382,7 +369,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAAAFzUkdC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\nMI88x3kAAAAASUVORK5CYII=\n", "text/plain": [ "" ] @@ -415,8 +402,8 @@ }, "outputs": [], "source": [ - "# Instantiate an empty TalliesFile\n", - "tallies_file = openmc.TalliesFile()\n", + "# Instantiate an empty Tallies object\n", + "tallies_file = openmc.Tallies()\n", "tallies_file._tallies = []" ] }, @@ -453,14 +440,11 @@ "\n", "# Instantiate the Tally\n", "tally = openmc.Tally(name='mesh tally')\n", - "tally.add_filter(mesh_filter)\n", - "tally.add_filter(energy_filter)\n", - "tally.add_score('fission')\n", - "tally.add_score('nu-fission')\n", + "tally.filters = [mesh_filter, energy_filter]\n", + "tally.scores = ['fission', 'nu-fission']\n", "\n", - "# Add mesh and Tally to TalliesFile\n", - "tallies_file.add_mesh(mesh)\n", - "tallies_file.add_tally(tally)" + "# Add mesh and Tally to Tallies\n", + "tallies_file.append(tally)" ] }, { @@ -483,13 +467,12 @@ "\n", "# Instantiate the tally\n", "tally = openmc.Tally(name='cell tally')\n", - "tally.add_filter(cell_filter)\n", - "tally.add_score('scatter-y2')\n", - "tally.add_nuclide(u235)\n", - "tally.add_nuclide(u238)\n", + "tally.filters = [cell_filter]\n", + "tally.scores = ['scatter-y2']\n", + "tally.nuclides = [u235, u238]\n", "\n", - "# Add mesh and tally to TalliesFile\n", - "tallies_file.add_tally(tally)" + "# Add mesh and tally to Tallies\n", + "tallies_file.append(tally)" ] }, { @@ -503,7 +486,7 @@ "cell_type": "code", "execution_count": 18, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ @@ -512,17 +495,16 @@ "\n", "# Instantiate tally Trigger for kicks\n", "trigger = openmc.Trigger(trigger_type='std_dev', threshold=5e-5)\n", - "trigger.add_score('absorption')\n", + "trigger.scores = ['absorption']\n", "\n", "# Instantiate the Tally\n", "tally = openmc.Tally(name='distribcell tally')\n", - "tally.add_filter(distribcell_filter)\n", - "tally.add_score('absorption')\n", - "tally.add_score('scatter')\n", - "tally.add_trigger(trigger)\n", + "tally.filters = [distribcell_filter]\n", + "tally.scores = ['absorption', 'scatter']\n", + "tally.triggers = [trigger]\n", "\n", - "# Add mesh and tally to TalliesFile\n", - "tallies_file.add_tally(tally)" + "# Add mesh and tally to Tallies\n", + "tallies_file.append(tally)" ] }, { @@ -568,11 +550,11 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.io/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: 34381b40a9445a727e360873aaa6ef892af1cb6a\n", - " Date/Time: 2016-02-07 16:01:57\n", + " Git SHA1: ae588276014a905ecc6e0967bf08288ecec5b550\n", + " Date/Time: 2016-05-09 23:01:18\n", " MPI Processes: 1\n", "\n", " ===========================================================================\n", @@ -600,35 +582,34 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 0.54958 \n", - " 2/1 0.67628 \n", - " 3/1 0.70618 \n", - " 4/1 0.66601 \n", - " 5/1 0.70876 \n", - " 6/1 0.69708 \n", - " 7/1 0.68623 0.69166 +/- 0.00543\n", - " 8/1 0.69159 0.69163 +/- 0.00313\n", - " 9/1 0.69908 0.69349 +/- 0.00289\n", - " 10/1 0.63865 0.68253 +/- 0.01120\n", - " 11/1 0.65439 0.67784 +/- 0.01027\n", - " 12/1 0.68518 0.67889 +/- 0.00875\n", - " 13/1 0.69507 0.68091 +/- 0.00784\n", - " 14/1 0.70129 0.68317 +/- 0.00728\n", - " 15/1 0.71336 0.68619 +/- 0.00717\n", - " 16/1 0.68725 0.68629 +/- 0.00649\n", - " 17/1 0.72579 0.68958 +/- 0.00678\n", - " 18/1 0.67149 0.68819 +/- 0.00639\n", - " 19/1 0.67771 0.68744 +/- 0.00596\n", - " 20/1 0.68035 0.68697 +/- 0.00557\n", - " Triggers unsatisfied, max unc./thresh. is 1.09851 for absorption in tally 10002\n", - " The estimated number of batches is 24\n", + " 1/1 0.55921 \n", + " 2/1 0.63816 \n", + " 3/1 0.68834 \n", + " 4/1 0.71192 \n", + " 5/1 0.67935 \n", + " 6/1 0.68274 \n", + " 7/1 0.66339 0.67307 +/- 0.00967\n", + " 8/1 0.65835 0.66816 +/- 0.00743\n", + " 9/1 0.66697 0.66786 +/- 0.00527\n", + " 10/1 0.70498 0.67528 +/- 0.00847\n", + " 11/1 0.68596 0.67706 +/- 0.00714\n", + " 12/1 0.68481 0.67817 +/- 0.00614\n", + " 13/1 0.68369 0.67886 +/- 0.00536\n", + " 14/1 0.68785 0.67986 +/- 0.00483\n", + " 15/1 0.66145 0.67802 +/- 0.00470\n", + " 16/1 0.71831 0.68168 +/- 0.00561\n", + " 17/1 0.68428 0.68190 +/- 0.00512\n", + " 18/1 0.67527 0.68139 +/- 0.00474\n", + " 19/1 0.68166 0.68141 +/- 0.00439\n", + " 20/1 0.65475 0.67963 +/- 0.00446\n", + " Triggers unsatisfied, max unc./thresh. is 1.07581 for absorption in tally 10002\n", + " The estimated number of batches is 23\n", " Creating state point statepoint.020.h5...\n", - " 21/1 0.68105 0.68660 +/- 0.00522\n", - " 22/1 0.67168 0.68572 +/- 0.00498\n", - " 23/1 0.67520 0.68514 +/- 0.00473\n", - " 24/1 0.67940 0.68483 +/- 0.00449\n", - " Triggers satisfied for batch 24\n", - " Creating state point statepoint.024.h5...\n", + " 21/1 0.64538 0.67749 +/- 0.00469\n", + " 22/1 0.73275 0.68074 +/- 0.00547\n", + " 23/1 0.71674 0.68274 +/- 0.00553\n", + " Triggers satisfied for batch 23\n", + " Creating state point statepoint.023.h5...\n", "\n", " ===========================================================================\n", " ======================> SIMULATION FINISHED <======================\n", @@ -637,28 +618,28 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.0900E-01 seconds\n", - " Reading cross sections = 7.8000E-02 seconds\n", - " Total time in simulation = 4.9560E+00 seconds\n", - " Time in transport only = 4.9400E+00 seconds\n", - " Time in inactive batches = 7.3100E-01 seconds\n", - " Time in active batches = 4.2250E+00 seconds\n", - " Time synchronizing fission bank = 4.0000E-03 seconds\n", - " Sampling source sites = 3.0000E-03 seconds\n", + " Total time for initialization = 3.9000E-01 seconds\n", + " Reading cross sections = 8.6000E-02 seconds\n", + " Total time in simulation = 1.0830E+01 seconds\n", + " Time in transport only = 1.0818E+01 seconds\n", + " Time in inactive batches = 1.3590E+00 seconds\n", + " Time in active batches = 9.4710E+00 seconds\n", + " Time synchronizing fission bank = 3.0000E-03 seconds\n", + " Sampling source sites = 2.0000E-03 seconds\n", " SEND/RECV source sites = 1.0000E-03 seconds\n", - " Time accumulating tallies = 1.0000E-03 seconds\n", + " Time accumulating tallies = 0.0000E+00 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 5.2780E+00 seconds\n", - " Calculation Rate (inactive) = 17099.9 neutrons/second\n", - " Calculation Rate (active) = 8875.74 neutrons/second\n", + " Total time elapsed = 1.1234E+01 seconds\n", + " Calculation Rate (inactive) = 9197.94 neutrons/second\n", + " Calculation Rate (active) = 3959.46 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 0.68264 +/- 0.00405\n", - " k-effective (Track-length) = 0.68483 +/- 0.00449\n", - " k-effective (Absorption) = 0.68225 +/- 0.00336\n", - " Combined k-effective = 0.68275 +/- 0.00346\n", - " Leakage Fraction = 0.34345 +/- 0.00167\n", + " k-effective (Collision) = 0.67952 +/- 0.00434\n", + " k-effective (Track-length) = 0.68274 +/- 0.00553\n", + " k-effective (Absorption) = 0.68095 +/- 0.00369\n", + " Combined k-effective = 0.67994 +/- 0.00349\n", + " Leakage Fraction = 0.34133 +/- 0.00332\n", "\n" ] }, @@ -677,8 +658,8 @@ "# Remove old HDF5 (summary, statepoint) files\n", "!rm statepoint.*\n", "\n", - "# Run OpenMC with MPI!\n", - "executor.run_simulation()" + "# Run OpenMC!\n", + "openmc.run()" ] }, { @@ -701,21 +682,7 @@ "statepoints = glob.glob('statepoint.*.h5')\n", "\n", "# Load the last statepoint file\n", - "sp = StatePoint(statepoints[-1])" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [], - "source": [ - "# Load the summary file and link with statepoint\n", - "su = Summary('summary.h5')\n", - "sp.link_with_summary(su)" + "sp = openmc.StatePoint(statepoints[-1])" ] }, { @@ -727,7 +694,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -766,7 +733,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false }, @@ -775,13 +742,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[[ 0.18257268]]\n", + "[[[ 0.1508711 ]]\n", "\n", - " [[ 0.07111957]]\n", + " [[ 0.05389822]]\n", "\n", - " [[ 0.40880276]]\n", + " [[ 0.19633 ]]\n", "\n", - " [[ 0.16407535]]]\n" + " [[ 0.12963172]]]\n" ] } ], @@ -796,7 +763,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -804,293 +771,304 @@ { "data": { "text/html": [ - "
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(mesh 1, x)(mesh 1, y)(mesh 1, z)mesh 1energy low [MeV]energy high [MeV]scoremeanstd. dev.
xyz
0 1 1 101110.00e+006.25e-07 fission2.02e-043.69e-05fission2.34e-043.54e-05
1 1 1 111110.00e+006.25e-07 nu-fission4.92e-048.98e-05nu-fission5.71e-048.62e-05
2 1 1 121116.25e-072.00e+01 fission7.62e-053.74e-06fission7.03e-057.05e-06
3 1 1 131116.25e-072.00e+01 nu-fission2.04e-049.88e-06nu-fission1.87e-041.76e-05
4 1 2 141210.00e+006.25e-07 fission3.75e-043.86e-05fission3.67e-043.61e-05
5 1 2 151210.00e+006.25e-07 nu-fission9.14e-049.41e-05nu-fission8.94e-048.80e-05
6 1 2 161216.25e-072.00e+01 fission1.07e-041.26e-05fission1.04e-045.36e-06
7 1 2 171216.25e-072.00e+01 nu-fission2.78e-043.16e-05nu-fission2.76e-041.40e-05
8 1 3 181310.00e+006.25e-07 fission5.64e-045.60e-05fission6.04e-045.57e-05
9 1 3 191310.00e+006.25e-07 nu-fission1.37e-031.37e-04nu-fission1.47e-031.36e-04
10 1 3 11316.25e-072.00e+01 fission1.49e-047.25e-06fission1.41e-046.69e-06
11 1 3 11316.25e-072.00e+01 nu-fission3.88e-041.78e-05nu-fission3.72e-041.82e-05
12 1 4 11410.00e+006.25e-07 fission6.69e-044.44e-05fission6.45e-044.59e-05
13 1 4 11410.00e+006.25e-07 nu-fission1.63e-031.08e-04nu-fission1.57e-031.12e-04
14 1 4 11416.25e-072.00e+01 fission1.65e-041.09e-05fission1.82e-049.37e-06
15 1 4 11416.25e-072.00e+01 nu-fission4.33e-042.89e-05nu-fission4.76e-042.47e-05
16 1 5 11510.00e+006.25e-07 fission9.32e-046.90e-05fission7.28e-047.49e-05
17 1 5 11510.00e+006.25e-07 nu-fission2.27e-031.68e-04nu-fission1.77e-031.83e-04
18 1 5 11516.25e-072.00e+01 fission1.83e-041.10e-05fission1.81e-041.04e-05
19 1 5 11516.25e-072.00e+01 nu-fission4.77e-042.77e-05nu-fission4.72e-042.67e-05
\n", "
" ], "text/plain": [ - " (mesh 1, x) (mesh 1, y) (mesh 1, z) energy low [MeV] \\\n", - "0 1 1 1 0.00e+00 \n", - "1 1 1 1 0.00e+00 \n", - "2 1 1 1 6.25e-07 \n", - "3 1 1 1 6.25e-07 \n", - "4 1 2 1 0.00e+00 \n", - "5 1 2 1 0.00e+00 \n", - "6 1 2 1 6.25e-07 \n", - "7 1 2 1 6.25e-07 \n", - "8 1 3 1 0.00e+00 \n", - "9 1 3 1 0.00e+00 \n", - "10 1 3 1 6.25e-07 \n", - "11 1 3 1 6.25e-07 \n", - "12 1 4 1 0.00e+00 \n", - "13 1 4 1 0.00e+00 \n", - "14 1 4 1 6.25e-07 \n", - "15 1 4 1 6.25e-07 \n", - "16 1 5 1 0.00e+00 \n", - "17 1 5 1 0.00e+00 \n", - "18 1 5 1 6.25e-07 \n", - "19 1 5 1 6.25e-07 \n", + " mesh 1 energy low [MeV] energy high [MeV] score mean \\\n", + " x y z \n", + "0 1 1 1 0.00e+00 6.25e-07 fission 2.34e-04 \n", + "1 1 1 1 0.00e+00 6.25e-07 nu-fission 5.71e-04 \n", + "2 1 1 1 6.25e-07 2.00e+01 fission 7.03e-05 \n", + "3 1 1 1 6.25e-07 2.00e+01 nu-fission 1.87e-04 \n", + "4 1 2 1 0.00e+00 6.25e-07 fission 3.67e-04 \n", + "5 1 2 1 0.00e+00 6.25e-07 nu-fission 8.94e-04 \n", + "6 1 2 1 6.25e-07 2.00e+01 fission 1.04e-04 \n", + "7 1 2 1 6.25e-07 2.00e+01 nu-fission 2.76e-04 \n", + "8 1 3 1 0.00e+00 6.25e-07 fission 6.04e-04 \n", + "9 1 3 1 0.00e+00 6.25e-07 nu-fission 1.47e-03 \n", + "10 1 3 1 6.25e-07 2.00e+01 fission 1.41e-04 \n", + "11 1 3 1 6.25e-07 2.00e+01 nu-fission 3.72e-04 \n", + "12 1 4 1 0.00e+00 6.25e-07 fission 6.45e-04 \n", + "13 1 4 1 0.00e+00 6.25e-07 nu-fission 1.57e-03 \n", + "14 1 4 1 6.25e-07 2.00e+01 fission 1.82e-04 \n", + "15 1 4 1 6.25e-07 2.00e+01 nu-fission 4.76e-04 \n", + "16 1 5 1 0.00e+00 6.25e-07 fission 7.28e-04 \n", + "17 1 5 1 0.00e+00 6.25e-07 nu-fission 1.77e-03 \n", + "18 1 5 1 6.25e-07 2.00e+01 fission 1.81e-04 \n", + "19 1 5 1 6.25e-07 2.00e+01 nu-fission 4.72e-04 \n", "\n", - " energy high [MeV] score mean std. dev. \n", - "0 6.25e-07 fission 2.02e-04 3.69e-05 \n", - "1 6.25e-07 nu-fission 4.92e-04 8.98e-05 \n", - "2 2.00e+01 fission 7.62e-05 3.74e-06 \n", - "3 2.00e+01 nu-fission 2.04e-04 9.88e-06 \n", - "4 6.25e-07 fission 3.75e-04 3.86e-05 \n", - "5 6.25e-07 nu-fission 9.14e-04 9.41e-05 \n", - "6 2.00e+01 fission 1.07e-04 1.26e-05 \n", - "7 2.00e+01 nu-fission 2.78e-04 3.16e-05 \n", - "8 6.25e-07 fission 5.64e-04 5.60e-05 \n", - "9 6.25e-07 nu-fission 1.37e-03 1.37e-04 \n", - "10 2.00e+01 fission 1.49e-04 7.25e-06 \n", - "11 2.00e+01 nu-fission 3.88e-04 1.78e-05 \n", - "12 6.25e-07 fission 6.69e-04 4.44e-05 \n", - "13 6.25e-07 nu-fission 1.63e-03 1.08e-04 \n", - "14 2.00e+01 fission 1.65e-04 1.09e-05 \n", - "15 2.00e+01 nu-fission 4.33e-04 2.89e-05 \n", - "16 6.25e-07 fission 9.32e-04 6.90e-05 \n", - "17 6.25e-07 nu-fission 2.27e-03 1.68e-04 \n", - "18 2.00e+01 fission 1.83e-04 1.10e-05 \n", - "19 2.00e+01 nu-fission 4.77e-04 2.77e-05 " + " std. dev. \n", + " \n", + "0 3.54e-05 \n", + "1 8.62e-05 \n", + "2 7.05e-06 \n", + "3 1.76e-05 \n", + "4 3.61e-05 \n", + "5 8.80e-05 \n", + "6 5.36e-06 \n", + "7 1.40e-05 \n", + "8 5.57e-05 \n", + "9 1.36e-04 \n", + "10 6.69e-06 \n", + "11 1.82e-05 \n", + "12 4.59e-05 \n", + "13 1.12e-04 \n", + "14 9.37e-06 \n", + "15 2.47e-05 \n", + "16 7.49e-05 \n", + "17 1.83e-04 \n", + "18 1.04e-05 \n", + "19 2.67e-05 " ] }, - "execution_count": 25, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1109,16 +1087,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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vRAwAFwIbJB1ZsA42Qb4/bN3G52zrNRsRvhvozaV7yVoMjfIsSHkOr7F+d1re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\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1133,7 +1111,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "collapsed": false }, @@ -1141,18 +1119,18 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1167,11 +1145,11 @@ "# Extract mean and reshape as 2D NumPy arrays\n", "mean = fiss['mean'].reshape((17,17))\n", "\n", - "pylab.imshow(mean, interpolation='nearest')\n", - "pylab.title('fission rate')\n", - "pylab.xlabel('x')\n", - "pylab.ylabel('y')\n", - "pylab.colorbar()" + "plt.imshow(mean, interpolation='nearest')\n", + "plt.title('fission rate')\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')\n", + "plt.colorbar()" ] }, { @@ -1183,7 +1161,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "collapsed": false }, @@ -1214,7 +1192,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -1222,7 +1200,7 @@ { "data": { "text/html": [ - "
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16 10000 U-238 scatter-Y2,1-6.48e-041.55e-0310000U-238scatter-Y2,13.75e-031.97e-03
17 10000 U-238 scatter-Y2,2-1.03e-031.31e-0310000U-238scatter-Y2,22.07e-031.60e-03
\n", @@ -1385,27 +1363,27 @@ ], "text/plain": [ " cell nuclide score mean std. dev.\n", - "0 10000 U-235 scatter-Y0,0 3.71e-02 1.15e-03\n", - "1 10000 U-235 scatter-Y1,-1 2.66e-04 3.23e-04\n", - "2 10000 U-235 scatter-Y1,0 -4.17e-04 2.74e-04\n", - "3 10000 U-235 scatter-Y1,1 -2.28e-04 2.37e-04\n", - "4 10000 U-235 scatter-Y2,-2 2.57e-05 1.99e-04\n", - "5 10000 U-235 scatter-Y2,-1 -1.15e-04 1.85e-04\n", - "6 10000 U-235 scatter-Y2,0 1.51e-04 1.59e-04\n", - "7 10000 U-235 scatter-Y2,1 -1.22e-04 2.80e-04\n", - "8 10000 U-235 scatter-Y2,2 7.65e-06 1.81e-04\n", - "9 10000 U-238 scatter-Y0,0 2.33e+00 1.31e-02\n", - "10 10000 U-238 scatter-Y1,-1 2.45e-02 2.27e-03\n", - "11 10000 U-238 scatter-Y1,0 -5.87e-05 2.80e-03\n", - "12 10000 U-238 scatter-Y1,1 -2.80e-02 2.54e-03\n", - "13 10000 U-238 scatter-Y2,-2 -4.86e-03 1.58e-03\n", - "14 10000 U-238 scatter-Y2,-1 5.57e-04 2.02e-03\n", - "15 10000 U-238 scatter-Y2,0 6.24e-03 1.63e-03\n", - "16 10000 U-238 scatter-Y2,1 -6.48e-04 1.55e-03\n", - "17 10000 U-238 scatter-Y2,2 -1.03e-03 1.31e-03" + "0 10000 U-235 scatter-Y0,0 3.86e-02 1.11e-03\n", + "1 10000 U-235 scatter-Y1,-1 2.75e-04 2.96e-04\n", + "2 10000 U-235 scatter-Y1,0 -5.55e-05 4.33e-04\n", + "3 10000 U-235 scatter-Y1,1 -4.22e-04 3.51e-04\n", + "4 10000 U-235 scatter-Y2,-2 5.88e-05 2.04e-04\n", + "5 10000 U-235 scatter-Y2,-1 1.00e-04 2.49e-04\n", + "6 10000 U-235 scatter-Y2,0 -8.09e-05 1.59e-04\n", + "7 10000 U-235 scatter-Y2,1 1.93e-04 2.14e-04\n", + "8 10000 U-235 scatter-Y2,2 1.12e-04 1.86e-04\n", + "9 10000 U-238 scatter-Y0,0 2.34e+00 1.34e-02\n", + "10 10000 U-238 scatter-Y1,-1 2.32e-02 2.97e-03\n", + "11 10000 U-238 scatter-Y1,0 7.50e-04 2.55e-03\n", + "12 10000 U-238 scatter-Y1,1 -2.73e-02 3.28e-03\n", + "13 10000 U-238 scatter-Y2,-2 -2.36e-03 1.21e-03\n", + "14 10000 U-238 scatter-Y2,-1 -1.80e-04 1.49e-03\n", + "15 10000 U-238 scatter-Y2,0 3.23e-03 2.25e-03\n", + "16 10000 U-238 scatter-Y2,1 3.75e-03 1.97e-03\n", + "17 10000 U-238 scatter-Y2,2 2.07e-03 1.60e-03" ] }, - "execution_count": 29, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1427,7 +1405,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -1436,8 +1414,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[[ 0.00131009 0.01310707]\n", - " [ 0.00018089 0.00114976]]]\n" + "[[[ 0.00159927 0.01341406]\n", + " [ 0.00018637 0.00111048]]]\n" ] } ], @@ -1458,7 +1436,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -1496,7 +1474,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, @@ -1505,13 +1483,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "[[[ 0.04537029]]]\n" + "[[[ 0.05767856]]]\n" ] } ], "source": [ "# Get the relative error for the scattering reaction rates in\n", - "# the first 30 distribcell instances \n", + "# the first 10 distribcell instances \n", "data = tally.get_values(scores=['scatter'], filters=['distribcell'],\n", " filter_bins=[(i,) for i in range(10)], value='rel_err')\n", "print(data)" @@ -1521,12 +1499,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Print the distribcell tally dataframe **without** OpenCG info" + "Print the distribcell tally dataframe" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false }, @@ -1534,187 +1512,403 @@ { "data": { "text/html": [ - "
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level 1level 2level 3distribcellscoremeanstd. dev.
univcelllatunivcell
idididxyzidid
558 279 absorption9.27e-051.33e-050100031000116701000010002279absorption8.19e-057.82e-06
559 279 scatter1.35e-028.05e-040100031000116701000010002279scatter1.33e-026.19e-04
560 280 absorption8.41e-059.92e-060100031000116801000010002280absorption1.00e-047.93e-06
561 280 scatter1.42e-026.12e-040100031000116801000010002280scatter1.40e-025.61e-04
562 281 absorption9.12e-058.26e-060100031000116901000010002281absorption9.52e-057.08e-06
563 281 scatter1.45e-025.90e-040100031000116901000010002281scatter1.51e-026.50e-04
564 282 absorption1.12e-041.24e-0501000310001161001000010002282absorption9.85e-059.47e-06
565 282 scatter1.63e-027.29e-0401000310001161001000010002282scatter1.53e-024.63e-04
566 283 absorption9.18e-057.12e-0601000310001161101000010002283absorption1.08e-041.34e-05
567 283 scatter1.62e-026.61e-0401000310001161101000010002283scatter1.65e-027.04e-04
568 284 absorption1.04e-041.10e-0501000310001161201000010002284absorption1.13e-047.91e-06
569 284 scatter1.74e-025.99e-0401000310001161201000010002284scatter1.67e-025.51e-04
570 285 absorption1.11e-041.14e-0501000310001161301000010002285absorption1.23e-049.53e-06
571 285 scatter1.80e-027.74e-0401000310001161301000010002285scatter1.88e-027.25e-04
572 286 absorption1.25e-041.20e-0501000310001161401000010002286absorption1.44e-041.34e-05
573 286 scatter1.83e-028.28e-0401000310001161401000010002286scatter1.90e-027.07e-04
574 287 absorption1.19e-041.30e-0501000310001161501000010002287absorption1.26e-048.66e-06
575 287 scatter1.75e-027.57e-0401000310001161501000010002287scatter1.97e-027.23e-04
576 288 absorption1.13e-041.40e-0501000310001161601000010002288absorption1.25e-049.59e-06
577 288 scatter1.82e-027.82e-0401000310001161601000010002288scatter2.01e-026.75e-04
\n", "
" ], "text/plain": [ - " distribcell score mean std. dev.\n", - "558 279 absorption 9.27e-05 1.33e-05\n", - "559 279 scatter 1.35e-02 8.05e-04\n", - "560 280 absorption 8.41e-05 9.92e-06\n", - "561 280 scatter 1.42e-02 6.12e-04\n", - "562 281 absorption 9.12e-05 8.26e-06\n", - "563 281 scatter 1.45e-02 5.90e-04\n", - "564 282 absorption 1.12e-04 1.24e-05\n", - "565 282 scatter 1.63e-02 7.29e-04\n", - "566 283 absorption 9.18e-05 7.12e-06\n", - "567 283 scatter 1.62e-02 6.61e-04\n", - "568 284 absorption 1.04e-04 1.10e-05\n", - "569 284 scatter 1.74e-02 5.99e-04\n", - "570 285 absorption 1.11e-04 1.14e-05\n", - "571 285 scatter 1.80e-02 7.74e-04\n", - "572 286 absorption 1.25e-04 1.20e-05\n", - "573 286 scatter 1.83e-02 8.28e-04\n", - "574 287 absorption 1.19e-04 1.30e-05\n", - "575 287 scatter 1.75e-02 7.57e-04\n", - "576 288 absorption 1.13e-04 1.40e-05\n", - "577 288 scatter 1.82e-02 7.82e-04" + " level 1 level 2 level 3 distribcell score \\\n", + " univ cell lat univ cell \n", + " id id id x y z id id \n", + "558 0 10003 10001 16 7 0 10000 10002 279 absorption \n", + "559 0 10003 10001 16 7 0 10000 10002 279 scatter \n", + "560 0 10003 10001 16 8 0 10000 10002 280 absorption \n", + "561 0 10003 10001 16 8 0 10000 10002 280 scatter \n", + "562 0 10003 10001 16 9 0 10000 10002 281 absorption \n", + "563 0 10003 10001 16 9 0 10000 10002 281 scatter \n", + "564 0 10003 10001 16 10 0 10000 10002 282 absorption \n", + "565 0 10003 10001 16 10 0 10000 10002 282 scatter \n", + "566 0 10003 10001 16 11 0 10000 10002 283 absorption \n", + "567 0 10003 10001 16 11 0 10000 10002 283 scatter \n", + "568 0 10003 10001 16 12 0 10000 10002 284 absorption \n", + "569 0 10003 10001 16 12 0 10000 10002 284 scatter \n", + "570 0 10003 10001 16 13 0 10000 10002 285 absorption \n", + "571 0 10003 10001 16 13 0 10000 10002 285 scatter \n", + "572 0 10003 10001 16 14 0 10000 10002 286 absorption \n", + "573 0 10003 10001 16 14 0 10000 10002 286 scatter \n", + "574 0 10003 10001 16 15 0 10000 10002 287 absorption \n", + "575 0 10003 10001 16 15 0 10000 10002 287 scatter \n", + "576 0 10003 10001 16 16 0 10000 10002 288 absorption \n", + "577 0 10003 10001 16 16 0 10000 10002 288 scatter \n", + "\n", + " mean std. dev. \n", + " \n", + " \n", + "558 8.19e-05 7.82e-06 \n", + "559 1.33e-02 6.19e-04 \n", + "560 1.00e-04 7.93e-06 \n", + "561 1.40e-02 5.61e-04 \n", + "562 9.52e-05 7.08e-06 \n", + "563 1.51e-02 6.50e-04 \n", + "564 9.85e-05 9.47e-06 \n", + "565 1.53e-02 4.63e-04 \n", + "566 1.08e-04 1.34e-05 \n", + "567 1.65e-02 7.04e-04 \n", + "568 1.13e-04 7.91e-06 \n", + "569 1.67e-02 5.51e-04 \n", + "570 1.23e-04 9.53e-06 \n", + "571 1.88e-02 7.25e-04 \n", + "572 1.44e-04 1.34e-05 \n", + "573 1.90e-02 7.07e-04 \n", + "574 1.26e-04 8.66e-06 \n", + "575 1.97e-02 7.23e-04 \n", + "576 1.25e-04 9.59e-06 \n", + "577 2.01e-02 6.75e-04 " ] }, - "execution_count": 33, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1727,16 +1921,9 @@ "df.tail(20)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Print the distribcell tally dataframe **with** OpenCG info" - ] - }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "collapsed": false }, @@ -1744,451 +1931,24 @@ { "data": { "text/html": [ - "
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(level 1, cell, id)(level 1, univ, id)(level 2, lat, id)(level 2, lat, x)(level 2, lat, y)(level 2, lat, z)(level 3, cell, id)(level 3, univ, id)distribcellscoremeanstd. dev.
0 10003 0 10001 0 0 0 10002 10000 0 absorption1.23e-041.19e-05
1 10003 0 10001 0 0 0 10002 10000 0 scatter1.78e-028.08e-04
2 10003 0 10001 0 1 0 10002 10000 1 absorption2.17e-041.96e-05
3 10003 0 10001 0 1 0 10002 10000 1 scatter2.89e-021.26e-03
4 10003 0 10001 0 2 0 10002 10000 2 absorption3.18e-042.03e-05
5 10003 0 10001 0 2 0 10002 10000 2 scatter4.05e-021.27e-03
6 10003 0 10001 0 3 0 10002 10000 3 absorption3.86e-041.80e-05
7 10003 0 10001 0 3 0 10002 10000 3 scatter4.86e-021.34e-03
8 10003 0 10001 0 4 0 10002 10000 4 absorption5.01e-042.60e-05
9 10003 0 10001 0 4 0 10002 10000 4 scatter5.71e-021.72e-03
10 10003 0 10001 0 5 0 10002 10000 5 absorption4.84e-042.58e-05
11 10003 0 10001 0 5 0 10002 10000 5 scatter6.08e-021.58e-03
12 10003 0 10001 0 6 0 10002 10000 6 absorption5.32e-043.90e-05
13 10003 0 10001 0 6 0 10002 10000 6 scatter6.91e-022.25e-03
14 10003 0 10001 0 7 0 10002 10000 7 absorption5.77e-043.92e-05
15 10003 0 10001 0 7 0 10002 10000 7 scatter7.67e-022.34e-03
16 10003 0 10001 0 8 0 10002 10000 8 absorption6.49e-043.90e-05
17 10003 0 10001 0 8 0 10002 10000 8 scatter8.16e-021.61e-03
18 10003 0 10001 0 9 0 10002 10000 9 absorption6.80e-043.17e-05
19 10003 0 10001 0 9 0 10002 10000 9 scatter8.77e-021.96e-03
\n", - "
" - ], - "text/plain": [ - " (level 1, cell, id) (level 1, univ, id) (level 2, lat, id) \\\n", - "0 10003 0 10001 \n", - "1 10003 0 10001 \n", - "2 10003 0 10001 \n", - "3 10003 0 10001 \n", - "4 10003 0 10001 \n", - "5 10003 0 10001 \n", - "6 10003 0 10001 \n", - "7 10003 0 10001 \n", - "8 10003 0 10001 \n", - "9 10003 0 10001 \n", - "10 10003 0 10001 \n", - "11 10003 0 10001 \n", - "12 10003 0 10001 \n", - "13 10003 0 10001 \n", - "14 10003 0 10001 \n", - "15 10003 0 10001 \n", - "16 10003 0 10001 \n", - "17 10003 0 10001 \n", - "18 10003 0 10001 \n", - "19 10003 0 10001 \n", - "\n", - " (level 2, lat, x) (level 2, lat, y) (level 2, lat, z) \\\n", - "0 0 0 0 \n", - "1 0 0 0 \n", - "2 0 1 0 \n", - "3 0 1 0 \n", - "4 0 2 0 \n", - "5 0 2 0 \n", - "6 0 3 0 \n", - "7 0 3 0 \n", - "8 0 4 0 \n", - "9 0 4 0 \n", - "10 0 5 0 \n", - "11 0 5 0 \n", - "12 0 6 0 \n", - "13 0 6 0 \n", - "14 0 7 0 \n", - "15 0 7 0 \n", - "16 0 8 0 \n", - "17 0 8 0 \n", - "18 0 9 0 \n", - "19 0 9 0 \n", - "\n", - " (level 3, cell, id) (level 3, univ, id) distribcell score \\\n", - "0 10002 10000 0 absorption \n", - "1 10002 10000 0 scatter \n", - "2 10002 10000 1 absorption \n", - "3 10002 10000 1 scatter \n", - "4 10002 10000 2 absorption \n", - "5 10002 10000 2 scatter \n", - "6 10002 10000 3 absorption \n", - "7 10002 10000 3 scatter \n", - "8 10002 10000 4 absorption \n", - "9 10002 10000 4 scatter \n", - "10 10002 10000 5 absorption \n", - "11 10002 10000 5 scatter \n", - "12 10002 10000 6 absorption \n", - "13 10002 10000 6 scatter \n", - "14 10002 10000 7 absorption \n", - "15 10002 10000 7 scatter \n", - "16 10002 10000 8 absorption \n", - "17 10002 10000 8 scatter \n", - "18 10002 10000 9 absorption \n", - "19 10002 10000 9 scatter \n", - "\n", - " mean std. dev. \n", - "0 1.23e-04 1.19e-05 \n", - "1 1.78e-02 8.08e-04 \n", - "2 2.17e-04 1.96e-05 \n", - "3 2.89e-02 1.26e-03 \n", - "4 3.18e-04 2.03e-05 \n", - "5 4.05e-02 1.27e-03 \n", - "6 3.86e-04 1.80e-05 \n", - "7 4.86e-02 1.34e-03 \n", - "8 5.01e-04 2.60e-05 \n", - "9 5.71e-02 1.72e-03 \n", - "10 4.84e-04 2.58e-05 \n", - "11 6.08e-02 1.58e-03 \n", - "12 5.32e-04 3.90e-05 \n", - "13 6.91e-02 2.25e-03 \n", - "14 5.77e-04 3.92e-05 \n", - "15 7.67e-02 2.34e-03 \n", - "16 6.49e-04 3.90e-05 \n", - "17 8.16e-02 1.61e-03 \n", - "18 6.80e-04 3.17e-05 \n", - "19 8.77e-02 1.96e-03 " - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Get a pandas dataframe for the distribcell tally data\n", - "df = tally.get_pandas_dataframe(summary=su, nuclides=False)\n", - "\n", - "# Print the last twenty rows in the dataframe\n", - "df.head(20)" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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meanstd. dev.
mean4.18e-042.17e-054.19e-042.24e-05
std2.39e-048.82e-062.42e-049.14e-06
min1.81e-053.82e-061.90e-053.44e-06
25%2.02e-041.49e-051.56e-05
50%4.02e-042.11e-054.05e-042.20e-05
75%6.15e-042.67e-056.07e-042.89e-05
max8.92e-044.43e-059.19e-044.95e-05
\n", "
" ], "text/plain": [ - " mean std. dev.\n", - "count 2.89e+02 2.89e+02\n", - "mean 4.18e-04 2.17e-05\n", - "std 2.39e-04 8.82e-06\n", - "min 1.81e-05 3.82e-06\n", - "25% 2.02e-04 1.49e-05\n", - "50% 4.02e-04 2.11e-05\n", - "75% 6.15e-04 2.67e-05\n", - "max 8.92e-04 4.43e-05" + " mean std. dev.\n", + " \n", + " \n", + "count 2.89e+02 2.89e+02\n", + "mean 4.19e-04 2.24e-05\n", + "std 2.42e-04 9.14e-06\n", + "min 1.90e-05 3.44e-06\n", + "25% 2.02e-04 1.56e-05\n", + "50% 4.05e-04 2.20e-05\n", + "75% 6.07e-04 2.89e-05\n", + "max 9.19e-04 4.95e-05" ] }, - "execution_count": 35, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -2270,7 +2032,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 34, "metadata": { "collapsed": false }, @@ -2279,7 +2041,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Mann-Whitney Test p-value: 0.414863173548\n" + "Mann-Whitney Test p-value: 0.303583331507\n" ] } ], @@ -2308,7 +2070,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 35, "metadata": { "collapsed": false }, @@ -2317,7 +2079,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Mann-Whitney Test p-value: 3.28554363741e-42\n" + "Mann-Whitney Test p-value: 6.038663783e-42\n" ] } ], @@ -2344,7 +2106,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 36, "metadata": { "collapsed": false }, @@ -2353,28 +2115,28 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/smharper/.local/lib/python2.7/site-packages/ipykernel/__main__.py:4: SettingWithCopyWarning: \n", + "/usr/local/lib/python2.7/dist-packages/IPython/kernel/__main__.py:4: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", - "See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n" + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 38, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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KlcydOxeAjo4O5s2bx+LFi4Fi/LPZ64VttbS/5557uOKKf2Z4+N3ABcAO4Dja21fxznde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\nEtjPzH5gZg8C/xDu+xegNwx7vQb4dYV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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2393,7 +2155,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 37, "metadata": { "collapsed": false }, @@ -2401,18 +2163,18 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 39, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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qq6/SuHFjrr32WoYOHVpqmfLiLfu4V4feVodv1z4SkXbAS0ALnIObn1PVJ0SkGfA60AHI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\n", 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DlnoznkkeyJPJ/qpSks3oorJstUPi00rHX03uFWEkUtbX3oa7Sn7FgYX/j5ML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\nlcvmVCblU7lsLlvKpCE+qXx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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2423,29 +2185,29 @@ "# Plot a histogram and kernel density estimate for the scattering rates\n", "scatter['mean'].plot(kind='hist', bins=25)\n", "scatter['mean'].plot(kind='kde')\n", - "pylab.title('Scattering Rates')\n", - "pylab.xlabel('Mean')\n", - "pylab.legend(['KDE', 'Histogram'])" + "plt.title('Scattering Rates')\n", + "plt.xlabel('Mean')\n", + "plt.legend(['KDE', 'Histogram'])" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.10" + "pygments_lexer": "ipython3", + "version": "3.5.1" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/post-processing.ipynb b/docs/source/pythonapi/examples/post-processing.ipynb index 7fbca6864..de92c2bcb 100644 --- a/docs/source/pythonapi/examples/post-processing.ipynb +++ b/docs/source/pythonapi/examples/post-processing.ipynb @@ -15,16 +15,12 @@ }, "outputs": [], "source": [ + "%matplotlib inline\n", "from IPython.display import Image\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", - "import openmc\n", - "from openmc.statepoint import StatePoint\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", - "\n", - "%matplotlib inline" + "import openmc" ] }, { @@ -108,11 +104,8 @@ }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, add Materials\n", - "materials_file = openmc.MaterialsFile()\n", - "materials_file.add_material(fuel)\n", - "materials_file.add_material(water)\n", - "materials_file.add_material(zircaloy)\n", + "# Instantiate a Materials collection\n", + "materials_file = openmc.Materials((fuel, water, zircaloy))\n", "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", @@ -240,12 +233,8 @@ }, "outputs": [], "source": [ - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "geometry.export_to_xml()" ] }, { @@ -268,14 +257,16 @@ "inactive = 10\n", "particles = 5000\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", - "source_bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", - "settings_file.source = Source(space=Box(\n", - " source_bounds[:3], source_bounds[3:]))\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", + "bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Export to \"settings.xml\"\n", "settings_file.export_to_xml()" @@ -304,9 +295,8 @@ "plot.pixels = [250, 250]\n", "plot.color = 'mat'\n", "\n", - "# Instantiate a PlotsFile, add Plot, and export to \"plots.xml\"\n", - "plot_file = openmc.PlotsFile()\n", - "plot_file.add_plot(plot)\n", + "# Instantiate a Plots collection and export to \"plots.xml\"\n", + "plot_file = openmc.Plots([plot])\n", "plot_file.export_to_xml()" ] }, @@ -337,8 +327,7 @@ ], "source": [ "# Run openmc in plotting mode\n", - "executor = openmc.Executor()\n", - "executor.plot_geometry(output=False)" + "openmc.plot_geometry(output=False)" ] }, { @@ -350,7 +339,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -383,8 +372,8 @@ }, "outputs": [], "source": [ - "# Instantiate an empty TalliesFile\n", - "tallies_file = openmc.TalliesFile()" + "# Instantiate an empty Tallies object\n", + "tallies_file = openmc.Tallies()" ] }, { @@ -400,18 +389,16 @@ "mesh.dimension = [100, 100]\n", "mesh.lower_left = [-0.63, -0.63]\n", "mesh.upper_right = [0.63, 0.63]\n", - "tallies_file.add_mesh(mesh)\n", "\n", "# Create mesh filter for tally\n", - "mesh_filter = openmc.Filter(type='mesh', bins=[1])\n", + "mesh_filter = openmc.Filter(type='mesh')\n", "mesh_filter.mesh = mesh\n", "\n", "# Create mesh tally to score flux and fission rate\n", "tally = openmc.Tally(name='flux')\n", - "tally.add_filter(mesh_filter)\n", - "tally.add_score('flux')\n", - "tally.add_score('fission')\n", - "tallies_file.add_tally(tally)" + "tally.filters = [mesh_filter]\n", + "tally.scores = ['flux', 'fission']\n", + "tallies_file.append(tally)" ] }, { @@ -458,11 +445,11 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.org/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: ea9fb637f63f9374c7436456141afa850b84acf9\n", - " Date/Time: 2016-01-14 07:02:06\n", + " Git SHA1: df280b60eb1c6d7b7f842e05ede734a4883a0fc8\n", + " Date/Time: 2016-05-05 14:41:55\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -489,106 +476,106 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 1.04894 \n", - " 2/1 1.01711 \n", - " 3/1 1.05357 \n", - " 4/1 1.03052 \n", - " 5/1 1.06523 \n", - " 6/1 1.06806 \n", - " 7/1 1.05161 \n", - " 8/1 1.04199 \n", - " 9/1 1.05010 \n", - " 10/1 1.04617 \n", - " 11/1 1.04894 \n", - " 12/1 1.06806 1.05850 +/- 0.00956\n", - " 13/1 1.05002 1.05567 +/- 0.00620\n", - " 14/1 1.03471 1.05043 +/- 0.00683\n", - " 15/1 1.01803 1.04395 +/- 0.00837\n", - " 16/1 1.05588 1.04594 +/- 0.00712\n", - " 17/1 1.07503 1.05010 +/- 0.00731\n", - " 18/1 1.02786 1.04732 +/- 0.00691\n", - " 19/1 1.00071 1.04214 +/- 0.00800\n", - " 20/1 1.05587 1.04351 +/- 0.00729\n", - " 21/1 1.03886 1.04309 +/- 0.00660\n", - " 22/1 1.04335 1.04311 +/- 0.00603\n", - " 23/1 1.04057 1.04292 +/- 0.00555\n", - " 24/1 1.01976 1.04126 +/- 0.00540\n", - " 25/1 1.05811 1.04238 +/- 0.00515\n", - " 26/1 1.02351 1.04120 +/- 0.00496\n", - " 27/1 1.05261 1.04188 +/- 0.00471\n", - " 28/1 1.03355 1.04141 +/- 0.00446\n", - " 29/1 1.02797 1.04071 +/- 0.00428\n", - " 30/1 1.03758 1.04055 +/- 0.00406\n", - " 31/1 1.04883 1.04094 +/- 0.00388\n", - " 32/1 1.03557 1.04070 +/- 0.00371\n", - " 33/1 1.02947 1.04021 +/- 0.00358\n", - " 34/1 1.03651 1.04006 +/- 0.00343\n", - " 35/1 1.03331 1.03979 +/- 0.00330\n", - " 36/1 1.05947 1.04054 +/- 0.00326\n", - " 37/1 1.05093 1.04093 +/- 0.00316\n", - " 38/1 1.06787 1.04189 +/- 0.00319\n", - " 39/1 1.01451 1.04095 +/- 0.00322\n", - " 40/1 1.02351 1.04037 +/- 0.00317\n", - " 41/1 1.04826 1.04062 +/- 0.00307\n", - " 42/1 1.04228 1.04067 +/- 0.00298\n", - " 43/1 1.03214 1.04041 +/- 0.00290\n", - " 44/1 1.04950 1.04068 +/- 0.00282\n", - " 45/1 1.06616 1.04141 +/- 0.00284\n", - " 46/1 1.07039 1.04221 +/- 0.00287\n", - " 47/1 1.00292 1.04115 +/- 0.00299\n", - " 48/1 1.04477 1.04125 +/- 0.00291\n", - " 49/1 1.03360 1.04105 +/- 0.00284\n", - " 50/1 1.04783 1.04122 +/- 0.00277\n", - " 51/1 1.03985 1.04119 +/- 0.00271\n", - " 52/1 1.02507 1.04080 +/- 0.00267\n", - " 53/1 1.03477 1.04066 +/- 0.00261\n", - " 54/1 1.00412 1.03983 +/- 0.00268\n", - " 55/1 1.02239 1.03945 +/- 0.00265\n", - " 56/1 1.04308 1.03952 +/- 0.00259\n", - " 57/1 1.05534 1.03986 +/- 0.00256\n", - " 58/1 1.06667 1.04042 +/- 0.00257\n", - " 59/1 1.06458 1.04091 +/- 0.00256\n", - " 60/1 1.00304 1.04015 +/- 0.00262\n", - " 61/1 1.05038 1.04036 +/- 0.00258\n", - " 62/1 1.02904 1.04014 +/- 0.00254\n", - " 63/1 1.00249 1.03943 +/- 0.00259\n", - " 64/1 1.01779 1.03903 +/- 0.00257\n", - " 65/1 1.05335 1.03929 +/- 0.00254\n", - " 66/1 1.06231 1.03970 +/- 0.00253\n", - " 67/1 1.02382 1.03942 +/- 0.00250\n", - " 68/1 1.03796 1.03939 +/- 0.00245\n", - " 69/1 1.03672 1.03935 +/- 0.00241\n", - " 70/1 1.02926 1.03918 +/- 0.00238\n", - " 71/1 1.05834 1.03950 +/- 0.00236\n", - " 72/1 1.04332 1.03956 +/- 0.00232\n", - " 73/1 1.05613 1.03982 +/- 0.00230\n", - " 74/1 1.01963 1.03950 +/- 0.00228\n", - " 75/1 1.02228 1.03924 +/- 0.00226\n", - " 76/1 1.04842 1.03938 +/- 0.00223\n", - " 77/1 1.02157 1.03911 +/- 0.00222\n", - " 78/1 1.02810 1.03895 +/- 0.00219\n", - " 79/1 1.05030 1.03912 +/- 0.00216\n", - " 80/1 1.02391 1.03890 +/- 0.00214\n", - " 81/1 1.02488 1.03870 +/- 0.00212\n", - " 82/1 1.04957 1.03885 +/- 0.00210\n", - " 83/1 1.03499 1.03880 +/- 0.00207\n", - " 84/1 1.05922 1.03907 +/- 0.00206\n", - " 85/1 1.05898 1.03934 +/- 0.00205\n", - " 86/1 1.02242 1.03912 +/- 0.00204\n", - " 87/1 1.03278 1.03904 +/- 0.00201\n", - " 88/1 1.06134 1.03932 +/- 0.00201\n", - " 89/1 1.04521 1.03940 +/- 0.00198\n", - " 90/1 1.04277 1.03944 +/- 0.00196\n", - " 91/1 1.04214 1.03947 +/- 0.00193\n", - " 92/1 1.05610 1.03967 +/- 0.00192\n", - " 93/1 1.04531 1.03974 +/- 0.00190\n", - " 94/1 1.01534 1.03945 +/- 0.00190\n", - " 95/1 1.03971 1.03945 +/- 0.00187\n", - " 96/1 1.07183 1.03983 +/- 0.00189\n", - " 97/1 1.07214 1.04020 +/- 0.00191\n", - " 98/1 1.03710 1.04017 +/- 0.00188\n", - " 99/1 1.02532 1.04000 +/- 0.00187\n", - " 100/1 1.03965 1.04000 +/- 0.00185\n", + " 1/1 1.04359 \n", + " 2/1 1.04244 \n", + " 3/1 1.03020 \n", + " 4/1 1.03630 \n", + " 5/1 1.06478 \n", + " 6/1 1.05450 \n", + " 7/1 1.02369 \n", + " 8/1 1.03614 \n", + " 9/1 1.05193 \n", + " 10/1 1.02886 \n", + " 11/1 1.05011 \n", + " 12/1 1.04597 1.04804 +/- 0.00207\n", + " 13/1 1.07035 1.05548 +/- 0.00753\n", + " 14/1 1.06150 1.05698 +/- 0.00554\n", + " 15/1 1.07094 1.05977 +/- 0.00512\n", + " 16/1 1.05131 1.05836 +/- 0.00441\n", + " 17/1 1.04733 1.05679 +/- 0.00405\n", + " 18/1 1.08130 1.05985 +/- 0.00465\n", + " 19/1 1.02559 1.05605 +/- 0.00560\n", + " 20/1 1.03399 1.05384 +/- 0.00547\n", + " 21/1 1.04617 1.05314 +/- 0.00500\n", + " 22/1 1.06981 1.05453 +/- 0.00477\n", + " 23/1 1.05270 1.05439 +/- 0.00439\n", + " 24/1 1.02487 1.05228 +/- 0.00458\n", + " 25/1 1.05905 1.05273 +/- 0.00429\n", + " 26/1 1.07658 1.05422 +/- 0.00428\n", + " 27/1 1.03455 1.05307 +/- 0.00418\n", + " 28/1 1.00971 1.05066 +/- 0.00462\n", + " 29/1 1.06111 1.05121 +/- 0.00440\n", + " 30/1 1.01777 1.04954 +/- 0.00450\n", + " 31/1 1.04718 1.04942 +/- 0.00428\n", + " 32/1 1.03340 1.04870 +/- 0.00415\n", + " 33/1 1.04570 1.04857 +/- 0.00397\n", + " 34/1 1.02728 1.04768 +/- 0.00390\n", + " 35/1 1.02852 1.04691 +/- 0.00382\n", + " 36/1 1.03242 1.04636 +/- 0.00371\n", + " 37/1 1.01479 1.04519 +/- 0.00376\n", + " 38/1 1.06045 1.04573 +/- 0.00366\n", + " 39/1 1.03810 1.04547 +/- 0.00354\n", + " 40/1 1.05281 1.04571 +/- 0.00343\n", + " 41/1 1.03941 1.04551 +/- 0.00332\n", + " 42/1 1.04049 1.04535 +/- 0.00322\n", + " 43/1 1.04586 1.04537 +/- 0.00312\n", + " 44/1 1.05437 1.04563 +/- 0.00304\n", + " 45/1 1.03445 1.04531 +/- 0.00297\n", + " 46/1 1.05104 1.04547 +/- 0.00289\n", + " 47/1 1.00773 1.04445 +/- 0.00299\n", + " 48/1 1.06879 1.04509 +/- 0.00298\n", + " 49/1 1.06625 1.04564 +/- 0.00295\n", + " 50/1 1.02641 1.04515 +/- 0.00292\n", + " 51/1 1.05701 1.04544 +/- 0.00286\n", + " 52/1 1.02868 1.04504 +/- 0.00282\n", + " 53/1 1.04592 1.04506 +/- 0.00275\n", + " 54/1 1.05757 1.04535 +/- 0.00271\n", + " 55/1 1.02329 1.04486 +/- 0.00269\n", + " 56/1 1.04116 1.04478 +/- 0.00263\n", + " 57/1 1.01990 1.04425 +/- 0.00263\n", + " 58/1 1.06202 1.04462 +/- 0.00260\n", + " 59/1 1.03550 1.04443 +/- 0.00255\n", + " 60/1 1.01383 1.04382 +/- 0.00258\n", + " 61/1 1.04111 1.04377 +/- 0.00253\n", + " 62/1 1.02061 1.04332 +/- 0.00252\n", + " 63/1 1.00456 1.04259 +/- 0.00257\n", + " 64/1 1.02277 1.04222 +/- 0.00255\n", + " 65/1 1.04544 1.04228 +/- 0.00251\n", + " 66/1 1.04487 1.04233 +/- 0.00246\n", + " 67/1 1.02699 1.04206 +/- 0.00243\n", + " 68/1 1.06160 1.04240 +/- 0.00241\n", + " 69/1 1.02989 1.04218 +/- 0.00238\n", + " 70/1 1.03107 1.04200 +/- 0.00235\n", + " 71/1 1.06571 1.04239 +/- 0.00234\n", + " 72/1 1.03444 1.04226 +/- 0.00231\n", + " 73/1 1.05059 1.04239 +/- 0.00228\n", + " 74/1 1.03352 1.04225 +/- 0.00224\n", + " 75/1 1.03707 1.04217 +/- 0.00221\n", + " 76/1 1.02994 1.04199 +/- 0.00219\n", + " 77/1 1.05416 1.04217 +/- 0.00216\n", + " 78/1 1.03794 1.04211 +/- 0.00213\n", + " 79/1 1.04652 1.04217 +/- 0.00210\n", + " 80/1 1.05715 1.04239 +/- 0.00208\n", + " 81/1 1.08146 1.04294 +/- 0.00212\n", + " 82/1 1.02159 1.04264 +/- 0.00211\n", + " 83/1 1.01968 1.04233 +/- 0.00211\n", + " 84/1 1.05577 1.04251 +/- 0.00209\n", + " 85/1 1.07808 1.04298 +/- 0.00211\n", + " 86/1 1.03943 1.04293 +/- 0.00209\n", + " 87/1 1.03431 1.04282 +/- 0.00206\n", + " 88/1 1.02414 1.04258 +/- 0.00205\n", + " 89/1 1.02316 1.04234 +/- 0.00204\n", + " 90/1 1.03342 1.04223 +/- 0.00202\n", + " 91/1 1.02781 1.04205 +/- 0.00200\n", + " 92/1 1.01293 1.04169 +/- 0.00201\n", + " 93/1 1.04347 1.04171 +/- 0.00198\n", + " 94/1 1.05357 1.04186 +/- 0.00196\n", + " 95/1 1.04740 1.04192 +/- 0.00194\n", + " 96/1 1.05215 1.04204 +/- 0.00192\n", + " 97/1 1.06667 1.04232 +/- 0.00192\n", + " 98/1 1.04926 1.04240 +/- 0.00190\n", + " 99/1 1.05386 1.04253 +/- 0.00188\n", + " 100/1 1.05088 1.04262 +/- 0.00186\n", " Creating state point statepoint.100.h5...\n", "\n", " ===========================================================================\n", @@ -598,27 +585,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.6000E-01 seconds\n", - " Reading cross sections = 1.0600E-01 seconds\n", - " Total time in simulation = 2.5756E+02 seconds\n", - " Time in transport only = 2.5751E+02 seconds\n", - " Time in inactive batches = 9.7270E+00 seconds\n", - " Time in active batches = 2.4783E+02 seconds\n", - " Time synchronizing fission bank = 2.1000E-02 seconds\n", - " Sampling source sites = 1.3000E-02 seconds\n", - " SEND/RECV source sites = 8.0000E-03 seconds\n", - " Time accumulating tallies = 1.3000E-02 seconds\n", - " Total time for finalization = 1.4600E-01 seconds\n", - " Total time elapsed = 2.5809E+02 seconds\n", - " Calculation Rate (inactive) = 5140.33 neutrons/second\n", - " Calculation Rate (active) = 1815.75 neutrons/second\n", + " Total time for initialization = 4.4900E-01 seconds\n", + " Reading cross sections = 1.2100E-01 seconds\n", + " Total time in simulation = 3.4132E+02 seconds\n", + " Time in transport only = 3.4128E+02 seconds\n", + " Time in inactive batches = 1.0748E+01 seconds\n", + " Time in active batches = 3.3057E+02 seconds\n", + " Time synchronizing fission bank = 1.1000E-02 seconds\n", + " Sampling source sites = 1.1000E-02 seconds\n", + " SEND/RECV source sites = 0.0000E+00 seconds\n", + " Time accumulating tallies = 1.9000E-02 seconds\n", + " Total time for finalization = 1.5600E-01 seconds\n", + " Total time elapsed = 3.4196E+02 seconds\n", + " Calculation Rate (inactive) = 4652.03 neutrons/second\n", + " Calculation Rate (active) = 1361.27 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.03912 +/- 0.00160\n", - " k-effective (Track-length) = 1.04000 +/- 0.00185\n", - " k-effective (Absorption) = 1.04240 +/- 0.00156\n", - " Combined k-effective = 1.04078 +/- 0.00127\n", + " k-effective (Collision) = 1.04214 +/- 0.00161\n", + " k-effective (Track-length) = 1.04262 +/- 0.00186\n", + " k-effective (Absorption) = 1.04338 +/- 0.00158\n", + " Combined k-effective = 1.04278 +/- 0.00122\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -636,7 +623,7 @@ ], "source": [ "# Run OpenMC!\n", - "executor.run_simulation()" + "openmc.run()" ] }, { @@ -663,7 +650,7 @@ "outputs": [], "source": [ "# Load the statepoint file\n", - "sp = StatePoint('statepoint.100.h5')" + "sp = openmc.StatePoint('statepoint.100.h5')" ] }, { @@ -686,11 +673,11 @@ "text": [ "Tally\n", "\tID =\t10000\n", - "\tName =\t\n", + "\tName =\tflux\n", "\tFilters =\t\n", " \t\tmesh\t[10000]\n", "\tNuclides =\ttotal \n", - "\tScores =\t[u'flux', u'fission']\n", + "\tScores =\t['flux', 'fission']\n", "\tEstimator =\ttracklength\n", "\n" ] @@ -718,18 +705,18 @@ { "data": { "text/plain": [ - "array([[[ 0.4107676 , 0. ]],\n", + "array([[[ 0.40945685, 0. ]],\n", "\n", - " [[ 0.40849402, 0. ]],\n", + " [[ 0.40939021, 0. ]],\n", "\n", - " [[ 0.41014343, 0. ]],\n", + " [[ 0.410625 , 0. ]],\n", "\n", " ..., \n", - " [[ 0.41049467, 0. ]],\n", + " [[ 0.41130501, 0. ]],\n", "\n", - " [[ 0.40982242, 0. ]],\n", + " [[ 0.41228849, 0. ]],\n", "\n", - " [[ 0.40996987, 0. ]]])" + " [[ 0.41420317, 0. ]]])" ] }, "execution_count": 20, @@ -765,30 +752,30 @@ { "data": { "text/plain": [ - "(array([[[ 0.00456408, 0. ]],\n", + "(array([[[ 0.00454952, 0. ]],\n", " \n", - " [[ 0.00453882, 0. ]],\n", + " [[ 0.00454878, 0. ]],\n", " \n", - " [[ 0.00455715, 0. ]],\n", + " [[ 0.0045625 , 0. ]],\n", " \n", " ..., \n", - " [[ 0.00456105, 0. ]],\n", + " [[ 0.00457006, 0. ]],\n", " \n", - " [[ 0.00455358, 0. ]],\n", + " [[ 0.00458098, 0. ]],\n", " \n", - " [[ 0.00455522, 0. ]]]),\n", - " array([[[ 1.95085625e-05, 0.00000000e+00]],\n", + " [[ 0.00460226, 0. ]]]),\n", + " array([[[ 1.64748193e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.78129859e-05, 0.00000000e+00]],\n", + " [[ 1.70922989e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.89709648e-05, 0.00000000e+00]],\n", + " [[ 1.67622385e-05, 0.00000000e+00]],\n", " \n", " ..., \n", - " [[ 1.56286612e-05, 0.00000000e+00]],\n", + " [[ 1.69274948e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.65813279e-05, 0.00000000e+00]],\n", + " [[ 1.57842763e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.67530331e-05, 0.00000000e+00]]]))" + " [[ 2.06590062e-05, 0.00000000e+00]]]))" ] }, "execution_count": 21, @@ -820,12 +807,12 @@ "output_type": "stream", "text": [ "Tally\n", - "\tID =\t10000\n", - "\tName =\t\n", + "\tID =\t10001\n", + "\tName =\tflux\n", "\tFilters =\t\n", " \t\tmesh\t[10000]\n", "\tNuclides =\ttotal \n", - "\tScores =\t[u'flux']\n", + "\tScores =\t['flux']\n", "\tEstimator =\ttracklength\n", "\n" ] @@ -868,7 +855,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 24, @@ -877,9 +864,9 @@ }, { "data": { - "image/png": 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3CYgyeqSJ80yPit9HFT8AEYpYSBioHKmt0DB03g+epCiHqRAgQIVn3W8gNKjKPvxUiZFD\nxaBAmBwxBDZdNCJ2EX+nwUXjHer+f4pXbXCVc7zJc2xlppD6NmeSNyjJQfooTLHGE86reNUG18QJ\nsnIET6/FD7a+wJi+ydnhK0TJcZhFfByE9zZjzHGfLhr7DFMhyHVO08bFNQoUeRIAD02G2cdA5V2e\nYpQdJlnj63yDwH4Dq6Dw3vQ5rnfO8nL+C8guk1P+93nJ/zJ3vYdZtGcwhMKSMo0munxSfZnNkSkU\n+iDBXY5Rs33cs+fJSkuoLoOQL49frRD0Voh4i3RlDUNWmQ6sETuaJdgsE5vOsiTN0hIeqsLPBCV+\n3vp9vrn2S2y0EvQDCsHodXyeGluMcegz93jxlJPLnfO0W172vpfiVUOnMel+1KU7MPDYeeSB7aZJ\nDxU/Ncadm6haj35fwdXrsNscx+up03E4yTqGyBLDTROdBgYO6sJLV3GQlpLUJC81p85/7CR30UZg\nYyGQMOngJE+EtnAhhwxaQ33W3ZN0cTAhNghSZsSRZsq/wffVT5MnyirTTLCBgcpVnmBMpJEk2BAT\n2AhUDIKUCaplVNXgJqcwUBHYDLOHTJ8KQZwPj6WJh55wI8kWM9oyAbtCyQpzz5qnKXwMyxnCFHDT\nRKHPURYIKmUkxSJPlBo6Rl9hWxqjIxzoVIiRo4+CSv9hl0wDjS41fHipE6REA50eDhT6hKwSmt3F\nIzcJUKaHgwZedklSQ+cUN0lKGYJqjVtinr4k01ac+OQqfaGSF1GKjjAKfWRMvDTw9WvkuzFUVxdd\nqeOhiYWgjpdtxnBqt5gN3iTgyuOTa0QoMOVeY584aZIE9QLRkSxhigcfblUnrYKPOl7ivhzJyB7D\nyj7byjhFItgIejgO3tuJFiG9gHTDpr+k0t3z0HT58EQrj7p0BwYeO488sHUabDJBgj2OssCMWMan\n1rhSe5rf3v8Nzo9dYkpdJkKB09xghhVCdoldMUJJD3Jx7hV2GKVq++kLlRIhNLqc5z127FHucowG\nXly0cUpt3tGf4DAPcLHIFuN0cOJ5OOEibuQZq++j+kz25AQVAjjp0MDL/8nfY9q3SsLeI0+UJ+0r\nTIgN7nAcNy0ASoSwEXhpcJE3iVCgi5MRdunhICPiZJ1JbnnGqaFz3L5L13TS6rnRoxWCSu7hh1eV\nIbIc4gFuWnRx0sZJmiQVLYBjskkLjfv2HO+J8wQoc5glfoV/i5MOb/MMeSKMss1x+w4FEaWPQsfe\n5L8wLqHaBpvSQdufgUqQMn/Cl/g2X+QdnubLw3/Ms8NvUSJI1J3lxeAPOMQSHZwscYgoeUIUCdDi\nFDfp9Zz8q8LfZSK8xjHPbUKiRIgiuqhzW5wk6Vnls9EMAAIbLw2OssAtTrLGFAvMscsIIYoYOFjY\nP8Hdd09jy4Kh6Tz5aISJyWUafY33u09Q1XTyRBkiS4Ughe0Inf9DxyopCN1COmQTVEo0H3XxDgw8\nZh55YKdJYjHBIZbQqVNHp4WLluxGc/T4Yue7HFNvUXQF8FNlu5Hiv8z8c/aHotQkHxuZWZrbXsbE\nFp84/3vccx7lLsf5jvV58ltx8rtx+ihMjy7hSO1yk1MIbCQWmOM+AFP2GmP1PbAFf+p7AVMVDyeR\nTLHKND5qnOE6K4Uj3EmfpbumsTJzCN90mYai45B7eKUGIUqc4DZPWleZba6xJk8S1Cqcyd5hRx3h\n/eg5Mowj8wRNPBRElKrsJ6wVOSIvEiNHHZ0CUTLEqaMTIY+HJgYqOnWmWWVGrLCwcJz7y/PMf+wW\nbZeHy7VnORu6TsepodBnlhWOlRcY38zgTBlYtsTmapHgukE97KUcCTLa3cNnFjFdKheky/ipUiLM\nBhM08aDRRadGmRAbpPBRY4INfNQQ2FTxkyZJWfNzJnqV7KUEd+1TdF908nPK7zPLClHyJLvrPFHv\n813PZ7Ckg28mlzmPjEWYImVCAMiYjLGGP1HDc7HJzeJZ+n7l4L0iiixbnNfe46x8jQk2cNKhi8bR\niXsc/e8W2e6NIWz4pPEqxpjg7z/q4h0YeMw88sDeI4FGABuBhUQD70GrnkNh3n8bj9qkgc4+w/RR\n2CPBLfskvaJCx3JSbQcJGBW8ah0fVdy06BkaK7VD1DaD9JZcYMKwmsZIqbRxkSGOQZwQJn0Udhhj\niCJ1SeeSdoEAVXTq6NRQMbARmMhodAnbBVxWh74NDXTqtpeRzj5j5i5Rd45ZeZkJ1nHZbero7NpJ\n+sjo1IiRI43EvpFkq51i2zWOZUoYZSe2X0JxG3hpIAAbQRX/w3E7SFjYcBDgosWGNU3HcDFtr9LB\nTcf2sEWKJi5auNlup4i3CwTsJu52A9sWVC0fVdGnL8lIWEgPl861EQSoMsYOGl2cZg+X1cNSQBM9\nPDTIEaOJ94OQ/Y+BbSNwyF0C7hJ5OU6j5yVtJ6ij46GJkw4GKgU7SJ4IMiaeh+e+9sObsi7axMgx\nxjY6dRpeD4rWQdZ6oFr0UZCwGOvucLJ8BxHoY7gUTDxEyBMJ5rGfluiioHZMPrv/PbL+x6vdamDg\nb8IjD+x9EkxgU8FPhQCrTHOLE4y6d/my65u8xQU2RIoSIUbZJuCt8OT0Ja6+9wyZegIx12M2dY8J\n1zIL8lH2GcboqDTX/fQ2XQerPHSgMeGlgp8Umwcz+ziFzBQ5YjwQh9nRf4CKwQ1Oc5QFxtjhOd5g\nnntskuIdnual8I95IfQqyWNp8iLGqjTNbU7wmdKPeKH6Ju+MnUN29SlIEWp6lxv2CX5gf4ZkPM1x\ncZfP8n1yuKm1bJb2jhFJ7kHLpnAzgXHMgeFWeJEffxBkKgYVAhSIUkcnSp4IBXLEaBxyoU8UmXff\nJSIVmPUssiJmWGWarB3nX5f/Lm+J5/nKyd/jC5kfgg1Xpmc5NltnUqwTFTk6LpkSw+ySZI/Ew5uo\nVT7Wu8xMb51/6f06tgwptthm/OHPGD5qhCghYTHDCioGb3ER5/N1vFTwy1V2SVJ+2GJ4RztGUX8G\nWZjo1Blmj1/g33OF8/yYl0ixyTz3OM4dbnGSxf4cb3aexfLKpBydDzpmDpVX+cUbf8A/OvkbXE2e\nJkmaj/MqQcq8xsdZZhavaGEoKg3J86hLd2DgsfPIA9tPlS5OygRx0UGnzmluotBnoz/B/SvH2F0c\no7fnQPwcGHMOwqKA5RY4pQ7RQJo8Ud6qPIdWN2m0vdTqAXoZDWRwzHQZmkgzMblGsF/lVv4cZdlH\nudWgee1FRrw7fOrQn/Lx1ptEG0UuNt/FGJLoeBw08dBFw02Lj3GJcbGFKRQ2STFa2uN85xqVaICa\n38st1zxpR4IAFdy02BOzRESB/8b+35gSa2h0aOEhSZpE7QE/WPoitUyISDDHU/NvktYS7DUSFD0R\nWsL9MJqjjLLDBOsc5R5OunTR2GWEUXWHcXmLFWmGVTEFCJ6132KILBvGJP1vy+QcQ1z91XNkA8N4\nadCRFlmTYjTwotKjTJBNM8WV1nnqqo7H0eSsdI2rjrPckeeZl+5yp3ucb1W+xv71EQ5HF3nh3Gvs\nkaCBl1mWGSLLPsOUCdLM+vFZNVKJTQxJRcbkApe5zgZRMckyM3ho4qeGTgMHPVqGhyu5p7lfOEmw\nWaKYCLMnJei2dPR4GdXRp4GXJh52/EnePH6BWsDDMBmOcY8GOi08TLJOHZ2GonM1dJo9NQ5cfdTl\nOzDwWHn0fdhkSPAAH3UENjp1DvOAAhFu2aeotgM0dnW611zkzvToDyl03Rqyv8+wP03KtcJKc5b1\n0hj2ukZc2yeq5fB7q5i6hKZ3GD+yxphnC2e3y5u1MTJyDHpXKFYPERIlplkhYe0RMwuEjBJbVpKs\nOcGD3hGy8hA+ucYF+TJR8niMFs2Gl6FyEb3fYCScpugKkHeF6eEgUK2i15o4/X0kVxW32sRFmwYe\n9kjQo4hqA30wuiqq3GN8ZB2jJSFbB1//KwTIMHwwy9NeYtw+WKGugp+iFWGjOUVUzTPhXCNNkjo6\nDnoE7ArDYp+AXaaci2E5BQYqi+5DSLZJyc6TtmMYQgUOFr3atFJcNc7hk+rMc4+EvYdhOmj3XQwr\n+6zbk9T6OmZTYcS1x4X2Ff6l/Ktsy2Pocp1KP8CKNUNd0mlsBnCYfZzxLj3JQR+FOBkcGLT7LvLN\nOJpmkHMM8X77SbaUFN22k/VLM9h9CV+iiqvfQlYsEuzjUFq4lDYmCh2cZNxDXHOfQqPDFAWi5Knj\nxUZmlB06ONmWx7jrmWOrlXrUpTsw8Nh55IE9zgb/OQvU8LHDKHmiHOcOy8zwlnqR4MU8hl9h15qg\nUoxSXQiylZrkUHiRKfcKKXmTghVjp5qCu3D+qXe4cPZtcnaMDhpC2PiUGj6qdIQLVTKwkEDIMGPR\n8SgURIQV7wTrnjHSsRFycpS7neO8UvwkirPLefe7/APXbzFq7+Bv1NGWLByOPpWgjyGRYZ0J1phi\nknViq0VO3Vng+NkHfHfsM3zD/8s8x+sIbJY5xB0UzMAFOGbjjDRQ9A51ycuc5z5hioRFkTJB3LQ4\nwiLPmO8wbm/xW+J/YluM0e65Se+kOOq/SySZY5QdygTZI8EN6TRdHMzIq+SfShJRCjwt3qVImFV7\nmmXrEKdsiIgCW4wzRJa4yKIpXY4rd/gZ8V2et18nXKtiNJwsDk+T0Pb4xeHf4e7PHOdk8yaH8huU\nPSFuuk+y5pwi04xT6/swVAVzUcK2BP0nFdq4qRDEwMEafgqdZyluDNOI+dgLJfjdvV/B7y/jbVSx\nf1sQv5DmxM9fY1TeQWBTtoPsyiPo1HHSwUb6oEae4l0iFNhnmDAFQpRw0yJBmhZuFjnCzezZR126\nAwOPnUce2BYy2+YYr9Q/xbCa5inP2+SJ4KTLV8U3aTi8XB17kj98LomVU/C3m4z611GcPRqyly4a\nz7te4+TYTa6/8AQ7nlGKm1+itePC9Cto8TYT0VUMSSHfj6JGWhyW7tFxbFJsNFEtC1e4xYaYoCZ8\n7IthVq4cJm2M4DjRYUZdwqO0+Nf2r/JV61s8a76N07Iw3QIjyMFlF3qYhsw75YtUfRHSTyRxDPUo\nOoOc4DbTrOGhSZI9CljEXVeYG75PxelDUk3CFDgtbhInQxMPJYJIWBznDl1J4x2eJi+iOOjisVuk\njQmkvo2LNiYye9URbpdPMzSUw+VqocgGs0cXaVtOftj8NM9pr/MFvkPU2OUpM8GeFOcOx3mGtznN\nTWbMDcqWn4bwUiCCnxYeWsiYREUejS5v2Rd5RXueukPHVgWezTbrVw/TmPKgjnaJxbMUiirRbp4X\nrFe5yzHu2McxTJWa9S6a2kGNtgl7c4woO4SjZcKOAi65TfqrKUrJEGv9KYblfU5V7jCe2eHS2AXW\n9QmucZb93jCNjo7Ulmj7PcScB+vGNDb8BDsVPjb9Og61i0yfDVL4Q6VHXboDA4+dRx7YRcLct4+w\nYMzjEQ38VEkzh58qT/MONXx0QxrvnzyLZ6GHrtbx6UXyUpQWbmwESS1NMpamGfOwVDjK2s4sjZwH\nLEEgUCZk56nbHvYZJubPEpXyZNUs7W4HS1bootHASwcXDrtHvhKjbumkPOvMysv0LYXv9z/LDCvM\nKKv4/G3MAJS9fjqSEx81InaRy62LtAMuiBof9BsfzHrsEaLIEBlihDmq3kNX6zzgME08RMkxyjbD\ndoau6aIsBQlKZU5yiy1pnCwxIuRx0ENIsO0pYpoymWICyWdQ6ofptTVMU8FExhQyvkQZ2fBQbfuJ\n2AUOiwdkyEN2hLQYpRHXQYYhspyTbvGueJJVe4Ku6aIhe+g5NTqSRt3WyfaH2CmNUVAjbIXH8Ika\ncs2mvBDBF62gSxVcaptYJMNkd42j0gJ3OcaGNUHZCCI17+HLHaxZLu3bOOUe/tFN3FqTnuJEvGjT\nUVxUTT8CG6fRQW80SPU32bfjvGs9hWIamKaDVs/PvplAMQ20To+16jBlI8wZ+wptnOxbCba7E0Sk\nwqMu3YGBx84jD+wH9mHc8gznQ5eIiCI3OI2DHioGTTwHvchqgS8G/oT5cwuURJhvS5+ni4aXBmGK\nXOcMdXSmWEMLdtE9ZRYTR7A1QdiTYVJZQ8JiQtlAE11sBFkALxS1MPc5yjSrHOU+k9I61WcDbDHO\nCfkWHZxFeeB4AAAgAElEQVTsW3E6XY072nEivgKj7l1k2aAjuaiIAENkccst3gw+S0TNMMEG+wyz\nziTXOEsVP0dZYITdh/0ffZp4PthkYJJ1ioTBlLjQvIbllMlrQUIUkTFx02KORXYYYcMxweT4Mjtr\nKf7oxtdIntkkFdjgk/p3cSkt6uh00NgkxYyywn/r/V9xiB4POMT3tLPU3vs1rKrM+a+9RdBTZkce\n4YF+iG0ximqaTNR3MVSZBd8kGWmIS9bHeKX9EtmNEUy3RNel4tS6dGNupKct5ubvogx1eGAd5sKX\n3+M079NUD5aYMiyVblfD2A5Qf3kSS5NYWjlGzkwy/+s32UmOkraT1CwfETXHrGeJYWmfe9Ej/F7g\nqzzneAOn2aHSC/Bpxw+Jaxmyepyj8j1ONO5yaneBK8NnKAV8nFGv8W2+wI96nyS9n2K7Mv2oS3dg\n4LHz6M+wK1HuPziONt6j43ayQQqFPueq1zlXvMV2PMWeO0FFDpJ1DQEwyzJxMnQKbt69e5HsVAQ5\naeCRmwzJGTS5x4p9hOPSTU6r10iTRGCj0CfNyEGvsdThZ6N/QE9WqeFlgaMf9BXL7j5Hjft8ufod\nvuX8CjXFzzntGhd2r3C6cRdfuIrts8m7w9yT5rkn5kmTpCr8rPWmMEyVjuZEKDZuqUkVPxtMUMWP\nmyvMskwXjTRJNkjxPT5HtRNgzNwhpFXIKVH2iLPFOA56aA8XwXLSRe5ZFLaHCJslzk2+T9iVxSs3\n0OTuw3W3mw83PFgHAa+L57nAZcIUiUptzLkalU4QyyGzwgwPxGHawomLNsNSltuuozjlNg3ZQ44o\npiSR1HZJju0jVAtTFazXZmk1dIRqE1DLsGfTeCfIg5l5PGMdUr5NDFToCsw9Daeng3c8R/HqEL22\nRiPqpSr7cNEipWwyF1mi/CDE6mtH6Jz1kRpZ50nve5wwbzHDMm61xbS0SltykZeirDEJmiAaKSK8\nJqpmsMsIEQo8o1wiGKyyZMz9eft2DQz8/9ojD+xe10EuP8y6Zxo9XEXymDjokW0Ns5tNcV8/yj11\n7qB1zAoTE1mSjjSp9habuSmuPriAI9hiKJGmbnuZEC10u4VmGszaK5zjfRY4ioUgaJfZtFLooo5b\nglOBa3TRuM0JrnOGIuEP9k2csLY51FnBUiX6qswpx02ONJdIFvYRmo3ptGm6XGh0We7PcqV9gXbN\nRd4aYkuZJCQVGJG3GWYPB12KD2cQxo1LzFQydNsaO8FR1pxTvGq/gNw36doay+4pGsJLsR+h0dBR\nnT3cziY+atTRqfYD7OcTnIpc59mp1z7Y6qtiBwg1yqhtA8uQCYZKLLtm+H1+jpPcJMUWIbp45lbY\nI0EdL/vEaeClj8IIu/ilKmvOcUasXbxmE1uSiIgiLu02nTENBRPJtKgaEWxbweet4VNqdAsO9KUm\nu/oYWqTLCfs6tgC/VaXfdeMIFonPrdNddNIKeCBlU1JCjJl1UvImU8FVFtrH2bw/xfKEzlAswzz3\nCNtFoiKPRzlYW2WVaero9AliOwShaBGAPjI1dIJUOKNcxwxKtEzPILAHfuo88sAOhMtED2+xcvcw\n49UNzh27zDSrrDtn+GX/N6h3NDplFVOSkZsS444tnoq/yevpT7BSOUznhItkfItpeZUJsYEDg7pD\nJxTL0JUOZkZ6aCJhotoGzZaHjuLETYRLzDDKDnPcZ5EjaHQYZZsYOXAIfhx+jqqkE5LK6NS5PzPL\n5sQYqtpDVQw8UoNnxCWWqnO8mvksVkbC9oI23CIlbxKRcij0mWaNbcZ4zzrP56pOwjfqWMtNxl/a\nITqZw7QVnne9wRlxHVPIAIzXtnjqxjVuThzn9tRRLCQecJirjrO0Ug5aroPe9SnWiJBHNfrEFio4\nV3vYeeh/DpxTbfalOEn2aOFmgxQfY40Um1znDBIWQcp00CgRQsXgSa4y31/EZ9SxXDIZMUSOGG/z\nDB4aHJEXORK9gzvY5ph5j3UtRdUb4MVf+wG3nKfoaRJ3pONo9DjluUnv8AKZe+uMDCXo/qLzYJcf\nyct+N4m31WBC30CnzvwTd/HMNZB1E9Vp8DbPsCAfRcX44AOlSJgSIZ7iHYbIsc4ECuYHi15V8VN+\nOPkqGBhcwx746fPIA3tevcvRACyOzVMxg9zeOUMj6mM7nWLt3Ul8zxaRAgaGrdJO62SUYZbjs2y4\nxil4Q1gdCSQId0q8lH2DrcAI+UCECXWdAGXqPZ3dXIq+W8Llb1Dv+jC7Co1OjLSZpCc72LVHyPVi\nyIR5RX2JTslDjBznwu/R7ruomT6aqhuHs4dCHzcNbtdOU+4G+WLwj4k6c1wIv03CsceelmDXn2BE\n2WVYpAlQRcYkQoGL4k2E06QyrBM2K4x406TEJn6qnM7d5gnzOvvxGAU5Qs4Zwxh1kvYP08PBHAss\ntQ5T6sQI6GX8WgULiQJhOjhRZQN/vEGgXEXLGRh1CbkJBT3KNqM46aJTZ6uVQuv1+Fn7uxhuibJ2\nsB7IPsO0cLPCDCP2Hglrn6idY4MUixzBRKbQj/BO7xly/SGmlDV8noP5qS6lTdBZpmerWEjMcZ+x\n2i6q1WfTN8pbcgNDUWn7NbqmA9nsM6ZsMaFuMEQWAwcpbYuj0gP+VPs4hiwzSg5TyLRwH/RXM0aJ\nEAp9ohSYZJ0wBYpEqKPTxEOYInH20alTVoL84FEX78DAY+aRB/YRFnnWUWJoJsul7HO8l3mGTsBB\nPe9H3AD3iTZS3MDqKRh1m7qqs9w9TF3xomlt3EYFj2jgqnWI3SiyNDtL3j2ER7SQZZNa38duaYyW\n7cTjrdGq6QcbCxgeuqZGSQ5RR6fdd9HAw8vKp5BrEqe5wcfDP8JtthC2RUPRUYSJkzYBKmTaw9xt\nnmDefwe/p8zTnjdIxTdZZ5IHHGaWJca7W0Q7RZoeF16lziGxxLtei+3pBFZCQXN3GCJHXGQ4VFhl\nsrvNXixOXdZZc03x5vRFZNtkxNhF7luIpozUlZiLLTLrWMZHjRJhdhijJzuIjedw2D3MtoYuN+h3\nHXR0J2lGCFMkxBbrvUlcrR7/o/0PqaoeHmjTdHDSR3m4IfEUI2KPqFRACDB6Ko2uTsqxTc6Kcr97\nhGbPR0vLYLhVbFPCQZeIXCDWz2HbEjE5R6q9jdI3KepBun0nnU4UG0G/o+CwDI75bzOhbOC2W6R7\nI4z29jlh3uW7js/gNpqc6t2m5AiyKycpSBEsJLpoD8+m64xYu8yZdVbFNJtSioIUPtiNxq4xKV1i\ngblHXboDA4+dv4ENDHoEqDLCLnOhewjd4rh2m6WhOVbPHKaQHULkbcyqjBWWMcMKuUwSc00mIdI8\nd/oVgp4SzWUv//UP/zGZRpyGz42k9TjsvU/clUGdbuJQLPo9BXtJJhwqorvTxFUfCfYIiyJ3XcdY\nY4p9EefZ5EF/MgJecLxGjhhZMcT1hx0sfqqkQqtogRY99WAKtkaXH/MSk6zzdb5BlDzx3QLhB1VK\nT+jkomHyxGjh5r4yzWXvBWJSlip+pljD56pSU3zcFicwkdDMLiutGRqGzq3Oad4uv0An4GA0ts4v\nqf+OGZaxkVhhhk1SbNtjvNh7hdXIJD947rM853yDIUeGv8O/YIMJioQxUPHrFUy3zGXOUJX9rDHJ\nPeaZ4z4nuM0+w9xVj7KiTDMp1jixd4/PbL6KOtanGvawqw9x3z6KEDYBu8K3G1+gi0bAX+V26Qzr\nxhSv+58johdxKl2akpvVxg38mQkuJN7kXu8khWaMY9579BWZO8YJ7uydoeH0E4wWmJJXmchs88Tm\nTXrjCq+Enuc7zs/zNb6JwGaVKVy0ifRKREpVwo464640d91HeLn3SbbMMZ51XmJfGga+/ajLd2Dg\nsfLIA3u5P8MsXmwEc2KRE9I9TAHSkM3Hn/wRixwhn49h7qoQA5e3SdiTIzxcJCnvENbzhOQShtPB\ng7HDyFEDv6eEonSxFImq5MPlbhEjh241WBiRMGsKjXUf3aoTZ6DDEFmWpVmGyDLLEse0e0TJ0MHJ\n4fwKSTPDj+IfpyoFMJHJEKetOrGBCgGG2SfBHvsM08TNMrMYOHB5e3gSLbJajDZOgpTx0sQhulRl\nnTwRNLo8w9vE+xkUwyRGFgc9olKehuplWxqjJgI4rR5Br4HuqHLHPoawLabEGkFK+KgihE1JDhEy\nKxyrLSA5LdqKExcdmnipcdDj/KT8Hh3ZyRKzrFQPsdadJuuKMOtcZkTdJUiJ2+Ik98URnLQZ8+zi\njdW45T1J3hGirwgCVPDSIGiXSah75MQQaZIEnGVS6jpC6RNwlHHJbbzUqDqyDHs3kBUTe1dCSZsM\nhbLktQhlI0guPcRl71P0vQLVZRB2lSlFAhRdQTalFGkzSVYawiVamCjc5RhN2YvLZeBUOlT6Qa7u\nnsPbbvKMehn3SBsh2Y+6dAf+yjRA52ADW+/DxwA9oAlkgTrQ/UiO7ifZXxjYQohR4N8BMcAGftu2\n7X8ihAgB3wLGgU3g523b/jPbgGwaE6Q7GlFHjqPmPY70lnldeYbx0AYp/wb/xv4Vah4vVlHG8sk4\n3U2GXTtMTawSkCvUZJ0AZbRwB/mFPsFEkVHfBn6lQkc4qds6DmGQYI+EtsfekWG2L0/SuR8nmxkm\n5sgRtCpUnX6CSolP8iNahpseGg7VIFwo4+z1sGMS/m4N0bcxVYWO6qIu61i2RFTkGWcLE5lrnOH7\nfJYT3KE25KMx5D64CWZXOGHdxmt3CVEmQJUHHCbIwQSZsFnE6Guk7E28RgPZMok5cyyJQ2SI4wvV\naOMkyxDftr/Ivhjmy/wRMftgenpWDFFUwoy303x1+495oE6Rl4M0tYN+7woBAC7Y72Ki8H3xWdLV\nMbK1JN2IQFUMfHINZ68DMhTVMDV85KIRRNTk9/kSewwToMIx7h3siiP6HHUv4KVBkTBH/PdwPFxU\nKtCt4O61wAm4V0hFg2QZol+U0bY7KL0+vb6DRlvHrgmWrUPsNhPMOe7hDjRx+Zts2iluWqdomy7W\nxCRBUcFDk9uc4Kr6BJ2giwAVulUXtzNn+R/a/wuf9/wHrgyfpqwGPlThf9i6/uklQHGAw4Xq7+HW\nWvioIbVsaNnYLehZPgx8QBibGOB7+LsNBAUEeRTaqKKG5AbbLbA80sGly66bXs0B/xd77x0kSXbf\nd37Slvemq6t9T/d09/T0eLcza2YXu1gssCQIQ1L0lHgnhE6UTjSSeBdxcXehON5RlBgnXvAoxRFB\nIkRSB4AwJAAu1mB31szOjrc97W21q+7y3qS5P6pzunaJICEu5rgL8BeR0Vkv33uZlf3qm9/8vt/v\n9+pV0Bq0/jV/b5Z9Lwy7CfyKaZq3BEFwA9cFQXgZ+IfAy6Zp/ltBEP418Bu727vsI5VX+bmZPNqQ\ngeEQWZB6uScdIF5Lcr74Fl9RPosQ0AmeT1LUPJRyLqZnDrHiGcYRLePszyNJOg53Dc/BNJl8EGND\n5kT8EmnRTcLoxSbXWRH62dTjbG33Ut3xYFRlppcmSOwM4MqXUE+WOd5xDZ+Z55sbn8JJhV/v/d9Z\n748zY45QkLz8+LWvcmL9Jv7+HNd7D/NG+Bxvao+hiE06pCQxtvCTo4Jrd+FfO+XdDH37Gkt0VtOU\n9E5y+OlmjV5WaaJwj4N4I1XQBaakA5xduUxneZvF/fuIqK28fQBrdGMg4RLKZIQQd8zDfKb2NfrF\nBKu2XhqolF1OhE6TvtU1Arks2XHP7lJlflJEwVih31zmrPw2z7lewZBlbvkPcES+hVzW+Z25X2U+\nMoCzp5XDY5so8wxRxdHyA8dgmX62ieCijIxOkAwBsgyySIowL/MMhdkg/kqe00cv0mQZOzVGmUY/\nIbM13slMYD+TqUPMbI9jHtTp9CTocG0RklPMGCNc1M5RbHiQRJ199gWcYpUOkowyzR1a8lUNOyYC\nIVeK0yNvMWXsY0X6J6yrnXSy+X7H/vsa1z+8JkNoCHHsNN0/Pce5g2/yE7yI540q8htN6m/A/YpM\nwlABJwYKxi7MiOi7q6eWidNgUNVwnQbtSZXMRzz8OT/GpcmjLP2XEYz778DWHKD9nX7bD5r9jYBt\nmuYWsLW7XxIEYQroAn4UeGK32heAC3yXgd3FBj1ajnUzzC3xMFfFk+TxERVTNFWJbjlBn7JMUXVT\nWXBS33HRqLioBhx0OsrsF2aYqE7i1YvseCLsmB1QF7EJdWqbTjI7EWz+OkJQwO0uINmaBPt3MAZT\nlDWVQrkTxVXnlHQJlQY3OUraEaBuqtzhEDOuEdKEiLPOoG+BwfoCLlsVvSy2VhH3aKS1MK8b5znt\neIducZ1HuISMRm86wb7UCo1uiU01RlV2sST4UDlALyvYaOBsVuktbSDZNNaUbq5ygph9G7+Qwyvk\n8ZPFaVRwNWtEpDQBKcvJ+g08lSKxehLFrVGxO6gZDjpSKaKZNELaxDVVRfZrqJ0Net1rNFWVMln8\neoFIKcOR9F2iagbRrRNUtlDEBmtSDyveXjK2AB6yhEnRRGGdLrpJIAAV08Fsc4SQkOaMcgkDCTcl\nYmyxTheLDJLFj9tdpkPZwifmyDd93K1O0G1fQwpq2OtVrm2eZik7RL4WwOaqUNtxUlr3Eu5PkV4I\nce/CIbSIgmeoAAdhVt5PRXLSLy3veoRkmOAuJiJF2UPR60ZAx0GZKNvYqb2vgf9+x/UPh8ngcsLR\nPg70LhLeWGVwQadSWqOY3SAwtc5Y9R5RlvHM15FSOlW99WriBARaIojFk8VWj4hAEHAb4MxCc0Gm\n7nUywBVqy2U6s/cJ1afw9W6iPCvw7XsO1oUJuLUClQo/zCD+X6VhC4LQDxwFLgMdpmkmdw8lgY7v\n1kZXJbJ+Pwm5l9d5gr/gkzzBBeo2hRnbIDFjk0EWuW+OoSZ1GmmTpgOUSJX+8CKfNf+Ms8lrKHWN\n5qBMyh6ioPjYEmPo6yrGpI1mj4w6vEXEt4MWklH9DaoTmxQ92+RUH8r+CsPeGVQavCo8hSdaRGg2\n+H8LP0XSESWi7vApvoYwppEcDhErp+ndWKMrs8Hx4Wv8rvbP+Ub9R4mrGwyJc+xnFoUGfTvr9Nzb\n4hu+Z5mMjWHIIstSBdEcQtUb1CQ7A/VVHstcIRdxsmjvYcYYYTC2SETYwk8WB1V8ZpHu+jZRdZt9\nzDNemMOVrtCoKKwMxtkUY2zrHUQ303Rs7KBnRcxlATmgE1ovMNo7i1stkmMLn1HAma/Rf38duU9H\n8wn0C8usCXG2nWGCQ0mgQcRM0Wsk2BYimKLAMeMmIjoLwhC3akfpYY0nzQssyoMoYpMxprjePM6C\nOURAzXJk4DZDzOGjQE4Lc7/yCCPqDFFpG6WmcXn6MfIEEHwmxrZKbjtMNe8hEEpTfdtJ7TdccFIk\n96Mq+V4P644uEvYelqQBRFNnnEk+LXyVOfZzneNsE2HUnOYY1zEEiSUG/vaj/vswrn9wTUaUJWze\nBraGieJRaXxklMeeXGb/5Sk+8a3bpN9ospqF4m0wgDlA3W1dpQXUNkCiBdTvFTY0YBNYa4J0E/Sb\nGvU/KuDiBU7yAiZwEOg7JOP6FQfLf/I8JWEEZX4DTTSpqwL1goqh6fywgbdgmt+bRrT72vg68G9M\n0/y6IAhZ0zQDbcczpmkG39PG7DzeSbDLhSQ1kQ8Mkztwhl5WCZPGZla5XjlJSowgOHQ85RL1TQfr\nM70IXQYHo3f5RfcXCF7JkiqHeOXp86wsD1DNuIgc20RDRq/JhNQMblsBRW2Qx89GvpvEa2scfdSO\n7GiQtQXwiTlUsYGBSBUH2fUgG5d7kI838fVl6GeZbtaI7C4R1jG/Q2A7hxaTWAgOsOgdQJNFRKF1\nv8q4GKgtM169z4x7GEGEmJbk1at2Dh73Ei8kqfoU0mqQ1WY/TVkGyUQxmyhCE2l3STA7NRxmFbtR\npyy4MJsih1YncdrLNP0SVEQm7Qe47D1JqJamv7nCsD6LUZNQS018uTKbg2GWQn28dtHBc4/kiGvr\nFKp+QlIaRWmypnQiiCY6Mgl6aKDi0spM5Kcoq062XFEGyqtUZAcJWxe+WpFQKUOomCYRi5N0RcgR\noGd1A4depdDnZknso4gXPznuvFlBfeQ4PdIqHqFEuezi0sxjFEQ/ir9O3L+GLDRp6AqmB0oXfeT+\nNASSCUdB+DGDEc80XluWqugg1QzhNYucVK6SFKIU8OKgTuJukfL0GiEhjS6ITH91DtM0hff1A/hb\njmuIs6fNRna3/78sAfQ8pL5juDo8DH0ywdjiPF1X1ll2ubE5C6QrW4wUTIxyC6hNWuAssgfO1bae\nBEBvq2eZTKu9xh5jNGlpVNpuGzugukDuFrme9RIXOujNl9h8JM7s0D7m/ryP8naR3Zekh2gP8163\n287uZtn0dx3b3xPDFgRBAb4C/GfTNL++W5wUBCFmmuaWIAidwPZ3axv/1c8w+tOH6GWVDEHW6GEf\nLjAFNhpx8reeoGFzET+yyjCzlBb9bL7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iMlLCwDArSILGbeUwvcIabqNCCTsKTUKkKeDF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\ncpJ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5wWkCkSo++wGPu8scNqZo1ELYKYlKIcad965Tdkbw+Ft87h/9CVtjs+QPn6N+K4qRVFAm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\nHip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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1083,19 +1070,11 @@ "metadata": {}, "output_type": "execute_result" }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python2.7/dist-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n", - " if self._edgecolors == str('face'):\n" - ] - }, { "data": { - "image/png": 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T0BgIG1rgkS7gNEPzYRg5BV5cDg+/DYkaqJwMWWEQIuDIJpRpy9C51Sy97h7qx7eFdu3Q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\nclHkFUihhRAohR0VsOwWkGqg0A3bZEiIYuCmh5lmjmRIv4cvW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UQ9gffLu/CticR/rBt/\nTxr+z/cinfgRyyGB2uUisc6L1/UJ3YMEaq4XR041whpAmEKRov6M7WsfIuCDjFEw5TL48g449BEM\nuRxcA4R3n4e+9l/Skv8m+JH/6vZz4tcxH/+loKrQVA3xg6BnN6SvhgWvQv6LsOw2GJeC1JaCq6Ib\n3U9xaK5YB2GxMPFZOPsOVO5APm6A5OF44qIwhJ9BTXiRSuM3ZPjKCKTZkctzYM53sH049NXCoCbY\n3QF+F6RZMVStgVuOwheZoLGAcxS8tgaU35Hz7hYuzCpAX20iosuEbcN71BVdR4qohovvwjljsLLK\nMoKtu4ZzRd9Z0NbDgZcgUQe1XjgXCQXrEBmPEpV2JdXKzXC6k+TaDTQaGrF4nXDhDjBaiHCEog/X\n47rvcYzjF0D3Bdi1EuZPQTRvhH4d2o19KKEjUZJ7QdeKSNWhajsRSc/Dgd2w4eu/JPBXQdoAjLsM\nogMw4QAU74TPX8Df50HS2VDYiNoZQ09iPBFdRQjvGkT5CVh3FWiaISSdcsNs8tISwHAYoo+j6yzE\n98XbqMmTkBamIW58Apa/AOd2QpwH7Ho0g24lsR844wKjjQjtQSIq94EAddRZaGwIVvc1PIno2EqC\nIYzOu5dgevEx+u88Qe9xD+7PDMSPjECfKcHUJTDkWtQZg+GGdEhsxZ+Ri+G19/HP8pO+sht9hh79\nn7/D2HEW55YvaFn0NLqv3mLykX6UkmqE7OXcgecQkoOOyEvJ2HqU/vQWQtq7UNHgGpNI6IkaNOUB\npJ4mePB6OPg29AFN/VDhgSIbTN0Mdaeh+iTM+oumYfyD8ONK1O5KlOfmonxahiiYjLb7BIpXi6Pp\nG2zTDqPmDuAZo2KK+j2S+Up461o0mTNpOnQYnSULYZtGVHMyF31HaJ+mIzAyFc9POsx4UX0hyEkT\nkWo/h9MboLcDZiyBjlrY+Qa0VVKSdidJoQm/jC3/Hfi1hCN+HWfxS0EIWLsUssJgkAssYyHmCah5\nCm6+BV5fhYgPYLxjIe616xHDZaRpzYhNM0GTCVOfhO9fxhQ5DrXpG7joRVybREx6K1KHE5xAnx9c\npyH3JtD9BJ+dBEM3pOlBEwtzlsGnY8CtgSw3FJlh9zA4MYDttIrxwlFCp+ShdhwluqwS776NsOwT\nOJMHiVPh3R6wv0FBnR0qnGBpgRQzyF3QaYEb3BAwwYUtSFXfYM7vIRB3BtmfTkv8JGJj56O7MBk2\nXUC0KyRnh1Eu/4lxuwPQvD5IVLPuGahUIVOAORSptAoKpqN2nwD/SZAKYecLYMiBnDzInwIf3w1V\nToj7DhriglV/ykV48BF45hUC7TnIFXuxnpxB/5wDSB9vhtBRkOSHPiOcH4D8Tpq148krmgqnoqDs\nK8RcGenlOLzmVgwPbgRzKLz4KXj6ob0EvO2Q9j8ISzbvgJXTg/fCbUN0LwRnIcRuBmcvasQw7OE/\n4c9/G1dpM11XK+gX3Ubq4gREp4DaTXDoWej5HklyQt0RyL0d2bwSea6KODIY6+MfQtMu/H1h1D23\nFTk0nbRP5iG9fz9+qwGXxUB9YRppB6rwFhsZmroZgxOUpFAk42A8+RYs01dTc+ULZHxaA40/BoVl\n89+Fcy9C0iVw+Hlo8ELjduhSoOIguJwQStAh25Jhdg5EfIeYqEO6ek7wGbz0KsI/Xw+j5yGNaMYj\n1uBX1qL5YSsiowC2fkLXvuPEP/4qKC7Ub99DTvZh8EqUa3KxjzmG/8dGZEcoUnszCBukjIWRt8FX\nj0F8LtyyCgI++r/565f3vwb8WrIj/t8IR/yPseZAH9Gm09D8Aly4AcZXwenXwVEAjho49AI4SsHq\nh28boaMdcfB9jJc6oFiGZlBTLwO7DnYvBdGHVLsTqdmDOskI/RvRVLaDLwdftoCkkVCxDAZCwWOG\njKuD7OXdCowYDNtuQG1thRAnWAHTLqi7AAfaMKCw6qHlyPM2ImIW4Lj8Fsx+HerGT6FHgoMy6GJA\nChAz9ix0tsKkAohxgW0iJITCGQHHmiH5ctwF8zAHepGbDJzKbyPSmE6j77sgX8FvilDvncKQ2JnU\nFxpQjGWomgBqQkdQAidJhX4N3L0WokxQVIswJyC+tyC+OADlLRBVAXc8C4OyIEyCgrzgefq64cMs\nWH8P/ed7wWLAV6NBCUnAcNnd6C9m4R4WAp2nIH4MaulOlNgucIWRs/5b2L4a9m8FQzbIM5EXCkR1\nK/6PHwe/P3hfdRqICoVoFXpegvqFwTH3PQJaAREyxNvA9yGsvR9GDSJQdxy3phJv91B87y6g9aME\noh5cQrTThRh0Cag9YBoMpQ1w8TziigxYuAU1702U0wpoApBXgfrJZDqXfsnFS4uIzLARn2ZEfeQh\nBs704PfU4QqxkuJKIaxoPjEF7cg6GfplNA02pLJWjN+2o3nufmI+PIO/uwmMBVC8B7a9Dd0JqGG5\nMOdl6LOBMTGogDLvDxA3KFhwtG4pXLsYcdsDSHE+1GtikZq3QF4k9E1EfHYK0bAG2TUHk+4cmsBT\niMOrYOsrqM7TdDskLLFa6CvnYnUjhusFNRXTiN8/jrzvxiLJHtQx9wVjvUIPHR1wYj3c8B5c9hQY\nLMGX4T8Zfi4qSyHE80KIk0KIUiHETiFE4v+p/7/2TFhxQ9sy8JwHZAh0gWTBqgVsD0LMkxBdD5U3\nwvYd0LQfMq6ENhu4WsFshe864fY42OdCHh2Pkt2PcqAYWTWBfRhCOYJqVVALtCjdev4Le+cdJVWV\nrv3fPpVT5xzoHKADqck5KJIEARVFRTFgxpyzYrqCDmaFUQwomAhKzjmHhqaBzjmH6uqq6or7+6Pm\nm2/ufOvOmrtmnOvM3Get88dZtatOnTrnfWrv9zzv86pmrqVN83v0O3egtHqANtiyKeAHe3wf0pCJ\nc9wC/N+voqKmmsToHnyxkYSr25HHHIhUH7THw6QQim7dSoolKPAnsvFjgvok4smMQfqjEblvwIUV\nECagpS+Yt0GbFzafAH8WZOWCKxJMZZBZCKZ2uh0rMemGILpOE2RT4zQuRbYIpFEN9YegTYVOD4N2\n1eJrd6JWGxHOWMhIBVcpbr8fbeEPII9C71VwdhEc64L4RORkBRpKEF8OhcZuGBwGBhsckZB0GzI/\nk6ZD29CeW4Yuvy8r73qMAxEanj+8A/8aK5FfDEW9/SeszasIyexA5tyEMvJ9bHVzoOx9OAx0HgKt\nHdxGxEQvqsc/hfAiuLxXgBzU6aDNgmI9vPc1ZA+H6ma4chDoIqGuCJKm4otQQeFBlH6fovl6KlVv\nNyEcp8iorEOxBMHhLbDpB9A1gC0oMNP77g3kfSshtgXZPiPQCqvKRU95BB7ZRvA1rYQOWUrbhXLs\nP6xAb+lChigYrR70PVXg7II+iXTf0I+O1Q3EhHbiCr8KQ+8oCMkEtx1PthHfrrcJcSWBVCNtu/Hk\n9kN97kuETQtKOhR+Bbl3Bmw9AXZ+GVDTKJ/D/m+QrRGo7fEwcRoYfLD/ECQnIdMewb9zEUpLEMqZ\n8xCmRgbn4TO0kte/BsuJRXQNj6TniUjKFlvIXnI3GU8/Duo9iAG9UO/+Ei7WQ2Q6zFkGYf88aYf/\nCr/iTPhNKQMN7IQQ9wHPA7f9V4P/dUnYZ4X6F8FxIuB3mrgU1OEAlB5cxWBjPvRUQMkNoO34Q5eK\nBqjaDpM/CuRnT70K/Z8B/Sj4/XPw1WMooQmIlJXQ6cdT1oUmNw/OX8AbnYlPVYpn/TzEmLEoXW0o\nh5x06NfBhS4M59+i0qalXW3DFLWVjAgDfdJKUKVZ4EAjnPHCFVpkuAn6aBDDn2WwOYZMJBzfjBw5\nHeusgfgrGwl+7z9AHQWas6DkwYTPaDsykshPGqGgCM4egy3LA85Y+w7A4WAIex57ZB9CGqJRiRDS\ntgzBOusWGkM2480IRhNyGhpiIPpWijPWc/Q6I3NX1gfkRvvfxe39hYvtcUQWrifmxg8heS5UfQym\nfWBrQKp1iEgnaKzQUgsbnPD4bTBgE2x4l57Rr6DNG4axTx2F/SdSkZVGjtePatVaqqq8GIrslD84\niHhbD8pRI8rP30DULOrCBtDnmsfA/iDUn4XWHxFhqSiX/0Jn5qOEfpsDM+9D6hKQa9YgileAyQCz\nX0LkjoAProfgJvDW4w8Pwlf1DRR10S1C6FSvQL/PQfggL+rL+9HqeRA/RhgKOnEJw95DiMnpaP17\nYFI9hP0HeHshjA5aforAZ2vE09FNbG8Dvp8F3vpbCUlUIwbHoD4fARY7xFmgox7SUpAhJ3Gl1mCK\ncSNjDPiPnMatSkR73W3wy1MYC56leXAqIb+UIzX78QdJlNIyxIAHYPA22BIDe16FDh/MfA2OfAeX\n3gAUuGwBRE6ALx+B8beAewf45iFXLcSd1EL31pvo6m0gJFyiHtmJjByAY/z9KOfOE3n6FWQUdCSp\nqLWZ4OpIUoqfBusJfBHR+COCEJVnITQNrnnvX4KAAVz8OioOKaXtT3bNQOtfGv+vS8Kq4ADx/iW0\nbAXnwUA3qFw9FGbD3J8hIj7wevVGWPkETLoK6qthwCzw7kBMVJDEovysw6OORDOrB6UhB9nRjqKJ\nwFxbi1NrgnBJ1cYuss0gdDoyjH48IyehC3sPUZcJOZNhwJ3Q/2VI/hTx4R3Ifs9C2wyk4RvUxUeJ\nyHoVNr0PQ9zEHPoYpzsW6h0Bjaa1FCIM8NkgwsfXQwdQNA3iBsKdE2Hn/gDB3zAXnCa6U2tJaG+B\ntFGInnWEVJ/EUnIAb0cXhIdCwWDEsi9Jem4uR7U7ac5VEU6M0DoAACAASURBVN1eBReP4jMK9gwc\nQWSHm2tH3QpdpaBPhQn7IMwMRj90gKxrQhgl+JqQa37EPSgCnyMX9YGvCVlyCOVCI4PTFjBYJOL/\nKpst1XZcFoFWN5GCE0eRw55AuftmWHMbIGkJ6g3pY+CuxbB0ITjskNIX9alVBPuTkXPiEaUPI2rG\nQP0xfCcakEVVqD6cD+tfQvgsUDYOwnQoi9fi7HTT1SeKJdzBktUvkjn8Eb61LqB/xWFYHIycPQjM\nawOrKLUGdkioDUWkF0Da9ciUqXR+vpy67xcSMTGWqMdiUV84iVJjQ+5UEAlqGGWDjDbQzYDQTrB3\ngN2B7DGhdhtQd3bgmd2OoSUad2knrm/fQmc7gm7Da0R2noR+xdClgE2NuOojxMe/B/txCJ8KWgE1\nm+FAOZzaCK7+kDASMh4CwDviI7TDboIPVoNmIyI4Ge07x3h3Tw93zThN0E8N+CsfRu0+iHpTE84h\nD9KyKwmzoZ7gQhv9G5tRghV8F4yoLSqUk61o3y6EE89BwxqI++0XYfy1+DVzwkKIxcCNgAMY+hfH\n/jvqhDeueI0p2h2gORBIOfQaCNZyUI+EbY3wzHpQqaC8EH6cDItKYMlzMH8RHHkUYsLA8HtIqcRb\n/TKXwncRG/k5BnUone7VBFd14D60iqCadqTOgtLvOTj7JbLGhitnHrrWF/B3hSMiC1DMbRBbAEmT\noXAvBLkhGWTOG7BuKAzSQksHZK3HXz+GS8nXkfboerQXK2DSbWBYDw4NFV29SGk8Clc8CDGA3htQ\nfLQ2QVgQiGpOZ+fSr8kBvhboAsQguFhF4fhUcp2TUd74Au64E3/HZk6IFiKirKQcDYI+Q2HtG3yZ\nM4fUdhcjbhwKp58EAZySMDoWf+Ik5IHvUVocCFcE6JPBEopcX4sjZRz+lnKkOR598iYc6w10zNeh\nyuumdY2BnIc/Q3d4KLgL4IajgYvU1QgbHmKVmBbQdEsJi9Mh1gatRnjsApSvh/MPQU8mZD4OfSch\nnU7kmZOw6wM85y/iV7Wyb9zNfO/pj9UfhzEknidPXU1pYQQnE7J4sPVzTPpoCOuAYBscFyD14BNQ\nMCRwPY5sgpueAuUAvtjhdCxfhilSiz5IhajvAp0eZs4Alw2qj0JtJDRU4svwozrRDWkSlEgYPwen\nbRWqHiueCQrGD7VgCcVR0huVrgf9ve/DgVn4jF7YZkcZ5EHoUmFdcECKd7kBrNvBKSBlAew+D2MX\ngMECg2chZRtu73PoNO8HfsNNP0GXlV39b+Lm33dRlTsNuuqgshbC1JAZDu5ByJYLeNaVoZnhQ6Qt\npit5O6bSI6iEAq93w48PgW07FBbDqJchfCF4/NB2AuIm/DGu/j/9/a+Iv4dOOE2e+6vHl4nc/3Q8\nIcQ2ApH253hKSrnhT8Y9AWRJKf/LBsf/ujPhP0frRVg/H1w2LqstBa0Fho+AMV+DNhrc7eBugot3\nwMarYNwSeONFWPQ+HHsGGuogNAhZewxnn2H0pA5Fqu6lIV1LYvt0glUFgEJwhwF95GX0mLYiEoMR\nlTbkkXWIpnP479qNds2LiIdPISo/xrEmGF3Q7/FVXI5WKYPmoygnDgBaxBWxsLkSeSkU7noLfIsR\nwVaCO86gDL0V78XXUPyNKF1eyLmfw62JpIy9Fba8DZYksO4Huw/M48DlAruN1IISGKyCVhuUCegu\nB62gV00MfufTiGgvcskdiGMu+o400HB7OGjbwGWE0FCu2L8TtykE3joFcWNBtxOZAMgmlJZvkWaB\n77JHUO94G453QK4B8fzLmJasRc73I/LacBfGc3Gih7gdzYRtn4wpeiVyxSwcTTqEWoXhen/AWCko\nBmJyiSk5S0lFB5p1z5I89GGIrIT9v0DTFPBchKRoyFkNqkiQdoTBhBg6greq3JwcMJgrz35BWsk3\nvB63ltApryGSB0GzmVS1n/TP38I0WB04lyYbhNlhugu+OQr9r4TIfoGVUnQc7HsTwrSoSs8QltUX\nSTbi+Ebop0BBLASlQ+7TcORj4El8EfE0fVxGXJgEhxryQuDMWjTSiytMg642A/K8iNJLGB+7no6b\nNqBbPwCh642YsRqxZDIiti8ESbixMfDgK34KOMdDuxVcG2DMWNj7WkCz3nQUf5weJTYUmreBowk+\newWuz+XMdoFONQ1X9nx0+/4DMg0QPh8KT0D5BoRGoAkCed4PuqdwJg/HHV5AhPDDXXkgboTwKBjU\nAeQE4qH0c5i0838omP8++Fv0v1LKy/7KoauAjX9pwL8HCZdsDGhP/V4YMxFl/AXY2gv21kJ+F0RH\ngzYssA19BSr3wdbbYBqQmAnt+wM+At/egMiYjtE8D5+6mA5eJ8ZnREb6cIrvUDGKmuhYQlCjxoss\nGIC3w47zkIegDCP2rzegj+uPdsvPKLm1mO8difS9hu9oGJ2vvIku5TTGuRIxen+gkeOZFYgrl4Hl\nCqQ7HXqKiXAcRVW0G1+dDs7tQdbboOJthtkzIX8guFSQlB7IbccDmcWQ3g4qO0HnboDTbmj7Ckal\nwToPpPQiJO1+WGmHzr0gapDjBUpvN3FbG+jJikQpqUATFknE9jJ8Se0w3QtLG5Aq8FeCmOJDJIcg\n8zNQGj6BBAFGCVEOqH8Ynp6OeHsvNAShCY5j0LvHUTwZtE3ORLffi36OBWm+DH/8C//PAlFKyBlD\n1oF7sDkWUlveSHJBAQgtTFoMm6+CnNGQNhMczwZm994isLwOupk8cu04PLarUZ2vhqkjEM4D+Fc+\nB+7tKEHdqMvbUUZfjfvF59EmZwRSD63NsP4hGN0c8EAoLIaWcsgRoHihRYIrDNnuRAzSwYQm6JTg\ndkLMbNjxNJz+EdrsyN71dHer8U8YgxJjAs1F8DaidCsoBRLlQBAifQoErUGc6yZ4XCnucxLGXodu\nz0XobIPpLwYafdatgwufgzoukIY6+wAMehR8r4M5MdCJ5PgmlE/KUdQC2fEqol5CkAF/VQMTh/cn\nLF+Lru0g+EoCqyDlexh1CxQehkYQySH4DdEIxwVCdhymZWIWVAfBde8E1BgiPyCHK/8mkIrq+yxE\nFPxPRPPfDb+WTlgIkSGlLPnD7gzg1F8a/+9Bwloz3H0JTDrwlfH92nlce9ss6G6Fn56G3Ctg2E0B\n3bA5HJo74Xg8vPkmlC+Bc2vB0AlX/QA/Po0rcgsVcZ1ksB1D+WP4c97HzT6cnleIbCykVNpIdLXR\neddG9FG5WAY04g9z0/3gEpS+Gdg05YTeko6SsQCR/DX6GTNQoqKg8WWs6nN0KTvRV6wmsqULcXE/\nnvItnB/TCUF9seuNmMcrqPq70WqtaNq7UJmgPDgTy/ibaSgpJSJ1JlFf1qJ0N4LXDXUh4LRCyTEQ\nQXDPRaiYCJfXwAEnLL0fjl+ECWmIKBNMnY2KpWDPQfxch9J+DleiBSVC0v5EEMHf2dFnhSP9A5GV\n21BM0WCrRSl0481Xo3zqg4kGiO2GSKBiF9wyG1f5t1ir44jKCYekhVSv/pCcWD3UXULk5qFKSgqQ\nb/UGuLQCYvuipHpJX96bl8MPM678I7A0Qi8/5N2Lz+KCsAdQIcBxFsqvgYyNgXPsyUf9US2eyUdR\nJU5FOW9FdeUEpG4+ctk3+NrDibx7Hi1rNxL/yCOB+yQiCm5eCRvGQG4LbOuGYEuAfKf1QFk+KMfx\n6jLQzM+DnWEw8iEo/Ak2LoIpy6DwO8hMQ3ZEk3DzAdzj70G/4SN4cjN8loV9SiweXysuex4h5TtA\nuKDkS4TfT896Bbn2P9BeNQHZdzhCuxIh+0H8DIidBkVvQe0mCAmoO6ioC3TB6J0MM50wuBu4BRE9\ni57Fz+J4KQV770OYu5czxrGN1sgMiO4D/lbwugmueBPvfUGoXCko/nxE5gPw6AB0qT7MVTFwcQ+M\ncYHeBD4XHH8UDHEwYcM/jV3lX8KvmBN+TQiRBfiAMuCuvzT430MnnDQaQlNAGweGUfikFgxBEJkK\nt68KyIdW3goOKxSdg53r4O57oHgPnKiAvvNhSAbsfRqrsxh743f0ls9iuLQfLhxCOfgK+o1fELzb\nSXD7XHo978Up1JxfMQDmDkQ4BWKXHcuDsejvjME72YhwXIJtPfDjXbB+INqeR9HGWzFG1+N0f0Rt\nfzMeQw/+va/j7NOX/HqFvm+vY/BzR8kpCyf5gzaiP64gtFSiT7uBTOc27D9cTXuIgwbfFhrSfch7\n90H+y7CvBXLfgVYrlB2DQw/CJTWcNcKRRmh1woK+cNOLkLsI8fSbCOcTiDErUT+QjBKlRaPvjdri\nJvSLLmzTdDTc3Bt3+WF4sg9iVi9wh8J5L6p1rcheKijTgLc/tAaB2gOHd3IyeSzBscOgzgIn3iK8\nrRSt1Q47BJw+Dmc+gy1Xgr0Wxq+B3Jdo8uWiTtPi89ph7ttwvhC0A8DYyiVjCs94i/EgQSbApxeg\n8QZotMCjY6DPHajsL8Oez5C1CpywIirvREmOR5Wfg+XDB+n6YCly+wbocQbuFUUFE9dA7HCYlQKx\nQTDGDttc0HsWpM9A22c3svAtMNwIkWMhqhUMxbDxfghqhcxxaLrK8J70o296AUZNhuMHkLEz0V6q\nw2pPp+t4MRhGgqEB0iJp25mNb6AZn1FH65oduLsKoWUNdOwJfC9PJeQ9Dtn3gKcMrnoXrt4Jlkg4\nvwEulYNaICImQ/8p6LQRqN+NJLZnG41fF5D4zHkiHtpIxHs+IhzPEbExHI1Oh74sA8Veh29iP9wp\nH+B8uReOCWr0ShM+kwqPZh3SdgZ2XwNJsyH/iT/MjP/5qePX0glLKedIKfOklP2klLOllM1/afw/\n/y/5t0IImHAfTHwAls+D1b8DRwfsfhLW3gmKHnLuQoZH06pyUzdST4grA82xZXDidXA6If8emLIG\nLvsM1wkjppgrCbEqRKTM5fwIK23XK3gWaDAMaUI1dS8kxsDgpwIys8uWweDlEPsodBWg3awh6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CSgttCq5LrehW2AN556pPoN9IfJE6xO+Hwf52Xhv2IE83rMITl0DH1AsYI+7H2D4GtnyIt64Z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\n79QTVKkQcEUOyqo42jzyGW06doTwCwnwa06cNMQGWXPh4hu8LzSjU1DsNXS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qUWM9BKc/isdYh6muBNGcDzU6CErINWJzbqCHr4R7tq6hJPpEDCk7MK2qwx/f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qYxdsNyiiu3cKbqMY5G3EC/3cmxqy+nwGQlO3geid4iCp77AqkoG0U6hdrgxxm5BlUvZBMfMkFc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\niz1fo3ZfHG9C+VUB2d/SQvFNN5Hy5z9jrH8X9n8MShrknAZASdJw0Jtg8oX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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1114,21 +1093,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.10" + "pygments_lexer": "ipython3", + "version": "3.5.1" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/tally-arithmetic.ipynb b/docs/source/pythonapi/examples/tally-arithmetic.ipynb index 3a61b0979..56b3cb45c 100644 --- a/docs/source/pythonapi/examples/tally-arithmetic.ipynb +++ b/docs/source/pythonapi/examples/tally-arithmetic.ipynb @@ -4,9 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "This notebook shows the how tallies can be combined (added, subtracted, multiplied, etc.) using the Python API in order to create derived tallies. Since no covariance information is obtained, it is assumed that tallies are completely independent of one another when propagating uncertainties. The target problem is a simple pin cell.\n", - "\n", - "**Note:** that this Notebook was created using the latest Pandas v0.16.1. Everything in the Notebook will wun with older versions of Pandas, but the multi-indexing option in >v0.15.0 makes the tables look prettier." + "This notebook shows the how tallies can be combined (added, subtracted, multiplied, etc.) using the Python API in order to create derived tallies. Since no covariance information is obtained, it is assumed that tallies are completely independent of one another when propagating uncertainties. The target problem is a simple pin cell." ] }, { @@ -16,30 +14,12 @@ "collapsed": false }, "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, - "outputs": [], "source": [ "import glob\n", "from IPython.display import Image\n", "import numpy as np\n", "\n", - "import openmc\n", - "from openmc.statepoint import StatePoint\n", - "from openmc.summary import Summary\n", - "from openmc.source import Source\n", - "from openmc.stats import Box\n", - "\n", - "%matplotlib inline" + "import openmc" ] }, { @@ -58,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -82,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": false }, @@ -117,17 +97,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Instantiate a MaterialsFile, add Materials\n", - "materials_file = openmc.MaterialsFile()\n", - "materials_file.add_material(fuel)\n", - "materials_file.add_material(water)\n", - "materials_file.add_material(zircaloy)\n", + "# Instantiate a Materials collection\n", + "materials_file = openmc.Materials((fuel, water, zircaloy))\n", "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", @@ -143,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "collapsed": false }, @@ -172,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { "collapsed": false }, @@ -209,7 +186,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": false }, @@ -236,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": false }, @@ -249,18 +226,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Instantiate a GeometryFile\n", - "geometry_file = openmc.GeometryFile()\n", - "geometry_file.geometry = geometry\n", - "\n", "# Export to \"geometry.xml\"\n", - "geometry_file.export_to_xml()" + "geometry.export_to_xml()" ] }, { @@ -272,7 +245,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": true }, @@ -283,15 +256,17 @@ "inactive = 5\n", "particles = 2500\n", "\n", - "# Instantiate a SettingsFile\n", - "settings_file = openmc.SettingsFile()\n", + "# Instantiate a Settings object\n", + "settings_file = openmc.Settings()\n", "settings_file.batches = batches\n", "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "settings_file.output = {'tallies': True}\n", - "source_bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", - "settings_file.source = Source(space=Box(\n", - " source_bounds[:3], source_bounds[3:]))\n", + "\n", + "# Create an initial uniform spatial source distribution over fissionable zones\n", + "bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n", + "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n", + "settings_file.source = openmc.source.Source(space=uniform_dist)\n", "\n", "# Export to \"settings.xml\"\n", "settings_file.export_to_xml()" @@ -306,7 +281,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -320,9 +295,8 @@ "plot.pixels = [250, 250]\n", "plot.color = 'mat'\n", "\n", - "# Instantiate a PlotsFile, add Plot, and export to \"plots.xml\"\n", - "plot_file = openmc.PlotsFile()\n", - "plot_file.add_plot(plot)\n", + "# Instantiate a Plots collection and export to \"plots.xml\"\n", + "plot_file = openmc.Plots([plot])\n", "plot_file.export_to_xml()" ] }, @@ -335,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": false }, @@ -346,32 +320,31 @@ "0" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Run openmc in plotting mode\n", - "executor = openmc.Executor()\n", - "executor.plot_geometry(output=False)" + "openmc.plot_geometry(output=False)" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [ { "data": { - 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"execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -393,19 +366,19 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Instantiate an empty TalliesFile\n", - "tallies_file = openmc.TalliesFile()" + "# Instantiate an empty Tallies object\n", + "tallies_file = openmc.Tallies()" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "collapsed": false }, @@ -418,35 +391,31 @@ "\n", "# Instantiate flux Tally in moderator and fuel\n", "tally = openmc.Tally(name='flux')\n", - "tally.add_filter(openmc.Filter(type='cell', bins=[fuel_cell.id, moderator_cell.id]))\n", - "tally.add_filter(energy_filter)\n", - "tally.add_score('flux')\n", - "tallies_file.add_tally(tally)\n", + "tally.filters = [openmc.Filter(type='cell', bins=[fuel_cell.id, moderator_cell.id])]\n", + "tally.filters.append(energy_filter)\n", + "tally.scores = ['flux']\n", + "tallies_file.append(tally)\n", "\n", "# Instantiate reaction rate Tally in fuel\n", "tally = openmc.Tally(name='fuel rxn rates')\n", - "tally.add_filter(openmc.Filter(type='cell', bins=[fuel_cell.id]))\n", - "tally.add_filter(energy_filter)\n", - "tally.add_score('nu-fission')\n", - "tally.add_score('scatter')\n", - "tally.add_nuclide(u238)\n", - "tally.add_nuclide(u235)\n", - "tallies_file.add_tally(tally)\n", + "tally.filters = [openmc.Filter(type='cell', bins=[fuel_cell.id])]\n", + "tally.filters.append(energy_filter)\n", + "tally.scores = ['nu-fission', 'scatter']\n", + "tally.nuclides = [u238, u235]\n", + "tallies_file.append(tally)\n", "\n", "# Instantiate reaction rate Tally in moderator\n", "tally = openmc.Tally(name='moderator rxn rates')\n", - "tally.add_filter(openmc.Filter(type='cell', bins=[moderator_cell.id]))\n", - "tally.add_filter(energy_filter)\n", - "tally.add_score('absorption')\n", - "tally.add_score('total')\n", - "tally.add_nuclide(o16)\n", - "tally.add_nuclide(h1)\n", - "tallies_file.add_tally(tally)" + "tally.filters = [openmc.Filter(type='cell', bins=[moderator_cell.id])]\n", + "tally.filters.append(energy_filter)\n", + "tally.scores = ['absorption', 'total']\n", + "tally.nuclides = [o16, h1]\n", + "tallies_file.append(tally)" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": true }, @@ -455,10 +424,24 @@ "# K-Eigenvalue (infinity) tallies\n", "fiss_rate = openmc.Tally(name='fiss. rate')\n", "abs_rate = openmc.Tally(name='abs. rate')\n", - "fiss_rate.add_score('nu-fission')\n", - "abs_rate.add_score('absorption')\n", - "tallies_file.add_tally(fiss_rate)\n", - "tallies_file.add_tally(abs_rate)" + "fiss_rate.scores = ['nu-fission']\n", + "abs_rate.scores = ['absorption']\n", + "tallies_file += (fiss_rate, abs_rate)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "# Resonance Escape Probability tallies\n", + "therm_abs_rate = openmc.Tally(name='therm. abs. rate')\n", + "therm_abs_rate.scores = ['absorption']\n", + "therm_abs_rate.filters = [openmc.Filter(type='energy', bins=[0., 0.625e-6])]\n", + "tallies_file.append(therm_abs_rate)" ] }, { @@ -469,27 +452,27 @@ }, "outputs": [], "source": [ - "# Resonance Escape Probability tallies\n", - "therm_abs_rate = openmc.Tally(name='therm. abs. rate')\n", - "therm_abs_rate.add_score('absorption')\n", - "therm_abs_rate.add_filter(openmc.Filter(type='energy', bins=[0., 0.625e-6]))\n", - "tallies_file.add_tally(therm_abs_rate)" + "# Thermal Flux Utilization tallies\n", + "fuel_therm_abs_rate = openmc.Tally(name='fuel therm. abs. rate')\n", + "fuel_therm_abs_rate.scores = ['absorption']\n", + "fuel_therm_abs_rate.filters = [openmc.Filter(type='energy', bins=[0., 0.625e-6]),\n", + " openmc.Filter(type='cell', bins=[fuel_cell.id])]\n", + "tallies_file.append(fuel_therm_abs_rate)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ - "# Thermal Flux Utilization tallies\n", - "fuel_therm_abs_rate = openmc.Tally(name='fuel therm. abs. rate')\n", - "fuel_therm_abs_rate.add_score('absorption')\n", - "fuel_therm_abs_rate.add_filter(openmc.Filter(type='energy', bins=[0., 0.625e-6]))\n", - "fuel_therm_abs_rate.add_filter(openmc.Filter(type='cell', bins=[fuel_cell.id]))\n", - "tallies_file.add_tally(fuel_therm_abs_rate)" + "# Fast Fission Factor tallies\n", + "therm_fiss_rate = openmc.Tally(name='therm. fiss. rate')\n", + "therm_fiss_rate.scores = ['nu-fission']\n", + "therm_fiss_rate.filters = [openmc.Filter(type='energy', bins=[0., 0.625e-6])]\n", + "tallies_file.append(therm_fiss_rate)" ] }, { @@ -500,40 +483,23 @@ }, "outputs": [], "source": [ - "# Fast Fission Factor tallies\n", - "therm_fiss_rate = openmc.Tally(name='therm. fiss. rate')\n", - "therm_fiss_rate.add_score('nu-fission')\n", - "therm_fiss_rate.add_filter(openmc.Filter(type='energy', bins=[0., 0.625e-6]))\n", - "tallies_file.add_tally(therm_fiss_rate)" + "# Instantiate energy filter to illustrate Tally slicing\n", + "energy_filter = openmc.Filter(type='energy', bins=np.logspace(np.log10(1e-8), np.log10(20), 10))\n", + "\n", + "# Instantiate flux Tally in moderator and fuel\n", + "tally = openmc.Tally(name='need-to-slice')\n", + "tally.filters = [openmc.Filter(type='cell', bins=[fuel_cell.id, moderator_cell.id])]\n", + "tally.filters.append(energy_filter)\n", + "tally.scores = ['nu-fission', 'scatter']\n", + "tally.nuclides = [h1, u238]\n", + "tallies_file.append(tally)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Instantiate energy filter to illustrate Tally slicing\n", - "energy_filter = openmc.Filter(type='energy', bins=np.logspace(np.log10(1e-8), np.log10(20), 10))\n", - "\n", - "# Instantiate flux Tally in moderator and fuel\n", - "tally = openmc.Tally(name='need-to-slice')\n", - "tally.add_filter(openmc.Filter(type='cell', bins=[fuel_cell.id, moderator_cell.id]))\n", - "tally.add_filter(energy_filter)\n", - "tally.add_score('nu-fission')\n", - "tally.add_score('scatter')\n", - "tally.add_nuclide(h1)\n", - "tally.add_nuclide(u238)\n", - "tallies_file.add_tally(tally)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ @@ -550,7 +516,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": false, "scrolled": true @@ -573,12 +539,11 @@ " 888\n", " 888\n", "\n", - " Copyright: 2011-2015 Massachusetts Institute of Technology\n", - " License: http://mit-crpg.github.io/openmc/license.html\n", + " Copyright: 2011-2016 Massachusetts Institute of Technology\n", + " License: http://openmc.readthedocs.org/en/latest/license.html\n", " Version: 0.7.1\n", - " Git SHA1: 34381b40a9445a727e360873aaa6ef892af1cb6a\n", - " Date/Time: 2016-02-07 16:05:17\n", - " MPI Processes: 1\n", + " Git SHA1: df280b60eb1c6d7b7f842e05ede734a4883a0fc8\n", + " Date/Time: 2016-05-05 14:51:45\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -605,26 +570,26 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 1.05992 \n", - " 2/1 1.05251 \n", - " 3/1 1.05204 \n", - " 4/1 1.02100 \n", - " 5/1 1.07784 \n", - " 6/1 1.04814 \n", - " 7/1 1.02335 1.03574 +/- 0.01239\n", - " 8/1 1.02415 1.03188 +/- 0.00813\n", - " 9/1 1.10331 1.04974 +/- 0.01876\n", - " 10/1 1.05452 1.05069 +/- 0.01456\n", - " 11/1 1.07867 1.05536 +/- 0.01277\n", - " 12/1 1.04203 1.05345 +/- 0.01096\n", - " 13/1 1.04482 1.05237 +/- 0.00955\n", - " 14/1 1.04117 1.05113 +/- 0.00852\n", - " 15/1 1.07581 1.05360 +/- 0.00801\n", - " 16/1 1.04235 1.05257 +/- 0.00731\n", - " 17/1 1.02710 1.05045 +/- 0.00701\n", - " 18/1 1.01970 1.04809 +/- 0.00687\n", - " 19/1 1.01022 1.04538 +/- 0.00691\n", - " 20/1 1.01449 1.04332 +/- 0.00675\n", + " 1/1 1.03471 \n", + " 2/1 1.03257 \n", + " 3/1 1.00600 \n", + " 4/1 1.04547 \n", + " 5/1 1.02287 \n", + " 6/1 1.05752 \n", + " 7/1 1.04283 1.05017 +/- 0.00734\n", + " 8/1 1.05189 1.05074 +/- 0.00428\n", + " 9/1 1.01645 1.04217 +/- 0.00909\n", + " 10/1 1.04978 1.04369 +/- 0.00721\n", + " 11/1 1.03459 1.04218 +/- 0.00608\n", + " 12/1 1.04019 1.04189 +/- 0.00514\n", + " 13/1 1.05985 1.04414 +/- 0.00499\n", + " 14/1 1.02111 1.04158 +/- 0.00509\n", + " 15/1 1.04774 1.04219 +/- 0.00459\n", + " 16/1 1.00733 1.03902 +/- 0.00523\n", + " 17/1 1.02224 1.03763 +/- 0.00497\n", + " 18/1 1.03263 1.03724 +/- 0.00459\n", + " 19/1 1.01611 1.03573 +/- 0.00451\n", + " 20/1 1.04692 1.03648 +/- 0.00426\n", " Creating state point statepoint.20.h5...\n", "\n", " ===========================================================================\n", @@ -634,27 +599,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.4700E-01 seconds\n", - " Reading cross sections = 9.1000E-02 seconds\n", - " Total time in simulation = 7.3920E+00 seconds\n", - " Time in transport only = 7.3820E+00 seconds\n", - " Time in inactive batches = 1.0930E+00 seconds\n", - " Time in active batches = 6.2990E+00 seconds\n", - " Time synchronizing fission bank = 2.0000E-03 seconds\n", - " Sampling source sites = 1.0000E-03 seconds\n", + " Total time for initialization = 7.2500E-01 seconds\n", + " Reading cross sections = 4.4400E-01 seconds\n", + " Total time in simulation = 1.5547E+01 seconds\n", + " Time in transport only = 1.5527E+01 seconds\n", + " Time in inactive batches = 2.2880E+00 seconds\n", + " Time in active batches = 1.3259E+01 seconds\n", + " Time synchronizing fission bank = 1.0000E-03 seconds\n", + " Sampling source sites = 0.0000E+00 seconds\n", " SEND/RECV source sites = 0.0000E+00 seconds\n", - " Time accumulating tallies = 0.0000E+00 seconds\n", + " Time accumulating tallies = 1.0000E-03 seconds\n", " Total time for finalization = 2.0000E-03 seconds\n", - " Total time elapsed = 7.7510E+00 seconds\n", - " Calculation Rate (inactive) = 11436.4 neutrons/second\n", - " Calculation Rate (active) = 5953.33 neutrons/second\n", + " Total time elapsed = 1.6291E+01 seconds\n", + " Calculation Rate (inactive) = 5463.29 neutrons/second\n", + " Calculation Rate (active) = 2828.27 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.03935 +/- 0.00682\n", - " k-effective (Track-length) = 1.04332 +/- 0.00675\n", - " k-effective (Absorption) = 1.03845 +/- 0.00598\n", - " Combined k-effective = 1.04024 +/- 0.00523\n", + " k-effective (Collision) = 1.03296 +/- 0.00669\n", + " k-effective (Track-length) = 1.03648 +/- 0.00426\n", + " k-effective (Absorption) = 1.03431 +/- 0.00702\n", + " Combined k-effective = 1.03621 +/- 0.00456\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -665,7 +630,7 @@ "0" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -674,8 +639,8 @@ "# Remove old HDF5 (summary, statepoint) files\n", "!rm statepoint.*\n", "\n", - "# Run OpenMC with MPI!\n", - "executor.run_simulation()" + "# Run OpenMC!\n", + "openmc.run()" ] }, { @@ -694,7 +659,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false, "scrolled": true @@ -702,28 +667,7 @@ "outputs": [], "source": [ "# Load the statepoint file\n", - "sp = StatePoint('statepoint.20.h5')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You may have also noticed we instructed OpenMC to create a summary file with lots of geometry information in it. This can help to produce more sensible output from the Python API, so we will use the summary file to link against." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false, - "scrolled": true - }, - "outputs": [], - "source": [ - "# Load the summary file and link with statepoint\n", - "su = Summary('summary.h5')\n", - "sp.link_with_summary(su)" + "sp = openmc.StatePoint('statepoint.20.h5')" ] }, { @@ -737,7 +681,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -745,7 +689,7 @@ { "data": { "text/html": [ - "
\n", + "
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0 total (nu-fission / absorption) 1.040166 0.009069total(nu-fission / absorption)1.0383870.006141
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0 0 0.000001 total nu-fission 1.201216 0.0122880.06.250000e-07totalnu-fission1.2030420.0076
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0 0 0.000001 10000 total (nu-fission / absorption) 1.663616 0.0186240.06.250000e-0710000total(nu-fission / absorption)1.6633850.011253
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0 0 0.000001 10000 total (((absorption * nu-fission) * absorption) * (n... 1.040166 0.0219280.06.250000e-0710000total(((absorption * nu-fission) * absorption) * (n...1.0383870.01316
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0 10000 0.000000 0.000001 (U-238 / total) (nu-fission / flux) 0.000001 7.377419e-09100000.000000e+006.250000e-07(U-238 / total)(nu-fission / flux)6.636968e-074.132875e-09
1 10000 0.000000 0.000001 (U-238 / total) (scatter / flux) 0.209989 2.303838e-03100000.000000e+006.250000e-07(U-238 / total)(scatter / flux)2.099856e-011.232455e-03
2 10000 0.000000 0.000001 (U-235 / total) (nu-fission / flux) 0.356420 3.951669e-03100000.000000e+006.250000e-07(U-235 / total)(nu-fission / flux)3.552458e-012.252681e-03
3 10000 0.000000 0.000001 (U-235 / total) (scatter / flux) 0.005555 6.101004e-05100000.000000e+006.250000e-07(U-235 / total)(scatter / flux)5.554345e-033.265385e-05
4 10000 0.000001 20.000000 (U-238 / total) (nu-fission / flux) 0.007155 8.053460e-05100006.250000e-072.000000e+01(U-238 / total)(nu-fission / flux)7.126668e-035.296883e-05
5 10000 0.000001 20.000000 (U-238 / total) (scatter / flux) 0.227770 1.079289e-03100006.250000e-072.000000e+01(U-238 / total)(scatter / flux)2.277460e-011.003558e-03
6 10000 0.000001 20.000000 (U-235 / total) (nu-fission / flux) 0.008067 5.254797e-05100006.250000e-072.000000e+01(U-235 / total)(nu-fission / flux)8.010911e-036.802256e-05
7 10000 0.000001 20.000000 (U-235 / total) (scatter / flux) 0.003367 1.647058e-05100006.250000e-072.000000e+01(U-235 / total)(scatter / flux)3.367794e-031.443644e-05
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0 10000 0.000000 0.000001 U-238 nu-fission 0.000002 1.283958e-08100000.000000e+006.250000e-07U-238nu-fission0.0000027.473789e-09
1 10000 0.000000 0.000001 U-235 nu-fission 0.868553 6.880390e-03100000.000000e+006.250000e-07U-235nu-fission0.8615474.131310e-03
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7 10002 1.714488e-01 1.851749 H-1 scatter 2.011925 0.009406100021.714488e-011.851749e+00H-1scatter2.0105170.009187
8 10002 1.851749e+00 20.000000 H-1 scatter 0.371280 0.003949100021.851749e+002.000000e+01H-1scatter0.3720220.003196
\n", @@ -1583,29 +1527,29 @@ ], "text/plain": [ " cell energy low [MeV] energy high [MeV] nuclide score mean \\\n", - "0 10002 1.00e-08 1.08e-07 H-1 scatter 4.62e+00 \n", - "1 10002 1.08e-07 1.17e-06 H-1 scatter 2.03e+00 \n", + "0 10002 1.00e-08 1.08e-07 H-1 scatter 4.60e+00 \n", + "1 10002 1.08e-07 1.17e-06 H-1 scatter 2.04e+00 \n", "2 10002 1.17e-06 1.26e-05 H-1 scatter 1.66e+00 \n", - "3 10002 1.26e-05 1.36e-04 H-1 scatter 1.85e+00 \n", - "4 10002 1.36e-04 1.47e-03 H-1 scatter 2.05e+00 \n", - "5 10002 1.47e-03 1.59e-02 H-1 scatter 2.13e+00 \n", - "6 10002 1.59e-02 1.71e-01 H-1 scatter 2.21e+00 \n", + "3 10002 1.26e-05 1.36e-04 H-1 scatter 1.87e+00 \n", + "4 10002 1.36e-04 1.47e-03 H-1 scatter 2.08e+00 \n", + "5 10002 1.47e-03 1.59e-02 H-1 scatter 2.15e+00 \n", + "6 10002 1.59e-02 1.71e-01 H-1 scatter 2.22e+00 \n", "7 10002 1.71e-01 1.85e+00 H-1 scatter 2.01e+00 \n", - "8 10002 1.85e+00 2.00e+01 H-1 scatter 3.71e-01 \n", + "8 10002 1.85e+00 2.00e+01 H-1 scatter 3.72e-01 \n", "\n", " std. dev. \n", - "0 4.01e-02 \n", + "0 1.60e-02 \n", "1 1.12e-02 \n", - "2 9.78e-03 \n", - "3 7.38e-03 \n", - "4 1.25e-02 \n", - "5 7.82e-03 \n", - "6 1.52e-02 \n", - "7 9.41e-03 \n", - "8 3.95e-03 " + "2 1.03e-02 \n", + "3 1.21e-02 \n", + "4 1.32e-02 \n", + "5 1.20e-02 \n", + "6 8.53e-03 \n", + "7 9.19e-03 \n", + "8 3.20e-03 " ] }, - "execution_count": 38, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1614,28 +1558,28 @@ "# \"Slice\" the H-1 scatter data in the moderator Cell into a new derived Tally\n", "need_to_slice = sp.get_tally(name='need-to-slice')\n", "slice_test = need_to_slice.get_slice(scores=['scatter'], nuclides=['H-1'],\n", - " filters=['cell'], filter_bins=[(moderator_cell.id,)])\n", + " filters=['cell'], filter_bins=[(moderator_cell.id,)])\n", "slice_test.get_pandas_dataframe()" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.10" + "pygments_lexer": "ipython3", + "version": "3.5.1" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/executor.rst b/docs/source/pythonapi/executor.rst deleted file mode 100644 index ef6693ec9..000000000 --- a/docs/source/pythonapi/executor.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_executor: - -======== -Executor -======== - -.. automodule:: openmc.executor - :members: diff --git a/docs/source/pythonapi/filter.rst b/docs/source/pythonapi/filter.rst deleted file mode 100644 index f93ba5a15..000000000 --- a/docs/source/pythonapi/filter.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_filter: - -====== -Filter -====== - -.. automodule:: openmc.filter - :members: diff --git a/docs/source/pythonapi/geometry.rst b/docs/source/pythonapi/geometry.rst deleted file mode 100644 index 6b87edb97..000000000 --- a/docs/source/pythonapi/geometry.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_geometry: - -======== -Geometry -======== - -.. automodule:: openmc.geometry - :members: diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst index 6dd2ae10d..4b1d8cca7 100644 --- a/docs/source/pythonapi/index.rst +++ b/docs/source/pythonapi/index.rst @@ -13,62 +13,9 @@ online. We recommend going through the modules from Codecademy_ and/or the `Scipy lectures`_. The full API documentation serves to provide more information on a given module or class. -**Handling nuclear data:** - -.. toctree:: - :maxdepth: 1 - - ace - -**Creating input files:** - -.. toctree:: - :maxdepth: 1 - - cmfd - element - filter - geometry - material - mesh - nuclide - opencg_compatible - plots - settings - source - stats - surface - tallies - trigger - universe - -**Running OpenMC:** - -.. toctree:: - :maxdepth: 1 - - executor - -**Post-processing:** - -.. toctree:: - :maxdepth: 1 - - particle_restart - statepoint - summary - tallies - -**Multi-Group Cross Section Generation** - -.. toctree:: - :maxdepth: 1 - - mgxs - energy_groups - mgxs_library - -**Example Jupyter Notebooks:** +------------------------- +Example Jupyter Notebooks +------------------------- .. toctree:: :maxdepth: 1 @@ -79,6 +26,278 @@ on a given module or class. examples/mgxs-part-i examples/mgxs-part-ii examples/mgxs-part-iii + examples/mgxs-part-iv + +------------------------------------ +:mod:`openmc` -- Basic Functionality +------------------------------------ + +Handling nuclear data +--------------------- + +Classes ++++++++ + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.XSdata + openmc.MGXSLibrary + +Functions ++++++++++ + +.. autosummary:: + :toctree: generated + :nosignatures: + + openmc.ace.ascii_to_binary + +Simulation Settings +------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Source + openmc.ResonanceScattering + openmc.Settings + +Material Specification +---------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Nuclide + openmc.Element + openmc.Macroscopic + openmc.Material + openmc.Materials + +Building geometry +----------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Plane + openmc.XPlane + openmc.YPlane + openmc.ZPlane + openmc.XCylinder + openmc.YCylinder + openmc.ZCylinder + openmc.Sphere + openmc.Cone + openmc.XCone + openmc.YCone + openmc.ZCone + openmc.Quadric + openmc.Halfspace + openmc.Intersection + openmc.Union + openmc.Complement + openmc.Cell + openmc.Universe + openmc.RectLattice + openmc.HexLattice + openmc.Geometry + +Many of the above classes are derived from several abstract classes: + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Surface + openmc.Region + openmc.Lattice + +One function is also available to create a hexagonal region defined by the +intersection of six surface half-spaces. + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myfunction.rst + + openmc.make_hexagon_region + +Constructing Tallies +-------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Filter + openmc.Mesh + openmc.Trigger + openmc.Tally + openmc.Tallies + +Coarse Mesh Finite Difference Acceleration +------------------------------------------ + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.CMFDMesh + openmc.CMFD + +Plotting +-------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Plot + openmc.Plots + +Running OpenMC +-------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myfunction.rst + + openmc.run + openmc.plot_geometry + +Post-processing +--------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.Particle + openmc.StatePoint + openmc.Summary + +Various classes may be created when performing tally slicing and/or arithmetic: + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.arithmetic.CrossScore + openmc.arithmetic.CrossNuclide + openmc.arithmetic.CrossFilter + openmc.arithmetic.AggregateScore + openmc.arithmetic.AggregateNuclide + openmc.arithmetic.AggregateFilter + +--------------------------------- +:mod:`openmc.stats` -- Statistics +--------------------------------- + +Univariate Probability Distributions +------------------------------------ + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.stats.Univariate + openmc.stats.Discrete + openmc.stats.Uniform + openmc.stats.Maxwell + openmc.stats.Watt + openmc.stats.Tabular + +Angular Distributions +--------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.stats.UnitSphere + openmc.stats.PolarAzimuthal + openmc.stats.Isotropic + openmc.stats.Monodirectional + +Spatial Distributions +--------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.stats.Spatial + openmc.stats.CartesianIndependent + openmc.stats.Box + openmc.stats.Point + +---------------------------------------------------------- +:mod:`openmc.mgxs` -- Multi-Group Cross Section Generation +---------------------------------------------------------- + +Energy Groups +------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.mgxs.EnergyGroups + +Multi-group Cross Sections +-------------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclassinherit.rst + + openmc.mgxs.MGXS + openmc.mgxs.AbsorptionXS + openmc.mgxs.CaptureXS + openmc.mgxs.Chi + openmc.mgxs.FissionXS + openmc.mgxs.KappaFissionXS + openmc.mgxs.MultiplicityMatrixXS + openmc.mgxs.NuFissionXS + openmc.mgxs.NuFissionMatrixXS + openmc.mgxs.NuScatterXS + openmc.mgxs.NuScatterMatrixXS + openmc.mgxs.ScatterXS + openmc.mgxs.ScatterMatrixXS + openmc.mgxs.TotalXS + openmc.mgxs.TransportXS + +Multi-group Cross Section Libraries +----------------------------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + openmc.mgxs.Library .. _Jupyter: https://jupyter.org/ .. _NumPy: http://www.numpy.org/ diff --git a/docs/source/pythonapi/material.rst b/docs/source/pythonapi/material.rst deleted file mode 100644 index 16a3af701..000000000 --- a/docs/source/pythonapi/material.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_material: - -========= -Materials -========= - -.. automodule:: openmc.material - :members: diff --git a/docs/source/pythonapi/mesh.rst b/docs/source/pythonapi/mesh.rst deleted file mode 100644 index dbecd7c31..000000000 --- a/docs/source/pythonapi/mesh.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_mesh: - -==== -Mesh -==== - -.. automodule:: openmc.mesh - :members: diff --git a/docs/source/pythonapi/mgxs.rst b/docs/source/pythonapi/mgxs.rst deleted file mode 100644 index c7084e565..000000000 --- a/docs/source/pythonapi/mgxs.rst +++ /dev/null @@ -1,66 +0,0 @@ -.. _pythonapi_mgxs: - -========================== -Multi-Group Cross Sections -========================== - -.. currentmodule:: openmc.mgxs.mgxs - ----------------------------- -Summary of Available Classes ----------------------------- - -.. autosummary:: - - MGXS - AbsorptionXS - CaptureXS - Chi - FissionXS - NuFissionXS - NuScatterXS - NuScatterMatrixXS - ScatterXS - ScatterMatrixXS - TotalXS - TransportXS - -------------------- -Class Documentation -------------------- - -.. autoclass:: MGXS - :members: - -.. autoclass:: AbsorptionXS - :members: - -.. autoclass:: CaptureXS - :members: - -.. autoclass:: Chi - :members: - -.. autoclass:: FissionXS - :members: - -.. autoclass:: NuFissionXS - :members: - -.. autoclass:: NuScatterXS - :members: - -.. autoclass:: NuScatterMatrixXS - :members: - -.. autoclass:: ScatterXS - :members: - -.. autoclass:: ScatterMatrixXS - :members: - -.. autoclass:: TotalXS - :members: - -.. autoclass:: TransportXS - :members: diff --git a/docs/source/pythonapi/mgxs_library.rst b/docs/source/pythonapi/mgxs_library.rst deleted file mode 100644 index 8ac545700..000000000 --- a/docs/source/pythonapi/mgxs_library.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_mgxs_library: - -============ -MGXS Library -============ - -.. automodule:: openmc.mgxs.library - :members: diff --git a/docs/source/pythonapi/nuclide.rst b/docs/source/pythonapi/nuclide.rst deleted file mode 100644 index 9e3214e92..000000000 --- a/docs/source/pythonapi/nuclide.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_nuclide: - -======= -Nuclide -======= - -.. automodule:: openmc.nuclide - :members: diff --git a/docs/source/pythonapi/particle_restart.rst b/docs/source/pythonapi/particle_restart.rst deleted file mode 100644 index 66ed89988..000000000 --- a/docs/source/pythonapi/particle_restart.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_particle_restart: - -================ -Particle Restart -================ - -.. automodule:: openmc.particle_restart - :members: diff --git a/docs/source/pythonapi/plots.rst b/docs/source/pythonapi/plots.rst deleted file mode 100644 index 8ad5348be..000000000 --- a/docs/source/pythonapi/plots.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_plots: - -===== -Plots -===== - -.. automodule:: openmc.plots - :members: diff --git a/docs/source/pythonapi/settings.rst b/docs/source/pythonapi/settings.rst deleted file mode 100644 index 3a3915ff5..000000000 --- a/docs/source/pythonapi/settings.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_settings: - -======== -Settings -======== - -.. automodule:: openmc.settings - :members: diff --git a/docs/source/pythonapi/source.rst b/docs/source/pythonapi/source.rst deleted file mode 100644 index 4bc770363..000000000 --- a/docs/source/pythonapi/source.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_source: - -====== -Source -====== - -.. automodule:: openmc.source - :members: diff --git a/docs/source/pythonapi/statepoint.rst b/docs/source/pythonapi/statepoint.rst deleted file mode 100644 index 737fc03fc..000000000 --- a/docs/source/pythonapi/statepoint.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_statepoint: - -========== -Statepoint -========== - -.. automodule:: openmc.statepoint - :members: diff --git a/docs/source/pythonapi/stats.rst b/docs/source/pythonapi/stats.rst deleted file mode 100644 index 58060cacb..000000000 --- a/docs/source/pythonapi/stats.rst +++ /dev/null @@ -1,58 +0,0 @@ -.. _pythonapi_stats: - -===================== -Statistical Functions -===================== - ----------------------------- -Summary of Available Classes ----------------------------- - -Univariate Probability Distributions ------------------------------------- - -.. currentmodule:: openmc.stats.univariate - -.. autosummary:: - - Univariate - Discrete - Uniform - Maxwell - Watt - Tabular - -Angular Distributions ---------------------- - -.. currentmodule:: openmc.stats.multivariate - -.. autosummary:: - - UnitSphere - PolarAzimuthal - Isotropic - Monodirectional - -Spatial Distributions ---------------------- - -.. autosummary:: - - Spatial - CartesianIndependent - Box - Point - - -Univariate Probability Distributions ------------------------------------- - -.. automodule:: openmc.stats.univariate - :members: - -Multivariate Probability Distributions --------------------------------------- - -.. automodule:: openmc.stats.multivariate - :members: diff --git a/docs/source/pythonapi/summary.rst b/docs/source/pythonapi/summary.rst deleted file mode 100644 index 9a791127b..000000000 --- a/docs/source/pythonapi/summary.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_summary: - -======= -Summary -======= - -.. automodule:: openmc.summary - :members: diff --git a/docs/source/pythonapi/surface.rst b/docs/source/pythonapi/surface.rst deleted file mode 100644 index cc31f5b3e..000000000 --- a/docs/source/pythonapi/surface.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_surface: - -======= -Surface -======= - -.. automodule:: openmc.surface - :members: diff --git a/docs/source/pythonapi/tallies.rst b/docs/source/pythonapi/tallies.rst deleted file mode 100644 index 2f24edf3a..000000000 --- a/docs/source/pythonapi/tallies.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_tallies: - -======= -Tallies -======= - -.. automodule:: openmc.tallies - :members: diff --git a/docs/source/pythonapi/trigger.rst b/docs/source/pythonapi/trigger.rst deleted file mode 100644 index 82567c2cf..000000000 --- a/docs/source/pythonapi/trigger.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_trigger: - -======= -Trigger -======= - -.. automodule:: openmc.trigger - :members: diff --git a/docs/source/pythonapi/universe.rst b/docs/source/pythonapi/universe.rst deleted file mode 100644 index fd4a3c1e2..000000000 --- a/docs/source/pythonapi/universe.rst +++ /dev/null @@ -1,8 +0,0 @@ -.. _pythonapi_universe: - -======== -Universe -======== - -.. automodule:: openmc.universe - :members: diff --git a/docs/source/usersguide/input.rst b/docs/source/usersguide/input.rst index eb620b650..d7c8a239a 100644 --- a/docs/source/usersguide/input.rst +++ b/docs/source/usersguide/input.rst @@ -897,11 +897,19 @@ Each ```` element can have the following attributes or sub-elements: *Default*: None :boundary: - The boundary condition for the surface. This can be "transmission", - "vacuum", or "reflective". + The boundary condition for the surface. This can be "transmission", + "vacuum", "reflective", or "periodic". Periodic boundary conditions can + only be applied to x-, y-, and z-planes. Only axis-aligned periodicity is + supported, i.e., x-planes can only be paired with x-planes. Specify which + planes are periodic and the code will automatically identify which planes + are paired together. *Default*: "transmission" + :periodic_surface_id: + If a periodic boundary condition is applied, this attribute identifies the + ``id`` of the corresponding periodic sufrace. + The following quadratic surfaces can be modeled: :x-plane: @@ -1033,6 +1041,20 @@ Each ```` element can have the following attributes or sub-elements: + The rotation applied is an intrinsic rotation whose Tait-Bryan angles are + given as those specified about the x, y, and z axes respectively. That is to + say, if the angles are :math:`(\phi, \theta, \psi)`, then the rotation + matrix applied is :math:`R_z(\psi) R_y(\theta) R_x(\phi)` or + + .. math:: + + \left [ \begin{array}{ccc} \cos\theta \cos\psi & -\cos\theta \sin\psi + + \sin\phi \sin\theta \cos\psi & \sin\phi \sin\psi + \cos\phi \sin\theta + \cos\psi \\ \cos\theta \sin\psi & \cos\phi \cos\psi + \sin\phi \sin\theta + \sin\psi & -\sin\phi \cos\psi + \cos\phi \sin\theta \sin\psi \\ + -\sin\theta & \sin\phi \cos\theta & \cos\phi \cos\theta \end{array} + \right ] + *Default*: None :translation: @@ -1215,11 +1237,10 @@ Each ``material`` element can have the following attributes or sub-elements: An element with attributes/sub-elements called ``value`` and ``units``. The ``value`` attribute is the numeric value of the density while the ``units`` can be "g/cm3", "kg/m3", "atom/b-cm", "atom/cm3", or "sum". The "sum" unit - indicates that values appearing in ``ao`` attributes for ```` and - ```` sub-elements are to be interpreted as nuclide/element - densities in atom/b-cm, and the total density of the material is taken as - the sum of all nuclides/elements. The "sum" option cannot be used in - conjunction with weight percents. The "macro" unit is used with + indicates that values appearing in ``ao`` or ``wo`` attributes for ```` + and ```` sub-elements are to be interpreted as absolute nuclide/element + densities in atom/b-cm or g/cm3, and the total density of the material is + taken as the sum of all nuclides/elements. The "macro" unit is used with a ``macroscopic`` quantity to indicate that the density is already included in the library and thus not needed here. However, if a value is provided for the ``value``, then this is treated as a number density multiplier on @@ -1258,6 +1279,9 @@ Each ``material`` element can have the following attributes or sub-elements: *Default*: None + .. note:: The ``scattering`` attribute/sub-element is not used in the + multi-group :ref:`energy_mode`. + :element: Specifies that a natural element is present in the material. The natural @@ -1293,6 +1317,9 @@ Each ``material`` element can have the following attributes or sub-elements: *Default*: None + .. note:: The ``scattering`` attribute/sub-element is not used in the + multi-group :ref:`energy_mode`. + :sab: Associates an S(a,b) table with the material. This element has attributes/sub-elements called ``name`` and ``xs``. The ``name`` attribute @@ -1301,6 +1328,8 @@ Each ``material`` element can have the following attributes or sub-elements: *Default*: None + .. note:: This element is not used in the multi-group :ref:`energy_mode`. + :macroscopic: The ``macroscopic`` element is similar to the ``nuclide`` element, but, recognizes that some multi-group libraries may be providing material @@ -1569,7 +1598,8 @@ The ```` element accepts the following sub-elements: |Score | Description | +======================+===================================================+ |absorption |Total absorption rate. This accounts for all | - | |reactions which do not produce secondary neutrons. | + | |reactions which do not produce secondary neutrons | + | |as well as fission. | +----------------------+---------------------------------------------------+ |elastic |Elastic scattering reaction rate. | +----------------------+---------------------------------------------------+ diff --git a/docs/source/usersguide/mgxs_library.rst b/docs/source/usersguide/mgxs_library.rst index a5d2ec0d0..11ccae43d 100644 --- a/docs/source/usersguide/mgxs_library.rst +++ b/docs/source/usersguide/mgxs_library.rst @@ -8,10 +8,10 @@ OpenMC can be run in continuous-energy mode or multi-group mode, provided the nuclear data is available. In continuous-energy mode, the ``cross_sections.xml`` file contains necessary meta-data for each data set, including the name and a file system location where the complete library -can be found. In multi-group mode, this ``cross_sections.xml`` file contains +can be found. In multi-group mode, this ``mgxs.xml`` file contains this same meta-data describing the nuclide or material, but also contains the group-wise nuclear data. This portion of the manual describes the format of -the multi-group data library required to be used in the ``cross_sections.xml`` +the multi-group data library required to be used in the ``mgxs.xml`` file. Similar to the other input file types, the multi-group library is provided in @@ -22,9 +22,9 @@ materials. .. _XML: http://www.w3.org/XML/ ------------------------------------------------- -MGXS Library Specification -- cross_sections.xml ------------------------------------------------- +-------------------------------------- +MGXS Library Specification -- mgxs.xml +-------------------------------------- The multi-group library meta-data is contained within the groups_, group_structure_, and inverse_velocities_ elements. @@ -33,7 +33,7 @@ The actual multi-group data itself is contained within the xsdata_ element. .. _groups: ```` Element ----------------------------------- +-------------------- The ```` element has no attributes and simply provides the number of energy groups contained within the library. @@ -172,7 +172,7 @@ attributes/sub-elements required to describe the meta-data: during the scattering process. Specifically, the options are to either convert the Legendre expansion to a tabular representation or leave it as a set of Legendre coefficients. Converting to a tabular representation will - cost memory but is likely to decrease runtime compared to leaving as a + cost memory but can allow for a decrease in runtime compared to leaving as a set of Legendre coefficients. This element has the following attributes/sub-elements: @@ -181,7 +181,7 @@ attributes/sub-elements required to describe the meta-data: tabular format should be performed or not. A value of "true" means the conversion should be performed, "false" means it should not. - *Default*: "true" + *Default*: "false" :num_points: If the conversion is to take place the number of tabular points is diff --git a/docs/source/usersguide/output/statepoint.rst b/docs/source/usersguide/output/statepoint.rst index 225161965..95a3d842c 100644 --- a/docs/source/usersguide/output/statepoint.rst +++ b/docs/source/usersguide/output/statepoint.rst @@ -248,7 +248,7 @@ if run_mode == 'k-eigenvalue': Accumulated sum and sum-of-squares for each global tally. The compound type has fields named ``sum`` and ``sum_sq``. -**tallies_present** (*int*) +**/tallies_present** (*int*) Flag indicated if tallies are present in the file. @@ -260,3 +260,69 @@ if (run_mode == 'k-eigenvalue' and source_present > 0) ``wgt``, ``xyz``, ``uvw``, ``E``, ``g``, and ``delayed_group``, which represent the weight, position, direction, energy, energy group, and delayed_group of the source particle, respectively. + +**/runtime/total initialization** (*double*) + + Time (in seconds on the master process) spent reading inputs, allocating + arrays, etc. + +**/runtime/reading cross sections** (*double*) + + Time (in seconds on the master process) spent loading cross section + libraries (this is a subset of initialization). + +**/runtime/simulation** (*double*) + + Time (in seconds on the master process) spent between initialization and + finalization. + +**/runtime/transport** (*double*) + + Time (in seconds on the master process) spent transporting particles. + +**/runtime/inactive batches** (*double*) + + Time (in seconds on the master process) spent in the inactive batches + (including non-transport activities like communcating sites). + +**/runtime/active batches** (*double*) + + Time (in seconds on the master process) spent in the active batches + (including non-transport activities like communicating sites). + +**/runtime/synchronizing fission bank** (*double*) + + Time (in seconds on the master process) spent sampling source particles + from fission sites and communicating them to other processes for load + balancing. + +**/runtime/sampling source sites** (*double*) + + Time (in seconds on the master process) spent sampling source particles + from fission sites. + +**/runtime/SEND-RECV source sites** (*double*) + + Time (in seconds on the master process) spent communicating source sites + between processes for load balancing. + +**/runtime/accumulating tallies** (*double*) + + Time (in seconds on the master process) spent communicating tally results + and evaluating their statistics. + +**/runtime/CMFD** (*double*) + + Time (in seconds on the master process) spent evaluating CMFD. + +**/runtime/CMFD building matrices** (*double*) + + Time (in seconds on the master process) spent buliding CMFD matrices. + +**/runtime/CMFD solving matrices** (*double*) + + Time (in seconds on the master process) spent solving CMFD matrices. + +**/runtime/total** (*double*) + + Total time spent (in seconds on the master process) in the program. diff --git a/docs/source/usersguide/output/summary.rst b/docs/source/usersguide/output/summary.rst index 83602e506..8901e42e7 100644 --- a/docs/source/usersguide/output/summary.rst +++ b/docs/source/usersguide/output/summary.rst @@ -293,6 +293,13 @@ The current revision of the summary file format is 1. Filter offset (used for distribcell filter). +**/tallies/tally /filter /paths** (*char[][]*) + + The paths traversed through the CSG tree to reach each distribcell + instance (for 'distribcell' filters only). This consists of the integer + IDs for each universe, cell and lattice delimited by '->'. Each lattice + cell is specified by its (x,y) or (x,y,z) indices. + **/tallies/tally /filter /n_bins** (*int*) Number of bins for the j-th filter. diff --git a/docs/source/usersguide/processing.rst b/docs/source/usersguide/processing.rst index b18569ec6..059659dbc 100644 --- a/docs/source/usersguide/processing.rst +++ b/docs/source/usersguide/processing.rst @@ -196,10 +196,10 @@ Data Extraction A great deal of information is available in statepoint files (See :ref:`usersguide_statepoint`), all of which is accessible through the Python -API. The ``openmc.statepoint`` module (see :ref:`pythonapi_statepoint`) provides -a class to load statepoints and access data as requested; it is used in many of -the provided plotting utilities, OpenMC's regression test suite, and can be used -in user-created scripts to carry out manipulations of the data. +API. The :class:`openmc.StatePoint` class can load statepoints and access data +as requested; it is used in many of the provided plotting utilities, OpenMC's +regression test suite, and can be used in user-created scripts to carry out +manipulations of the data. An :ref:`example IPython notebook ` demonstrates how to extract data from a statepoint using the Python API. diff --git a/examples/python/basic/build-xml.py b/examples/python/basic/build-xml.py index 97591c992..81aecc9f9 100644 --- a/examples/python/basic/build-xml.py +++ b/examples/python/basic/build-xml.py @@ -1,6 +1,5 @@ import openmc -from openmc.source import Source -from openmc.stats import Box + ############################################################################### # Simulation Input File Parameters @@ -13,7 +12,7 @@ particles = 10000 ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate some Nuclides @@ -32,15 +31,14 @@ fuel = openmc.Material(material_id=40, name='fuel') fuel.set_density('g/cc', 4.5) fuel.add_nuclide(u235, 1.) -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([moderator, fuel]) materials_file.default_xs = '71c' -materials_file.add_materials([moderator, fuel]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate ZCylinder surfaces @@ -75,31 +73,31 @@ cell1.fill = universe1 universe1.add_cells([cell2, cell3]) root.add_cells([cell1, cell4]) -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box([-4, -4, -4], [4, 4, 4])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-4., -4., -4., 4., 4., 4.] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC tallies.xml File +# Exporting to OpenMC tallies.xml file ############################################################################### # Instantiate some tally Filters @@ -109,33 +107,21 @@ energyout_filter = openmc.Filter(type='energyout', bins=[0., 20.]) # Instantiate the first Tally first_tally = openmc.Tally(tally_id=1, name='first tally') -first_tally.add_filter(cell_filter) -scores = ['total', 'scatter', 'nu-scatter', \ +first_tally.filters = [cell_filter] +scores = ['total', 'scatter', 'nu-scatter', 'absorption', 'fission', 'nu-fission'] -for score in scores: - first_tally.add_score(score) +first_tally.scores = scores # Instantiate the second Tally second_tally = openmc.Tally(tally_id=2, name='second tally') -second_tally.add_filter(cell_filter) -second_tally.add_filter(energy_filter) -scores = ['total', 'scatter', 'nu-scatter', \ - 'absorption', 'fission', 'nu-fission'] -for score in scores: - second_tally.add_score(score) +second_tally.filters = [cell_filter, energy_filter] +second_tally.scores = scores # Instantiate the third Tally third_tally = openmc.Tally(tally_id=3, name='third tally') -third_tally.add_filter(cell_filter) -third_tally.add_filter(energy_filter) -third_tally.add_filter(energyout_filter) -scores = ['scatter', 'nu-scatter', 'nu-fission'] -for score in scores: - third_tally.add_score(score) +third_tally.filters = [cell_filter, energy_filter, energyout_filter] +third_tally.scores = ['scatter', 'nu-scatter', 'nu-fission'] -# Instantiate a TalliesFile, register all Tallies, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_tally(first_tally) -tallies_file.add_tally(second_tally) -tallies_file.add_tally(third_tally) +# Instantiate a Tallies collection and export to XML +tallies_file = openmc.Tallies((first_tally, second_tally, third_tally)) tallies_file.export_to_xml() diff --git a/examples/python/boxes/build-xml.py b/examples/python/boxes/build-xml.py index 2ae3ee612..4be33dcf1 100644 --- a/examples/python/boxes/build-xml.py +++ b/examples/python/boxes/build-xml.py @@ -1,8 +1,5 @@ import numpy as np - import openmc -from openmc.source import Source -from openmc.stats import Box ############################################################################### # Simulation Input File Parameters @@ -39,15 +36,14 @@ moderator.add_nuclide(h1, 2.) moderator.add_nuclide(o16, 1.) moderator.add_s_alpha_beta('HH2O', '71t') -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([fuel1, fuel2, moderator]) materials_file.default_xs = '71c' -materials_file.add_materials([fuel1, fuel2, moderator]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate planar surfaces @@ -100,26 +96,25 @@ outer_box.fill = moderator root = openmc.Universe(universe_id=0, name='root universe') root.add_cells([inner_box, middle_box, outer_box]) -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### # Exporting to OpenMC settings.xml File ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box(*outer_cube.bounding_box)) + +# Create an initial uniform spatial source distribution over fissionable zones +uniform_dist = openmc.stats.Box(*outer_cube.bounding_box, only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.export_to_xml() ############################################################################### @@ -132,7 +127,6 @@ plot.width = [20, 20] plot.pixels = [200, 200] plot.color = 'cell' -# Instantiate a PlotsFile, add Plot, and export to XML -plot_file = openmc.PlotsFile() -plot_file.add_plot(plot) +# Instantiate a Plots collection and export to XML +plot_file = openmc.Plots([plot]) plot_file.export_to_xml() diff --git a/examples/python/lattice/hexagonal/build-xml.py b/examples/python/lattice/hexagonal/build-xml.py index 1125e8ce0..05cb2cb01 100644 --- a/examples/python/lattice/hexagonal/build-xml.py +++ b/examples/python/lattice/hexagonal/build-xml.py @@ -1,6 +1,4 @@ import openmc -from openmc.source import Source -from openmc.stats import Box ############################################################################### # Simulation Input File Parameters @@ -37,15 +35,14 @@ iron = openmc.Material(material_id=3, name='iron') iron.set_density('g/cc', 7.9) iron.add_nuclide(fe56, 1.) -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([moderator, fuel, iron]) materials_file.default_xs = '71c' -materials_file.add_materials([moderator, fuel, iron]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate Surfaces @@ -107,27 +104,26 @@ lattice.outer = univ2 # Fill Cell with the Lattice cell1.fill = lattice -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box( - [-1, -1, -1], [1, 1, 1])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-1, -1, -1, 1, 1, 1] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.keff_trigger = {'type' : 'std_dev', 'threshold' : 5E-4} settings_file.trigger_active = True settings_file.trigger_max_batches = 100 @@ -135,7 +131,7 @@ settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC plots.xml File +# Exporting to OpenMC plots.xml file ############################################################################### plot_xy = openmc.Plot(plot_id=1) @@ -153,10 +149,8 @@ plot_yz.width = [8, 8] plot_yz.pixels = [400, 400] plot_yz.color = 'mat' -# Instantiate a PlotsFile, add Plot, and export to XML -plot_file = openmc.PlotsFile() -plot_file.add_plot(plot_xy) -plot_file.add_plot(plot_yz) +# Instantiate a Plots collection, add plots, and export to XML +plot_file = openmc.Plots((plot_xy, plot_yz)) plot_file.export_to_xml() @@ -166,10 +160,9 @@ plot_file.export_to_xml() # Instantiate a distribcell Tally tally = openmc.Tally(tally_id=1) -tally.add_filter(openmc.Filter(type='distribcell', bins=[cell2.id])) -tally.add_score('total') +tally.filters = [openmc.Filter(type='distribcell', bins=[cell2.id])] +tally.scores = ['total'] -# Instantiate a TalliesFile, register Tally/Mesh, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_tally(tally) +# Instantiate a Tallies collection and export to XML +tallies_file = openmc.Tallies([tally]) tallies_file.export_to_xml() diff --git a/examples/python/lattice/nested/build-xml.py b/examples/python/lattice/nested/build-xml.py index 389af8e9b..03cede9dc 100644 --- a/examples/python/lattice/nested/build-xml.py +++ b/examples/python/lattice/nested/build-xml.py @@ -1,6 +1,4 @@ import openmc -from openmc.source import Source -from openmc.stats import Box ############################################################################### # Simulation Input File Parameters @@ -13,7 +11,7 @@ particles = 10000 ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate some Nuclides @@ -32,15 +30,14 @@ moderator.add_nuclide(h1, 2.) moderator.add_nuclide(o16, 1.) moderator.add_s_alpha_beta('HH2O', '71t') -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials((moderator, fuel)) materials_file.default_xs = '71c' -materials_file.add_materials([moderator, fuel]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate Surfaces @@ -101,14 +98,12 @@ univ4.add_cell(cell2) # Instantiate nested Lattices lattice1 = openmc.RectLattice(lattice_id=4, name='4x4 assembly') -lattice1.dimension = [2, 2] lattice1.lower_left = [-1., -1.] lattice1.pitch = [1., 1.] lattice1.universes = [[univ1, univ2], [univ2, univ3]] lattice2 = openmc.RectLattice(lattice_id=6, name='4x4 core') -lattice2.dimension = [2, 2] lattice2.lower_left = [-2., -2.] lattice2.pitch = [2., 2.] lattice2.universes = [[univ4, univ4], @@ -118,32 +113,31 @@ lattice2.universes = [[univ4, univ4], cell1.fill = lattice2 cell2.fill = lattice1 -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box( - [-1, -1, -1], [1, 1, 1])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-1, -1, -1, 1, 1, 1] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC plots.xml File +# Exporting to OpenMC plots.xml file ############################################################################### plot = openmc.Plot(plot_id=1) @@ -152,14 +146,13 @@ plot.width = [4, 4] plot.pixels = [400, 400] plot.color = 'mat' -# Instantiate a PlotsFile, add Plot, and export to XML -plot_file = openmc.PlotsFile() -plot_file.add_plot(plot) +# Instantiate a Plots object and export to XML +plot_file = openmc.Plots([plot]) plot_file.export_to_xml() ############################################################################### -# Exporting to OpenMC tallies.xml File +# Exporting to OpenMC tallies.xml file ############################################################################### # Instantiate a tally mesh @@ -175,11 +168,9 @@ mesh_filter.mesh = mesh # Instantiate the Tally tally = openmc.Tally(tally_id=1) -tally.add_filter(mesh_filter) -tally.add_score('total') +tally.filters = [mesh_filter] +tally.scores = ['total'] -# Instantiate a TalliesFile, register Tally/Mesh, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_mesh(mesh) -tallies_file.add_tally(tally) +# Instantiate a Tallies collection, register Tally/Mesh, and export to XML +tallies_file = openmc.Tallies([tally]) tallies_file.export_to_xml() diff --git a/examples/python/lattice/simple/build-xml.py b/examples/python/lattice/simple/build-xml.py index e648c3d5b..5a642d308 100644 --- a/examples/python/lattice/simple/build-xml.py +++ b/examples/python/lattice/simple/build-xml.py @@ -1,6 +1,4 @@ import openmc -from openmc.source import Source -from openmc.stats import Box ############################################################################### # Simulation Input File Parameters @@ -13,7 +11,7 @@ particles = 10000 ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate some Nuclides @@ -32,15 +30,14 @@ moderator.add_nuclide(h1, 2.) moderator.add_nuclide(o16, 1.) moderator.add_s_alpha_beta('HH2O', '71t') -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([moderator, fuel]) materials_file.default_xs = '71c' -materials_file.add_materials([moderator, fuel]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate Surfaces @@ -97,7 +94,6 @@ root.add_cell(cell1) # Instantiate a Lattice lattice = openmc.RectLattice(lattice_id=5) -lattice.dimension = [4, 4] lattice.lower_left = [-2., -2.] lattice.pitch = [1., 1.] lattice.universes = [[univ1, univ2, univ1, univ2], @@ -108,34 +104,33 @@ lattice.universes = [[univ1, univ2, univ1, univ2], # Fill Cell with the Lattice cell1.fill = lattice -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box( - [-1, -1, -1], [1, 1, 1])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-1, -1, -1, 1, 1, 1] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.trigger_active = True settings_file.trigger_max_batches = 100 settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC plots.xml File +# Exporting to OpenMC plots.xml file ############################################################################### plot = openmc.Plot(plot_id=1) @@ -144,14 +139,13 @@ plot.width = [4, 4] plot.pixels = [400, 400] plot.color = 'mat' -# Instantiate a PlotsFile, add Plot, and export to XML -plot_file = openmc.PlotsFile() -plot_file.add_plot(plot) +# Instantiate a Plots collection and export to XML +plot_file = openmc.Plots([plot]) plot_file.export_to_xml() ############################################################################### -# Exporting to OpenMC tallies.xml File +# Exporting to OpenMC tallies.xml file ############################################################################### # Instantiate a tally mesh @@ -167,16 +161,14 @@ mesh_filter.mesh = mesh # Instantiate tally Trigger trigger = openmc.Trigger(trigger_type='rel_err', threshold=1E-2) -trigger.add_score('all') +trigger.scores = ['all'] # Instantiate the Tally tally = openmc.Tally(tally_id=1) -tally.add_filter(mesh_filter) -tally.add_score('total') -tally.add_trigger(trigger) +tally.filters = [mesh_filter] +tally.scores = ['total'] +tally.triggers = [trigger] -# Instantiate a TalliesFile, register Tally/Mesh, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_mesh(mesh) -tallies_file.add_tally(tally) +# Instantiate a Tallies collection and export to XML +tallies_file = openmc.Tallies([tally]) tallies_file.export_to_xml() diff --git a/examples/python/pincell/build-xml.py b/examples/python/pincell/build-xml.py index ca71b04e5..0afb2527f 100644 --- a/examples/python/pincell/build-xml.py +++ b/examples/python/pincell/build-xml.py @@ -1,6 +1,4 @@ import openmc -from openmc.source import Source -from openmc.stats import Box ############################################################################### # Simulation Input File Parameters @@ -13,7 +11,7 @@ particles = 1000 ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate some Nuclides @@ -102,15 +100,14 @@ borated_water.add_nuclide(o16, 2.4672e-2) borated_water.add_nuclide(o17, 6.0099e-5) borated_water.add_s_alpha_beta('HH2O', '71t') -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([uo2, helium, zircaloy, borated_water]) materials_file.default_xs = '71c' -materials_file.add_materials([uo2, helium, zircaloy, borated_water]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate ZCylinder surfaces @@ -151,27 +148,26 @@ root = openmc.Universe(universe_id=0, name='root universe') # Register Cells with Universe root.add_cells([fuel, gap, clad, water]) -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box( - [-0.62992, -0.62992, -1], [0.62992, 0.62992, 1])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-0.62992, -0.62992, -1, 0.62992, 0.62992, 1] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.entropy_lower_left = [-0.39218, -0.39218, -1.e50] settings_file.entropy_upper_right = [0.39218, 0.39218, 1.e50] settings_file.entropy_dimension = [10, 10, 1] @@ -179,7 +175,7 @@ settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC tallies.xml File +# Exporting to OpenMC tallies.xml file ############################################################################### # Instantiate a tally mesh @@ -196,14 +192,9 @@ mesh_filter.mesh = mesh # Instantiate the Tally tally = openmc.Tally(tally_id=1, name='tally 1') -tally.add_filter(energy_filter) -tally.add_filter(mesh_filter) -tally.add_score('flux') -tally.add_score('fission') -tally.add_score('nu-fission') +tally.filters = [energy_filter, mesh_filter] +tally.scores = ['flux', 'fission', 'nu-fission'] -# Instantiate a TalliesFile, register all Tallies, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_mesh(mesh) -tallies_file.add_tally(tally) +# Instantiate a Tallies collection and export to XML +tallies_file = openmc.Tallies([tally]) tallies_file.export_to_xml() diff --git a/examples/python/pincell_multigroup/build-xml.py b/examples/python/pincell_multigroup/build-xml.py index ff75a64d9..6dbfa336b 100644 --- a/examples/python/pincell_multigroup/build-xml.py +++ b/examples/python/pincell_multigroup/build-xml.py @@ -1,8 +1,5 @@ import openmc import openmc.mgxs -from openmc.source import Source -from openmc.stats import Box -import numpy as np ############################################################################### # Simulation Input File Parameters @@ -14,7 +11,7 @@ inactive = 10 particles = 1000 ############################################################################### -# Exporting to OpenMC mg_cross_sections.xml File +# Exporting to OpenMC mgxs.xml file ############################################################################### # Instantiate the energy group data @@ -24,50 +21,48 @@ groups = openmc.mgxs.EnergyGroups(group_edges=[1E-11, 0.0635E-6, 10.0E-6, # Instantiate the 7-group (C5G7) cross section data uo2_xsdata = openmc.XSdata('UO2.300K', groups) uo2_xsdata.order = 0 -uo2_xsdata.total = np.array([0.1779492, 0.3298048, 0.4803882, 0.5543674, - 0.3118013, 0.3951678, 0.5644058]) -uo2_xsdata.absorption = np.array([8.0248E-03, 3.7174E-03, 2.6769E-02, 9.6236E-02, - 3.0020E-02, 1.1126E-01, 2.8278E-01]) -scatter = [[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000], - [0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000], - [0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000], - [0.0000000, 0.0000000, 0.0000000, 0.4525650, 0.0055664, 0.0000000, 0.0000000], - [0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000], - [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090], - [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]] -uo2_xsdata.scatter = np.array(scatter[:][:]) -uo2_xsdata.fission = np.array([7.21206E-03, 8.19301E-04, 6.45320E-03, - 1.85648E-02, 1.78084E-02, 8.30348E-02, - 2.16004E-01]) -uo2_xsdata.nu_fission = np.array([2.005998E-02, 2.027303E-03, 1.570599E-02, - 4.518301E-02, 4.334208E-02, 2.020901E-01, - 5.257105E-01]) -uo2_xsdata.chi = np.array([5.8791E-01, 4.1176E-01, 3.3906E-04, 1.1761E-07, - 0.0000E+00, 0.0000E+00, 0.0000E+00]) +uo2_xsdata.total = [0.1779492, 0.3298048, 0.4803882, 0.5543674, + 0.3118013, 0.3951678, 0.5644058] +uo2_xsdata.absorption = [8.0248E-03, 3.7174E-03, 2.6769E-02, 9.6236E-02, + 3.0020E-02, 1.1126E-01, 2.8278E-01] +uo2_xsdata.scatter = [[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000], + [0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000], + [0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000], + [0.0000000, 0.0000000, 0.0000000, 0.4525650, 0.0055664, 0.0000000, 0.0000000], + [0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000], + [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090], + [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]] +uo2_xsdata.fission = [7.21206E-03, 8.19301E-04, 6.45320E-03, + 1.85648E-02, 1.78084E-02, 8.30348E-02, + 2.16004E-01] +uo2_xsdata.nu_fission = [2.005998E-02, 2.027303E-03, 1.570599E-02, + 4.518301E-02, 4.334208E-02, 2.020901E-01, + 5.257105E-01] +uo2_xsdata.chi = [5.8791E-01, 4.1176E-01, 3.3906E-04, 1.1761E-07, + 0.0000E+00, 0.0000E+00, 0.0000E+00] h2o_xsdata = openmc.XSdata('LWTR.300K', groups) h2o_xsdata.order = 0 -h2o_xsdata.total = np.array([0.15920605, 0.412969593, 0.59030986, 0.58435, - 0.718, 1.2544497, 2.650379]) -h2o_xsdata.absorption = np.array([6.0105E-04, 1.5793E-05, 3.3716E-04, - 1.9406E-03, 5.7416E-03, 1.5001E-02, - 3.7239E-02]) -scatter = [[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000], - [0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010], - [0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034], - [0.0000000, 0.0000000, 0.0000000, 0.0910284, 0.4155100, 0.0637320, 0.0121390], - [0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290], - [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200], - [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]] -h2o_xsdata.scatter = np.array(scatter) +h2o_xsdata.total = [0.15920605, 0.412969593, 0.59030986, 0.58435, + 0.718, 1.2544497, 2.650379] +h2o_xsdata.absorption = [6.0105E-04, 1.5793E-05, 3.3716E-04, + 1.9406E-03, 5.7416E-03, 1.5001E-02, + 3.7239E-02] +h2o_xsdata.scatter = [[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000], + [0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010], + [0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034], + [0.0000000, 0.0000000, 0.0000000, 0.0910284, 0.4155100, 0.0637320, 0.0121390], + [0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290], + [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200], + [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]] -mg_cross_sections_file = openmc.MGXSLibraryFile(groups) -mg_cross_sections_file.add_xsdatas([uo2_xsdata,h2o_xsdata]) +mg_cross_sections_file = openmc.MGXSLibrary(groups) +mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata]) mg_cross_sections_file.export_to_xml() ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate some Macroscopic Data @@ -83,15 +78,14 @@ water = openmc.Material(material_id=2, name='Water') water.set_density('macro', 1.0) water.add_macroscopic(h2o_data) -# Instantiate a MaterialsFile, register all Materials, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([uo2, water]) materials_file.default_xs = '300K' -materials_file.add_materials([uo2, water]) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate ZCylinder surfaces @@ -124,31 +118,32 @@ root = openmc.Universe(universe_id=0, name='root universe') # Register Cells with Universe root.add_cells([fuel, moderator]) -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.energy_mode = "multi-group" -settings_file.cross_sections = "./mg_cross_sections.xml" +settings_file.cross_sections = "./mgxs.xml" settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box([-0.63, -0.63, -1.], [0.63, 0.63, 1.])) + +# Create an initial uniform spatial source distribution over fissionable zones +bounds = [-0.63, -0.63, -1, 0.63, 0.63, 1] +uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:]) +settings_file.source = openmc.source.Source(space=uniform_dist) + +settings_file.export_to_xml() ############################################################################### -# Exporting to OpenMC tallies.xml File +# Exporting to OpenMC tallies.xml file ############################################################################### # Instantiate a tally mesh @@ -167,14 +162,9 @@ mesh_filter.mesh = mesh # Instantiate the Tally tally = openmc.Tally(tally_id=1, name='tally 1') -tally.add_filter(energy_filter) -tally.add_filter(mesh_filter) -tally.add_score('flux') -tally.add_score('fission') -tally.add_score('nu-fission') +tally.filters = [energy_filter, mesh_filter] +tally.scores = ['flux', 'fission', 'nu-fission'] -# Instantiate a TalliesFile, register all Tallies, and export to XML -tallies_file = openmc.TalliesFile() -tallies_file.add_mesh(mesh) -tallies_file.add_tally(tally) +# Instantiate a Tallies collection, register all Tallies, and export to XML +tallies_file = openmc.Tallies([tally]) tallies_file.export_to_xml() diff --git a/examples/python/reflective/build-xml.py b/examples/python/reflective/build-xml.py index 7e4fd30be..949e57c8c 100644 --- a/examples/python/reflective/build-xml.py +++ b/examples/python/reflective/build-xml.py @@ -1,8 +1,5 @@ import numpy as np - import openmc -from openmc.stats import Box -from openmc.source import Source ############################################################################### # Simulation Input File Parameters @@ -15,7 +12,7 @@ particles = 10000 ############################################################################### -# Exporting to OpenMC materials.xml File +# Exporting to OpenMC materials.xml file ############################################################################### # Instantiate a Nuclides @@ -26,15 +23,14 @@ fuel = openmc.Material(material_id=1, name='fuel') fuel.set_density('g/cc', 4.5) fuel.add_nuclide(u235, 1.) -# Instantiate a MaterialsFile, register Material, and export to XML -materials_file = openmc.MaterialsFile() +# Instantiate a Materials collection and export to XML +materials_file = openmc.Materials([fuel]) materials_file.default_xs = '71c' -materials_file.add_material(fuel) materials_file.export_to_xml() ############################################################################### -# Exporting to OpenMC geometry.xml File +# Exporting to OpenMC geometry.xml file ############################################################################### # Instantiate Surfaces @@ -67,24 +63,24 @@ root = openmc.Universe(universe_id=0, name='root universe') # Register Cell with Universe root.add_cell(cell) -# Instantiate a Geometry and register the root Universe -geometry = openmc.Geometry() -geometry.root_universe = root - -# Instantiate a GeometryFile, register Geometry, and export to XML -geometry_file = openmc.GeometryFile() -geometry_file.geometry = geometry -geometry_file.export_to_xml() +# Instantiate a Geometry, register the root Universe, and export to XML +geometry = openmc.Geometry(root) +geometry.export_to_xml() ############################################################################### -# Exporting to OpenMC settings.xml File +# Exporting to OpenMC settings.xml file ############################################################################### -# Instantiate a SettingsFile, set all runtime parameters, and export to XML -settings_file = openmc.SettingsFile() +# Instantiate a Settings object, set all runtime parameters, and export to XML +settings_file = openmc.Settings() settings_file.batches = batches settings_file.inactive = inactive settings_file.particles = particles -settings_file.source = Source(space=Box(*cell.region.bounding_box)) + +# Create an initial uniform spatial source distribution over fissionable zones +uniform_dist = openmc.stats.Box(*cell.region.bounding_box, + only_fissionable=True) +settings_file.source = openmc.source.Source(space=uniform_dist) + settings_file.export_to_xml() diff --git a/openmc/__init__.py b/openmc/__init__.py index 5bdc3f089..0bde0f584 100644 --- a/openmc/__init__.py +++ b/openmc/__init__.py @@ -1,3 +1,5 @@ +from openmc.cell import * +from openmc.lattice import * from openmc.element import * from openmc.geometry import * from openmc.nuclide import * @@ -16,6 +18,9 @@ from openmc.cmfd import * from openmc.executor import * from openmc.statepoint import * from openmc.summary import * +from openmc.region import * +from openmc.source import * +from openmc.particle_restart import * try: from openmc.opencg_compatible import * diff --git a/openmc/cell.py b/openmc/cell.py new file mode 100644 index 000000000..900c952e5 --- /dev/null +++ b/openmc/cell.py @@ -0,0 +1,480 @@ +from collections import OrderedDict, Iterable +from math import cos, sin, pi +from numbers import Real, Integral +from xml.etree import ElementTree as ET +import sys +import warnings + +import numpy as np + +import openmc +import openmc.checkvalue as cv +from openmc.surface import Halfspace +from openmc.region import Region, Intersection, Complement + +if sys.version_info[0] >= 3: + basestring = str + + +# A static variable for auto-generated Cell IDs +AUTO_CELL_ID = 10000 + + +def reset_auto_cell_id(): + global AUTO_CELL_ID + AUTO_CELL_ID = 10000 + + +class Cell(object): + r"""A region of space defined as the intersection of half-space created by + quadric surfaces. + + Parameters + ---------- + cell_id : int, optional + Unique identifier for the cell. If not specified, an identifier will + automatically be assigned. + name : str, optional + Name of the cell. If not specified, the name is the empty string. + fill : openmc.Material or openmc.Universe or openmc.Lattice or None or iterable of openmc.Material, optional + Indicates what the region of space is filled with + region : openmc.Region, optional + Region of space that is assigned to the cell. + + Attributes + ---------- + id : int + Unique identifier for the cell + name : str + Name of the cell + fill : openmc.Material or openmc.Universe or openmc.Lattice or None or iterable of openmc.Material + Indicates what the region of space is filled with. If None, the cell is + treated as a void. An iterable of materials is used to fill repeated + instances of a cell with different materials. + fill_type : {'material', 'universe', 'lattice', 'distribmat', 'void'} + Indicates what the cell is filled with. + region : openmc.Region or None + Region of space that is assigned to the cell. + rotation : Iterable of float + If the cell is filled with a universe, this array specifies the angles + in degrees about the x, y, and z axes that the filled universe should be + rotated. The rotation applied is an intrinsic rotation with specified + Tait-Bryan angles. That is to say, if the angles are :math:`(\phi, + \theta, \psi)`, then the rotation matrix applied is :math:`R_z(\psi) + R_y(\theta) R_x(\phi)` or + + .. math:: + + \left [ \begin{array}{ccc} \cos\theta \cos\psi & -\cos\theta \sin\psi + + \sin\phi \sin\theta \cos\psi & \sin\phi \sin\psi + \cos\phi + \sin\theta \cos\psi \\ \cos\theta \sin\psi & \cos\phi \cos\psi + + \sin\phi \sin\theta \sin\psi & -\sin\phi \cos\psi + \cos\phi + \sin\theta \sin\psi \\ -\sin\theta & \sin\phi \cos\theta & \cos\phi + \cos\theta \end{array} \right ] + + rotation_matrix : numpy.ndarray + The rotation matrix defined by the angles specified in the + :attr:`Cell.rotation` property. + translation : Iterable of float + If the cell is filled with a universe, this array specifies a vector + that is used to translate (shift) the universe. + offsets : ndarray + Array of offsets used for distributed cell searches + distribcell_index : int + Index of this cell in distribcell arrays + + """ + + def __init__(self, cell_id=None, name='', fill=None, region=None): + # Initialize Cell class attributes + self.id = cell_id + self.name = name + self.fill = fill + self.region = region + self._rotation = None + self._rotation_matrix = None + self._translation = None + self._offsets = None + self._distribcell_index = None + + def __contains__(self, point): + if self.region is None: + return True + else: + return point in self.region + + def __eq__(self, other): + if not isinstance(other, Cell): + return False + elif self.id != other.id: + return False + elif self.name != other.name: + return False + elif self.fill != other.fill: + return False + elif self.region != other.region: + return False + elif self.rotation != other.rotation: + return False + elif self.translation != other.translation: + return False + else: + return True + + def __ne__(self, other): + return not self == other + + def __hash__(self): + return hash(repr(self)) + + def __repr__(self): + string = 'Cell\n' + string += '{: <16}=\t{}\n'.format('\tID', self.id) + string += '{: <16}=\t{}\n'.format('\tName', self.name) + + if self.fill_type == 'material': + string += '{: <16}=\tMaterial {}\n'.format('\tFill', self.fill.id) + elif self.fill_type == 'void': + string += '{: <16}=\tNone\n'.format('\tFill') + elif self.fill_type == 'distribmat': + string += '{: <16}=\t{}\n'.format('\tFill', list(map( + lambda m: m if m is None else m.id, self.fill))) + else: + string += '{: <16}=\t{}\n'.format('\tFill', self.fill.id) + + string += '{: <16}=\t{}\n'.format('\tRegion', self.region) + string += '{: <16}=\t{}\n'.format('\tRotation', self.rotation) + string += '{: <16}=\t{}\n'.format('\tTranslation', self.translation) + string += '{: <16}=\t{}\n'.format('\tOffset', self.offsets) + string += '{: <16}=\t{}\n'.format('\tDistribcell index', self.distribcell_index) + + return string + + @property + def id(self): + return self._id + + @property + def name(self): + return self._name + + @property + def fill(self): + return self._fill + + @property + def fill_type(self): + if isinstance(self.fill, openmc.Material): + return 'material' + elif isinstance(self.fill, openmc.Universe): + return 'universe' + elif isinstance(self.fill, openmc.Lattice): + return 'lattice' + elif isinstance(self.fill, Iterable): + return 'distribmat' + else: + return 'void' + + @property + def region(self): + return self._region + + @property + def rotation(self): + return self._rotation + + @property + def rotation_matrix(self): + return self._rotation_matrix + + @property + def translation(self): + return self._translation + + @property + def offsets(self): + return self._offsets + + @property + def distribcell_index(self): + return self._distribcell_index + + @id.setter + def id(self, cell_id): + if cell_id is None: + global AUTO_CELL_ID + self._id = AUTO_CELL_ID + AUTO_CELL_ID += 1 + else: + cv.check_type('cell ID', cell_id, Integral) + cv.check_greater_than('cell ID', cell_id, 0, equality=True) + self._id = cell_id + + @name.setter + def name(self, name): + if name is not None: + cv.check_type('cell name', name, basestring) + self._name = name + else: + self._name = '' + + @fill.setter + def fill(self, fill): + if fill is not None: + if isinstance(fill, basestring): + if fill.strip().lower() != 'void': + msg = 'Unable to set Cell ID="{0}" to use a non-Material ' \ + 'or Universe fill "{1}"'.format(self._id, fill) + raise ValueError(msg) + fill = None + + elif isinstance(fill, Iterable): + for i, f in enumerate(fill): + if f is not None: + cv.check_type('cell.fill[i]', f, openmc.Material) + + elif not isinstance(fill, (openmc.Material, openmc.Lattice, + openmc.Universe)): + msg = 'Unable to set Cell ID="{0}" to use a non-Material or ' \ + 'Universe fill "{1}"'.format(self._id, fill) + raise ValueError(msg) + + self._fill = fill + + @rotation.setter + def rotation(self, rotation): + if not isinstance(self.fill, openmc.Universe): + raise RuntimeError('Cell rotation can only be applied if the cell ' + 'is filled with a Universe') + + cv.check_type('cell rotation', rotation, Iterable, Real) + cv.check_length('cell rotation', rotation, 3) + self._rotation = np.asarray(rotation) + + # Save rotation matrix + phi, theta, psi = self.rotation*(-pi/180.) + c3, s3 = cos(phi), sin(phi) + c2, s2 = cos(theta), sin(theta) + c1, s1 = cos(psi), sin(psi) + self._rotation_matrix = np.array([ + [c1*c2, c1*s2*s3 - c3*s1, s1*s3 + c1*c3*s2], + [c2*s1, c1*c3 + s1*s2*s3, c3*s1*s2 - c1*s3], + [-s2, c2*s3, c2*c3]]) + + @translation.setter + def translation(self, translation): + cv.check_type('cell translation', translation, Iterable, Real) + cv.check_length('cell translation', translation, 3) + self._translation = np.asarray(translation) + + @offsets.setter + def offsets(self, offsets): + cv.check_type('cell offsets', offsets, Iterable) + self._offsets = offsets + + @region.setter + def region(self, region): + if region is not None: + cv.check_type('cell region', region, Region) + self._region = region + + @distribcell_index.setter + def distribcell_index(self, ind): + cv.check_type('distribcell index', ind, Integral) + self._distribcell_index = ind + + def add_surface(self, surface, halfspace): + """Add a half-space to the list of half-spaces whose intersection defines the + cell. + + .. deprecated:: 0.7.1 + Use the :attr:`Cell.region` property to directly specify a Region + expression. + + Parameters + ---------- + surface : openmc.Surface + Quadric surface dividing space + halfspace : {-1, 1} + Indicate whether the negative or positive half-space is to be used + + """ + + warnings.warn("Cell.add_surface(...) has been deprecated and may be " + "removed in a future version. The region for a Cell " + "should be defined using the region property directly.", + DeprecationWarning) + + if not isinstance(surface, openmc.Surface): + msg = 'Unable to add Surface "{0}" to Cell ID="{1}" since it is ' \ + 'not a Surface object'.format(surface, self._id) + raise ValueError(msg) + + if halfspace not in [-1, +1]: + msg = 'Unable to add Surface "{0}" to Cell ID="{1}" with halfspace ' \ + '"{2}" since it is not +/-1'.format(surface, self._id, halfspace) + raise ValueError(msg) + + # If no region has been assigned, simply use the half-space. Otherwise, + # take the intersection of the current region and the half-space + # specified + region = +surface if halfspace == 1 else -surface + if self.region is None: + self.region = region + else: + if isinstance(self.region, Intersection): + self.region.nodes.append(region) + else: + self.region = Intersection(self.region, region) + + def get_cell_instance(self, path, distribcell_index): + + # If the Cell is filled by a Material + if self.fill_type in ('material', 'distribmat', 'void'): + offset = 0 + + # If the Cell is filled by a Universe + elif self.fill_type == 'universe': + offset = self.offsets[distribcell_index-1] + offset += self.fill.get_cell_instance(path, distribcell_index) + + # If the Cell is filled by a Lattice + else: + offset = self.fill.get_cell_instance(path, distribcell_index) + + return offset + + def get_all_nuclides(self): + """Return all nuclides contained in the cell + + Returns + ------- + nuclides : dict + Dictionary whose keys are nuclide names and values are 2-tuples of + (nuclide, density) + + """ + + nuclides = OrderedDict() + + if self.fill_type != 'void': + nuclides.update(self.fill.get_all_nuclides()) + + return nuclides + + def get_all_cells(self): + """Return all cells that are contained within this one if it is filled with a + universe or lattice + + Returns + ------- + cells : dict + Dictionary whose keys are cell IDs and values are :class:`Cell` + instances + + """ + + cells = OrderedDict() + + if self.fill_type in ('universe', 'lattice'): + cells.update(self.fill.get_all_cells()) + + return cells + + def get_all_materials(self): + """Return all materials that are contained within the cell + + Returns + ------- + materials : dict + Dictionary whose keys are material IDs and values are + :class:`Material` instances + + """ + + materials = OrderedDict() + if self.fill_type == 'material': + materials[self.fill.id] = self.fill + + # Append all Cells in each Cell in the Universe to the dictionary + cells = self.get_all_cells() + for cell_id, cell in cells.items(): + materials.update(cell.get_all_materials()) + + return materials + + def get_all_universes(self): + """Return all universes that are contained within this one if any of + its cells are filled with a universe or lattice. + + Returns + ------- + universes : dict + Dictionary whose keys are universe IDs and values are + :class:`Universe` instances + + """ + + universes = OrderedDict() + + if self.fill_type == 'universe': + universes[self.fill.id] = self.fill + universes.update(self.fill.get_all_universes()) + elif self.fill_type == 'lattice': + universes.update(self.fill.get_all_universes()) + + return universes + + def create_xml_subelement(self, xml_element): + element = ET.Element("cell") + element.set("id", str(self.id)) + + if len(self._name) > 0: + element.set("name", str(self.name)) + + if self.fill_type == 'void': + element.set("material", "void") + + elif self.fill_type == 'material': + element.set("material", str(self.fill.id)) + + elif self.fill_type == 'distribmat': + element.set("material", ' '.join(['void' if m is None else str(m.id) + for m in self.fill])) + + elif self.fill_type in ('universe', 'lattice'): + element.set("fill", str(self.fill.id)) + self.fill.create_xml_subelement(xml_element) + + if self.region is not None: + # Set the region attribute with the region specification + element.set("region", str(self.region)) + + # Only surfaces that appear in a region are added to the geometry + # file, so the appropriate check is performed here. First we create + # a function which is called recursively to navigate through the CSG + # tree. When it reaches a leaf (a Halfspace), it creates a + # element for the corresponding surface if none has been created + # thus far. + def create_surface_elements(node, element): + if isinstance(node, Halfspace): + path = './surface[@id=\'{0}\']'.format(node.surface.id) + if xml_element.find(path) is None: + surface_subelement = node.surface.create_xml_subelement() + xml_element.append(surface_subelement) + elif isinstance(node, Complement): + create_surface_elements(node.node, element) + else: + for subnode in node.nodes: + create_surface_elements(subnode, element) + + # Call the recursive function from the top node + create_surface_elements(self.region, xml_element) + + if self.translation is not None: + element.set("translation", ' '.join(map(str, self.translation))) + + if self.rotation is not None: + element.set("rotation", ' '.join(map(str, self.rotation))) + + return element diff --git a/openmc/checkvalue.py b/openmc/checkvalue.py index 303f78407..cc0e1190d 100644 --- a/openmc/checkvalue.py +++ b/openmc/checkvalue.py @@ -1,35 +1,9 @@ +import copy from collections import Iterable from numbers import Integral, Real import numpy as np -def _isinstance(value, expected_type): - """A Numpy-aware replacement for isinstance - - This function will be obsolete when Numpy v. >= 1.9 is established. - """ - - # Declare numpy numeric types. - np_ints = (np.int_, np.intc, np.intp, np.int8, np.int16, np.int32, np.int64, - np.uint8, np.uint16, np.uint32, np.uint64) - np_floats = (np.float_, np.float16, np.float32, np.float64) - - # Include numpy integers, if necessary. - if type(expected_type) is tuple: - if Integral in expected_type: - expected_type = expected_type + np_ints - elif expected_type is Integral: - expected_type = (Integral, ) + np_ints - - # Include numpy floats, if necessary. - if type(expected_type) is tuple: - if Real in expected_type: - expected_type = expected_type + np_floats - elif expected_type is Real: - expected_type = (Real, ) + np_floats - - # Now, make the instance check. - return isinstance(value, expected_type) def check_type(name, value, expected_type, expected_iter_type=None): """Ensure that an object is of an expected type. Optionally, if the object is @@ -41,26 +15,45 @@ def check_type(name, value, expected_type, expected_iter_type=None): Description of value being checked value : object Object to check type of - expected_type : type + expected_type : type or Iterable of type type to check object against - expected_iter_type : type or None, optional + expected_iter_type : type or Iterable of type or None, optional Expected type of each element in value, assuming it is iterable. If None, no check will be performed. """ - if not _isinstance(value, expected_type): - msg = 'Unable to set "{0}" to "{1}" which is not of type "{2}"'.format( - name, value, expected_type.__name__) - raise ValueError(msg) + if not isinstance(value, expected_type): + if isinstance(expected_type, Iterable): + msg = 'Unable to set "{0}" to "{1}" which is not one of the ' \ + 'following types: "{2}"'.format(name, value, ', '.join( + [t.__name__ for t in expected_type])) + else: + msg = 'Unable to set "{0}" to "{1}" which is not of type "{2}"'.format( + name, value, expected_type.__name__) + raise TypeError(msg) if expected_iter_type: - for item in value: - if not _isinstance(item, expected_iter_type): + if isinstance(value, np.ndarray): + if not issubclass(value.dtype.type, expected_iter_type): msg = 'Unable to set "{0}" to "{1}" since each item must be ' \ 'of type "{2}"'.format(name, value, - expected_iter_type.__name__) - raise ValueError(msg) + expected_iter_type.__name__) + else: + return + + for item in value: + if not isinstance(item, expected_iter_type): + if isinstance(expected_iter_type, Iterable): + msg = 'Unable to set "{0}" to "{1}" since each item must be ' \ + 'one of the following types: "{2}"'.format( + name, value, ', '.join([t.__name__ for t in + expected_iter_type])) + else: + msg = 'Unable to set "{0}" to "{1}" since each item must be ' \ + 'of type "{2}"'.format(name, value, + expected_iter_type.__name__) + raise TypeError(msg) def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1): @@ -106,12 +99,12 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1): # If this item is of the expected type, then we've reached the bottom # level of this branch. - if _isinstance(current_item, expected_type): + if isinstance(current_item, expected_type): # Is this deep enough? if len(tree) < min_depth: msg = 'Error setting "{0}": The item at {1} does not meet the '\ 'minimum depth of {2}'.format(name, ind_str, min_depth) - raise ValueError(msg) + raise TypeError(msg) # This item is okay. Move on to the next item. index[-1] += 1 @@ -129,7 +122,7 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1): msg = 'Error setting {0}: Found an iterable at {1}, items '\ 'in that iterable exceed the maximum depth of {2}' \ .format(name, ind_str, max_depth) - raise ValueError(msg) + raise TypeError(msg) else: # This item is completely unexpected. @@ -137,7 +130,7 @@ def check_iterable_type(name, value, expected_type, min_depth=1, max_depth=1): "item at {2} is of type '{3}'"\ .format(name, expected_type.__name__, ind_str, type(current_item).__name__) - raise ValueError(msg) + raise TypeError(msg) def check_length(name, value, length_min, length_max=None): @@ -245,3 +238,65 @@ def check_greater_than(name, value, minimum, equality=False): msg = 'Unable to set "{0}" to "{1}" since it is less than ' \ 'or equal to "{2}"'.format(name, value, minimum) raise ValueError(msg) + + +class CheckedList(list): + """A list for which each element is type-checked as it's added + + Parameters + ---------- + expected_type : type or Iterable of type + Type(s) which each element should be + name : str + Name of data being checked + items : Iterable, optional + Items to initialize the list with + + """ + + def __init__(self, expected_type, name, items=[]): + self.expected_type = expected_type + self.name = name + for item in items: + self.append(item) + + def __add__(self, other): + new_instance = copy.copy(self) + new_instance += other + return new_instance + + def __radd__(self, other): + return self + other + + def __iadd__(self, other): + check_type('CheckedList add operand', other, Iterable, + self.expected_type) + for item in other: + self.append(item) + return self + + def append(self, item): + """Append item to list + + Parameters + ---------- + item : object + Item to append + + """ + check_type(self.name, item, self.expected_type) + super(CheckedList, self).append(item) + + def insert(self, index, item): + """Insert item before index + + Parameters + ---------- + index : int + Index in list + item : object + Item to insert + + """ + check_type(self.name, item, self.expected_type) + super(CheckedList, self).insert(index, item) diff --git a/openmc/cmfd.py b/openmc/cmfd.py index c247719c9..d4cce2af5 100644 --- a/openmc/cmfd.py +++ b/openmc/cmfd.py @@ -69,7 +69,7 @@ class CMFDMesh(object): to any tallies far away from fission source neutron regions. A ``2`` must be used to identify any fission source region. -""" + """ def __init__(self): self._lower_left = None @@ -187,7 +187,7 @@ class CMFDMesh(object): return element -class CMFDFile(object): +class CMFD(object): """Parameters that control the use of coarse-mesh finite difference acceleration in OpenMC. This corresponds directly to the cmfd.xml input file. @@ -219,7 +219,7 @@ class CMFDFile(object): inner tolerance for Gauss-Seidel iterations when performing CMFD. ktol : float Tolerance on the eigenvalue when performing CMFD power iteration - cmfd_mesh : CMFDMesh + cmfd_mesh : openmc.CMFDMesh Structured mesh to be used for acceleration norm : float Normalization factor applied to the CMFD fission source distribution diff --git a/openmc/data/__init__.py b/openmc/data/__init__.py new file mode 100644 index 000000000..df22d8bbb --- /dev/null +++ b/openmc/data/__init__.py @@ -0,0 +1 @@ +from .data import * diff --git a/openmc/data/data.py b/openmc/data/data.py new file mode 100644 index 000000000..c6dd81ba6 --- /dev/null +++ b/openmc/data/data.py @@ -0,0 +1,101 @@ +# Isotopic abundances from M. Berglund and M. E. Wieser, "Isotopic compositions +# of the elements 2009 (IUPAC Technical Report)", Pure. Appl. Chem. 83 (2), +# pp. 397--410 (2011). +natural_abundance = { + 'H-1': 0.999885, 'H-2': 0.000115, 'He-3': 1.34e-06, + 'He-4': 0.99999866, 'Li-6': 0.0759, 'Li-7': 0.9241, + 'Be-9': 1.0, 'B-10': 0.199, 'B-11': 0.801, + 'C-12': 0.9893, 'C-13': 0.0107, 'N-14': 0.99636, + 'N-15': 0.00364, 'O-16': 0.99757, 'O-17': 0.00038, + 'O-18': 0.00205, 'F-19': 1.0, 'Ne-20': 0.9048, + 'Ne-21': 0.0027, 'Ne-22': 0.0925, 'Na-23': 1.0, + 'Mg-24': 0.7899, 'Mg-25': 0.1, 'Mg-26': 0.1101, + 'Al-27': 1.0, 'Si-28': 0.92223, 'Si-29': 0.04685, + 'Si-30': 0.03092, 'P-31': 1.0, 'S-32': 0.9499, + 'S-33': 0.0075, 'S-34': 0.0425, 'S-36': 0.0001, + 'Cl-35': 0.7576, 'Cl-37': 0.2424, 'Ar-36': 0.003336, + 'Ar-38': 0.000629, 'Ar-40': 0.996035, 'K-39': 0.932581, + 'K-40': 0.000117, 'K-41': 0.067302, 'Ca-40': 0.96941, + 'Ca-42': 0.00647, 'Ca-43': 0.00135, 'Ca-44': 0.02086, + 'Ca-46': 4e-05, 'Ca-48': 0.00187, 'Sc-45': 1.0, + 'Ti-46': 0.0825, 'Ti-47': 0.0744, 'Ti-48': 0.7372, + 'Ti-49': 0.0541, 'Ti-50': 0.0518, 'V-50': 0.0025, + 'V-51': 0.9975, 'Cr-50': 0.04345, 'Cr-52': 0.83789, + 'Cr-53': 0.09501, 'Cr-54': 0.02365, 'Mn-55': 1.0, + 'Fe-54': 0.05845, 'Fe-56': 0.91754, 'Fe-57': 0.02119, + 'Fe-58': 0.00282, 'Co-59': 1.0, 'Ni-58': 0.68077, + 'Ni-60': 0.26223, 'Ni-61': 0.011399, 'Ni-62': 0.036346, + 'Ni-64': 0.009255, 'Cu-63': 0.6915, 'Cu-65': 0.3085, + 'Zn-64': 0.4917, 'Zn-66': 0.2773, 'Zn-67': 0.0404, + 'Zn-68': 0.1845, 'Zn-70': 0.0061, 'Ga-69': 0.60108, + 'Ga-71': 0.39892, 'Ge-70': 0.2057, 'Ge-72': 0.2745, + 'Ge-73': 0.0775, 'Ge-74': 0.365, 'Ge-76': 0.0773, + 'As-75': 1.0, 'Se-74': 0.0089, 'Se-76': 0.0937, + 'Se-77': 0.0763, 'Se-78': 0.2377, 'Se-80': 0.4961, + 'Se-82': 0.0873, 'Br-79': 0.5069, 'Br-81': 0.4931, + 'Kr-78': 0.00355, 'Kr-80': 0.02286, 'Kr-82': 0.11593, + 'Kr-83': 0.115, 'Kr-84': 0.56987, 'Kr-86': 0.17279, + 'Rb-85': 0.7217, 'Rb-87': 0.2783, 'Sr-84': 0.0056, + 'Sr-86': 0.0986, 'Sr-87': 0.07, 'Sr-88': 0.8258, + 'Y-89': 1.0, 'Zr-90': 0.5145, 'Zr-91': 0.1122, + 'Zr-92': 0.1715, 'Zr-94': 0.1738, 'Zr-96': 0.028, + 'Nb-93': 1.0, 'Mo-92': 0.1453, 'Mo-94': 0.0915, + 'Mo-95': 0.1584, 'Mo-96': 0.1667, 'Mo-97': 0.096, + 'Mo-98': 0.2439, 'Mo-100': 0.0982, 'Ru-96': 0.0554, + 'Ru-98': 0.0187, 'Ru-99': 0.1276, 'Ru-100': 0.126, + 'Ru-101': 0.1706, 'Ru-102': 0.3155, 'Ru-104': 0.1862, + 'Rh-103': 1.0, 'Pd-102': 0.0102, 'Pd-104': 0.1114, + 'Pd-105': 0.2233, 'Pd-106': 0.2733, 'Pd-108': 0.2646, + 'Pd-110': 0.1172, 'Ag-107': 0.51839, 'Ag-109': 0.48161, + 'Cd-106': 0.0125, 'Cd-108': 0.0089, 'Cd-110': 0.1249, + 'Cd-111': 0.128, 'Cd-112': 0.2413, 'Cd-113': 0.1222, + 'Cd-114': 0.2873, 'Cd-116': 0.0749, 'In-113': 0.0429, + 'In-115': 0.9571, 'Sn-112': 0.0097, 'Sn-114': 0.0066, + 'Sn-115': 0.0034, 'Sn-116': 0.1454, 'Sn-117': 0.0768, + 'Sn-118': 0.2422, 'Sn-119': 0.0859, 'Sn-120': 0.3258, + 'Sn-122': 0.0463, 'Sn-124': 0.0579, 'Sb-121': 0.5721, + 'Sb-123': 0.4279, 'Te-120': 0.0009, 'Te-122': 0.0255, + 'Te-123': 0.0089, 'Te-124': 0.0474, 'Te-125': 0.0707, + 'Te-126': 0.1884, 'Te-128': 0.3174, 'Te-130': 0.3408, + 'I-127': 1.0, 'Xe-124': 0.000952, 'Xe-126': 0.00089, + 'Xe-128': 0.019102, 'Xe-129': 0.264006, 'Xe-130': 0.04071, + 'Xe-131': 0.212324, 'Xe-132': 0.269086, 'Xe-134': 0.104357, + 'Xe-136': 0.088573, 'Cs-133': 1.0, 'Ba-130': 0.00106, + 'Ba-132': 0.00101, 'Ba-134': 0.02417, 'Ba-135': 0.06592, + 'Ba-136': 0.07854, 'Ba-137': 0.11232, 'Ba-138': 0.71698, + 'La-138': 0.0008881, 'La-139': 0.9991119, 'Ce-136': 0.00185, + 'Ce-138': 0.00251, 'Ce-140': 0.8845, 'Ce-142': 0.11114, + 'Pr-141': 1.0, 'Nd-142': 0.27152, 'Nd-143': 0.12174, + 'Nd-144': 0.23798, 'Nd-145': 0.08293, 'Nd-146': 0.17189, + 'Nd-148': 0.05756, 'Nd-150': 0.05638, 'Sm-144': 0.0307, + 'Sm-147': 0.1499, 'Sm-148': 0.1124, 'Sm-149': 0.1382, + 'Sm-150': 0.0738, 'Sm-152': 0.2675, 'Sm-154': 0.2275, + 'Eu-151': 0.4781, 'Eu-153': 0.5219, 'Gd-152': 0.002, + 'Gd-154': 0.0218, 'Gd-155': 0.148, 'Gd-156': 0.2047, + 'Gd-157': 0.1565, 'Gd-158': 0.2484, 'Gd-160': 0.2186, + 'Tb-159': 1.0, 'Dy-156': 0.00056, 'Dy-158': 0.00095, + 'Dy-160': 0.02329, 'Dy-161': 0.18889, 'Dy-162': 0.25475, + 'Dy-163': 0.24896, 'Dy-164': 0.2826, 'Ho-165': 1.0, + 'Er-162': 0.00139, 'Er-164': 0.01601, 'Er-166': 0.33503, + 'Er-167': 0.22869, 'Er-168': 0.26978, 'Er-170': 0.1491, + 'Tm-169': 1.0, 'Yb-168': 0.00123, 'Yb-170': 0.02982, + 'Yb-171': 0.1409, 'Yb-172': 0.2168, 'Yb-173': 0.16103, + 'Yb-174': 0.32026, 'Yb-176': 0.12996, 'Lu-175': 0.97401, + 'Lu-176': 0.02599, 'Hf-174': 0.0016, 'Hf-176': 0.0526, + 'Hf-177': 0.186, 'Hf-178': 0.2728, 'Hf-179': 0.1362, + 'Hf-180': 0.3508, 'Ta-180': 0.0001201, 'Ta-181': 0.9998799, + 'W-180': 0.0012, 'W-182': 0.265, 'W-183': 0.1431, + 'W-184': 0.3064, 'W-186': 0.2843, 'Re-185': 0.374, + 'Re-187': 0.626, 'Os-184': 0.0002, 'Os-186': 0.0159, + 'Os-187': 0.0196, 'Os-188': 0.1324, 'Os-189': 0.1615, + 'Os-190': 0.2626, 'Os-192': 0.4078, 'Ir-191': 0.373, + 'Ir-193': 0.627, 'Pt-190': 0.00012, 'Pt-192': 0.00782, + 'Pt-194': 0.3286, 'Pt-195': 0.3378, 'Pt-196': 0.2521, + 'Pt-198': 0.07356, 'Au-197': 1.0, 'Hg-196': 0.0015, + 'Hg-198': 0.0997, 'Hg-199': 0.1687, 'Hg-200': 0.231, + 'Hg-201': 0.1318, 'Hg-202': 0.2986, 'Hg-204': 0.0687, + 'Tl-203': 0.2952, 'Tl-205': 0.7048, 'Pb-204': 0.014, + 'Pb-206': 0.241, 'Pb-207': 0.221, 'Pb-208': 0.524, + 'Bi-209': 1.0, 'Th-232': 1.0, 'Pa-231': 1.0, + 'U-234': 5.4e-05, 'U-235': 0.007204, 'U-238': 0.992742 +} diff --git a/openmc/element.py b/openmc/element.py index dda110ea7..c391d0823 100644 --- a/openmc/element.py +++ b/openmc/element.py @@ -1,6 +1,8 @@ import sys -from openmc.checkvalue import check_type +import openmc +from openmc.checkvalue import check_type, check_length +from openmc.data import natural_abundance if sys.version_info[0] >= 3: basestring = str @@ -24,7 +26,7 @@ class Element(object): Chemical symbol of the element, e.g. Pu xs : str Cross section identifier, e.g. 71c - scattering : 'data' or 'iso-in-lab' or None + scattering : {'data', 'iso-in-lab', None} The type of angular scattering distribution to use """ @@ -97,7 +99,8 @@ class Element(object): @name.setter def name(self, name): - check_type('name', name, basestring) + check_type('element name', name, basestring) + check_length('element name', name, 1, 2) self._name = name @scattering.setter @@ -109,3 +112,22 @@ class Element(object): raise ValueError(msg) self._scattering = scattering + + def expand(self): + """Expand natural element into its naturally-occurring isotopes. + + Returns + ------- + isotopes : list + Naturally-occurring isotopes of the element. Each item of the list + is a tuple consisting of an openmc.Nuclide instance and the natural + abundance of the isotope. + + """ + + isotopes = [] + for isotope, abundance in natural_abundance.items(): + if isotope.startswith(self.name + '-'): + nuc = openmc.Nuclide(isotope, self.xs) + isotopes.append((nuc, abundance)) + return isotopes diff --git a/openmc/executor.py b/openmc/executor.py index 58cb91246..fbd9e5d82 100644 --- a/openmc/executor.py +++ b/openmc/executor.py @@ -1,130 +1,103 @@ from __future__ import print_function import subprocess from numbers import Integral -import os import sys -from openmc.checkvalue import check_type - if sys.version_info[0] >= 3: basestring = str -class Executor(object): - """Control execution of OpenMC +def _run(command, output, cwd): + # Launch a subprocess + p = subprocess.Popen(command, shell=True, cwd=cwd, stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, universal_newlines=True) - Attributes + # Capture and re-print OpenMC output in real-time + while True: + # If OpenMC is finished, break loop + line = p.stdout.readline() + if not line and p.poll() != None: + break + + # If user requested output, print to screen + if output: + print(line, end='') + + # Return the returncode (integer, zero if no problems encountered) + return p.returncode + + +def plot_geometry(output=True, openmc_exec='openmc', cwd='.'): + """Run OpenMC in plotting mode + + Parameters ---------- - working_directory : str - Path to working directory to run in + output : bool + Capture OpenMC output from standard out + openmc_exec : str + Path to OpenMC executable + cwd : str, optional + Path to working directory to run in. Defaults to the current working directory. """ - def __init__(self): - self._working_directory = '.' + return _run(openmc_exec + ' -p', output, cwd) - def _run_openmc(self, command, output): - # Launch a subprocess to run OpenMC - p = subprocess.Popen(command, shell=True, - cwd=self._working_directory, - stdout=subprocess.PIPE) - # Capture and re-print OpenMC output in real-time - while True: - # If OpenMC is finished, break loop - line = p.stdout.readline() - if not line and p.poll() != None: - break +def run(particles=None, threads=None, geometry_debug=False, + restart_file=None, tracks=False, mpi_procs=1, output=True, + openmc_exec='openmc', mpi_exec='mpiexec', cwd='.'): + """Run an OpenMC simulation. - # If user requested output, print to screen - if output: - print(line, end='') + Parameters + ---------- + particles : int, optional + Number of particles to simulate per generation. + threads : int, optional + Number of OpenMP threads. If OpenMC is compiled with OpenMP threading + enabled, the default is implementation-dependent but is usually equal to + the number of hardware threads available (or a value set by the + OMP_NUM_THREADS environment variable). + geometry_debug : bool, optional + Turn on geometry debugging during simulation. Defaults to False. + restart_file : str, optional + Path to restart file to use + tracks : bool, optional + Write tracks for all particles. Defaults to False. + mpi_procs : int, optional + Number of MPI processes. + output : bool, optional + Capture OpenMC output from standard out. Defaults to True. + openmc_exec : str, optional + Path to OpenMC executable. Defaults to 'openmc'. + mpi_exec : str, optional + MPI execute command. Defaults to 'mpiexec'. + cwd : str, optional + Path to working directory to run in. Defaults to the current working directory. - # Return the returncode (integer, zero if no problems encountered) - return p.returncode + """ - @property - def working_directory(self): - return self._working_directory + post_args = ' ' + pre_args = '' - @working_directory.setter - def working_directory(self, working_directory): - check_type("Executor's working directory", working_directory, - basestring) - if not os.path.isdir(working_directory): - msg = 'Unable to set Executor\'s working directory to "{0}" ' \ - 'which does not exist'.format(working_directory) - raise ValueError(msg) + if isinstance(particles, Integral) and particles > 0: + post_args += '-n {0} '.format(particles) - self._working_directory = working_directory + if isinstance(threads, Integral) and threads > 0: + post_args += '-s {0} '.format(threads) - def plot_geometry(self, output=True, openmc_exec='openmc'): - """Run OpenMC in plotting mode""" + if geometry_debug: + post_args += '-g ' - return self._run_openmc(openmc_exec + ' -p', output) + if isinstance(restart_file, basestring): + post_args += '-r {0} '.format(restart_file) - def run_simulation(self, particles=None, threads=None, - geometry_debug=False, restart_file=None, - tracks=False, mpi_procs=1, output=True, - openmc_exec='openmc', mpi_exec=None): - """Run an OpenMC simulation. + if tracks: + post_args += '-t' - Parameters - ---------- - particles : int - Number of particles to simulate per generation - threads : int - Number of OpenMP threads - geometry_debug : bool - Turn on geometry debugging during simulation - restart_file : str - Path to restart file to use - tracks : bool - Write tracks for all particles - mpi_procs : int - Number of MPI processes - output : bool - Capture OpenMC output from standard out - openmc_exec : str - Path to OpenMC executable + if isinstance(mpi_procs, Integral) and mpi_procs > 1: + pre_args += '{} -n {} '.format(mpi_exec, mpi_procs) - """ + command = pre_args + openmc_exec + ' ' + post_args - post_args = ' ' - pre_args = '' - - if isinstance(particles, Integral) and particles > 0: - post_args += '-n {0} '.format(particles) - - if isinstance(threads, Integral) and threads > 0: - post_args += '-s {0} '.format(threads) - - if geometry_debug: - post_args += '-g ' - - if isinstance(restart_file, basestring): - post_args += '-r {0} '.format(restart_file) - - if tracks: - post_args += '-t' - - if isinstance(mpi_procs, Integral) and mpi_procs > 1: - np_present = True - else: - np_present = False - - if mpi_exec is not None and isinstance(mpi_exec, basestring): - mpi_exec_present = True - else: - mpi_exec_present = False - - if np_present or mpi_exec_present: - if mpi_exec_present: - pre_args += mpi_exec + ' ' - else: - pre_args += 'mpirun ' - pre_args += '-n {0} '.format(mpi_procs) - - command = pre_args + openmc_exec + ' ' + post_args - - return self._run_openmc(command, output) + return _run(command, output, cwd) diff --git a/openmc/filter.py b/openmc/filter.py index 2ae8eeb62..b34400cbb 100644 --- a/openmc/filter.py +++ b/openmc/filter.py @@ -1,4 +1,4 @@ -from collections import Iterable +from collections import Iterable, OrderedDict import copy from numbers import Real, Integral import sys @@ -27,7 +27,8 @@ class Filter(object): type : str The type of the tally filter. Acceptable values are "universe", "material", "cell", "cellborn", "surface", "mesh", "energy", - "energyout", and "distribcell". + "energyout", "distribcell", "mu", "polar", "azimuthal", and + "delayedgroup". bins : Integral or Iterable of Integral or Iterable of Real The bins for the filter. This takes on different meaning for different filters. See the OpenMC online documentation for more details. @@ -40,11 +41,14 @@ class Filter(object): The bins for the filter num_bins : Integral The number of filter bins - mesh : Mesh or None + mesh : openmc.Mesh or None A Mesh object for 'mesh' type filters. stride : Integral The number of filter, nuclide and score bins within each of this filter's bins. + distribcell_paths : list of str + The paths traversed through the CSG tree to reach each distribcell + instance (for 'distribcell' filters only) """ @@ -56,6 +60,7 @@ class Filter(object): self._bins = None self._mesh = None self._stride = None + self._distribcell_paths = None if type is not None: self.type = type @@ -110,6 +115,7 @@ class Filter(object): clone._num_bins = self.num_bins clone._mesh = copy.deepcopy(self.mesh, memo) clone._stride = self.stride + clone._distribcell_paths = copy.deepcopy(self.distribcell_paths) memo[id(self)] = clone @@ -152,6 +158,10 @@ class Filter(object): def stride(self): return self._stride + @property + def distribcell_paths(self): + return self._distribcell_paths + @type.setter def type(self, type): if type is None: @@ -186,7 +196,7 @@ class Filter(object): elif self.type in ['energy', 'energyout']: for edge in bins: - if not cv._isinstance(edge, Real): + if not isinstance(edge, Real): msg = 'Unable to add bin edge "{0}" to a "{1}" Filter ' \ 'since it is a non-integer or floating point ' \ 'value'.format(edge, self.type) @@ -210,7 +220,7 @@ class Filter(object): msg = 'Unable to add bins "{0}" to a mesh Filter since ' \ 'only a single mesh can be used per tally'.format(bins) raise ValueError(msg) - elif not cv._isinstance(bins[0], Integral): + elif not isinstance(bins[0], Integral): msg = 'Unable to add bin "{0}" to mesh Filter since it ' \ 'is a non-integer'.format(bins[0]) raise ValueError(msg) @@ -246,12 +256,17 @@ class Filter(object): self._stride = stride + @distribcell_paths.setter + def distribcell_paths(self, distribcell_paths): + cv.check_iterable_type('distribcell_paths', distribcell_paths, str) + self._distribcell_paths = distribcell_paths + def can_merge(self, other): """Determine if filter can be merged with another. Parameters ---------- - other : Filter + other : openmc.Filter Filter to compare with Returns @@ -296,12 +311,12 @@ class Filter(object): Parameters ---------- - other : Filter + other : openmc.Filter Filter to merge with Returns ------- - merged_filter : Filter + merged_filter : openmc.Filter Filter resulting from the merge """ @@ -341,7 +356,7 @@ class Filter(object): Parameters ---------- - other : Filter + other : openmc.Filter The filter to query as a subset of this filter Returns @@ -501,12 +516,12 @@ class Filter(object): return filter_bin - def get_pandas_dataframe(self, data_size, summary=None): + def get_pandas_dataframe(self, data_size, distribcell_paths=True): """Builds a Pandas DataFrame for the Filter's bins. This method constructs a Pandas DataFrame object for the filter with - columns annotated by filter bin information. This is a helper method - for the Tally.get_pandas_dataframe(...) method. + columns annotated by filter bin information. This is a helper method for + :meth:`Tally.get_pandas_dataframe`. This capability has been tested for Pandas >=0.13.1. However, it is recommended to use v0.16 or newer versions of Pandas since this method @@ -516,12 +531,13 @@ class Filter(object): ---------- data_size : Integral The total number of bins in the tally corresponding to this filter - summary : None or Summary - An optional Summary object to be used to construct columns for - distribcell tally filters (default is None). The geometric - information in the Summary object is embedded into a Multi-index - column with a geometric "path" to each distribcell instance. - NOTE: This option requires the OpenCG Python package. + distribcell_paths : bool, optional + Construct columns for distribcell tally filters (default is True). + The geometric information in the Summary object is embedded into a + Multi-index column with a geometric "path" to each distribcell + instance. NOTE: This option assumes that all distribcell paths are + of the same length and do not have the same universes and cells but + different lattice cell indices. Returns ------- @@ -539,7 +555,7 @@ class Filter(object): 1. a single column with the cell instance IDs (without summary info) 2. separate columns for the cell IDs, universe IDs, and lattice IDs - and x,y,z cell indices corresponding to each (with summary info). + and x,y,z cell indices corresponding to each (distribcell paths). For 'energy' and 'energyout' filters, the DataFrame includes one column for the lower energy bound and one column for the upper @@ -551,8 +567,7 @@ class Filter(object): Raises ------ ImportError - When Pandas is not installed, or summary info is requested but - OpenCG is not installed. + When Pandas is not installed See also -------- @@ -611,114 +626,117 @@ class Filter(object): elif self.type == 'distribcell': level_df = None - if isinstance(summary, Summary): - # Attempt to import the OpenCG package - try: - import opencg - except ImportError: - msg = 'The OpenCG package must be installed ' \ - 'to use a Summary for distribcell dataframes' - raise ImportError(msg) + # Create Pandas Multi-index columns for each level in CSG tree + if distribcell_paths: - # Extract the OpenCG geometry from the Summary - opencg_geometry = summary.opencg_geometry - openmc_geometry = summary.openmc_geometry + # Distribcell paths require linked metadata from the Summary + if self.distribcell_paths is None: + msg = 'Unable to construct distribcell paths since ' \ + 'the Summary is not linked to the StatePoint' + raise ValueError(msg) - # Use OpenCG to compute the number of regions - opencg_geometry.initialize_cell_offsets() - num_regions = opencg_geometry.num_regions + # Make copy of array of distribcell paths to use in + # Pandas Multi-index column construction + distribcell_paths = copy.deepcopy(self.distribcell_paths) + num_offsets = len(distribcell_paths) - # Initialize a dictionary mapping OpenMC distribcell - # offsets to OpenCG LocalCoords linked lists - offsets_to_coords = {} - - # Use OpenCG to compute LocalCoords linked list for - # each region and store in dictionary - for region in range(num_regions): - coords = opencg_geometry.find_region(region) - path = opencg.get_path(coords) - cell_id = path[-1] - - # If this region is in Cell corresponding to the - # distribcell filter bin, store it in dictionary - if cell_id == self.bins[0]: - offset = openmc_geometry.get_cell_instance(path) - offsets_to_coords[offset] = coords - - # Each distribcell offset is a DataFrame bin - # Unravel the paths into DataFrame columns - num_offsets = len(offsets_to_coords) - - # Initialize termination condition for while loop + # Loop over CSG levels in the distribcell paths + level_counter = 0 levels_remain = True - counter = 0 - - # Iterate over each level in the CSG tree hierarchy while levels_remain: - levels_remain = False - # Initialize dictionary to build Pandas Multi-index - # column for this level in the CSG tree hierarchy - level_dict = {} + # Use level key as first index in Pandas Multi-index column + level_counter += 1 + level_key = 'level {}'.format(level_counter) - # Initialize prefix Multi-index keys - counter += 1 - level_key = 'level {0}'.format(counter) - univ_key = (level_key, 'univ', 'id') - cell_key = (level_key, 'cell', 'id') - lat_id_key = (level_key, 'lat', 'id') - lat_x_key = (level_key, 'lat', 'x') - lat_y_key = (level_key, 'lat', 'y') - lat_z_key = (level_key, 'lat', 'z') + # Use the first distribcell path to determine if level + # is a universe/cell or lattice level + first_path = distribcell_paths[0] + next_index = first_path.index('-') + level = first_path[:next_index] - # Allocate NumPy arrays for each CSG level and - # each Multi-index column in the DataFrame - level_dict[univ_key] = np.empty(num_offsets) - level_dict[cell_key] = np.empty(num_offsets) - level_dict[lat_id_key] = np.empty(num_offsets) - level_dict[lat_x_key] = np.empty(num_offsets) - level_dict[lat_y_key] = np.empty(num_offsets) - level_dict[lat_z_key] = np.empty(num_offsets) + # Trim universe/lattice info from path + first_path = first_path[next_index+2:] - # Initialize Multi-index columns to NaN - this is - # necessary since some distribcell instances may - # have very different LocalCoords linked lists - level_dict[univ_key][:] = np.NAN - level_dict[cell_key][:] = np.NAN - level_dict[lat_id_key][:] = np.NAN - level_dict[lat_x_key][:] = np.NAN - level_dict[lat_y_key][:] = np.NAN - level_dict[lat_z_key][:] = np.NAN + # Create a dictionary for this level for Pandas Multi-index + level_dict = OrderedDict() - # Iterate over all regions (distribcell instances) - for offset in range(num_offsets): - coords = offsets_to_coords[offset] + # This level is a lattice (e.g., ID(x,y,z)) + if '(' in level: + level_type = 'lattice' - # If entire LocalCoords has been unraveled into - # Multi-index columns already, continue - if coords is None: - continue + # Initialize prefix Multi-index keys + lat_id_key = (level_key, 'lat', 'id') + lat_x_key = (level_key, 'lat', 'x') + lat_y_key = (level_key, 'lat', 'y') + lat_z_key = (level_key, 'lat', 'z') - # Assign entry to Universe Multi-index column - if coords._type == 'universe': - level_dict[univ_key][offset] = coords._universe._id - level_dict[cell_key][offset] = coords._cell._id + # Allocate NumPy arrays for each CSG level and + # each Multi-index column in the DataFrame + level_dict[lat_id_key] = np.empty(num_offsets) + level_dict[lat_x_key] = np.empty(num_offsets) + level_dict[lat_y_key] = np.empty(num_offsets) + level_dict[lat_z_key] = np.empty(num_offsets) + + # This level is a universe / cell (e.g., ID->ID) + else: + level_type = 'universe' + + # Initialize prefix Multi-index keys + univ_key = (level_key, 'univ', 'id') + cell_key = (level_key, 'cell', 'id') + + # Allocate NumPy arrays for each CSG level and + # each Multi-index column in the DataFrame + level_dict[univ_key] = np.empty(num_offsets) + level_dict[cell_key] = np.empty(num_offsets) + + # Determine any levels remain in path + if '-' not in first_path: + levels_remain = False + + # Populate Multi-index arrays with all distribcell paths + for i, path in enumerate(distribcell_paths): + + if level_type == 'lattice': + # Extract lattice ID, indices from path + next_index = path.index('-') + lat_id_indices = path[:next_index] + + # Trim lattice info from distribcell path + distribcell_paths[i] = path[next_index+2:] + + # Extract the lattice cell indices from the path + i1 = lat_id_indices.index('(') + i2 = lat_id_indices.index(')') + i3 = lat_id_indices[i1+1:i2] + + # Assign entry to Lattice Multi-index column + level_dict[lat_id_key][i] = path[:i1] + level_dict[lat_x_key][i] = int(i3.split(',')[0]) - 1 + level_dict[lat_y_key][i] = int(i3.split(',')[1]) - 1 + level_dict[lat_z_key][i] = int(i3.split(',')[2]) - 1 - # Assign entry to Lattice Multi-index column else: - # Reverse y index per lattice ordering in OpenCG - level_dict[lat_id_key][offset] = coords._lattice._id - level_dict[lat_x_key][offset] = coords._lat_x - level_dict[lat_y_key][offset] = \ - coords._lattice.dimension[1] - coords._lat_y - 1 - level_dict[lat_z_key][offset] = coords._lat_z + # Extract universe ID from path + next_index = path.index('-') + universe_id = int(path[:next_index]) - # Move to next node in LocalCoords linked list - if coords._next is None: - offsets_to_coords[offset] = None - else: - offsets_to_coords[offset] = coords._next - levels_remain = True + # Trim universe info from distribcell path + path = path[next_index+2:] + + # Extract cell ID from path + if '-' in path: + next_index = path.index('-') + cell_id = int(path[:next_index]) + distribcell_paths[i] = path[next_index+2:] + else: + cell_id = int(path) + distribcell_paths[i] = '' + + # Assign entry to Universe, Cell Multi-index columns + level_dict[univ_key][i] = universe_id + level_dict[cell_key][i] = cell_id # Tile the Multi-index columns for level_key, level_bins in level_dict.items(): @@ -733,7 +751,7 @@ class Filter(object): else: level_df = pd.concat([level_df, pd.DataFrame(level_dict)], axis=1) - # Create DataFrame column for distribcell instances IDs + # Create DataFrame column for distribcell instance IDs # NOTE: This is performed regardless of whether the user # requests Summary geometric information filter_bins = np.arange(self.num_bins) diff --git a/openmc/geometry.py b/openmc/geometry.py index dac0bd90f..2625ed3fa 100644 --- a/openmc/geometry.py +++ b/openmc/geometry.py @@ -15,17 +15,23 @@ def reset_auto_ids(): class Geometry(object): """Geometry representing a collection of surfaces, cells, and universes. + Parameters + ---------- + root_universe : openmc.Universe, optional + Root universe which contains all others + Attributes ---------- - root_universe : openmc.universe.Universe + root_universe : openmc.Universe Root universe which contains all others """ - def __init__(self): - # Initialize Geometry class attributes + def __init__(self, root_universe=None): self._root_universe = None self._offsets = {} + if root_universe is not None: + self.root_universe = root_universe @property def root_universe(self): @@ -42,6 +48,44 @@ class Geometry(object): self._root_universe = root_universe + def export_to_xml(self): + """Create a geometry.xml file that can be used for a simulation. + + """ + + # Clear OpenMC written IDs used to optimize XML generation + openmc.universe.WRITTEN_IDS = {} + + # Create XML representation + geometry_file = ET.Element("geometry") + self.root_universe.create_xml_subelement(geometry_file) + + # Clean the indentation in the file to be user-readable + sort_xml_elements(geometry_file) + clean_xml_indentation(geometry_file) + + # Write the XML Tree to the geometry.xml file + tree = ET.ElementTree(geometry_file) + tree.write("geometry.xml", xml_declaration=True, encoding='utf-8', + method="xml") + + def find(self, point): + """Find cells/universes/lattices which contain a given point + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates of the point + + Returns + ------- + list + Sequence of universes, cells, and lattices which are traversed to + find the given point + + """ + return self.root_universe.find(point) + def get_cell_instance(self, path): """Return the instance number for the final cell in a geometry path. @@ -63,15 +107,19 @@ class Geometry(object): """ + # Extract the cell id from the path + last_index = path.rfind('>') + cell_id = int(path[last_index+1:]) + # Find the distribcell index of the cell. cells = self.get_all_cells() for cell in cells: - if cell.id == path[-1]: + if cell.id == cell_id: distribcell_index = cell.distribcell_index break else: raise RuntimeError('Could not find cell {} specified in a \ - distribcell filter'.format(path[-1])) + distribcell filter'.format(cell_id)) # Return memoize'd offset if possible if (path, distribcell_index) in self._offsets: @@ -91,19 +139,13 @@ class Geometry(object): Returns ------- - list of openmc.universe.Cell + list of openmc.Cell Cells in the geometry """ - all_cells = self._root_universe.get_all_cells() - cells = set() - - for cell in all_cells.values(): - if cell._type == 'normal': - cells.add(cell) - - cells = list(cells) + all_cells = self.root_universe.get_all_cells() + cells = list(set(all_cells.values())) cells.sort(key=lambda x: x.id) return cells @@ -112,18 +154,13 @@ class Geometry(object): Returns ------- - list of openmc.universe.Universe + list of openmc.Universe Universes in the geometry """ all_universes = self._root_universe.get_all_universes() - universes = set() - - for universe in all_universes.values(): - universes.add(universe) - - universes = list(universes) + universes = list(set(all_universes.values())) universes.sort(key=lambda x: x.id) return universes @@ -132,7 +169,7 @@ class Geometry(object): Returns ------- - list of openmc.nuclide.Nuclide + list of openmc.Nuclide Nuclides in the geometry """ @@ -150,21 +187,23 @@ class Geometry(object): Returns ------- - list of openmc.material.Material + list of openmc.Material Materials in the geometry """ material_cells = self.get_all_material_cells() - materials = set() + materials = [] for cell in material_cells: - if isinstance(cell.fill, Iterable): - for m in cell.fill: materials.add(m) - else: - materials.add(cell.fill) + if cell.fill_type == 'distribmat': + for m in cell.fill: + if m is not None and m not in materials: + materials.append(m) + elif cell.fill_type == 'material': + if cell.fill not in materials: + materials.append(cell.fill) - materials = list(materials) materials.sort(key=lambda x: x.id) return materials @@ -173,19 +212,19 @@ class Geometry(object): Returns ------- - list of openmc.universe.Cell + list of openmc.Cell Cells filled by Materials in the geometry """ all_cells = self.get_all_cells() - material_cells = set() + material_cells = [] for cell in all_cells: - if cell._type == 'normal': - material_cells.add(cell) + if cell.fill_type in ('material', 'distribmat'): + if cell not in material_cells: + material_cells.append(cell) - material_cells = list(material_cells) material_cells.sort(key=lambda x: x.id) return material_cells @@ -194,21 +233,21 @@ class Geometry(object): Returns ------- - list of openmc.universe.Universe + list of openmc.Universe Universes with non-fill cells """ all_universes = self.get_all_universes() - material_universes = set() + material_universes = [] for universe in all_universes: cells = universe.cells for cell in cells: - if cell._type == 'normal': - material_universes.add(universe) + if cell.fill_type in ('material', 'distribmat', 'void'): + if universe not in material_universes: + material_universes.append(universe) - material_universes = list(material_universes) material_universes.sort(key=lambda x: x.id) return material_universes @@ -217,19 +256,19 @@ class Geometry(object): Returns ------- - list of openmc.universe.Lattice + list of openmc.Lattice Lattices in the geometry """ cells = self.get_all_cells() - lattices = set() + lattices = [] for cell in cells: - if isinstance(cell.fill, openmc.Lattice): - lattices.add(cell.fill) + if cell.fill_type == 'lattice': + if cell.fill not in lattices: + lattices.append(cell.fill) - lattices = list(lattices) lattices.sort(key=lambda x: x.id) return lattices @@ -248,7 +287,7 @@ class Geometry(object): Returns ------- - list of openmc.material.Material + list of openmc.Material Materials matching the queried name """ @@ -288,7 +327,7 @@ class Geometry(object): Returns ------- - list of openmc.universe.Cell + list of openmc.Cell Cells matching the queried name """ @@ -328,7 +367,7 @@ class Geometry(object): Returns ------- - list of openmc.universe.Cell + list of openmc.Cell Cells with fills matching the queried name """ @@ -368,7 +407,7 @@ class Geometry(object): Returns ------- - list of openmc.universe.Universe + list of openmc.Universe Universes matching the queried name """ @@ -408,7 +447,7 @@ class Geometry(object): Returns ------- - list of openmc.universe.Lattice + list of openmc.Lattice Lattices matching the queried name """ @@ -432,52 +471,3 @@ class Geometry(object): lattices = list(lattices) lattices.sort(key=lambda x: x.id) return lattices - - -class GeometryFile(object): - """Geometry file used for an OpenMC simulation. Corresponds directly to the - geometry.xml input file. - - Attributes - ---------- - geometry : Geometry - The geometry to be used - - """ - - def __init__(self): - # Initialize GeometryFile class attributes - self._geometry = None - self._geometry_file = ET.Element("geometry") - - @property - def geometry(self): - return self._geometry - - @geometry.setter - def geometry(self, geometry): - check_type('the geometry', geometry, Geometry) - self._geometry = geometry - - def export_to_xml(self): - """Create a geometry.xml file that can be used for a simulation. - - """ - - # Clear OpenMC written IDs used to optimize XML generation - openmc.universe.WRITTEN_IDS = {} - - # Reset xml element tree - self._geometry_file.clear() - - root_universe = self.geometry.root_universe - root_universe.create_xml_subelement(self._geometry_file) - - # Clean the indentation in the file to be user-readable - sort_xml_elements(self._geometry_file) - clean_xml_indentation(self._geometry_file) - - # Write the XML Tree to the geometry.xml file - tree = ET.ElementTree(self._geometry_file) - tree.write("geometry.xml", xml_declaration=True, - encoding='utf-8', method="xml") diff --git a/openmc/lattice.py b/openmc/lattice.py new file mode 100644 index 000000000..7690104c7 --- /dev/null +++ b/openmc/lattice.py @@ -0,0 +1,1328 @@ +from __future__ import division + +import abc +from collections import OrderedDict, Iterable +from math import sqrt, floor +from numbers import Real, Integral +from xml.etree import ElementTree as ET +import sys +import warnings + +import numpy as np + +import openmc.checkvalue as cv +import openmc + +if sys.version_info[0] >= 3: + basestring = str + + +class Lattice(object): + """A repeating structure wherein each element is a universe. + + Parameters + ---------- + lattice_id : int, optional + Unique identifier for the lattice. If not specified, an identifier will + automatically be assigned. + name : str, optional + Name of the lattice. If not specified, the name is the empty string. + + Attributes + ---------- + id : int + Unique identifier for the lattice + name : str + Name of the lattice + pitch : Iterable of float + Pitch of the lattice in each direction in cm + outer : openmc.Universe + A universe to fill all space outside the lattice + universes : Iterable of Iterable of openmc.Universe + A two- or three-dimensional list/array of universes filling each element + of the lattice + + """ + + # This is an abstract class which cannot be instantiated + __metaclass__ = abc.ABCMeta + + def __init__(self, lattice_id=None, name=''): + # Initialize Lattice class attributes + self.id = lattice_id + self.name = name + self._pitch = None + self._outer = None + self._universes = None + + def __eq__(self, other): + if not isinstance(other, Lattice): + return False + elif self.id != other.id: + return False + elif self.name != other.name: + return False + elif self.pitch != other.pitch: + return False + elif self.outer != other.outer: + return False + elif self.universes != other.universes: + return False + else: + return True + + def __ne__(self, other): + return not self == other + + @property + def id(self): + return self._id + + @property + def name(self): + return self._name + + @property + def pitch(self): + return self._pitch + + @property + def outer(self): + return self._outer + + @property + def universes(self): + return self._universes + + @id.setter + def id(self, lattice_id): + if lattice_id is None: + self._id = openmc.universe.AUTO_UNIVERSE_ID + openmc.universe.AUTO_UNIVERSE_ID += 1 + else: + cv.check_type('lattice ID', lattice_id, Integral) + cv.check_greater_than('lattice ID', lattice_id, 0, equality=True) + self._id = lattice_id + + @name.setter + def name(self, name): + if name is not None: + cv.check_type('lattice name', name, basestring) + self._name = name + else: + self._name = '' + + @outer.setter + def outer(self, outer): + cv.check_type('outer universe', outer, openmc.Universe) + self._outer = outer + + def get_unique_universes(self): + """Determine all unique universes in the lattice + + Returns + ------- + universes : collections.OrderedDict + Dictionary whose keys are universe IDs and values are + :class:`openmc.Universe` instances + + """ + + univs = OrderedDict() + for k in range(len(self._universes)): + for j in range(len(self._universes[k])): + if isinstance(self._universes[k][j], openmc.Universe): + u = self._universes[k][j] + univs[u._id] = u + else: + for i in range(len(self._universes[k][j])): + u = self._universes[k][j][i] + assert isinstance(u, openmc.Universe) + univs[u._id] = u + + if self.outer is not None: + univs[self.outer._id] = self.outer + + return univs + + def get_all_nuclides(self): + """Return all nuclides contained in the lattice + + Returns + ------- + nuclides : collections.OrderedDict + Dictionary whose keys are nuclide names and values are 2-tuples of + (nuclide, density) + + """ + + nuclides = OrderedDict() + + # Get all unique Universes contained in each of the lattice cells + unique_universes = self.get_unique_universes() + + # Append all Universes containing each cell to the dictionary + for universe_id, universe in unique_universes.items(): + nuclides.update(universe.get_all_nuclides()) + + return nuclides + + def get_all_cells(self): + """Return all cells that are contained within the lattice + + Returns + ------- + cells : collections.OrderedDict + Dictionary whose keys are cell IDs and values are :class:`Cell` + instances + + """ + + cells = OrderedDict() + unique_universes = self.get_unique_universes() + + for universe_id, universe in unique_universes.items(): + cells.update(universe.get_all_cells()) + + return cells + + def get_all_materials(self): + """Return all materials that are contained within the lattice + + Returns + ------- + materials : collections.OrderedDict + Dictionary whose keys are material IDs and values are + :class:`Material` instances + + """ + + materials = OrderedDict() + + # Append all Cells in each Cell in the Universe to the dictionary + cells = self.get_all_cells() + for cell_id, cell in cells.items(): + materials.update(cell.get_all_materials()) + + return materials + + def get_all_universes(self): + """Return all universes that are contained within the lattice + + Returns + ------- + universes : collections.OrderedDict + Dictionary whose keys are universe IDs and values are + :class:`Universe` instances + + """ + + # Initialize a dictionary of all Universes contained by the Lattice + # in each nested Universe level + all_universes = OrderedDict() + + # Get all unique Universes contained in each of the lattice cells + unique_universes = self.get_unique_universes() + + # Add the unique Universes filling each Lattice cell + all_universes.update(unique_universes) + + # Append all Universes containing each cell to the dictionary + for universe_id, universe in unique_universes.items(): + all_universes.update(universe.get_all_universes()) + + return all_universes + + +class RectLattice(Lattice): + """A lattice consisting of rectangular prisms. + + To completely define a rectangular lattice, the + :attr:`RectLattice.lower_left` :attr:`RectLattice.pitch`, + :attr:`RectLattice.outer`, and :attr:`RectLattice.universes` properties need + to be set. + + Most methods for this class use a natural indexing scheme wherein elements + are assigned an index corresponding to their position relative to the + (x,y,z) axes in a Cartesian coordinate system, i.e., an index of (0,0,0) in + the lattice gives the element whose x, y, and z coordinates are the + smallest. However, note that when universes are assigned to lattice elements + using the :attr:`RectLattice.universes` property, the array indices do not + correspond to natural indices. + + Parameters + ---------- + lattice_id : int, optional + Unique identifier for the lattice. If not specified, an identifier will + automatically be assigned. + name : str, optional + Name of the lattice. If not specified, the name is the empty string. + + Attributes + ---------- + id : int + Unique identifier for the lattice + name : str + Name of the lattice + pitch : Iterable of float + Pitch of the lattice in the x, y, and (if applicable) z directions in + cm. + outer : openmc.Universe + A universe to fill all space outside the lattice + universes : Iterable of Iterable of openmc.Universe + A two- or three-dimensional list/array of universes filling each element + of the lattice. The first dimension corresponds to the z-direction (if + applicable), the second dimension corresponds to the y-direction, and + the third dimension corresponds to the x-direction. Note that for the + y-direction, a higher index corresponds to a lower physical + y-value. Each z-slice in the array can be thought of as a top-down view + of the lattice. + lower_left : Iterable of float + The Cartesian coordinates of the lower-left corner of the lattice. If + the lattice is two-dimensional, only the x- and y-coordinates are + specified. + indices : list of tuple + A list of all possible (z,y,x) or (y,x) lattice element indices. These + indices correspond to indices in the :attr:`RectLattice.universes` + property. + ndim : int + The number of dimensions of the lattice + shape : Iterable of int + An array of two or three integers representing the number of lattice + cells in the x- and y- (and z-) directions, respectively. + + """ + + def __init__(self, lattice_id=None, name=''): + super(RectLattice, self).__init__(lattice_id, name) + + # Initialize Lattice class attributes + self._lower_left = None + self._offsets = None + + def __eq__(self, other): + if not isinstance(other, RectLattice): + return False + elif not super(RectLattice, self).__eq__(other): + return False + elif self.shape != other.shape: + return False + elif self.lower_left != other.lower_left: + return False + else: + return True + + def __ne__(self, other): + return not self == other + + def __hash__(self): + return hash(repr(self)) + + def __repr__(self): + string = 'RectLattice\n' + string += '{0: <16}{1}{2}\n'.format('\tID', '=\t', self._id) + string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) + string += '{0: <16}{1}{2}\n'.format('\tShape', '=\t', + self.shape) + string += '{0: <16}{1}{2}\n'.format('\tLower Left', '=\t', + self._lower_left) + string += '{0: <16}{1}{2}\n'.format('\tPitch', '=\t', self._pitch) + + if self._outer is not None: + string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', + self._outer._id) + else: + string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', + self._outer) + + string += '{0: <16}\n'.format('\tUniverses') + + # Lattice nested Universe IDs - column major for Fortran + for i, universe in enumerate(np.ravel(self._universes)): + string += '{0} '.format(universe._id) + + # Add a newline character every time we reach end of row of cells + if (i+1) % self.shape[0] == 0: + string += '\n' + + string = string.rstrip('\n') + + if self._offsets is not None: + string += '{0: <16}\n'.format('\tOffsets') + + # Lattice cell offsets + for i, offset in enumerate(np.ravel(self._offsets)): + string += '{0} '.format(offset) + + # Add a newline character when we reach end of row of cells + if (i+1) % self.shape[0] == 0: + string += '\n' + + string = string.rstrip('\n') + + return string + + @property + def indices(self): + if self.ndim == 2: + return list(np.broadcast(*np.ogrid[ + :self.shape[1], :self.shape[0]])) + else: + return list(np.broadcast(*np.ogrid[ + :self.shape[2], :self.shape[1], :self.shape[0]])) + + @property + def lower_left(self): + return self._lower_left + + @property + def ndim(self): + return len(self.pitch) + + @property + def offsets(self): + return self._offsets + + @property + def shape(self): + return self._universes.shape[::-1] + + @lower_left.setter + def lower_left(self, lower_left): + cv.check_type('lattice lower left corner', lower_left, Iterable, Real) + cv.check_length('lattice lower left corner', lower_left, 2, 3) + self._lower_left = lower_left + + @offsets.setter + def offsets(self, offsets): + cv.check_type('lattice offsets', offsets, Iterable) + self._offsets = offsets + + @Lattice.pitch.setter + def pitch(self, pitch): + cv.check_type('lattice pitch', pitch, Iterable, Real) + cv.check_length('lattice pitch', pitch, 2, 3) + for dim in pitch: + cv.check_greater_than('lattice pitch', dim, 0.0) + self._pitch = pitch + + @Lattice.universes.setter + def universes(self, universes): + cv.check_iterable_type('lattice universes', universes, openmc.Universe, + min_depth=2, max_depth=3) + self._universes = np.asarray(universes) + + def get_cell_instance(self, path, distribcell_index): + # Extract the lattice element from the path + next_index = path.index('-') + lat_id_indices = path[:next_index] + path = path[next_index+2:] + + # Extract the lattice cell indices from the path + i1 = lat_id_indices.index('(') + i2 = lat_id_indices.index(')') + i = lat_id_indices[i1+1:i2] + lat_x = int(i.split(',')[0]) - 1 + lat_y = int(i.split(',')[1]) - 1 + lat_z = int(i.split(',')[2]) - 1 + + # For 2D Lattices + if self.ndim == 2: + offset = self._offsets[lat_z, lat_y, lat_x, distribcell_index-1] + offset += self._universes[lat_x][lat_y].get_cell_instance(path, + distribcell_index) + + # For 3D Lattices + else: + offset = self._offsets[lat_z, lat_y, lat_x, distribcell_index-1] + offset += self._universes[lat_z][lat_y][lat_x].get_cell_instance( + path, distribcell_index) + + return offset + + def find_element(self, point): + """Determine index of lattice element and local coordinates for a point + + Parameters + ---------- + point : Iterable of float + Cartesian coordinates of point + + Returns + ------- + 2- or 3-tuple of int + A tuple of the corresponding (x,y,z) lattice element indices + 3-tuple of float + Carestian coordinates of the point in the corresponding lattice + element coordinate system + + """ + ix = floor((point[0] - self.lower_left[0])/self.pitch[0]) + iy = floor((point[1] - self.lower_left[1])/self.pitch[1]) + if self.ndim == 2: + idx = (ix, iy) + else: + iz = floor((point[2] - self.lower_left[2])/self.pitch[2]) + idx = (ix, iy, iz) + return idx, self.get_local_coordinates(point, idx) + + def get_local_coordinates(self, point, idx): + """Determine local coordinates of a point within a lattice element + + Parameters + ---------- + point : Iterable of float + Cartesian coordinates of point + idx : Iterable of int + (x,y,z) indices of lattice element. If the lattice is 2D, the z + index can be omitted. + + Returns + ------- + 3-tuple of float + Cartesian coordinates of point in the lattice element coordinate + system + + """ + x = point[0] - (self.lower_left[0] + (idx[0] + 0.5)*self.pitch[0]) + y = point[1] - (self.lower_left[1] + (idx[1] + 0.5)*self.pitch[1]) + if self.ndim == 2: + z = point[2] + else: + z = point[2] - (self.lower_left[2] + (idx[2] + 0.5)*self.pitch[2]) + return (x, y, z) + + def get_universe_index(self, idx): + """Return index in the universes array corresponding to a lattice element index + + Parameters + ---------- + idx : Iterable of int + Lattice element indices in the :math:`(x,y,z)` coordinate system + + Returns + ------- + 2- or 3-tuple of int + Indices used when setting the :attr:`RectLattice.universes` property + + """ + max_y = self.shape[1] - 1 + if self.ndim == 2: + x, y = idx + return (max_y - y, x) + else: + x, y, z = idx + return (z, max_y - y, x) + + def is_valid_index(self, idx): + """Determine whether lattice element index is within defined range + + Parameters + ---------- + idx : Iterable of int + Lattice element indices in the :math:`(x,y,z)` coordinate system + + Returns + ------- + bool + Whether index is valid + + """ + if self.ndim == 2: + return (0 <= idx[0] < self.shape[0] and + 0 <= idx[1] < self.shape[1]) + else: + return (0 <= idx[0] < self.shape[0] and + 0 <= idx[1] < self.shape[1] and + 0 <= idx[2] < self.shape[2]) + + def find(self, point): + """Find cells/universes/lattices which contain a given point + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinatesof the point + + Returns + ------- + list + Sequence of universes, cells, and lattices which are traversed to + find the given point + + """ + idx, p = self.find_element(point) + if self.is_valid_index(idx): + idx_u = self.get_universe_index(idx) + u = self.universes[idx_u] + else: + if self.outer is not None: + u = self.outer + else: + return [] + return [(self, idx)] + u.find(p) + + def create_xml_subelement(self, xml_element): + + # Determine if XML element already contains subelement for this Lattice + path = './lattice[@id=\'{0}\']'.format(self._id) + test = xml_element.find(path) + + # If the element does contain the Lattice subelement, then return + if test is not None: + return + + lattice_subelement = ET.Element("lattice") + lattice_subelement.set("id", str(self._id)) + + if len(self._name) > 0: + lattice_subelement.set("name", str(self._name)) + + # Export the Lattice cell pitch + pitch = ET.SubElement(lattice_subelement, "pitch") + pitch.text = ' '.join(map(str, self._pitch)) + + # Export the Lattice outer Universe (if specified) + if self._outer is not None: + outer = ET.SubElement(lattice_subelement, "outer") + outer.text = '{0}'.format(self._outer._id) + self._outer.create_xml_subelement(xml_element) + + # Export Lattice cell dimensions + dimension = ET.SubElement(lattice_subelement, "dimension") + dimension.text = ' '.join(map(str, self.shape)) + + # Export Lattice lower left + lower_left = ET.SubElement(lattice_subelement, "lower_left") + lower_left.text = ' '.join(map(str, self._lower_left)) + + # Export the Lattice nested Universe IDs - column major for Fortran + universe_ids = '\n' + + # 3D Lattices + if self.ndim == 3: + for z in range(self.shape[2]): + for y in range(self.shape[1]): + for x in range(self.shape[0]): + universe = self._universes[z][y][x] + + # Append Universe ID to the Lattice XML subelement + universe_ids += '{0} '.format(universe._id) + + # Create XML subelement for this Universe + universe.create_xml_subelement(xml_element) + + # Add newline character when we reach end of row of cells + universe_ids += '\n' + + # Add newline character when we reach end of row of cells + universe_ids += '\n' + + # 2D Lattices + else: + for y in range(self.shape[1]): + for x in range(self.shape[0]): + universe = self._universes[y][x] + + # Append Universe ID to Lattice XML subelement + universe_ids += '{0} '.format(universe._id) + + # Create XML subelement for this Universe + universe.create_xml_subelement(xml_element) + + # Add newline character when we reach end of row of cells + universe_ids += '\n' + + # Remove trailing newline character from Universe IDs string + universe_ids = universe_ids.rstrip('\n') + + universes = ET.SubElement(lattice_subelement, "universes") + universes.text = universe_ids + + # Append the XML subelement for this Lattice to the XML element + xml_element.append(lattice_subelement) + + +class HexLattice(Lattice): + r"""A lattice consisting of hexagonal prisms. + + To completely define a hexagonal lattice, the :attr:`HexLattice.center`, + :attr:`HexLattice.pitch`, :attr:`HexLattice.universes`, and + :attr:`HexLattice.outer` properties need to be set. + + Most methods for this class use a natural indexing scheme wherein elements + are assigned an index corresponding to their position relative to skewed + :math:`(x,\alpha,z)` axes as described fully in + :ref:`hexagonal_indexing`. However, note that when universes are assigned to + lattice elements using the :attr:`HexLattice.universes` property, the array + indices do not correspond to natural indices. + + Parameters + ---------- + lattice_id : int, optional + Unique identifier for the lattice. If not specified, an identifier will + automatically be assigned. + name : str, optional + Name of the lattice. If not specified, the name is the empty string. + + Attributes + ---------- + id : int + Unique identifier for the lattice + name : str + Name of the lattice + pitch : Iterable of float + Pitch of the lattice in cm. The first item in the iterable specifies the + pitch in the radial direction and, if the lattice is 3D, the second item + in the iterable specifies the pitch in the axial direction. + outer : openmc.Universe + A universe to fill all space outside the lattice + universes : Nested Iterable of openmc.Universe + A two- or three-dimensional list/array of universes filling each element + of the lattice. Each sub-list corresponds to one ring of universes and + should be ordered from outermost ring to innermost ring. The universes + within each sub-list are ordered from the "top" and proceed in a + clockwise fashion. The :meth:`HexLattice.show_indices` method can be + used to help figure out indices for this property. + center : Iterable of float + Coordinates of the center of the lattice. If the lattice does not have + axial sections then only the x- and y-coordinates are specified + indices : list of tuple + A list of all possible (z,r,i) or (r,i) lattice element indices that are + possible, where z is the axial index, r is in the ring index (starting + from the outermost ring), and i is the index with a ring starting from + the top and proceeding clockwise. + num_rings : int + Number of radial ring positions in the xy-plane + num_axial : int + Number of positions along the z-axis. + + """ + + def __init__(self, lattice_id=None, name=''): + super(HexLattice, self).__init__(lattice_id, name) + + # Initialize Lattice class attributes + self._num_rings = None + self._num_axial = None + self._center = None + + def __eq__(self, other): + if not isinstance(other, HexLattice): + return False + elif not super(HexLattice, self).__eq__(other): + return False + elif self.num_rings != other.num_rings: + return False + elif self.num_axial != other.num_axial: + return False + elif self.center != other.center: + return False + else: + return True + + def __ne__(self, other): + return not self == other + + def __hash__(self): + return hash(repr(self)) + + def __repr__(self): + string = 'HexLattice\n' + string += '{0: <16}{1}{2}\n'.format('\tID', '=\t', self._id) + string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) + string += '{0: <16}{1}{2}\n'.format('\t# Rings', '=\t', self._num_rings) + string += '{0: <16}{1}{2}\n'.format('\t# Axial', '=\t', self._num_axial) + string += '{0: <16}{1}{2}\n'.format('\tCenter', '=\t', + self._center) + string += '{0: <16}{1}{2}\n'.format('\tPitch', '=\t', self._pitch) + + if self._outer is not None: + string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', + self._outer._id) + else: + string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', + self._outer) + + string += '{0: <16}\n'.format('\tUniverses') + + if self._num_axial is not None: + slices = [self._repr_axial_slice(x) for x in self._universes] + string += '\n'.join(slices) + + else: + string += self._repr_axial_slice(self._universes) + + return string + + @property + def num_rings(self): + return self._num_rings + + @property + def num_axial(self): + return self._num_axial + + @property + def center(self): + return self._center + + @property + def indices(self): + if self.num_axial is None: + return [(r, i) for r in range(self.num_rings) + for i in range(max(6*(self.num_rings - 1 - r), 1))] + else: + return [(z, r, i) for z in range(self.num_axial) + for r in range(self.num_rings) + for i in range(max(6*(self.num_rings - 1 - r), 1))] + + @center.setter + def center(self, center): + cv.check_type('lattice center', center, Iterable, Real) + cv.check_length('lattice center', center, 2, 3) + self._center = center + + @Lattice.pitch.setter + def pitch(self, pitch): + cv.check_type('lattice pitch', pitch, Iterable, Real) + cv.check_length('lattice pitch', pitch, 1, 2) + for dim in pitch: + cv.check_greater_than('lattice pitch', dim, 0) + self._pitch = pitch + + @Lattice.universes.setter + def universes(self, universes): + cv.check_iterable_type('lattice universes', universes, openmc.Universe, + min_depth=2, max_depth=3) + self._universes = universes + + # NOTE: This routine assumes that the user creates a "ragged" list of + # lists, where each sub-list corresponds to one ring of Universes. + # The sub-lists are ordered from outermost ring to innermost ring. + # The Universes within each sub-list are ordered from the "top" in a + # clockwise fashion. + + # Check to see if the given universes look like a 2D or a 3D array. + if isinstance(self._universes[0][0], openmc.Universe): + n_dims = 2 + + elif isinstance(self._universes[0][0][0], openmc.Universe): + n_dims = 3 + + else: + msg = 'HexLattice ID={0:d} does not appear to be either 2D or ' \ + '3D. Make sure set_universes was given a two-deep or ' \ + 'three-deep iterable of universes.'.format(self._id) + raise RuntimeError(msg) + + # Set the number of axial positions. + if n_dims == 3: + self._num_axial = len(self._universes) + else: + self._num_axial = None + + # Set the number of rings and make sure this number is consistent for + # all axial positions. + if n_dims == 3: + self._num_rings = len(self._universes[0]) + for rings in self._universes: + if len(rings) != self._num_rings: + msg = 'HexLattice ID={0:d} has an inconsistent number of ' \ + 'rings per axial positon'.format(self._id) + raise ValueError(msg) + + else: + self._num_rings = len(self._universes) + + # Make sure there are the correct number of elements in each ring. + if n_dims == 3: + for axial_slice in self._universes: + # Check the center ring. + if len(axial_slice[-1]) != 1: + msg = 'HexLattice ID={0:d} has the wrong number of ' \ + 'elements in the innermost ring. Only 1 element is ' \ + 'allowed in the innermost ring.'.format(self._id) + raise ValueError(msg) + + # Check the outer rings. + for r in range(self._num_rings-1): + if len(axial_slice[r]) != 6*(self._num_rings - 1 - r): + msg = 'HexLattice ID={0:d} has the wrong number of ' \ + 'elements in ring number {1:d} (counting from the '\ + 'outermost ring). This ring should have {2:d} ' \ + 'elements.'.format(self._id, r, + 6*(self._num_rings - 1 - r)) + raise ValueError(msg) + + else: + axial_slice = self._universes + # Check the center ring. + if len(axial_slice[-1]) != 1: + msg = 'HexLattice ID={0:d} has the wrong number of ' \ + 'elements in the innermost ring. Only 1 element is ' \ + 'allowed in the innermost ring.'.format(self._id) + raise ValueError(msg) + + # Check the outer rings. + for r in range(self._num_rings-1): + if len(axial_slice[r]) != 6*(self._num_rings - 1 - r): + msg = 'HexLattice ID={0:d} has the wrong number of ' \ + 'elements in ring number {1:d} (counting from the '\ + 'outermost ring). This ring should have {2:d} ' \ + 'elements.'.format(self._id, r, + 6*(self._num_rings - 1 - r)) + raise ValueError(msg) + + def find_element(self, point): + r"""Determine index of lattice element and local coordinates for a point + + Parameters + ---------- + point : Iterable of float + Cartesian coordinates of point + + Returns + ------- + 3-tuple of int + Indices of corresponding lattice element in :math:`(x,\alpha,z)` + bases + numpy.ndarray + Carestian coordinates of the point in the corresponding lattice + element coordinate system + + """ + # Convert coordinates to skewed bases + x = point[0] - self.center[0] + y = point[1] - self.center[1] + if self._num_axial is None: + iz = 1 + else: + z = point[2] - self.center[2] + iz = floor(z/self.pitch[1] + 0.5*self.num_axial) + alpha = y - x/sqrt(3.) + ix = floor(x/(sqrt(0.75) * self.pitch[0])) + ia = floor(alpha/self.pitch[0]) + + # Check four lattice elements to see which one is closest based on local + # coordinates + d_min = np.inf + for idx in [(ix, ia, iz), (ix + 1, ia, iz), (ix, ia + 1, iz), + (ix + 1, ia + 1, iz)]: + p = self.get_local_coordinates(point, idx) + d = p[0]**2 + p[1]**2 + if d < d_min: + d_min = d + idx_min = idx + p_min = p + + return idx_min, p_min + + def get_local_coordinates(self, point, idx): + r"""Determine local coordinates of a point within a lattice element + + Parameters + ---------- + point : Iterable of float + Cartesian coordinates of point + idx : Iterable of int + Indices of lattice element in :math:`(x,\alpha,z)` bases + + Returns + ------- + 3-tuple of float + Cartesian coordinates of point in the lattice element coordinate + system + + """ + x = point[0] - (self.center[0] + sqrt(0.75)*self.pitch[0]*idx[0]) + y = point[1] - (self.center[1] + (0.5*idx[0] + idx[1])*self.pitch[0]) + if self._num_axial is None: + z = point[2] + else: + z = point[2] - (self.center[2] + (idx[2] + 0.5 - 0.5*self.num_axial)* + self.pitch[1]) + return (x, y, z) + + def get_universe_index(self, idx): + r"""Return index in the universes array corresponding to a lattice element index + + Parameters + ---------- + idx : Iterable of int + Lattice element indices in the :math:`(x,\alpha,z)` coordinate + system + + Returns + ------- + 2- or 3-tuple of int + Indices used when setting the :attr:`HexLattice.universes` property + + """ + + # First we determine which ring the index corresponds to. + x = idx[0] + a = idx[1] + z = -a - x + g = max(abs(x), abs(a), abs(z)) + + # Next we use a clever method to figure out where along the ring we are. + i_ring = self._num_rings - 1 - g + if x >= 0: + if a >= 0: + i_within = x + else: + i_within = 2*g + z + else: + if a <= 0: + i_within = 3*g - x + else: + i_within = 5*g - z + + if self.num_axial is None: + return (i_ring, i_within) + else: + return (idx[2], i_ring, i_within) + + def is_valid_index(self, idx): + r"""Determine whether lattice element index is within defined range + + Parameters + ---------- + idx : Iterable of int + Lattice element indices in the :math:`(x,\alpha,z)` coordinate + system + + Returns + ------- + bool + Whether index is valid + + """ + x = idx[0] + y = idx[1] + z = 0 - y - x + g = max(abs(x), abs(y), abs(z)) + if self.num_axial is None: + return g < self.num_rings + else: + return g < self.num_rings and 0 <= idx[2] < self.num_axial + + def find(self, point): + """Find cells/universes/lattices which contain a given point + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinatesof the point + + Returns + ------- + list + Sequence of universes, cells, and lattices which are traversed to + find the given point + + """ + idx, p = self.find_element(point) + if self.is_valid_index(idx): + idx_u = self.get_universe_index(idx) + if self.num_axial is None: + u = self.universes[idx_u[0]][idx_u[1]] + else: + u = self.universes[idx_u[0]][idx_u[1]][idx_u[2]] + else: + if self.outer is not None: + u = self.outer + else: + return [] + + return [(self, idx)] + u.find(p) + + def create_xml_subelement(self, xml_element): + # Determine if XML element already contains subelement for this Lattice + path = './hex_lattice[@id=\'{0}\']'.format(self._id) + test = xml_element.find(path) + + # If the element does contain the Lattice subelement, then return + if test is not None: + return + + lattice_subelement = ET.Element("hex_lattice") + lattice_subelement.set("id", str(self._id)) + + if len(self._name) > 0: + lattice_subelement.set("name", str(self._name)) + + # Export the Lattice cell pitch + pitch = ET.SubElement(lattice_subelement, "pitch") + pitch.text = ' '.join(map(str, self._pitch)) + + # Export the Lattice outer Universe (if specified) + if self._outer is not None: + outer = ET.SubElement(lattice_subelement, "outer") + outer.text = '{0}'.format(self._outer._id) + self._outer.create_xml_subelement(xml_element) + + lattice_subelement.set("n_rings", str(self._num_rings)) + + if self._num_axial is not None: + lattice_subelement.set("n_axial", str(self._num_axial)) + + # Export Lattice cell center + center = ET.SubElement(lattice_subelement, "center") + center.text = ' '.join(map(str, self._center)) + + # Export the Lattice nested Universe IDs. + + # 3D Lattices + if self._num_axial is not None: + slices = [] + for z in range(self._num_axial): + # Initialize the center universe. + universe = self._universes[z][-1][0] + universe.create_xml_subelement(xml_element) + + # Initialize the remaining universes. + for r in range(self._num_rings-1): + for theta in range(6*(self._num_rings - 1 - r)): + universe = self._universes[z][r][theta] + universe.create_xml_subelement(xml_element) + + # Get a string representation of the universe IDs. + slices.append(self._repr_axial_slice(self._universes[z])) + + # Collapse the list of axial slices into a single string. + universe_ids = '\n'.join(slices) + + # 2D Lattices + else: + # Initialize the center universe. + universe = self._universes[-1][0] + universe.create_xml_subelement(xml_element) + + # Initialize the remaining universes. + for r in range(self._num_rings - 1): + for theta in range(6*(self._num_rings - 1 - r)): + universe = self._universes[r][theta] + universe.create_xml_subelement(xml_element) + + # Get a string representation of the universe IDs. + universe_ids = self._repr_axial_slice(self._universes) + + universes = ET.SubElement(lattice_subelement, "universes") + universes.text = '\n' + universe_ids + + # Append the XML subelement for this Lattice to the XML element + xml_element.append(lattice_subelement) + + def _repr_axial_slice(self, universes): + """Return string representation for the given 2D group of universes. + + The 'universes' argument should be a list of lists of universes where + each sub-list represents a single ring. The first list should be the + outer ring. + """ + + # Find the largest universe ID and count the number of digits so we can + # properly pad the output string later. + largest_id = max([max([univ._id for univ in ring]) + for ring in universes]) + n_digits = len(str(largest_id)) + pad = ' '*n_digits + id_form = '{: ^' + str(n_digits) + 'd}' + + # Initialize the list for each row. + rows = [[] for i in range(1 + 4 * (self._num_rings-1))] + middle = 2 * (self._num_rings - 1) + + # Start with the degenerate first ring. + universe = universes[-1][0] + rows[middle] = [id_form.format(universe._id)] + + # Add universes one ring at a time. + for r in range(1, self._num_rings): + # r_prime increments down while r increments up. + r_prime = self._num_rings - 1 - r + theta = 0 + y = middle + 2*r + + # Climb down the top-right. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].append(id_form.format(universe._id)) + + # Translate the indices. + y -= 1 + theta += 1 + + # Climb down the right. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].append(id_form.format(universe._id)) + + # Translate the indices. + y -= 2 + theta += 1 + + # Climb down the bottom-right. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].append(id_form.format(universe._id)) + + # Translate the indices. + y -= 1 + theta += 1 + + # Climb up the bottom-left. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].insert(0, id_form.format(universe._id)) + + # Translate the indices. + y += 1 + theta += 1 + + # Climb up the left. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].insert(0, id_form.format(universe._id)) + + # Translate the indices. + y += 2 + theta += 1 + + # Climb up the top-left. + for i in range(r): + # Add the universe. + universe = universes[r_prime][theta] + rows[y].insert(0, id_form.format(universe._id)) + + # Translate the indices. + y += 1 + theta += 1 + + # Flip the rows and join each row into a single string. + rows = [pad.join(x) for x in rows[::-1]] + + # Pad the beginning of the rows so they line up properly. + for y in range(self._num_rings - 1): + rows[y] = (self._num_rings - 1 - y)*pad + rows[y] + rows[-1 - y] = (self._num_rings - 1 - y)*pad + rows[-1 - y] + + for y in range(self._num_rings % 2, self._num_rings, 2): + rows[middle + y] = pad + rows[middle + y] + if y != 0: + rows[middle - y] = pad + rows[middle - y] + + # Join the rows together and return the string. + universe_ids = '\n'.join(rows) + return universe_ids + + @staticmethod + def show_indices(num_rings): + """Return a diagram of the hexagonal lattice layout with indices. + + This method can be used to show the proper indices to be used when + setting the :attr:`HexLattice.universes` property. For example, running + this method with num_rings=3 will return the following diagram:: + + (0, 0) + (0,11) (0, 1) + (0,10) (1, 0) (0, 2) + (1, 5) (1, 1) + (0, 9) (2, 0) (0, 3) + (1, 4) (1, 2) + (0, 8) (1, 3) (0, 4) + (0, 7) (0, 5) + (0, 6) + + Parameters + ---------- + num_rings : int + Number of rings in the hexagonal lattice + + Returns + ------- + str + Diagram of the hexagonal lattice showing indices + + """ + + # Find the largest string and count the number of digits so we can + # properly pad the output string later + largest_index = 6*(num_rings - 1) + n_digits_index = len(str(largest_index)) + n_digits_ring = len(str(num_rings - 1)) + str_form = '({{:{}}},{{:{}}})'.format(n_digits_ring, n_digits_index) + pad = ' '*(n_digits_index + n_digits_ring + 3) + + # Initialize the list for each row. + rows = [[] for i in range(1 + 4 * (num_rings-1))] + middle = 2 * (num_rings - 1) + + # Start with the degenerate first ring. + rows[middle] = [str_form.format(num_rings - 1, 0)] + + # Add universes one ring at a time. + for r in range(1, num_rings): + # r_prime increments down while r increments up. + r_prime = num_rings - 1 - r + theta = 0 + y = middle + 2*r + + for i in range(r): + # Climb down the top-right. + rows[y].append(str_form.format(r_prime, theta)) + y -= 1 + theta += 1 + + for i in range(r): + # Climb down the right. + rows[y].append(str_form.format(r_prime, theta)) + y -= 2 + theta += 1 + + for i in range(r): + # Climb down the bottom-right. + rows[y].append(str_form.format(r_prime, theta)) + y -= 1 + theta += 1 + + for i in range(r): + # Climb up the bottom-left. + rows[y].insert(0, str_form.format(r_prime, theta)) + y += 1 + theta += 1 + + for i in range(r): + # Climb up the left. + rows[y].insert(0, str_form.format(r_prime, theta)) + y += 2 + theta += 1 + + for i in range(r): + # Climb up the top-left. + rows[y].insert(0, str_form.format(r_prime, theta)) + y += 1 + theta += 1 + + # Flip the rows and join each row into a single string. + rows = [pad.join(x) for x in rows[::-1]] + + # Pad the beginning of the rows so they line up properly. + for y in range(num_rings - 1): + rows[y] = (num_rings - 1 - y)*pad + rows[y] + rows[-1 - y] = (num_rings - 1 - y)*pad + rows[-1 - y] + + for y in range(num_rings % 2, num_rings, 2): + rows[middle + y] = pad + rows[middle + y] + if y != 0: + rows[middle - y] = pad + rows[middle - y] + + # Join the rows together and return the string. + return '\n'.join(rows) diff --git a/openmc/material.py b/openmc/material.py index e51586205..6b2b07f2d 100644 --- a/openmc/material.py +++ b/openmc/material.py @@ -8,8 +8,9 @@ if sys.version_info[0] >= 3: basestring = str import openmc -from openmc.checkvalue import check_type, check_value, check_greater_than +import openmc.checkvalue as cv from openmc.clean_xml import * +from openmc.data import natural_abundance # A static variable for auto-generated Material IDs @@ -25,9 +26,6 @@ def reset_auto_material_id(): DENSITY_UNITS = ['g/cm3', 'g/cc', 'kg/cm3', 'atom/b-cm', 'atom/cm3', 'sum', 'macro'] -# Constant for density when not needed -NO_DENSITY = 99999. - class Material(object): """A material composed of a collection of nuclides/elements that can be @@ -52,6 +50,14 @@ class Material(object): Units used for `density`. Can be one of 'g/cm3', 'g/cc', 'kg/cm3', 'atom/b-cm', 'atom/cm3', 'sum', or 'macro'. The 'macro' unit only applies in the case of a multi-group calculation. + elements : collections.OrderedDict + Dictionary whose keys are element names and values are 3-tuples + consisting of an :class:`openmc.Element` instance, the percent density, + and the percent type (atom or weight fraction). + nuclides : collections.OrderedDict + Dictionary whose keys are nuclide names and values are 3-tuples + consisting of an :class:`openmc.Nuclide` instance, the percent density, + and the percent type (atom or weight fraction). """ @@ -141,9 +147,9 @@ class Material(object): string += '{0: <16}\n'.format('\tElements') for element in self._elements: - percent = self._nuclides[element][1] - percent_type = self._nuclides[element][2] - string += '{0: >16}'.format('\t{0}'.format(element)) + percent = self._elements[element][1] + percent_type = self._elements[element][2] + string += '{0: <16}'.format('\t{0}'.format(element)) string += '=\t{0: <12} [{1}]\n'.format(percent, percent_type) return string @@ -189,6 +195,14 @@ class Material(object): def density_units(self): return self._density_units + @property + def elements(self): + return self._elements + + @property + def nuclides(self): + return self._nuclides + @property def convert_to_distrib_comps(self): return self._convert_to_distrib_comps @@ -205,45 +219,51 @@ class Material(object): self._id = AUTO_MATERIAL_ID AUTO_MATERIAL_ID += 1 else: - check_type('material ID', material_id, Integral) - check_greater_than('material ID', material_id, 0, equality=True) + cv.check_type('material ID', material_id, Integral) + cv.check_greater_than('material ID', material_id, 0, equality=True) self._id = material_id @name.setter def name(self, name): if name is not None: - check_type('name for Material ID="{0}"'.format(self._id), - name, basestring) + cv.check_type('name for Material ID="{0}"'.format(self._id), + name, basestring) self._name = name else: self._name = '' - def set_density(self, units, density=NO_DENSITY): + def set_density(self, units, density=None): """Set the density of the material Parameters ---------- - units : str - Physical units of density + units : {'g/cm3', 'g/cc', 'km/cm3', 'atom/b-cm', 'atom/cm3', 'sum', 'macro'} + Physical units of density. density : float, optional Value of the density. Must be specified unless units is given as 'sum'. """ - check_type('the density for Material ID="{0}"'.format(self._id), - density, Real) - check_value('density units', units, DENSITY_UNITS) - - if density == NO_DENSITY and units is not 'sum': - msg = 'Unable to set the density Material ID="{0}" ' \ - 'because a density must be set when not using ' \ - 'sum unit'.format(self._id) - raise ValueError(msg) - - self._density = density + cv.check_value('density units', units, DENSITY_UNITS) self._density_units = units + if units is 'sum': + if density is not None: + msg = 'Density "{0}" for Material ID="{1}" is ignored ' \ + 'because the unit is "sum"'.format(density, self.id) + warnings.warn(msg) + else: + if density is None: + msg = 'Unable to set the density for Material ID="{0}" ' \ + 'because a density value must be given when not using ' \ + '"sum" unit'.format(self.id) + raise ValueError(msg) + + cv.check_type('the density for Material ID="{0}"'.format(self.id), + density, Real) + self._density = density + @distrib_otf_file.setter def distrib_otf_file(self, filename): # TODO: remove this when distributed materials are merged @@ -270,11 +290,11 @@ class Material(object): Parameters ---------- - nuclide : str or openmc.nuclide.Nuclide + nuclide : str or openmc.Nuclide Nuclide to add percent : float Atom or weight percent - percent_type : str + percent_type : {'ao', 'wo'} 'ao' for atom percent and 'wo' for weight percent """ @@ -284,7 +304,7 @@ class Material(object): 'macroscopic data-set has already been added'.format(self._id) raise ValueError(msg) - if not isinstance(nuclide, (openmc.Nuclide, str)): + if not isinstance(nuclide, (openmc.Nuclide, basestring)): msg = 'Unable to add a Nuclide to Material ID="{0}" with a ' \ 'non-Nuclide value "{1}"'.format(self._id, nuclide) raise ValueError(msg) @@ -313,7 +333,7 @@ class Material(object): Parameters ---------- - nuclide : openmc.nuclide.Nuclide + nuclide : openmc.Nuclide Nuclide to remove """ @@ -328,11 +348,13 @@ class Material(object): del self._nuclides[nuclide._name] def add_macroscopic(self, macroscopic): - """Add a macroscopic to the material + """Add a macroscopic to the material. This will also set the + density of the material to 1.0, unless it has been otherwise set, + as a default for Macroscopic cross sections. Parameters ---------- - macroscopic : str or Macroscopic + macroscopic : str or openmc.Macroscopic Macroscopic to add """ @@ -366,12 +388,20 @@ class Material(object): 'Material!'.format(self._id, macroscopic) raise ValueError(msg) + # Generally speaking, the density for a macroscopic object will + # be 1.0. Therefore, lets set density to 1.0 so that the user + # doesnt need to set it unless its needed. + # Of course, if the user has already set a value of density, + # then we will not override it. + if self._density is None: + self.set_density('macro', 1.0) + def remove_macroscopic(self, macroscopic): """Remove a macroscopic from the material Parameters ---------- - macroscopic : Macroscopic + macroscopic : openmc.Macroscopic Macroscopic to remove """ @@ -385,17 +415,21 @@ class Material(object): if macroscopic._name == self._macroscopic.name: self._macroscopic = None - def add_element(self, element, percent, percent_type='ao'): + def add_element(self, element, percent, percent_type='ao', expand=False): """Add a natural element to the material Parameters ---------- - element : openmc.element.Element + element : openmc.Element or str Element to add percent : float Atom or weight percent - percent_type : str - 'ao' for atom percent and 'wo' for weight percent + percent_type : {'ao', 'wo'}, optional + 'ao' for atom percent and 'wo' for weight percent. Defaults to atom + percent. + expand : bool, optional + Whether to expand the natural element into its naturally-occurring + isotopes. Defaults to False. """ @@ -404,7 +438,7 @@ class Material(object): 'macroscopic data-set has already been added'.format(self._id) raise ValueError(msg) - if not isinstance(element, openmc.Element): + if not isinstance(element, (openmc.Element, basestring)): msg = 'Unable to add an Element to Material ID="{0}" with a ' \ 'non-Element value "{1}"'.format(self._id, element) raise ValueError(msg) @@ -420,16 +454,27 @@ class Material(object): raise ValueError(msg) # Copy this Element to separate it from same Element in other Materials - element = deepcopy(element) + if isinstance(element, openmc.Element): + element = deepcopy(element) + else: + element = openmc.Element(element) - self._elements[element._name] = (element, percent, percent_type) + if expand: + if percent_type == 'wo': + raise NotImplementedError('Expanding natural element based on ' + 'weight percent is not yet supported.') + for isotope, abundance in element.expand(): + self._nuclides[isotope.name] = ( + isotope, percent*abundance, percent_type) + else: + self._elements[element.name] = (element, percent, percent_type) def remove_element(self, element): """Remove a natural element from the material Parameters ---------- - element : openmc.element.Element + element : openmc.Element Element to remove """ @@ -471,7 +516,7 @@ class Material(object): for nuclide_name in self._nuclides: self._nuclides[nuclide_name][0].scattering = 'iso-in-lab' for element_name in self._elements: - self._element[element_name][0].scattering = 'iso-in-lab' + self._elements[element_name][0].scattering = 'iso-in-lab' def get_all_nuclides(self): """Returns all nuclides in the material @@ -491,6 +536,14 @@ class Material(object): density = nuclide_tuple[1] nuclides[nuclide._name] = (nuclide, density) + for element_name, element_tuple in self._elements.items(): + element = element_tuple[0] + density = element_tuple[1] + + # Expand natural element into isotopes + for isotope, abundance in element.expand(): + nuclides[isotope.name] = (isotope, density*abundance) + return nuclides def _get_nuclide_xml(self, nuclide, distrib=False): @@ -498,7 +551,7 @@ class Material(object): xml_element.set("name", nuclide[0]._name) if not distrib: - if nuclide[2] is 'ao': + if nuclide[2] == 'ao': xml_element.set("ao", str(nuclide[1])) else: xml_element.set("wo", str(nuclide[1])) @@ -525,11 +578,14 @@ class Material(object): xml_element.set("name", str(element[0]._name)) if not distrib: - if element[2] is 'ao': + if element[2] == 'ao': xml_element.set("ao", str(element[1])) else: xml_element.set("wo", str(element[1])) + if element[0].xs is not None: + xml_element.set("xs", element[0].xs) + if not element[0].scattering is None: xml_element.set("scattering", element[0].scattering) @@ -639,9 +695,25 @@ class Material(object): return element -class MaterialsFile(object): - """Materials file used for an OpenMC simulation. Corresponds directly to the - materials.xml input file. +class Materials(cv.CheckedList): + """Collection of Materials used for an OpenMC simulation. + + This class corresponds directly to the materials.xml input file. It can be + thought of as a normal Python list where each member is a + :class:`Material`. It behaves like a list as the following example + demonstrates: + + >>> fuel = openmc.Material() + >>> clad = openmc.Material() + >>> water = openmc.Material() + >>> m = openmc.Materials([fuel]) + >>> m.append(water) + >>> m += [clad] + + Parameters + ---------- + materials : Iterable of openmc.Material + Materials to add to the collection Attributes ---------- @@ -651,11 +723,12 @@ class MaterialsFile(object): """ - def __init__(self): - # Initialize MaterialsFile class attributes - self._materials = [] + def __init__(self, materials=None): + super(Materials, self).__init__(Material, 'materials collection') self._default_xs = None self._materials_file = ET.Element("materials") + if materials is not None: + self += materials @property def default_xs(self): @@ -663,72 +736,95 @@ class MaterialsFile(object): @default_xs.setter def default_xs(self, xs): - check_type('default xs', xs, basestring) + cv.check_type('default xs', xs, basestring) self._default_xs = xs def add_material(self, material): - """Add a material to the file. + """Append material to collection + + .. deprecated:: 0.8 + Use :meth:`Materials.append` instead. Parameters ---------- - material : Material + material : openmc.Material Material to add """ - - if not isinstance(material, Material): - msg = 'Unable to add a non-Material "{0}" to the ' \ - 'MaterialsFile'.format(material) - raise ValueError(msg) - - self._materials.append(material) + warnings.warn("Materials.add_material(...) has been deprecated and may be " + "removed in a future version. Use Material.append(...) " + "instead.", DeprecationWarning) + self.append(material) def add_materials(self, materials): - """Add multiple materials to the file. + """Add multiple materials to the collection + + .. deprecated:: 0.8 + Use compound assignment instead. Parameters ---------- - materials : tuple or list of Material + materials : Iterable of openmc.Material Materials to add """ - - if not isinstance(materials, Iterable): - msg = 'Unable to create OpenMC materials.xml file from "{0}" which ' \ - 'is not iterable'.format(materials) - raise ValueError(msg) - + warnings.warn("Materials.add_materials(...) has been deprecated and may be " + "removed in a future version. Use compound assignment " + "instead.", DeprecationWarning) for material in materials: - self.add_material(material) + self.append(material) + + def append(self, material): + """Append material to collection + + Parameters + ---------- + material : openmc.Material + Material to append + + """ + super(Materials, self).append(material) + + def insert(self, index, material): + """Insert material before index + + Parameters + ---------- + index : int + Index in list + material : openmc.Material + Material to insert + + """ + super(Materials, self).insert(index, material) def remove_material(self, material): """Remove a material from the file + .. deprecated:: 0.8 + Use :meth:`Materials.remove` instead. + Parameters ---------- - material : Material + material : openmc.Material Material to remove """ - - if not isinstance(material, Material): - msg = 'Unable to remove a non-Material "{0}" from the ' \ - 'MaterialsFile'.format(material) - raise ValueError(msg) - - self._materials.remove(material) + warnings.warn("Materials.remove_material(...) has been deprecated and " + "may be removed in a future version. Use " + "Materials.remove(...) instead.", DeprecationWarning) + self.remove(material) def make_isotropic_in_lab(self): - for material in self._materials: + for material in self: material.make_isotropic_in_lab() def _create_material_subelements(self): - subelement = ET.SubElement(self._materials_file, "default_xs") - if self._default_xs is not None: + subelement = ET.SubElement(self._materials_file, "default_xs") subelement.text = self._default_xs - for material in self._materials: + for material in self: xml_element = material.get_material_xml() self._materials_file.append(xml_element) diff --git a/openmc/mgxs/groups.py b/openmc/mgxs/groups.py index a1e03c337..068977d88 100644 --- a/openmc/mgxs/groups.py +++ b/openmc/mgxs/groups.py @@ -24,7 +24,7 @@ class EnergyGroups(object): ---------- group_edges : Iterable of Real The energy group boundaries [MeV] - num_groups : Integral + num_groups : int The number of energy groups """ @@ -86,7 +86,7 @@ class EnergyGroups(object): Parameters ---------- - energy : Real + energy : float The energy of interest in MeV Returns @@ -115,7 +115,7 @@ class EnergyGroups(object): Parameters ---------- - group : Integral + group : int The energy group index, starting at 1 for the highest energies Returns @@ -153,7 +153,7 @@ class EnergyGroups(object): Returns ------- - ndarray + numpy.ndarray The ndarray array indices for each energy group of interest Raises @@ -200,7 +200,7 @@ class EnergyGroups(object): Returns ------- - EnergyGroups + openmc.mgxs.EnergyGroups A coarsened version of this EnergyGroups object. Raises @@ -244,7 +244,7 @@ class EnergyGroups(object): Parameters ---------- - other : EnergyGroups + other : openmc.mgxs.EnergyGroups EnergyGroups to compare with Returns @@ -275,12 +275,12 @@ class EnergyGroups(object): Parameters ---------- - other : EnergyGroups + other : openmc.mgxs.EnergyGroups EnergyGroups to merge with Returns ------- - merged_groups : EnergyGroups + merged_groups : openmc.mgxs.EnergyGroups EnergyGroups resulting from the merge """ diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py index a38e42d24..e0e14b862 100644 --- a/openmc/mgxs/library.py +++ b/openmc/mgxs/library.py @@ -2,8 +2,12 @@ import sys import os import copy import pickle +import warnings from numbers import Integral from collections import OrderedDict +from warnings import warn + +import numpy as np import openmc import openmc.mgxs @@ -30,7 +34,7 @@ class Library(object): Parameters ---------- openmc_geometry : openmc.Geometry - An geometry which has been initialized with a root universe + A geometry which has been initialized with a root universe by_nuclide : bool If true, computes cross sections for each nuclide in each domain mgxs_types : Iterable of str @@ -53,22 +57,24 @@ class Library(object): The types of cross sections in the library (e.g., ['total', 'scatter']) domain_type : {'material', 'cell', 'distribcell', 'universe'} Domain type for spatial homogenization - domains : Iterable of Material, Cell or Universe + domains : Iterable of openmc.Material, openmc.Cell or openmc.Universe The spatial domain(s) for which MGXS in the Library are computed - correction : 'P0' or None + correction : {'P0', None} Apply the P0 correction to scattering matrices if set to 'P0' - energy_groups : EnergyGroups + legendre_order : int + The highest legendre moment in the scattering matrices (default is 0) + energy_groups : openmc.mgxs.EnergyGroups Energy group structure for energy condensation - tally_trigger : Trigger + tally_trigger : openmc.Trigger An (optional) tally precision trigger given to each tally used to compute the cross section - all_mgxs : OrderedDict + all_mgxs : collections.OrderedDict MGXS objects keyed by domain ID and cross section type sp_filename : str The filename of the statepoint with tally data used to the compute cross sections keff : Real or None - The combined keff from the statepoint file with tally data used to + The combined keff from the statepoint file with tally data used to compute cross sections (for eigenvalue calculations only) name : str, optional Name of the multi-group cross section library. Used as a label to @@ -89,8 +95,9 @@ class Library(object): self._mgxs_types = [] self._domain_type = None self._domains = 'all' - self._correction = 'P0' self._energy_groups = None + self._correction = 'P0' + self._legendre_order = 0 self._tally_trigger = None self._all_mgxs = OrderedDict() self._sp_filename = None @@ -118,6 +125,7 @@ class Library(object): clone._domain_type = self.domain_type clone._domains = copy.deepcopy(self.domains) clone._correction = self.correction + clone._legendre_order = self.legendre_order clone._energy_groups = copy.deepcopy(self.energy_groups, memo) clone._tally_trigger = copy.deepcopy(self.tally_trigger, memo) clone._all_mgxs = copy.deepcopy(self.all_mgxs) @@ -185,13 +193,17 @@ class Library(object): else: return self._domains + @property + def energy_groups(self): + return self._energy_groups + @property def correction(self): return self._correction @property - def energy_groups(self): - return self._energy_groups + def legendre_order(self): + return self._legendre_order @property def tally_trigger(self): @@ -245,7 +257,7 @@ class Library(object): @domain_type.setter def domain_type(self, domain_type): - cv.check_value('domain type', domain_type, tuple(openmc.mgxs.DOMAIN_TYPES)) + cv.check_value('domain type', domain_type, openmc.mgxs.DOMAIN_TYPES) self._domain_type = domain_type @domains.setter @@ -280,16 +292,36 @@ class Library(object): self._domains = domains - @correction.setter - def correction(self, correction): - cv.check_value('correction', correction, ('P0', None)) - self._correction = correction - @energy_groups.setter def energy_groups(self, energy_groups): cv.check_type('energy groups', energy_groups, openmc.mgxs.EnergyGroups) self._energy_groups = energy_groups + @correction.setter + def correction(self, correction): + cv.check_value('correction', correction, ('P0', None)) + + if correction == 'P0' and self.legendre_order > 0: + msg = 'The P0 correction will be ignored since the scattering ' \ + 'order {} is greater than zero'.format(self.legendre_order) + warnings.warn(msg) + + self._correction = correction + + @legendre_order.setter + def legendre_order(self, legendre_order): + cv.check_type('legendre_order', legendre_order, Integral) + cv.check_greater_than('legendre_order', legendre_order, 0, equality=True) + cv.check_less_than('legendre_order', legendre_order, 10, equality=True) + + if self.correction == 'P0' and legendre_order > 0: + msg = 'The P0 correction will be ignored since the scattering ' \ + 'order {} is greater than zero'.format(self.legendre_order) + warnings.warn(msg, RuntimeWarning) + self.correction = None + + self._legendre_order = legendre_order + @tally_trigger.setter def tally_trigger(self, tally_trigger): cv.check_type('tally trigger', tally_trigger, openmc.Trigger) @@ -308,7 +340,7 @@ class Library(object): """ cv.check_type('sparse', sparse, bool) - + # Sparsify or densify each MGXS in the Library for domain in self.domains: for mgxs_type in self.mgxs_types: @@ -344,33 +376,34 @@ class Library(object): # Specify whether to use a transport ('P0') correction if isinstance(mgxs, openmc.mgxs.ScatterMatrixXS): mgxs.correction = self.correction + mgxs.legendre_order = self.legendre_order self.all_mgxs[domain.id][mgxs_type] = mgxs def add_to_tallies_file(self, tallies_file, merge=True): """Add all tallies from all MGXS objects to a tallies file. - NOTE: This assumes that build_library() has been called + NOTE: This assumes that :meth:`Library.build_library` has been called Parameters ---------- - tallies_file : openmc.TalliesFile - A TalliesFile object to add each MGXS' tallies to generate a - "tallies.xml" input file for OpenMC + tallies_file : openmc.Tallies + A Tallies collection to add each MGXS' tallies to generate a + 'tallies.xml' input file for OpenMC merge : bool Indicate whether tallies should be merged when possible. Defaults to True. """ - cv.check_type('tallies_file', tallies_file, openmc.TalliesFile) + cv.check_type('tallies_file', tallies_file, openmc.Tallies) # Add tallies from each MGXS for each domain and mgxs type for domain in self.domains: for mgxs_type in self.mgxs_types: mgxs = self.get_mgxs(domain, mgxs_type) for tally_id, tally in mgxs.tallies.items(): - tallies_file.add_tally(tally, merge=merge) + tallies_file.append(tally, merge=merge) def load_from_statepoint(self, statepoint): """Extracts tallies in an OpenMC StatePoint with the data needed to @@ -403,6 +436,7 @@ class Library(object): self._sp_filename = statepoint._f.filename self._openmc_geometry = statepoint.summary.openmc_geometry + self._nuclides = statepoint.summary.nuclides if statepoint.run_mode == 'k-eigenvalue': self._keff = statepoint.k_combined[0] @@ -426,7 +460,7 @@ class Library(object): ---------- domain : Material or Cell or Universe or Integral The material, cell, or universe object of interest (or its ID) - mgxs_type : {'total', 'transport', 'absorption', 'capture', 'fission', 'nu-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'chi'} + mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi'} The type of multi-group cross section object to return Returns @@ -450,14 +484,14 @@ class Library(object): cv.check_type('domain', domain, (openmc.Universe, Integral)) # Check that requested domain is included in library - if cv._isinstance(domain, Integral): + if isinstance(domain, Integral): domain_id = domain for domain in self.domains: if domain_id == domain.id: break else: - msg = 'Unable to find MGXS for {0} "{1}" in ' \ - 'library'.format(self.domain_type, domain) + msg = 'Unable to find MGXS for "{0}" "{1}" in ' \ + 'library'.format(self.domain_type, domain_id) raise ValueError(msg) else: domain_id = domain.id @@ -537,7 +571,7 @@ class Library(object): Returns ------- - Library + openmc.mgxs.Library A new multi-group cross section library averaged across subdomains Raises @@ -575,7 +609,8 @@ class Library(object): return subdomain_avg_library def build_hdf5_store(self, filename='mgxs.h5', directory='mgxs', - subdomains='all', nuclides='all', xs_type='macro'): + subdomains='all', nuclides='all', xs_type='macro', + row_column='inout'): """Export the multi-group cross section library to an HDF5 binary file. This method constructs an HDF5 file which stores the library's @@ -605,6 +640,10 @@ class Library(object): xs_type: {'macro', 'micro'} Store the macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. + row_column: {'inout', 'outin'} + Store scattering matrices indexed first by incoming group and + second by outgoing group ('inout'), or vice versa ('outin'). + Defaults to 'inout'. Raises ------ @@ -635,7 +674,7 @@ class Library(object): full_filename = os.path.join(directory, filename) full_filename = full_filename.replace(' ', '-') f = h5py.File(full_filename, 'w') - f.attrs["# groups"] = self.num_groups + f.attrs['# groups'] = self.num_groups f.close() # Export MGXS for each domain and mgxs type to an HDF5 file @@ -646,8 +685,8 @@ class Library(object): if subdomains == 'avg': mgxs = mgxs.get_subdomain_avg_xs() - mgxs.build_hdf5_store(filename, directory, - xs_type=xs_type, nuclides=nuclides) + mgxs.build_hdf5_store(filename, directory, xs_type=xs_type, + nuclides=nuclides, row_column=row_column) def dump_to_file(self, filename='mgxs', directory='mgxs'): """Store this Library object in a pickle binary file. @@ -712,3 +751,419 @@ class Library(object): # Load and return pickled Library object return pickle.load(open(full_filename, 'rb')) + + def get_xsdata(self, domain, xsdata_name, nuclide='total', xs_type='macro', + xs_id='1m', order=None): + """Generates an openmc.XSdata object describing a multi-group cross section + data set for eventual combination in to an openmc.MGXSLibrary object + (i.e., the library). + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + xsdata_name : str + Name to apply to the "xsdata" entry produced by this method + nuclide : str + A nuclide name string (e.g., 'U-235'). Defaults to 'total' to + obtain a material-wise macroscopic cross section. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. If the Library object is not tallied by + nuclide this will be set to 'macro' regardless. + xs_ids : str + Cross section set identifier. Defaults to '1m'. + order : Scattering order for this data entry. Default is None, + which will set the XSdata object to use the order of the + Library. + + Returns + ------- + xsdata : openmc.XSdata + Multi-Group Cross Section data set object. + + Raises + ------ + ValueError + When the Library object is initialized with insufficient types of + cross sections for the Library. + + See also + -------- + Library.create_mg_library() + + """ + + cv.check_type('domain', domain, (openmc.Material, openmc.Cell, + openmc.Cell)) + cv.check_type('xsdata_name', xsdata_name, basestring) + cv.check_type('nuclide', nuclide, basestring) + cv.check_value('xs_type', xs_type, ['macro', 'micro']) + cv.check_type('xs_id', xs_id, basestring) + cv.check_type('order', order, (type(None), Integral)) + if order is not None: + cv.check_greater_than('order', order, 0, equality=True) + cv.check_less_than('order', order, 10, equality=True) + + # Make sure statepoint has been loaded + if self._sp_filename is None: + msg = 'A StatePoint must be loaded before calling ' \ + 'the create_mg_library() function' + raise ValueError(msg) + + # If gathering material-specific data, set the xs_type to macro + if not self.by_nuclide: + xs_type = 'macro' + + # Build & add metadata to XSdata object + name = xsdata_name + if nuclide is not 'total': + name += '_' + nuclide + name += '.' + xs_id + xsdata = openmc.XSdata(name, self.energy_groups) + + if order is None: + # Set the order to the Library's order (the defualt behavior) + xsdata.order = self.legendre_order + else: + # Set the order of the xsdata object to the minimum of + # the provided order or the Library's order. + xsdata.order = min(order, self.legendre_order) + + if nuclide is not 'total': + xsdata.zaid = self._nuclides[nuclide][0] + xsdata.awr = self._nuclides[nuclide][1] + + # Now get xs data itself + if 'nu-transport' in self.mgxs_types and self.correction == 'P0': + mymgxs = self.get_mgxs(domain, 'nu-transport') + xsdata.set_total_mgxs(mymgxs, xs_type=xs_type, nuclide=[nuclide]) + elif 'total' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'total') + xsdata.set_total_mgxs(mymgxs, xs_type=xs_type, nuclide=[nuclide]) + if 'absorption' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'absorption') + xsdata.set_absorption_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + if 'fission' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'fission') + xsdata.set_fission_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + if 'kappa-fission' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'kappa-fission') + xsdata.set_kappa_fission_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + # For chi and nu-fission we can either have only a nu-fission matrix + # provided, or vectors of chi and nu-fission provided + if 'nu-fission matrix' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'nu-fission matrix') + xsdata.set_nu_fission_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + else: + if 'chi' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'chi') + xsdata.set_chi_mgxs(mymgxs, xs_type=xs_type, nuclide=[nuclide]) + if 'nu-fission' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'nu-fission') + xsdata.set_nu_fission_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + # If multiplicity matrix is available, prefer that + if 'multiplicity matrix' in self.mgxs_types: + mymgxs = self.get_mgxs(domain, 'multiplicity matrix') + xsdata.set_multiplicity_mgxs(mymgxs, xs_type=xs_type, + nuclide=[nuclide]) + using_multiplicity = True + # multiplicity wil fall back to using scatter and nu-scatter + elif ((('scatter matrix' in self.mgxs_types) and + ('nu-scatter matrix' in self.mgxs_types))): + scatt_mgxs = self.get_mgxs(domain, 'scatter matrix') + nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix') + xsdata.set_multiplicity_mgxs(nuscatt_mgxs, scatt_mgxs, + xs_type=xs_type, nuclide=[nuclide]) + using_multiplicity = True + else: + using_multiplicity = False + + if using_multiplicity: + nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix') + xsdata.set_scatter_mgxs(nuscatt_mgxs, xs_type=xs_type, + nuclide=[nuclide]) + else: + if 'nu-scatter matrix' in self.mgxs_types: + nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix') + xsdata.set_scatter_mgxs(nuscatt_mgxs, xs_type=xs_type, + nuclide=[nuclide]) + + # Since we are not using multiplicity, then + # scattering multiplication (nu-scatter) must be + # accounted for approximately by using an adjusted + # absorption cross section. + if 'total' in self.mgxs_types: + xsdata._absorption = \ + np.subtract(xsdata.total, + np.sum(xsdata.scatter[0, :, :], axis=1)) + + return xsdata + + def create_mg_library(self, xs_type='macro', xsdata_names=None, + xs_ids=None): + """Creates an openmc.MGXSLibrary object to contain the MGXS data for the + Multi-Group mode of OpenMC. + + Parameters + ---------- + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. If the Library object is not tallied by + nuclide this will be set to 'macro' regardless. + xsdata_names : Iterable of str + List of names to apply to the "xsdata" entries in the + resultant mgxs data file. Defaults to 'set1', 'set2', ... + xs_ids : str or Iterable of str + Cross section set identifier (i.e., '71c') for all + data sets (if only str) or for each individual one + (if iterable of str). Defaults to '1m'. + + Returns + ------- + mgxs_file : openmc.MGXSLibrary + Multi-Group Cross Section File that is ready to be printed to the + file of choice by the user. + + Raises + ------ + ValueError + When the Library object is initialized with insufficient types of + cross sections for the Library. + + See also + -------- + Library.dump_to_file() + Library.create_mg_mode() + + """ + + # Check to ensure the Library contains the correct + # multi-group cross section types + self.check_library_for_openmc_mgxs() + + cv.check_value('xs_type', xs_type, ['macro', 'micro']) + if xsdata_names is not None: + cv.check_iterable_type('xsdata_names', xsdata_names, basestring) + if xs_ids is not None: + if isinstance(xs_ids, basestring): + # If we only have a string lets convert it now to a list + # of strings. + xs_ids = [xs_ids for i in range(len(self.domains))] + else: + cv.check_iterable_type('xs_ids', xs_ids, basestring) + else: + xs_ids = ['1m' for i in range(len(self.domains))] + + # If gathering material-specific data, set the xs_type to macro + if not self.by_nuclide: + xs_type = 'macro' + + # Initialize file + mgxs_file = openmc.MGXSLibrary(self.energy_groups) + + # Create the xsdata object and add it to the mgxs_file + for i, domain in enumerate(self.domains): + if self.by_nuclide: + nuclides = list(domain.get_all_nuclides().keys()) + else: + nuclides = ['total'] + for nuclide in nuclides: + # Build & add metadata to XSdata object + if xsdata_names is None: + xsdata_name = 'set' + str(i + 1) + else: + xsdata_name = xsdata_names[i] + if nuclide is not 'total': + xsdata_name += '_' + nuclide + + xsdata = self.get_xsdata(domain, xsdata_name, nuclide=nuclide, + xs_type=xs_type, xs_id=xs_ids[i]) + + mgxs_file.add_xsdata(xsdata) + + return mgxs_file + + def create_mg_mode(self, xsdata_names=None, xs_ids=None): + """Creates an openmc.MGXSLibrary object to contain the MGXS data for the + Multi-Group mode of OpenMC as well as the associated openmc.Materials + and openmc.Geometry objects. The created Geometry is the same as that + used to generate the MGXS data, with the only differences being + modifications to point to newly-created Materials which point to the + multi-group data. This method only creates a macroscopic + MGXS Library even if nuclidic tallies are specified in the Library. + + Parameters + ---------- + xsdata_names : Iterable of str + List of names to apply to the "xsdata" entries in the + resultant mgxs data file. Defaults to 'set1', 'set2', ... + xs_ids : str or Iterable of str + Cross section set identifier (i.e., '71c') for all + data sets (if only str) or for each individual one + (if iterable of str). Defaults to '1m'. + + Returns + ------- + mgxs_file : openmc.MGXSLibrary + Multi-Group Cross Section File that is ready to be printed to the + file of choice by the user. + materials : openmc.Materials + Materials file ready to be printed with all the macroscopic data + present within this Library. + geometry : openmc.Geometry + Materials file ready to be printed with all the macroscopic data + present within this Library. + + Raises + ------ + ValueError + When the Library object is initialized with insufficient types of + cross sections for the Library. + + See also + -------- + Library.create_mg_library() + Library.dump_to_file() + + """ + + # Check to ensure the Library contains the correct + # multi-group cross section types + self.check_library_for_openmc_mgxs() + + if xsdata_names is not None: + cv.check_iterable_type('xsdata_names', xsdata_names, basestring) + if xs_ids is not None: + if isinstance(xs_ids, basestring): + # If we only have a string lets convert it now to a list + # of strings. + xs_ids = [xs_ids for i in range(len(self.domains))] + else: + cv.check_iterable_type('xs_ids', xs_ids, basestring) + else: + xs_ids = ['1m' for i in range(len(self.domains))] + xs_type = 'macro' + + # Initialize MGXS File + mgxs_file = openmc.MGXSLibrary(self.energy_groups) + + # Create a copy of the Geometry to differentiate for these Macroscopics + geometry = copy.deepcopy(self.openmc_geometry) + materials = openmc.Materials() + + # Get all Cells from the Geometry for differentiation + all_cells = geometry.get_all_material_cells() + + # Create the xsdata object and add it to the mgxs_file + for i, domain in enumerate(self.domains): + + # Build & add metadata to XSdata object + if xsdata_names is None: + xsdata_name = 'set' + str(i + 1) + else: + xsdata_name = xsdata_names[i] + + # Create XSdata and Macroscopic for this domain + xsdata = self.get_xsdata(domain, xsdata_name, nuclide='total', + xs_type=xs_type, xs_id=xs_ids[i]) + mgxs_file.add_xsdata(xsdata) + macroscopic = openmc.Macroscopic(name=xsdata_name, xs=xs_ids[i]) + + # Create Material and add to collection + material = openmc.Material(name=xsdata_name + '.' + xs_ids[i]) + material.add_macroscopic(macroscopic) + materials.append(material) + + # Differentiate Geometry with new Material + if self.domain_type == 'material': + # Fill all appropriate Cells with new Material + for cell in all_cells: + if cell.fill.id == domain.id: + cell.fill = material + + elif self.domain_type == 'cell': + for cell in all_cells: + if cell.id == domain.id: + cell.fill = material + + return mgxs_file, materials, geometry + + def check_library_for_openmc_mgxs(self): + """This routine will check the MGXS Types within a Library + to ensure the MGXS types provided can be used to create + a MGXS Library for OpenMC's Multi-Group mode. + + The rules to check include: + + - Either total or transport should be present. + + - Both can be available if one wants, but we should + use whatever corresponds to Library.correction (if P0: transport) + + - Absorption and total (or transport) are required. + - A nu-fission cross section and chi values are not required as a + fixed source problem could be the target. + - Fission and kappa-fission are not required as they are only + needed to support tallies the user may wish to request. + - A nu-scatter matrix is required. + + - Having a multiplicity matrix is preferred. + - Having both nu-scatter (of any order) and scatter + (at least isotropic) matrices is the second choice. + - If only nu-scatter, need total (not transport), to + be used in adjusting absorption + (i.e., reduced_abs = tot - nuscatt) + + See also + -------- + Library.create_mg_library() + Library.create_mg_mode() + + """ + + error_flag = False + # Ensure absorption is present + if 'absorption' not in self.mgxs_types: + error_flag = True + msg = '"absorption" MGXS type is required but not provided.' + warn(msg) + # Ensure nu-scattering matrix is required + if 'nu-scatter matrix' not in self.mgxs_types: + error_flag = True + msg = '"nu-scatter matrix" MGXS type is required but not provided.' + warn(msg) + else: + # Ok, now see the status of scatter and/or multiplicity + if ((('scatter matrix' not in self.mgxs_types) and + ('multiplicity matrix' not in self.mgxs_types))): + # We dont have data needed for multiplicity matrix, therefore + # we need total, and not transport. + if 'total' not in self.mgxs_types: + error_flag = True + msg = '"total" MGXS type is required if a ' \ + 'scattering matrix is not provided.' + warn(msg) + # Total or transport can be present, but if using + # self.correction=="P0", then we should use transport. + if (((self.correction is "P0") and + ('nu-transport' not in self.mgxs_types))): + error_flag = True + msg = 'A "nu-transport" MGXS type is required since a "P0" ' \ + 'correction is applied, but a "nu-transport" MGXS is ' \ + 'not provided.' + warn(msg) + elif (((self.correction is None) and + ('total' not in self.mgxs_types))): + error_flag = True + msg = '"total" MGXS type is required, but not provided.' + warn(msg) + + if error_flag: + msg = 'Invalid MGXS configuration encountered.' + raise ValueError(msg) diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py index 6be8255f4..088db649f 100644 --- a/openmc/mgxs/mgxs.py +++ b/openmc/mgxs/mgxs.py @@ -2,6 +2,7 @@ from __future__ import division from collections import Iterable, OrderedDict from numbers import Integral +import warnings import os import sys import copy @@ -21,6 +22,7 @@ if sys.version_info[0] >= 3: # Supported cross section types MGXS_TYPES = ['total', 'transport', + 'nu-transport', 'absorption', 'capture', 'fission', @@ -30,6 +32,8 @@ MGXS_TYPES = ['total', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', + 'multiplicity matrix', + 'nu-fission matrix', 'chi'] @@ -42,9 +46,9 @@ DOMAIN_TYPES = ['cell', # Supported domain classes # TODO: Implement Mesh domains -_DOMAINS = [openmc.Cell, - openmc.Universe, - openmc.Material] +_DOMAINS = (openmc.Cell, + openmc.Universe, + openmc.Material) class MGXS(object): @@ -53,24 +57,20 @@ class MGXS(object): This class can be used for both OpenMC input generation and tally data post-processing to compute spatially-homogenized and energy-integrated - multi-group cross sections for deterministic neutronics calculations. + multi-group cross sections for multi-group neutronics calculations. NOTE: Users should instantiate the subclasses of this abstract class. Parameters ---------- - domain : Material or Cell or Universe + domain : openmc.Material or openmc.Cell or openmc.Universe The domain for spatial homogenization domain_type : {'material', 'cell', 'distribcell', 'universe'} The domain type for spatial homogenization - energy_groups : EnergyGroups + energy_groups : openmc.mgxs.EnergyGroups The energy group structure for energy condensation by_nuclide : bool If true, computes cross sections for each nuclide in domain - nuclides : Iterable of basestring - The user-specified nuclides to compute cross sections. If by_nuclide - is True but nuclides are not specified by the user, all nuclides in the - spatial domain will be used. name : str, optional Name of the multi-group cross section. Used as a label to identify tallies in OpenMC 'tallies.xml' file. @@ -87,36 +87,51 @@ class MGXS(object): Domain for spatial homogenization domain_type : {'material', 'cell', 'distribcell', 'universe'} Domain type for spatial homogenization - energy_groups : EnergyGroups + energy_groups : openmc.mgxs.EnergyGroups Energy group structure for energy condensation - tally_trigger : Trigger + tally_trigger : openmc.Trigger An (optional) tally precision trigger given to each tally used to compute the cross section - tallies : OrderedDict + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict OpenMC tallies needed to compute the multi-group cross section - rxn_rate_tally : Tally + rxn_rate_tally : openmc.Tally Derived tally for the reaction rate tally used in the numerator to compute the multi-group cross section. This attribute is None unless the multi-group cross section has been computed. - xs_tally : Tally + xs_tally : openmc.Tally Derived tally for the multi-group cross section. This attribute is None unless the multi-group cross section has been computed. - num_subdomains : Integral + num_subdomains : int The number of subdomains is unity for 'material', 'cell' and 'universe' domain types. When the This is equal to the number of cell instances for 'distribcell' domain types (it is equal to unity prior to loading tally data from a statepoint file). - num_nuclides : Integral + num_nuclides : int The number of nuclides for which the multi-group cross section is being tracked. This is unity if the by_nuclide attribute is False. - nuclides : list of str or 'sum' - A list of nuclide string names (e.g., 'U-238', 'O-16') when by_nuclide - is True and 'sum' when by_nuclide is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. sparse : bool Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data derived : bool Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store """ @@ -138,7 +153,9 @@ class MGXS(object): self._rxn_rate_tally = None self._xs_tally = None self._sparse = False + self._loaded_sp = False self._derived = False + self._hdf5_key = None self.name = name self.by_nuclide = by_nuclide @@ -213,18 +230,74 @@ class MGXS(object): def num_groups(self): return self.energy_groups.num_groups + @property + def scores(self): + return ['flux', self.rxn_type] + + @property + def filters(self): + group_edges = self.energy_groups.group_edges + energy_filter = openmc.Filter('energy', group_edges) + return [[energy_filter]] * len(self.scores) + + @property + def tally_keys(self): + return self.scores + + @property + def estimator(self): + return 'tracklength' + @property def tallies(self): + + # Instantiate tallies if they do not exist + if self._tallies is None: + + # Initialize a collection of Tallies + self._tallies = OrderedDict() + + # Create a domain Filter object + domain_filter = openmc.Filter(self.domain_type, self.domain.id) + + # Create each Tally needed to compute the multi group cross section + tally_metadata = zip(self.scores, self.tally_keys, self.filters) + for score, key, filters in tally_metadata: + self._tallies[key] = openmc.Tally(name=self.name) + self._tallies[key].scores = [score] + self._tallies[key].estimator = self.estimator + self._tallies[key].filters = [domain_filter] + + # If a tally trigger was specified, add it to each tally + if self.tally_trigger: + trigger_clone = copy.deepcopy(self.tally_trigger) + trigger_clone.scores = [score] + self._tallies[key].triggers.append(trigger_clone) + + # Add non-domain specific Filters (e.g., 'energy') to the Tally + for add_filter in filters: + self._tallies[key].filters.append(add_filter) + + # If this is a by-nuclide cross-section, add nuclides to Tally + if self.by_nuclide and score != 'flux': + all_nuclides = self.get_all_nuclides() + for nuclide in all_nuclides: + self._tallies[key].nuclides.append(nuclide) + else: + self._tallies[key].nuclides.append('total') + return self._tallies @property def rxn_rate_tally(self): + if self._rxn_rate_tally is None: + self._rxn_rate_tally = self.tallies[self.rxn_type] + self._rxn_rate_tally.sparse = self.sparse + return self._rxn_rate_tally @property def xs_tally(self): - """Computes multi-group cross section using OpenMC tally arithmetic.""" - if self._xs_tally is None: if self.tallies is None: msg = 'Unable to get xs_tally since tallies have ' \ @@ -259,10 +332,21 @@ class MGXS(object): else: return 'sum' + @property + def loaded_sp(self): + return self._loaded_sp + @property def derived(self): return self._derived + @property + def hdf5_key(self): + if self._hdf5_key is not None: + return self._hdf5_key + else: + return self._rxn_type + @name.setter def name(self, name): cv.check_type('name', name, basestring) @@ -280,12 +364,21 @@ class MGXS(object): @domain.setter def domain(self, domain): - cv.check_type('domain', domain, tuple(_DOMAINS)) + cv.check_type('domain', domain, _DOMAINS) self._domain = domain + # Assign a domain type + if self.domain_type is None: + if isinstance(domain, openmc.Material): + self._domain_type = 'material' + elif isinstance(domain, openmc.Cell): + self._domain_type = 'cell' + elif isinstance(domain, openmc.Universe): + self._domain_type = 'universe' + @domain_type.setter def domain_type(self, domain_type): - cv.check_value('domain type', domain_type, tuple(DOMAIN_TYPES)) + cv.check_value('domain type', domain_type, DOMAIN_TYPES) self._domain_type = domain_type @energy_groups.setter @@ -334,13 +427,13 @@ class MGXS(object): Parameters ---------- - mgxs_type : {'total', 'transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'chi'} + mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi'} The type of multi-group cross section object to return - domain : Material or Cell or Universe + domain : openmc.Material or openmc.Cell or openmc.Universe The domain for spatial homogenization domain_type : {'material', 'cell', 'distribcell', 'universe'} The domain type for spatial homogenization - energy_groups : EnergyGroups + energy_groups : openmc.mgxs.EnergyGroups The energy group structure for energy condensation by_nuclide : bool If true, computes cross sections for each nuclide in domain. @@ -351,7 +444,7 @@ class MGXS(object): Returns ------- - MGXS + openmc.mgxs.MGXS A subclass of the abstract MGXS class for the multi-group cross section type requested by the user @@ -363,6 +456,8 @@ class MGXS(object): mgxs = TotalXS(domain, domain_type, energy_groups) elif mgxs_type == 'transport': mgxs = TransportXS(domain, domain_type, energy_groups) + elif mgxs_type == 'nu-transport': + mgxs = NuTransportXS(domain, domain_type, energy_groups) elif mgxs_type == 'absorption': mgxs = AbsorptionXS(domain, domain_type, energy_groups) elif mgxs_type == 'capture': @@ -381,6 +476,10 @@ class MGXS(object): mgxs = ScatterMatrixXS(domain, domain_type, energy_groups) elif mgxs_type == 'nu-scatter matrix': mgxs = NuScatterMatrixXS(domain, domain_type, energy_groups) + elif mgxs_type == 'multiplicity matrix': + mgxs = MultiplicityMatrixXS(domain, domain_type, energy_groups) + elif mgxs_type == 'nu-fission matrix': + mgxs = NuFissionMatrixXS(domain, domain_type, energy_groups) elif mgxs_type == 'chi': mgxs = Chi(domain, domain_type, energy_groups) @@ -414,7 +513,7 @@ class MGXS(object): # Otherwise, return all nuclides in the spatial domain else: nuclides = self.domain.get_all_nuclides() - return nuclides.keys() + return list(nuclides.keys()) def get_nuclide_density(self, nuclide): """Get the atomic number density in units of atoms/b-cm for a nuclide @@ -427,7 +526,7 @@ class MGXS(object): Returns ------- - Real + float The atomic number density (atom/b-cm) for the nuclide of interest Raises @@ -466,7 +565,7 @@ class MGXS(object): Returns ------- - ndarray of Real + numpy.ndarray of float An array of the atomic number densities (atom/b-cm) for each of the nuclides in the spatial domain @@ -502,63 +601,6 @@ class MGXS(object): return densities - def _create_tallies(self, scores, all_filters, keys, estimator): - """Instantiates tallies needed to compute the multi-group cross section. - - This is a helper method for MGXS subclasses to create tallies - for input file generation. The tallies are stored in the tallies dict. - This method is called by each subclass' tallies property getter - which define the parameters given to this parent class method. - - Parameters - ---------- - scores : Iterable of str - Scores for each tally - all_filters : Iterable of tuple of Filter - Tuples of non-spatial domain filters for each tally - keys : Iterable of str - Key string used to store each tally in the tallies dictionary - estimator : {'analog' or 'tracklength'} - Type of estimator to use for each tally - - """ - - cv.check_iterable_type('scores', scores, basestring) - cv.check_length('scores', scores, len(keys)) - cv.check_iterable_type('filters', all_filters, openmc.Filter, 1, 2) - cv.check_type('keys', keys, Iterable, basestring) - cv.check_value('estimator', estimator, ['analog', 'tracklength']) - - self._tallies = OrderedDict() - - # Create a domain Filter object - domain_filter = openmc.Filter(self.domain_type, self.domain.id) - - # Create each Tally needed to compute the multi group cross section - for score, key, filters in zip(scores, keys, all_filters): - self.tallies[key] = openmc.Tally(name=self.name) - self.tallies[key].add_score(score) - self.tallies[key].estimator = estimator - self.tallies[key].add_filter(domain_filter) - - # If a tally trigger was specified, add it to each tally - if self.tally_trigger: - trigger_clone = copy.deepcopy(self.tally_trigger) - trigger_clone.add_score(score) - self.tallies[key].add_trigger(trigger_clone) - - # Add all non-domain specific Filters (e.g., 'energy') to the Tally - for add_filter in filters: - self.tallies[key].add_filter(add_filter) - - # If this is a by-nuclide cross-section, add all nuclides to Tally - if self.by_nuclide and score != 'flux': - all_nuclides = self.domain.get_all_nuclides() - for nuclide in all_nuclides: - self.tallies[key].add_nuclide(nuclide) - else: - self.tallies[key].add_nuclide('total') - def _compute_xs(self): """Performs generic cleanup after a subclass' uses tally arithmetic to compute a multi-group cross section as a derived tally. @@ -579,7 +621,7 @@ class MGXS(object): self.xs_tally._nuclides = [] nuclides = self.get_all_nuclides() for nuclide in nuclides: - self.xs_tally.add_nuclide(openmc.Nuclide(nuclide)) + self.xs_tally.nuclides.append(openmc.Nuclide(nuclide)) # Remove NaNs which may have resulted from divide-by-zero operations self.xs_tally._mean = np.nan_to_num(self.xs_tally.mean) @@ -640,23 +682,28 @@ class MGXS(object): filter_bins = [] # Clear any tallies previously loaded from a statepoint - self._tallies = None - self._xs_tally = None - self._rxn_rate_tally = None + if self.loaded_sp: + self._tallies = None + self._xs_tally = None + self._rxn_rate_tally = None + self._loaded_sp = False # Find, slice and store Tallies from StatePoint # The tally slicing is needed if tally merging was used for tally_type, tally in self.tallies.items(): - sp_tally = statepoint.get_tally(tally.scores, tally.filters, - tally.nuclides, - estimator=tally.estimator) - sp_tally = sp_tally.get_slice(tally.scores, filters, - filter_bins, tally.nuclides) + sp_tally = statepoint.get_tally( + tally.scores, tally.filters, tally.nuclides, + estimator=tally.estimator, exact_filters=True) + sp_tally = sp_tally.get_slice( + tally.scores, filters, filter_bins, tally.nuclides) sp_tally.sparse = self.sparse self.tallies[tally_type] = sp_tally + self._loaded_sp = True + def get_xs(self, groups='all', subdomains='all', nuclides='all', - xs_type='macro', order_groups='increasing', value='mean'): + xs_type='macro', order_groups='increasing', + value='mean', **kwargs): """Returns an array of multi-group cross sections. This method constructs a 2D NumPy array for the requested multi-group @@ -680,13 +727,12 @@ class MGXS(object): Return the cross section indexed according to increasing or decreasing energy groups (decreasing or increasing energies). Defaults to 'increasing'. - value : str - A string for the type of value to return - 'mean', 'std_dev' or - 'rel_err' are accepted. Defaults to 'mean'. + value : {'mean', 'std_dev', 'rel_err'} + A string for the type of value to return. Defaults to 'mean'. Returns ------- - ndarray + numpy.ndarray A NumPy array of the multi-group cross section indexed in the order each group, subdomain and nuclide is listed in the parameters. @@ -761,10 +807,9 @@ class MGXS(object): # Reverse energies to align with increasing energy groups xs = xs[:, ::-1, :] - # Eliminate trivial dimensions - xs = np.squeeze(xs) - xs = np.atleast_1d(xs) - + # Eliminate trivial dimensions + xs = np.squeeze(xs) + xs = np.atleast_1d(xs) return xs def get_condensed_xs(self, coarse_groups): @@ -858,7 +903,7 @@ class MGXS(object): Returns ------- - MGXS + openmc.mgxs.MGXS A new MGXS averaged across the subdomains of interest Raises @@ -910,15 +955,16 @@ class MGXS(object): nuclides : list of str A list of nuclide name strings (e.g., ['U-235', 'U-238']; default is []) - groups : list of Integral + groups : list of int A list of energy group indices starting at 1 for the high energies (e.g., [1, 2, 3]; default is []) Returns ------- - MGXS - A new tally which encapsulates the subset of data requested for the - nuclide(s) and/or energy group(s) requested in the parameters. + openmc.mgxs.MGXS + A new MGXS object which encapsulates the subset of data requested + for the nuclide(s) and/or energy group(s) requested in the + parameters. """ @@ -976,7 +1022,7 @@ class MGXS(object): Parameters ---------- - other : MGXS + other : openmc.mgxs.MGXS MGXS to check for merging """ @@ -1013,12 +1059,12 @@ class MGXS(object): Parameters ---------- - other : MGXS + other : openmc.mgxs.MGXS MGXS to merge with this one Returns ------- - merged_mgxs : MGXS + merged_mgxs : openmc.mgxs.MGXS Merged MGXS """ @@ -1146,7 +1192,7 @@ class MGXS(object): def build_hdf5_store(self, filename='mgxs.h5', directory='mgxs', subdomains='all', nuclides='all', - xs_type='macro', append=True): + xs_type='macro', row_column='inout', append=True): """Export the multi-group cross section data to an HDF5 binary file. This method constructs an HDF5 file which stores the multi-group @@ -1175,6 +1221,10 @@ class MGXS(object): xs_type: {'macro', 'micro'} Store the macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. + row_column: {'inout', 'outin'} + Store scattering matrices indexed first by incoming group and + second by outgoing group ('inout'), or vice versa ('outin'). + Defaults to 'inout'. append : bool If true, appends to an existing HDF5 file with the same filename directory (if one exists). Defaults to True. @@ -1245,8 +1295,8 @@ class MGXS(object): else: subdomain_group = domain_group - # Create a separate HDF5 group for the rxn type - rxn_group = subdomain_group.require_group(self.rxn_type) + # Create a separate HDF5 group for this cross section + rxn_group = subdomain_group.require_group(self.hdf5_key) # Create a separate HDF5 group for each nuclide for j, nuclide in enumerate(nuclides): @@ -1261,9 +1311,9 @@ class MGXS(object): # Extract the cross section for this subdomain and nuclide average = self.get_xs(subdomains=[subdomain], nuclides=[nuclide], - xs_type=xs_type, value='mean') + xs_type=xs_type, value='mean', row_column=row_column) std_dev = self.get_xs(subdomains=[subdomain], nuclides=[nuclide], - xs_type=xs_type, value='std_dev') + xs_type=xs_type, value='std_dev', row_column=row_column) average = average.squeeze() std_dev = std_dev.squeeze() @@ -1349,10 +1399,10 @@ class MGXS(object): modified.write('\n\\end{document}') def get_pandas_dataframe(self, groups='all', nuclides='all', - xs_type='macro', summary=None): + xs_type='macro', distribcell_paths=True): """Build a Pandas DataFrame for the MGXS data. - This method leverages the Tally.get_pandas_dataframe(...) method, but + This method leverages :meth:`openmc.Tally.get_pandas_dataframe`, but renames the columns with terminology appropriate for cross section data. Parameters @@ -1369,12 +1419,11 @@ class MGXS(object): xs_type: {'macro', 'micro'} Return macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. - summary : None or Summary - An optional Summary object to be used to construct columns for - distribcell tally filters (default is None). The geometric - information in the Summary object is embedded into a multi-index - column with a geometric "path" to each distribcell intance. - NOTE: This option requires the OpenCG Python package. + distribcell_paths : bool, optional + Construct columns for distribcell tally filters (default is True). + The geometric information in the Summary object is embedded into + a Multi-index column with a geometric "path" to each distribcell + instance. Returns ------- @@ -1401,7 +1450,8 @@ class MGXS(object): # Use tally summation to sum across all nuclides query_nuclides = self.get_all_nuclides() xs_tally = self.xs_tally.summation(nuclides=query_nuclides) - df = xs_tally.get_pandas_dataframe(summary=summary) + df = xs_tally.get_pandas_dataframe( + distribcell_paths=distribcell_paths) # Remove nuclide column since it is homogeneous and redundant df.drop('nuclide', axis=1, inplace=True) @@ -1409,17 +1459,16 @@ class MGXS(object): # If the user requested a specific set of nuclides elif self.by_nuclide and nuclides != 'all': xs_tally = self.xs_tally.get_slice(nuclides=nuclides) - df = xs_tally.get_pandas_dataframe(summary=summary) + df = xs_tally.get_pandas_dataframe( + distribcell_paths=distribcell_paths) # If the user requested all nuclides, keep nuclide column in dataframe else: - df = self.xs_tally.get_pandas_dataframe(summary=summary) + df = self.xs_tally.get_pandas_dataframe( + distribcell_paths=distribcell_paths) # Remove the score column since it is homogeneous and redundant - if summary and 'distribcell' in self.domain_type: - df = df.drop('score', level=0, axis=1) - else: - df = df.drop('score', axis=1) + df = df.drop('score', axis=1) # Override energy groups bounds with indices all_groups = np.arange(self.num_groups, 0, -1, dtype=np.int) @@ -1434,7 +1483,8 @@ class MGXS(object): df.rename(columns={'energyout low [MeV]': 'group out'}, inplace=True) - out_groups = np.tile(all_groups, df.shape[0] / all_groups.size) + out_groups = np.repeat(all_groups, self.xs_tally.num_scores) + out_groups = np.tile(out_groups, df.shape[0] / out_groups.size) df['group out'] = out_groups del df['energyout high [MeV]'] columns = ['group in', 'group out'] @@ -1477,510 +1527,117 @@ class MGXS(object): return df -class TotalXS(MGXS): - """A total multi-group cross section.""" +class MatrixMGXS(MGXS): + """An abstract multi-group cross section for some energy group structure + within some spatial domain. This class is specifically intended for + cross sections which depend on both the incoming and outgoing energy groups + and are therefore represented by matrices. Examples of this include the + scattering and nu-fission matrices. - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(TotalXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'total' + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. + NOTE: Users should instantiate the subclasses of this abstract class. - This method constructs two tracklength tallies to compute the 'flux' - and 'total' reaction rates in the spatial domain and energy groups - of interest. + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. - """ + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'total'] - estimator = 'tracklength' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None : - self._rxn_rate_tally = self.tallies['total'] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - - -class TransportXS(MGXS): - """A transport-corrected total multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(TransportXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'transport' - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs three analog tallies to compute the 'flux', - 'total' and 'scatter-P1' reaction rates in the spatial domain and - energy groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'total', 'scatter-P1'] - estimator = 'analog' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - energyout_filter = openmc.Filter('energyout', group_edges) - filters = [[energy_filter], [energy_filter], [energyout_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - scatter_p1 = copy.deepcopy(self.tallies['scatter-P1']) - - # Use tally slicing to remove scatter-P0 data from scatter-P1 tally - self.tallies['scatter-P1'] = \ - scatter_p1.get_slice(scores=['scatter-P1']) - - self.tallies['scatter-P1'].filters[-1].type = 'energy' - self._rxn_rate_tally = \ - self.tallies['total'] - self.tallies['scatter-P1'] - self._rxn_rate_tally.sparse = self.sparse - - return self._rxn_rate_tally - - -class AbsorptionXS(MGXS): - """An absorption multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(AbsorptionXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'absorption' - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs two tracklength tallies to compute the 'flux' - and 'absorption' reaction rates in the spatial domain and energy - groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'absorption'] - estimator = 'tracklength' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - self._rxn_rate_tally = self.tallies['absorption'] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - - -class CaptureXS(MGXS): - """A capture multi-group cross section. - - The neutron capture reaction rate is defined as the difference between - OpenMC's 'absorption' and 'fission' reaction rate score types. This includes - not only radiative capture, but all forms of neutron disappearance aside - from fission (e.g., MT > 100). - - """ - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(CaptureXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'capture' - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs two tracklength tallies to compute the 'flux' - and 'capture' reaction rates in the spatial domain and energy - groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'absorption', 'fission'] - estimator = 'tracklength' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter], [energy_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - self._rxn_rate_tally = \ - self.tallies['absorption'] - self.tallies['fission'] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - -class FissionXSBase(MGXS): - """A fission production multi-group cross section base class - for NuFission and KappaFission """ # This is an abstract class which cannot be instantiated __metaclass__ = abc.ABCMeta - def __init__(self, rxn_type, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(FissionXSBase, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = rxn_type + @property + def filters(self): + # Create the non-domain specific Filters for the Tallies + group_edges = self.energy_groups.group_edges + energy = openmc.Filter('energy', group_edges) + energyout = openmc.Filter('energyout', group_edges) + + return [[energy], [energy, energyout]] @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs two tracklength tallies to compute the 'flux' - and 'rxn_type' reaction rates in the spatial domain and energy - groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', self._rxn_type] - estimator = 'tracklength' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - self._rxn_rate_tally = self.tallies[self._rxn_type] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - - -class FissionXS(FissionXSBase): - """A fission multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(FissionXS, self).__init__('fission', domain, domain_type, - groups, by_nuclide, name) - - -class NuFissionXS(FissionXSBase): - """A fission production multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(NuFissionXS, self).__init__('nu-fission', domain, domain_type, - groups, by_nuclide, name) - -class KappaFissionXS(FissionXSBase): - """A recoverable fission energy production rate multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(KappaFissionXS, self).__init__('kappa-fission', domain, domain_type, - groups, by_nuclide, name) - -class ScatterXS(MGXS): - """A scatter multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(ScatterXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'scatter' - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs two tracklength tallies to compute the 'flux' - and 'scatter' reaction rates in the spatial domain and energy - groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'scatter'] - estimator = 'tracklength' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter]] - - # Intialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - self._rxn_rate_tally = self.tallies['scatter'] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - - -class NuScatterXS(MGXS): - """A nu-scatter multi-group cross section.""" - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(NuScatterXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'nu-scatter' - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs two analog tallies to compute the 'flux' - and 'nu-scatter' reaction rates in the spatial domain and energy - groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['flux', 'nu-scatter'] - estimator = 'analog' - keys = scores - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy_filter = openmc.Filter('energy', group_edges) - filters = [[energy_filter], [energy_filter]] - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - if self._rxn_rate_tally is None: - self._rxn_rate_tally = self.tallies['nu-scatter'] - self._rxn_rate_tally.sparse = self.sparse - return self._rxn_rate_tally - - -class ScatterMatrixXS(MGXS): - """A scattering matrix multi-group cross section. - - Attributes - ---------- - correction : 'P0' or None - Apply the P0 correction to scattering matrices if set to 'P0' - - """ - - def __init__(self, domain=None, domain_type=None, - groups=None, by_nuclide=False, name=''): - super(ScatterMatrixXS, self).__init__(domain, domain_type, - groups, by_nuclide, name) - self._rxn_type = 'scatter matrix' - self._correction = 'P0' - - def __deepcopy__(self, memo): - clone = super(ScatterMatrixXS, self).__deepcopy__(memo) - clone._correction = self.correction - return clone - - @property - def correction(self): - return self._correction - - @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. - - This method constructs three analog tallies to compute the 'flux', - 'scatter' and 'scatter-P1' reaction rates in the spatial domain and - energy groups of interest. - - """ - - # Instantiate tallies if they do not exist - if self._tallies is None: - - group_edges = self.energy_groups.group_edges - energy = openmc.Filter('energy', group_edges) - energyout = openmc.Filter('energyout', group_edges) - - # Create a list of scores for each Tally to be created - if self.correction == 'P0': - scores = ['flux', 'scatter', 'scatter-P1'] - filters = [[energy], [energy, energyout], [energyout]] - else: - scores = ['flux', 'scatter'] - filters = [[energy], [energy, energyout]] - - estimator = 'analog' - keys = scores - - # Initialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies - - @property - def rxn_rate_tally(self): - - if self._rxn_rate_tally is None: - # If using P0 correction subtract scatter-P1 from the diagonal - if self.correction == 'P0': - scatter_p1 = self.tallies['scatter-P1'] - scatter_p1 = scatter_p1.get_slice(scores=['scatter-P1']) - energy_filter = self.tallies['scatter'].find_filter('energy') - energy_filter = copy.deepcopy(energy_filter) - scatter_p1 = scatter_p1.diagonalize_filter(energy_filter) - self._rxn_rate_tally = self.tallies['scatter'] - scatter_p1 - else: - self._rxn_rate_tally = self.tallies['scatter'] - - self._rxn_rate_tally.sparse = self.sparse - - return self._rxn_rate_tally - - @correction.setter - def correction(self, correction): - cv.check_value('correction', correction, ('P0', None)) - self._correction = correction - - def get_slice(self, nuclides=[], in_groups=[], out_groups=[]): - """Build a sliced ScatterMatrix for the specified nuclides and - energy groups. - - This method constructs a new MGXS to encapsulate a subset of the data - represented by this MGXS. The subset of data to include in the tally - slice is determined by the nuclides and energy groups specified in - the input parameters. - - Parameters - ---------- - nuclides : list of str - A list of nuclide name strings - (e.g., ['U-235', 'U-238']; default is []) - in_groups : list of Integral - A list of incoming energy group indices starting at 1 for the high - energies (e.g., [1, 2, 3]; default is []) - out_groups : list of Integral - A list of outgoing energy group indices starting at 1 for the high - energies (e.g., [1, 2, 3]; default is []) - - Returns - ------- - MGXS - A new tally which encapsulates the subset of data requested for the - nuclide(s) and/or energy group(s) requested in the parameters. - - """ - - # Call super class method and null out derived tallies - slice_xs = super(ScatterMatrixXS, self).get_slice(nuclides, in_groups) - slice_xs._rxn_rate_tally = None - slice_xs._xs_tally = None - - # Slice outgoing energy groups if needed - if len(out_groups) != 0: - filter_bins = [] - for group in out_groups: - group_bounds = self.energy_groups.get_group_bounds(group) - filter_bins.append(group_bounds) - filter_bins = [tuple(filter_bins)] - - # Slice each of the tallies across energyout groups - for tally_type, tally in slice_xs.tallies.items(): - if tally.contains_filter('energyout'): - tally_slice = tally.get_slice(filters=['energyout'], - filter_bins=filter_bins) - slice_xs.tallies[tally_type] = tally_slice - - slice_xs.sparse = self.sparse - return slice_xs + def estimator(self): + return 'analog' def get_xs(self, in_groups='all', out_groups='all', - subdomains='all', nuclides='all', xs_type='macro', - order_groups='increasing', value='mean'): + subdomains='all', nuclides='all', + xs_type='macro', order_groups='increasing', + row_column='inout', value='mean', **kwargs): """Returns an array of multi-group cross sections. - This method constructs a 2D NumPy array for the requested scattering - matrix data data for one or more energy groups and subdomains. + This method constructs a 2D NumPy array for the requested multi-group + matrix data for one or more energy groups and subdomains. Parameters ---------- @@ -1992,9 +1649,10 @@ class ScatterMatrixXS(MGXS): Subdomain IDs of interest. Defaults to 'all'. nuclides : Iterable of str or 'all' or 'sum' A list of nuclide name strings (e.g., ['U-235', 'U-238']). The - special string 'all' will return the cross sections for all nuclides - in the spatial domain. The special string 'sum' will return the - cross section summed over all nuclides. Defaults to 'all'. + special string 'all' will return the cross sections for all + nuclides in the spatial domain. The special string 'sum' will + return the cross section summed over all nuclides. Defaults to + 'all'. xs_type: {'macro', 'micro'} Return the macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. @@ -2002,9 +1660,12 @@ class ScatterMatrixXS(MGXS): Return the cross section indexed according to increasing or decreasing energy groups (decreasing or increasing energies). Defaults to 'increasing'. - value : str - A string for the type of value to return - 'mean', 'std_dev', or - 'rel_err' are accepted. Defaults to the empty string. + row_column: {'inout', 'outin'} + Return the cross section indexed first by incoming group and + second by outgoing group ('inout'), or vice versa ('outin'). + Defaults to 'inout'. + value : {'mean', 'std_dev', 'rel_err'} + A string for the type of value to return. Defaults to 'mean'. Returns ------- @@ -2028,7 +1689,8 @@ class ScatterMatrixXS(MGXS): # Construct a collection of the domain filter bins if not isinstance(subdomains, basestring): - cv.check_iterable_type('subdomains', subdomains, Integral, max_depth=2) + cv.check_iterable_type('subdomains', subdomains, Integral, + max_depth=2) for subdomain in subdomains: filters.append(self.domain_type) filter_bins.append((subdomain,)) @@ -2038,14 +1700,16 @@ class ScatterMatrixXS(MGXS): cv.check_iterable_type('groups', in_groups, Integral) for group in in_groups: filters.append('energy') - filter_bins.append((self.energy_groups.get_group_bounds(group),)) + filter_bins.append(( + self.energy_groups.get_group_bounds(group),)) # Construct list of energy group bounds tuples for all requested groups if not isinstance(out_groups, basestring): cv.check_iterable_type('groups', out_groups, Integral) for group in out_groups: filters.append('energyout') - filter_bins.append((self.energy_groups.get_group_bounds(group),)) + filter_bins.append(( + self.energy_groups.get_group_bounds(group),)) # Construct a collection of the nuclides to retrieve from the xs tally if self.by_nuclide: @@ -2059,8 +1723,8 @@ class ScatterMatrixXS(MGXS): # Use tally summation if user requested the sum for all nuclides if nuclides == 'sum' or nuclides == ['sum']: xs_tally = self.xs_tally.summation(nuclides=query_nuclides) - xs = xs_tally.get_values(filters=filters, - filter_bins=filter_bins, value=value) + xs = xs_tally.get_values(filters=filters, filter_bins=filter_bins, + value=value) else: xs = self.xs_tally.get_values(filters=filters, filter_bins=filter_bins, @@ -2090,11 +1754,16 @@ class ScatterMatrixXS(MGXS): num_out_groups = len(out_groups) # Reshape tally data array with separate axes for domain and energy - num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups)) + num_subdomains = int(xs.shape[0] / + (num_in_groups * num_out_groups)) new_shape = (num_subdomains, num_in_groups, num_out_groups) new_shape += xs.shape[1:] xs = np.reshape(xs, new_shape) + # Transpose the matrix if requested by user + if row_column == 'outin': + xs = np.swapaxes(xs, 1, 2) + # Reverse energies to align with increasing energy groups xs = xs[:, ::-1, ::-1, :] @@ -2104,6 +1773,59 @@ class ScatterMatrixXS(MGXS): return xs + def get_slice(self, nuclides=[], in_groups=[], out_groups=[]): + """Build a sliced MatrixMGXS object for the specified nuclides and + energy groups. + + This method constructs a new MGXS to encapsulate a subset of the data + represented by this MGXS. The subset of data to include in the tally + slice is determined by the nuclides and energy groups specified in + the input parameters. + + Parameters + ---------- + nuclides : list of str + A list of nuclide name strings + (e.g., ['U-235', 'U-238']; default is []) + in_groups : list of int + A list of incoming energy group indices starting at 1 for the high + energies (e.g., [1, 2, 3]; default is []) + out_groups : list of int + A list of outgoing energy group indices starting at 1 for the high + energies (e.g., [1, 2, 3]; default is []) + + Returns + ------- + openmc.mgxs.MatrixMGXS + A new MatrixMGXS object which encapsulates the subset of data + requested for the nuclide(s) and/or energy group(s) requested in + the parameters. + + """ + + # Call super class method and null out derived tallies + slice_xs = super(MatrixMGXS, self).get_slice(nuclides, in_groups) + slice_xs._rxn_rate_tally = None + slice_xs._xs_tally = None + + # Slice outgoing energy groups if needed + if len(out_groups) != 0: + filter_bins = [] + for group in out_groups: + group_bounds = self.energy_groups.get_group_bounds(group) + filter_bins.append(group_bounds) + filter_bins = [tuple(filter_bins)] + + # Slice each of the tallies across energyout groups + for tally_type, tally in slice_xs.tallies.items(): + if tally.contains_filter('energyout'): + tally_slice = tally.get_slice(filters=['energyout'], + filter_bins=filter_bins) + slice_xs.tallies[tally_type] = tally_slice + + slice_xs.sparse = self.sparse + return slice_xs + def print_xs(self, subdomains='all', nuclides='all', xs_type='macro'): """Prints a string representation for the multi-group cross section. @@ -2116,8 +1838,9 @@ class ScatterMatrixXS(MGXS): The nuclides of the cross-sections to include in the report. This may be a list of nuclide name strings (e.g., ['U-235', 'U-238']). The special string 'all' will report the cross sections for all - nuclides in the spatial domain. The special string 'sum' will report - the cross sections summed over all nuclides. Defaults to 'all'. + nuclides in the spatial domain. The special string 'sum' will + report the cross sections summed over all nuclides. Defaults to + 'all'. xs_type: {'macro', 'micro'} Return the macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. @@ -2160,7 +1883,7 @@ class ScatterMatrixXS(MGXS): template = '{0: <12}Group {1} [{2: <10} - {3: <10}MeV]\n' # Loop over energy groups ranges - for group in range(1, self.num_groups+1): + for group in range(1, self.num_groups + 1): bounds = self.energy_groups.get_group_bounds(group) string += template.format('', group, bounds[0], bounds[1]) @@ -2187,8 +1910,8 @@ class ScatterMatrixXS(MGXS): template = '{0: <12}Group {1} -> Group {2}:\t\t' # Loop over incoming/outgoing energy groups ranges - for in_group in range(1, self.num_groups+1): - for out_group in range(1, self.num_groups+1): + for in_group in range(1, self.num_groups + 1): + for out_group in range(1, self.num_groups + 1): string += template.format('', in_group, out_group) average = \ self.get_xs([in_group], [out_group], @@ -2200,7 +1923,1853 @@ class ScatterMatrixXS(MGXS): xs_type=xs_type, value='rel_err') average = average.flatten()[0] rel_err = rel_err.flatten()[0] * 100. - string += '{:1.2e} +/- {:1.2e}%'.format(average, rel_err) + string += '{:1.2e} +/- {:1.2e}%'.format(average, + rel_err) + string += '\n' + string += '\n' + string += '\n' + string += '\n' + + print(string) + + +class TotalXS(MGXS): + r"""A total multi-group cross section. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group total cross sections for multi-group neutronics calculations. At + a minimum, one needs to set the :attr:`TotalXS.energy_groups` and + :attr:`TotalXS.domain` properties. Tallies for the flux and appropriate + reaction rates over the specified domain are generated automatically via the + :attr:`TotalXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`TotalXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + total cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \sigma_t (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`TotalXS.tally_keys` property and values + are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(TotalXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'total' + + +class TransportXS(MGXS): + r"""A transport-corrected total multi-group cross section. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`TransportXS.energy_groups` and + :attr:`TransportXS.domain` properties. Tallies for the flux and appropriate + reaction rates over the specified domain are generated automatically via the + :attr:`TransportXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`TransportXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + transport-corrected total cross section is calculated as: + + .. math:: + + \langle \sigma_t \phi \rangle &= \int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \sigma_t (r, E) \psi + (r, E, \Omega) \\ + \langle \sigma_{s1} \phi \rangle &= \int_{r \in V} dr + \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \int_{4\pi} + d\Omega' \int_0^\infty dE' \int_{-1}^1 d\mu \; \mu \sigma_s + (r, E' \rightarrow E, \Omega' \cdot \Omega) + \phi (r, E', \Omega) \\ + \langle \phi \rangle &= \int_{r \in V} dr \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega) \\ + \sigma_{tr} &= \frac{\langle \sigma_t \phi \rangle - \langle \sigma_{s1} + \phi \rangle}{\langle \phi \rangle} + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`TransportXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(TransportXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'transport' + + @property + def scores(self): + return ['flux', 'total', 'scatter-1'] + + @property + def filters(self): + group_edges = self.energy_groups.group_edges + energy_filter = openmc.Filter('energy', group_edges) + energyout_filter = openmc.Filter('energyout', group_edges) + return [[energy_filter], [energy_filter], [energyout_filter]] + + @property + def estimator(self): + return 'analog' + + @property + def rxn_rate_tally(self): + if self._rxn_rate_tally is None: + self.tallies['scatter-1'].filters[-1].type = 'energy' + self._rxn_rate_tally = \ + self.tallies['total'] - self.tallies['scatter-1'] + self._rxn_rate_tally.sparse = self.sparse + + return self._rxn_rate_tally + + +class NuTransportXS(TransportXS): + r"""A transport-corrected total multi-group cross section which + accounts for neutron multiplicity in scattering reactions. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`NuTransportXS.energy_groups` and + :attr:`NuTransportXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`NuTransportXS.tallies` property, which can then + be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`NuTransportXS.xs_tally` property. + + The calculation of the transport-corrected cross section is the same as that + for :class:`TransportXS` except that the scattering multiplicity is + accounted for. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`NuTransportXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(NuTransportXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'nu-transport' + + @property + def scores(self): + return ['flux', 'total', 'nu-scatter-1'] + + @property + def tally_keys(self): + return ['flux', 'total', 'scatter-1'] + + +class AbsorptionXS(MGXS): + r"""An absorption multi-group cross section. + + Absorption is defined as all reactions that do not produce secondary + neutrons (disappearance) plus fission reactions. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group absorption cross sections for multi-group neutronics + calculations. At a minimum, one needs to set the + :attr:`AbsorptionXS.energy_groups` and :attr:`AbsorptionXS.domain` + properties. Tallies for the flux and appropriate reaction rates over the + specified domain are generated automatically via the + :attr:`AbsorptionXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`AbsorptionXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + absorption cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \sigma_a (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`AbsorptionXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(AbsorptionXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'absorption' + + +class CaptureXS(MGXS): + r"""A capture multi-group cross section. + + The neutron capture reaction rate is defined as the difference between + OpenMC's 'absorption' and 'fission' reaction rate score types. This includes + not only radiative capture, but all forms of neutron disappearance aside + from fission (i.e., MT > 100). + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group capture cross sections for multi-group neutronics + calculations. At a minimum, one needs to set the + :attr:`CaptureXS.energy_groups` and :attr:`CaptureXS.domain` + properties. Tallies for the flux and appropriate reaction rates over the + specified domain are generated automatically via the + :attr:`CaptureXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`CaptureXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + capture cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \left [ \sigma_a (r, E) \psi (r, E, \Omega) - \sigma_f (r, E) \psi (r, E, + \Omega) \right ]}{\int_{r \in V} dr \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`CaptureXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(CaptureXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'capture' + + @property + def scores(self): + return ['flux', 'absorption', 'fission'] + + @property + def rxn_rate_tally(self): + if self._rxn_rate_tally is None: + self._rxn_rate_tally = \ + self.tallies['absorption'] - self.tallies['fission'] + self._rxn_rate_tally.sparse = self.sparse + return self._rxn_rate_tally + + +class FissionXS(MGXS): + r"""A fission multi-group cross section. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group fission cross sections for multi-group neutronics + calculations. At a minimum, one needs to set the + :attr:`FissionXS.energy_groups` and :attr:`FissionXS.domain` + properties. Tallies for the flux and appropriate reaction rates over the + specified domain are generated automatically via the + :attr:`FissionXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`FissionXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + fission cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \sigma_f (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`FissionXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(FissionXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'fission' + + +class NuFissionXS(MGXS): + r"""A fission neutron production multi-group cross section. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group fission neutron production cross sections for multi-group + neutronics calculations. At a minimum, one needs to set the + :attr:`NuFissionXS.energy_groups` and :attr:`NuFissionXS.domain` + properties. Tallies for the flux and appropriate reaction rates over the + specified domain are generated automatically via the + :attr:`NuFissionXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`NuFissionXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + fission neutron production cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \nu\sigma_f (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`NuFissionXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(NuFissionXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'nu-fission' + + +class KappaFissionXS(MGXS): + r"""A recoverable fission energy production rate multi-group cross section. + + The recoverable energy per fission, :math:`\kappa`, is defined as the + fission product kinetic energy, prompt and delayed neutron kinetic energies, + prompt and delayed :math:`\gamma`-ray total energies, and the total energy + released by the delayed :math:`\beta` particles. The neutrino energy does + not contribute to this response. The prompt and delayed :math:`\gamma`-rays + are assumed to deposit their energy locally. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`KappaFissionXS.energy_groups` and + :attr:`KappaFissionXS.domain` properties. Tallies for the flux and appropriate + reaction rates over the specified domain are generated automatically via the + :attr:`KappaFissionXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`KappaFissionXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + recoverable fission energy production rate cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \kappa\sigma_f (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`KappaFissionXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(KappaFissionXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'kappa-fission' + + +class ScatterXS(MGXS): + r"""A scattering multi-group cross section. + + The scattering cross section is defined as the difference between the total + and absorption cross sections. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`ScatterXS.energy_groups` and + :attr:`ScatterXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`ScatterXS.tallies` property, which can + then be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`ScatterXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + scattering cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \left [ \sigma_t (r, E) \psi (r, E, \Omega) - \sigma_a (r, E) \psi (r, E, + \Omega) \right ]}{\int_{r \in V} dr \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`ScatterXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(ScatterXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'scatter' + + +class NuScatterXS(MGXS): + r"""A scattering neutron production multi-group cross section. + + The neutron production from scattering is defined as the average number of + neutrons produced from all neutron-producing reactions except for fission. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`NuScatterXS.energy_groups` and + :attr:`NuScatterXS.domain` properties. Tallies for the flux and appropriate + reaction rates over the specified domain are generated automatically via the + :attr:`NuScatterXS.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`NuScatterXS.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + scattering neutron production cross section is calculated as: + + .. math:: + + \frac{\int_{r \in V} dr \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; + \sum_i \upsilon_i \sigma_i (r, E) \psi (r, E, \Omega)}{\int_{r \in V} dr + \int_{4\pi} d\Omega \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega)}. + + where :math:`\upsilon_i` is the multiplicity of the :math:`i`-th scattering + reaction. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`NuScatterXS.tally_keys` property and + values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(NuScatterXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'nu-scatter' + + @property + def estimator(self): + return 'analog' + + +class ScatterMatrixXS(MatrixMGXS): + r"""A scattering matrix multi-group cross section for one or more Legendre + moments. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`ScatterMatrixXS.energy_groups` and + :attr:`ScatterMatrixXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`ScatterMatrixXS.tallies` property, which can + then be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`ScatterMatrixXS.xs_tally` property. + + For a spatial domain :math:`V`, incoming energy group + :math:`[E_{g'},E_{g'-1}]`, and outgoing energy group :math:`[E_g,E_{g-1}]`, + the scattering moments are calculated as: + + .. math:: + + \langle \sigma_{s,\ell,g'\rightarrow g} \phi \rangle &= \int_{r \in V} dr + \int_{4\pi} d\Omega' \int_{E_{g'}}^{E_{g'-1}} dE' \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; P_\ell (\Omega \cdot \Omega') \sigma_s (r, E' + \rightarrow E, \Omega' \cdot \Omega) \psi(r, E', \Omega')\\ + \langle \phi \rangle &= \int_{r \in V} dr \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega) \\ + \sigma_{s,\ell,g'\rightarrow g} &= \frac{\langle + \sigma_{s,\ell,g'\rightarrow g} \phi \rangle}{\langle \phi \rangle} + + If the order is zero and a :math:`P_0` transport-correction is applied + (default), the scattering matrix elements are: + + .. math:: + + \sigma_{s,g'\rightarrow g} = \frac{\langle \sigma_{s,0,g'\rightarrow g} + \phi \rangle - \delta_{gg'} \sum_{g''} \langle \sigma_{s,1,g''\rightarrow + g} \phi \rangle}{\langle \phi \rangle} + + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + correction : 'P0' or None + Apply the P0 correction to scattering matrices if set to 'P0' + legendre_order : int + The highest Legendre moment in the scattering matrix (default is 0) + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`ScatterMatrixXS.tally_keys` property + and values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(ScatterMatrixXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'scatter' + self._correction = 'P0' + self._legendre_order = 0 + self._hdf5_key = 'scatter matrix' + + def __deepcopy__(self, memo): + clone = super(ScatterMatrixXS, self).__deepcopy__(memo) + clone._correction = self.correction + clone._legendre_order = self.legendre_order + return clone + + @property + def correction(self): + return self._correction + + @property + def legendre_order(self): + return self._legendre_order + + @property + def scores(self): + scores = ['flux'] + + if self.correction == 'P0' and self.legendre_order == 0: + scores += ['{}-0'.format(self.rxn_type), + '{}-1'.format(self.rxn_type)] + else: + scores += ['{}-P{}'.format(self.rxn_type, self.legendre_order)] + + return scores + + @property + def filters(self): + group_edges = self.energy_groups.group_edges + energy = openmc.Filter('energy', group_edges) + energyout = openmc.Filter('energyout', group_edges) + + if self.correction == 'P0' and self.legendre_order == 0: + filters = [[energy], [energy, energyout], [energyout]] + else: + filters = [[energy], [energy, energyout]] + + return filters + + @property + def rxn_rate_tally(self): + + if self._rxn_rate_tally is None: + + # If using P0 correction subtract scatter-1 from the diagonal + if self.correction == 'P0' and self.legendre_order == 0: + scatter_p0 = self.tallies['{}-0'.format(self.rxn_type)] + scatter_p1 = self.tallies['{}-1'.format(self.rxn_type)] + energy_filter = scatter_p0.find_filter('energy') + energy_filter = copy.deepcopy(energy_filter) + scatter_p1 = scatter_p1.diagonalize_filter(energy_filter) + self._rxn_rate_tally = scatter_p0 - scatter_p1 + + # Extract scattering moment reaction rate Tally + else: + tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order) + self._rxn_rate_tally = self.tallies[tally_key] + + self._rxn_rate_tally.sparse = self.sparse + + return self._rxn_rate_tally + + @correction.setter + def correction(self, correction): + cv.check_value('correction', correction, ('P0', None)) + + if correction == 'P0' and self.legendre_order > 0: + msg = 'The P0 correction will be ignored since the scattering ' \ + 'order {} is greater than zero'.format(self.legendre_order) + warnings.warn(msg) + + self._correction = correction + + @legendre_order.setter + def legendre_order(self, legendre_order): + cv.check_type('legendre_order', legendre_order, Integral) + cv.check_greater_than('legendre_order', legendre_order, 0, equality=True) + cv.check_less_than('legendre_order', legendre_order, 10, equality=True) + + if self.correction == 'P0' and legendre_order > 0: + msg = 'The P0 correction will be ignored since the scattering ' \ + 'order {} is greater than zero'.format(self.legendre_order) + warnings.warn(msg, RuntimeWarning) + self.correction = None + + self._legendre_order = legendre_order + + def load_from_statepoint(self, statepoint): + """Extracts tallies in an OpenMC StatePoint with the data needed to + compute multi-group cross sections. + + This method is needed to compute cross section data from tallies + in an OpenMC StatePoint object. + + NOTE: The statepoint must first be linked with an OpenMC Summary object. + + Parameters + ---------- + statepoint : openmc.StatePoint + An OpenMC StatePoint object with tally data + + Raises + ------ + ValueError + When this method is called with a statepoint that has not been + linked with a summary object. + + """ + + # Clear any tallies previously loaded from a statepoint + if self.loaded_sp: + self._tallies = None + self._xs_tally = None + self._rxn_rate_tally = None + self._loaded_sp = False + + # Expand scores to match the format in the statepoint + # e.g., "scatter-P2" -> "scatter-0", "scatter-1", "scatter-2" + if self.correction != 'P0' or self.legendre_order != 0: + tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order) + self.tallies[tally_key].scores = \ + [self.rxn_type + '-{}'.format(i) for i in range(self.legendre_order+1)] + + super(ScatterMatrixXS, self).load_from_statepoint(statepoint) + + def get_slice(self, nuclides=[], in_groups=[], out_groups=[], + legendre_order='same'): + """Build a sliced ScatterMatrix for the specified nuclides and + energy groups. + + This method constructs a new MGXS to encapsulate a subset of the data + represented by this MGXS. The subset of data to include in the tally + slice is determined by the nuclides and energy groups specified in + the input parameters. + + Parameters + ---------- + nuclides : list of str + A list of nuclide name strings + (e.g., ['U-235', 'U-238']; default is []) + in_groups : list of int + A list of incoming energy group indices starting at 1 for the high + energies (e.g., [1, 2, 3]; default is []) + out_groups : list of int + A list of outgoing energy group indices starting at 1 for the high + energies (e.g., [1, 2, 3]; default is []) + legendre_order : int or 'same' + The highest Legendre moment in the sliced MGXS. If order is 'same' + then the sliced MGXS will have the same Legendre moments as the + original MGXS (default). If order is an integer less than the + original MGXS' order, then only those Legendre moments up to that + order will be included in the sliced MGXS. + + Returns + ------- + openmc.mgxs.MatrixMGXS + A new MatrixMGXS which encapsulates the subset of data requested + for the nuclide(s) and/or energy group(s) requested in the + parameters. + + """ + + # Call super class method and null out derived tallies + slice_xs = super(ScatterMatrixXS, self).get_slice(nuclides, in_groups) + slice_xs._rxn_rate_tally = None + slice_xs._xs_tally = None + + # Slice the Legendre order if needed + if legendre_order != 'same': + cv.check_type('legendre_order', legendre_order, Integral) + cv.check_less_than('legendre_order', legendre_order, + self.legendre_order, equality=True) + slice_xs.legendre_order = legendre_order + + # Slice the scattering tally + tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order) + expand_scores = \ + [self.rxn_type + '-{}'.format(i) for i in range(self.legendre_order+1)] + slice_xs.tallies[tally_key] = \ + slice_xs.tallies[tally_key].get_slice(scores=expand_scores) + + # Slice outgoing energy groups if needed + if len(out_groups) != 0: + filter_bins = [] + for group in out_groups: + group_bounds = self.energy_groups.get_group_bounds(group) + filter_bins.append(group_bounds) + filter_bins = [tuple(filter_bins)] + + # Slice each of the tallies across energyout groups + for tally_type, tally in slice_xs.tallies.items(): + if tally.contains_filter('energyout'): + tally_slice = tally.get_slice(filters=['energyout'], + filter_bins=filter_bins) + slice_xs.tallies[tally_type] = tally_slice + + slice_xs.sparse = self.sparse + return slice_xs + + def get_xs(self, in_groups='all', out_groups='all', + subdomains='all', nuclides='all', moment='all', + xs_type='macro', order_groups='increasing', + row_column='inout', value='mean', **kwargs): + r"""Returns an array of multi-group cross sections. + + This method constructs a 2D NumPy array for the requested scattering + matrix data data for one or more energy groups and subdomains. + + NOTE: The scattering moments are not multiplied by the :math:`(2l+1)/2` + prefactor in the expansion of the scattering source into Legendre + moments in the neutron transport equation. + + Parameters + ---------- + in_groups : Iterable of Integral or 'all' + Incoming energy groups of interest. Defaults to 'all'. + out_groups : Iterable of Integral or 'all' + Outgoing energy groups of interest. Defaults to 'all'. + subdomains : Iterable of Integral or 'all' + Subdomain IDs of interest. Defaults to 'all'. + nuclides : Iterable of str or 'all' or 'sum' + A list of nuclide name strings (e.g., ['U-235', 'U-238']). The + special string 'all' will return the cross sections for all nuclides + in the spatial domain. The special string 'sum' will return the + cross section summed over all nuclides. Defaults to 'all'. + moment : int or 'all' + The scattering matrix moment to return. All moments will be + returned if the moment is 'all' (default); otherwise, a specific + moment will be returned. + xs_type: {'macro', 'micro'} + Return the macro or micro cross section in units of cm^-1 or barns. + Defaults to 'macro'. + order_groups: {'increasing', 'decreasing'} + Return the cross section indexed according to increasing or + decreasing energy groups (decreasing or increasing energies). + Defaults to 'increasing'. + row_column: {'inout', 'outin'} + Return the cross section indexed first by incoming group and + second by outgoing group ('inout'), or vice versa ('outin'). + Defaults to 'inout'. + value : {'mean', 'std_dev', 'rel_err'} + A string for the type of value to return. Defaults to 'mean'. + + Returns + ------- + ndarray + A NumPy array of the multi-group cross section indexed in the order + each group and subdomain is listed in the parameters. + + Raises + ------ + ValueError + When this method is called before the multi-group cross section is + computed from tally data. + + """ + + cv.check_value('value', value, ['mean', 'std_dev', 'rel_err']) + cv.check_value('xs_type', xs_type, ['macro', 'micro']) + + filters = [] + filter_bins = [] + + # Construct a collection of the domain filter bins + if not isinstance(subdomains, basestring): + cv.check_iterable_type('subdomains', subdomains, Integral, max_depth=2) + for subdomain in subdomains: + filters.append(self.domain_type) + filter_bins.append((subdomain,)) + + # Construct list of energy group bounds tuples for all requested groups + if not isinstance(in_groups, basestring): + cv.check_iterable_type('groups', in_groups, Integral) + for group in in_groups: + filters.append('energy') + filter_bins.append((self.energy_groups.get_group_bounds(group),)) + + # Construct list of energy group bounds tuples for all requested groups + if not isinstance(out_groups, basestring): + cv.check_iterable_type('groups', out_groups, Integral) + for group in out_groups: + filters.append('energyout') + filter_bins.append((self.energy_groups.get_group_bounds(group),)) + + # Construct CrossScore for requested scattering moment + if moment != 'all': + cv.check_type('moment', moment, Integral) + cv.check_greater_than('moment', moment, 0, equality=True) + cv.check_less_than( + 'moment', moment, self.legendre_order, equality=True) + scores = [self.xs_tally.scores[moment]] + else: + scores = [] + + # Construct a collection of the nuclides to retrieve from the xs tally + if self.by_nuclide: + if nuclides == 'all' or nuclides == 'sum' or nuclides == ['sum']: + query_nuclides = self.get_all_nuclides() + else: + query_nuclides = nuclides + else: + query_nuclides = ['total'] + + # Use tally summation if user requested the sum for all nuclides + if nuclides == 'sum' or nuclides == ['sum']: + xs_tally = self.xs_tally.summation(nuclides=query_nuclides) + xs = xs_tally.get_values(scores=scores, filters=filters, + filter_bins=filter_bins, value=value) + else: + xs = self.xs_tally.get_values(scores=scores, filters=filters, + filter_bins=filter_bins, + nuclides=query_nuclides, value=value) + + xs = np.nan_to_num(xs) + + # Divide by atom number densities for microscopic cross sections + if xs_type == 'micro': + if self.by_nuclide: + densities = self.get_nuclide_densities(nuclides) + else: + densities = self.get_nuclide_densities('sum') + if value == 'mean' or value == 'std_dev': + xs /= densities[np.newaxis, :, np.newaxis] + + # Reverse data if user requested increasing energy groups since + # tally data is stored in order of increasing energies + if order_groups == 'increasing': + if in_groups == 'all': + num_in_groups = self.num_groups + else: + num_in_groups = len(in_groups) + if out_groups == 'all': + num_out_groups = self.num_groups + else: + num_out_groups = len(out_groups) + + # Reshape tally data array with separate axes for domain and energy + num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups)) + new_shape = (num_subdomains, num_in_groups, num_out_groups) + new_shape += xs.shape[1:] + xs = np.reshape(xs, new_shape) + + # Transpose the scattering matrix if requested by user + if row_column == 'outin': + xs = np.swapaxes(xs, 1, 2) + + # Reverse energies to align with increasing energy groups + xs = xs[:, ::-1, ::-1, :] + + # Eliminate trivial dimensions + xs = np.squeeze(xs) + xs = np.atleast_2d(xs) + + return xs + + def get_pandas_dataframe(self, groups='all', nuclides='all', moment='all', + xs_type='macro', distribcell_paths=True): + """Build a Pandas DataFrame for the MGXS data. + + This method leverages :meth:`openmc.Tally.get_pandas_dataframe`, but + renames the columns with terminology appropriate for cross section data. + + Parameters + ---------- + groups : Iterable of Integral or 'all' + Energy groups of interest. Defaults to 'all'. + nuclides : Iterable of str or 'all' or 'sum' + The nuclides of the cross-sections to include in the dataframe. This + may be a list of nuclide name strings (e.g., ['U-235', 'U-238']). + The special string 'all' will include the cross sections for all + nuclides in the spatial domain. The special string 'sum' will + include the cross sections summed over all nuclides. Defaults + to 'all'. + moment : int or 'all' + The scattering matrix moment to return. All moments will be + returned if the moment is 'all' (default); otherwise, a specific + moment will be returned. + xs_type: {'macro', 'micro'} + Return macro or micro cross section in units of cm^-1 or barns. + Defaults to 'macro'. + distribcell_paths : bool, optional + Construct columns for distribcell tally filters (default is True). + The geometric information in the Summary object is embedded into a + Multi-index column with a geometric "path" to each distribcell + instance. + + Returns + ------- + pandas.DataFrame + A Pandas DataFrame for the cross section data. + + Raises + ------ + ValueError + When this method is called before the multi-group cross section is + computed from tally data. + + """ + + df = super(ScatterMatrixXS, self).get_pandas_dataframe( + groups, nuclides, xs_type, distribcell_paths) + + # Add a moment column to dataframe + if self.legendre_order > 0: + # Insert a column corresponding to the Legendre moments + moments = ['P{}'.format(i) for i in range(self.legendre_order+1)] + moments = np.tile(moments, df.shape[0] / len(moments)) + df['moment'] = moments + + # Place the moment column before the mean column + mean_index = df.columns.get_loc('mean') + columns = df.columns.tolist() + df = df[columns[:mean_index] + ['moment'] + columns[mean_index:-1]] + + # Select rows corresponding to requested scattering moment + if moment != 'all': + cv.check_type('moment', moment, Integral) + cv.check_greater_than('moment', moment, 0, equality=True) + cv.check_less_than( + 'moment', moment, self.legendre_order, equality=True) + df = df[df['moment'] == 'P{}'.format(moment)] + + return df + + def print_xs(self, subdomains='all', nuclides='all', + xs_type='macro', moment=0): + """Prints a string representation for the multi-group cross section. + + Parameters + ---------- + subdomains : Iterable of Integral or 'all' + The subdomain IDs of the cross sections to include in the report. + Defaults to 'all'. + nuclides : Iterable of str or 'all' or 'sum' + The nuclides of the cross-sections to include in the report. This + may be a list of nuclide name strings (e.g., ['U-235', 'U-238']). + The special string 'all' will report the cross sections for all + nuclides in the spatial domain. The special string 'sum' will report + the cross sections summed over all nuclides. Defaults to 'all'. + xs_type: {'macro', 'micro'} + Return the macro or micro cross section in units of cm^-1 or barns. + Defaults to 'macro'. + moment : int + The scattering moment to print (default is 0) + + """ + + # Construct a collection of the subdomains to report + if not isinstance(subdomains, basestring): + cv.check_iterable_type('subdomains', subdomains, Integral) + elif self.domain_type == 'distribcell': + subdomains = np.arange(self.num_subdomains, dtype=np.int) + else: + subdomains = [self.domain.id] + + # Construct a collection of the nuclides to report + if self.by_nuclide: + if nuclides == 'all': + nuclides = self.get_all_nuclides() + if nuclides == 'sum': + nuclides = ['sum'] + else: + cv.check_iterable_type('nuclides', nuclides, basestring) + else: + nuclides = ['sum'] + + cv.check_value('xs_type', xs_type, ['macro', 'micro']) + + if self.correction != 'P0': + rxn_type = '{0} (P{1})'.format(self.rxn_type, moment) + else: + rxn_type = self.rxn_type + + # Build header for string with type and domain info + string = 'Multi-Group XS\n' + string += '{0: <16}=\t{1}\n'.format('\tReaction Type', rxn_type) + string += '{0: <16}=\t{1}\n'.format('\tDomain Type', self.domain_type) + string += '{0: <16}=\t{1}\n'.format('\tDomain ID', self.domain.id) + + # If cross section data has not been computed, only print string header + if self.tallies is None: + print(string) + return + + string += '{0: <16}\n'.format('\tEnergy Groups:') + template = '{0: <12}Group {1} [{2: <10} - {3: <10}MeV]\n' + + # Loop over energy groups ranges + for group in range(1, self.num_groups + 1): + bounds = self.energy_groups.get_group_bounds(group) + string += template.format('', group, bounds[0], bounds[1]) + + # Loop over all subdomains + for subdomain in subdomains: + + if self.domain_type == 'distribcell': + string += \ + '{0: <16}=\t{1}\n'.format('\tSubdomain', subdomain) + + # Loop over all Nuclides + for nuclide in nuclides: + + # Build header for nuclide type + if xs_type != 'sum': + string += '{0: <16}=\t{1}\n'.format('\tNuclide', nuclide) + + # Build header for cross section type + if xs_type == 'macro': + string += '{0: <16}\n'.format('\tCross Sections [cm^-1]:') + else: + string += '{0: <16}\n'.format('\tCross Sections [barns]:') + + template = '{0: <12}Group {1} -> Group {2}:\t\t' + + # Loop over incoming/outgoing energy groups ranges + for in_group in range(1, self.num_groups + 1): + for out_group in range(1, self.num_groups + 1): + string += template.format('', in_group, out_group) + average = \ + self.get_xs([in_group], [out_group], + [subdomain], [nuclide], moment=moment, + xs_type=xs_type, value='mean') + rel_err = \ + self.get_xs([in_group], [out_group], + [subdomain], [nuclide], moment=moment, + xs_type=xs_type, value='rel_err') + average = average.flatten()[0] + rel_err = rel_err.flatten()[0] * 100. + string += '{:1.2e} +/- {:1.2e}%'.format(average, + rel_err) string += '\n' string += '\n' string += '\n' @@ -2210,51 +3779,490 @@ class ScatterMatrixXS(MGXS): class NuScatterMatrixXS(ScatterMatrixXS): - """A scattering production matrix multi-group cross section.""" + """A scattering production matrix multi-group cross section for one or + more Legendre moments. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`NuScatterMatrixXS.energy_groups` and + :attr:`NuScatterMatrixXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`NuScatterMatrixXS.tallies` property, which can + then be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`NuScatterMatrixXS.xs_tally` property. + + The calculation of the scattering-production matrix is the same as that for + :class:`ScatterMatrixXS` except that the scattering multiplicity is + accounted for. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + correction : 'P0' or None + Apply the P0 correction to scattering matrices if set to 'P0' + legendre_order : int + The highest legendre moment in the scattering matrix (default is 0) + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`NuScatterMatrixXS.tally_keys` property + and values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ def __init__(self, domain=None, domain_type=None, groups=None, by_nuclide=False, name=''): super(NuScatterMatrixXS, self).__init__(domain, domain_type, groups, by_nuclide, name) - self._rxn_type = 'nu-scatter matrix' + self._rxn_type = 'nu-scatter' + self._hdf5_key = 'nu-scatter matrix' + + +class MultiplicityMatrixXS(MatrixMGXS): + r"""The scattering multiplicity matrix. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`MultiplicityMatrixXS.energy_groups` and + :attr:`MultiplicityMatrixXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`MultiplicityMatrixXS.tallies` property, which + can then be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`MultiplicityMatrixXS.xs_tally` + property. + + For a spatial domain :math:`V`, incoming energy group + :math:`[E_{g'},E_{g'-1}]`, and outgoing energy group :math:`[E_g,E_{g-1}]`, + the multiplicity is calculated as: + + .. math:: + + \langle \upsilon \sigma_{s,g'\rightarrow g} \phi \rangle &= \int_{r \in + D} dr \int_{4\pi} d\Omega' \int_{E_{g'}}^{E_{g'-1}} dE' \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \sum_i \upsilon_i \sigma_i (r, E' \rightarrow + E, \Omega' \cdot \Omega) \psi(r, E', \Omega') \\ + \langle \sigma_{s,g'\rightarrow g} \phi \rangle &= \int_{r \in + D} dr \int_{4\pi} d\Omega' \int_{E_{g'}}^{E_{g'-1}} dE' \int_{4\pi} + d\Omega \int_{E_g}^{E_{g-1}} dE \; \sum_i \upsilon_i \sigma_i (r, E' \rightarrow + E, \Omega' \cdot \Omega) \psi(r, E', \Omega') \\ + \upsilon_{g'\rightarrow g} &= \frac{\langle \upsilon + \sigma_{s,g'\rightarrow g} \rangle}{\langle \sigma_{s,g'\rightarrow g} + \rangle} + + where :math:`\upsilon_i` is the multiplicity for the :math:`i`-th reaction. + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`MultiplicityMatrixXS.tally_keys` + property and values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(MultiplicityMatrixXS, self).__init__(domain, domain_type, groups, + by_nuclide, name) + self._rxn_type = 'multiplicity matrix' @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. + def scores(self): + scores = ['nu-scatter', 'scatter'] + return scores - This method constructs three analog tallies to compute the 'flux', - 'nu-scatter' and 'scatter-P1' reaction rates in the spatial domain and - energy groups of interest. + @property + def filters(self): + # Create the non-domain specific Filters for the Tallies + group_edges = self.energy_groups.group_edges + energy = openmc.Filter('energy', group_edges) + energyout = openmc.Filter('energyout', group_edges) - """ + return [[energy, energyout], [energy, energyout]] - # Instantiate tallies if they do not exist - if self._tallies is None: + @property + def rxn_rate_tally(self): + if self._rxn_rate_tally is None: + self._rxn_rate_tally = self.tallies['nu-scatter'] + self._rxn_rate_tally.sparse = self.sparse + return self._rxn_rate_tally - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energy = openmc.Filter('energy', group_edges) - energyout = openmc.Filter('energyout', group_edges) + @property + def xs_tally(self): - # Create a list of scores for each Tally to be created - if self.correction == 'P0': - scores = ['flux', 'nu-scatter', 'scatter-P1'] - estimator = 'analog' - keys = ['flux', 'scatter', 'scatter-P1'] - filters = [[energy], [energy, energyout], [energyout]] - else: - scores = ['flux', 'nu-scatter'] - estimator = 'analog' - keys = ['flux', 'scatter'] - filters = [[energy], [energy, energyout]] + if self._xs_tally is None: + scatter = self.tallies['scatter'] - # Intialize the Tallies - self._create_tallies(scores, filters, keys, estimator) + # Compute the multiplicity + self._xs_tally = self.rxn_rate_tally / scatter + super(MultiplicityMatrixXS, self)._compute_xs() + + return self._xs_tally + + +class NuFissionMatrixXS(MatrixMGXS): + r"""A fission production matrix multi-group cross section. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`NuFissionMatrixXS.energy_groups` and + :attr:`NuFissionMatrixXS.domain` properties. Tallies for the flux and + appropriate reaction rates over the specified domain are generated + automatically via the :attr:`NuFissionMatrixXS.tallies` property, which can + then be appended to a :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`NuFissionMatrixXS.xs_tally` property. + + For a spatial domain :math:`V`, incoming energy group + :math:`[E_{g'},E_{g'-1}]`, and outgoing energy group :math:`[E_g,E_{g-1}]`, + the fission production is calculated as: + + .. math:: + + \langle \nu\sigma_{f,g'\rightarrow g} \phi \rangle &= \int_{r \in V} dr + \int_{4\pi} d\Omega' \int_{E_{g'}}^{E_{g'-1}} dE' \int_{E_g}^{E_{g-1}} dE + \; \chi(E) \nu\sigma_f (r, E') \psi(r, E', \Omega')\\ + \langle \phi \rangle &= \int_{r \in V} dr \int_{4\pi} d\Omega + \int_{E_g}^{E_{g-1}} dE \; \psi (r, E, \Omega) \\ + \nu\sigma_{f,g'\rightarrow g} &= \frac{\langle \nu\sigma_{f,g'\rightarrow + g} \phi \rangle}{\langle \phi \rangle} + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`NuFissionMatrixXS.tally_keys` + property and values are instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ + + def __init__(self, domain=None, domain_type=None, + groups=None, by_nuclide=False, name=''): + super(NuFissionMatrixXS, self).__init__(domain, domain_type, + groups, by_nuclide, name) + self._rxn_type = 'nu-fission' + self._hdf5_key = 'nu-fission matrix' - return self._tallies class Chi(MGXS): - """The fission spectrum.""" + r"""The fission spectrum. + + This class can be used for both OpenMC input generation and tally data + post-processing to compute spatially-homogenized and energy-integrated + multi-group cross sections for multi-group neutronics calculations. At a + minimum, one needs to set the :attr:`Chi.energy_groups` and + :attr:`Chi.domain` properties. Tallies for the flux and appropriate reaction + rates over the specified domain are generated automatically via the + :attr:`Chi.tallies` property, which can then be appended to a + :class:`openmc.Tallies` instance. + + For post-processing, the :meth:`MGXS.load_from_statepoint` will pull in the + necessary data to compute multi-group cross sections from a + :class:`openmc.StatePoint` instance. The derived multi-group cross section + can then be obtained from the :attr:`Chi.xs_tally` property. + + For a spatial domain :math:`V` and energy group :math:`[E_g,E_{g-1}]`, the + fission spectrum is calculated as: + + .. math:: + + \langle \nu\sigma_{f,\rightarrow g} \phi \rangle &= \int_{r \in V} dr + \int_{4\pi} d\Omega' \int_0^\infty dE' \int_{E_g}^{E_{g-1}} dE \; \chi(E) + \nu\sigma_f (r, E') \psi(r, E', \Omega')\\ + \langle \nu\sigma_f \phi \rangle &= \int_{r \in V} dr \int_{4\pi} + d\Omega' \int_0^\infty dE' \int_0^\infty dE \; \chi(E) \nu\sigma_f (r, + E') \psi(r, E', \Omega') \\ + \chi_g &= \frac{\langle \nu\sigma_{f,\rightarrow g} \phi \rangle}{\langle + \nu\sigma_f \phi \rangle} + + Parameters + ---------- + domain : openmc.Material or openmc.Cell or openmc.Universe + The domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + The domain type for spatial homogenization + groups : openmc.mgxs.EnergyGroups + The energy group structure for energy condensation + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + name : str, optional + Name of the multi-group cross section. Used as a label to identify + tallies in OpenMC 'tallies.xml' file. + + Attributes + ---------- + name : str, optional + Name of the multi-group cross section + rxn_type : str + Reaction type (e.g., 'total', 'nu-fission', etc.) + by_nuclide : bool + If true, computes cross sections for each nuclide in domain + domain : Material or Cell or Universe + Domain for spatial homogenization + domain_type : {'material', 'cell', 'distribcell', 'universe'} + Domain type for spatial homogenization + energy_groups : openmc.mgxs.EnergyGroups + Energy group structure for energy condensation + tally_trigger : openmc.Trigger + An (optional) tally precision trigger given to each tally used to + compute the cross section + scores : list of str + The scores in each tally used to compute the multi-group cross section + filters : list of openmc.Filter + The filters in each tally used to compute the multi-group cross section + tally_keys : list of str + The keys into the tallies dictionary for each tally used to compute + the multi-group cross section + estimator : {'tracklength', 'analog'} + The tally estimator used to compute the multi-group cross section + tallies : collections.OrderedDict + OpenMC tallies needed to compute the multi-group cross section. The keys + are strings listed in the :attr:`Chi.tally_keys` property and values are + instances of :class:`openmc.Tally`. + rxn_rate_tally : openmc.Tally + Derived tally for the reaction rate tally used in the numerator to + compute the multi-group cross section. This attribute is None + unless the multi-group cross section has been computed. + xs_tally : openmc.Tally + Derived tally for the multi-group cross section. This attribute + is None unless the multi-group cross section has been computed. + num_subdomains : int + The number of subdomains is unity for 'material', 'cell' and 'universe' + domain types. When the This is equal to the number of cell instances + for 'distribcell' domain types (it is equal to unity prior to loading + tally data from a statepoint file). + num_nuclides : int + The number of nuclides for which the multi-group cross section is + being tracked. This is unity if the by_nuclide attribute is False. + nuclides : Iterable of str or 'sum' + The optional user-specified nuclides for which to compute cross + sections (e.g., 'U-238', 'O-16'). If by_nuclide is True but nuclides + are not specified by the user, all nuclides in the spatial domain + are included. This attribute is 'sum' if by_nuclide is false. + sparse : bool + Whether or not the MGXS' tallies use SciPy's LIL sparse matrix format + for compressed data storage + loaded_sp : bool + Whether or not a statepoint file has been loaded with tally data + derived : bool + Whether or not the MGXS is merged from one or more other MGXS + hdf5_key : str + The key used to index multi-group cross sections in an HDF5 data store + + """ def __init__(self, domain=None, domain_type=None, groups=None, by_nuclide=False, name=''): @@ -2262,33 +4270,24 @@ class Chi(MGXS): self._rxn_type = 'chi' @property - def tallies(self): - """Construct the OpenMC tallies needed to compute this cross section. + def scores(self): + return ['nu-fission', 'nu-fission'] - This method constructs two analog tallies to compute 'nu-fission' - reaction rates with 'energy' and 'energyout' filters in the spatial - domain and energy groups of interest. + @property + def filters(self): + # Create the non-domain specific Filters for the Tallies + group_edges = self.energy_groups.group_edges + energyout = openmc.Filter('energyout', group_edges) + energyin = openmc.Filter('energy', [group_edges[0], group_edges[-1]]) + return [[energyin], [energyout]] - """ + @property + def tally_keys(self): + return ['nu-fission-in', 'nu-fission-out'] - # Instantiate tallies if they do not exist - if self._tallies is None: - - # Create a list of scores for each Tally to be created - scores = ['nu-fission', 'nu-fission'] - estimator = 'analog' - keys = ['nu-fission-in', 'nu-fission-out'] - - # Create the non-domain specific Filters for the Tallies - group_edges = self.energy_groups.group_edges - energyout = openmc.Filter('energyout', group_edges) - energyin = openmc.Filter('energy', [group_edges[0], group_edges[-1]]) - filters = [[energyin], [energyout]] - - # Intialize the Tallies - self._create_tallies(scores, filters, keys, estimator) - - return self._tallies + @property + def estimator(self): + return 'analog' @property def rxn_rate_tally(self): @@ -2299,7 +4298,6 @@ class Chi(MGXS): @property def xs_tally(self): - """Computes chi fission spectrum using OpenMC tally arithmetic.""" if self._xs_tally is None: nu_fission_in = self.tallies['nu-fission-in'] @@ -2313,7 +4311,7 @@ class Chi(MGXS): super(Chi, self)._compute_xs() # Add the coarse energy filter back to the nu-fission tally - nu_fission_in.add_filter(energy_filter) + nu_fission_in.filters.append(energy_filter) return self._xs_tally @@ -2336,9 +4334,10 @@ class Chi(MGXS): Returns ------- - MGXS - A new tally which encapsulates the subset of data requested for the - nuclide(s) and/or energy group(s) requested in the parameters. + openmc.mgxs.MGXS + A new MGXS which encapsulates the subset of data requested + for the nuclide(s) and/or energy group(s) requested in the + parameters. """ @@ -2382,12 +4381,12 @@ class Chi(MGXS): Parameters ---------- - other : MGXS + other : openmc.mgxs.MGXS MGXS to merge with this one Returns ------- - merged_mgxs : MGXS + merged_mgxs : openmc.mgxs.MGXS Merged MGXS """ @@ -2425,7 +4424,8 @@ class Chi(MGXS): return merged_mgxs def get_xs(self, groups='all', subdomains='all', nuclides='all', - xs_type='macro', order_groups='increasing', value='mean'): + xs_type='macro', order_groups='increasing', + value='mean', **kwargs): """Returns an array of the fission spectrum. This method constructs a 2D NumPy array for the requested multi-group @@ -2449,13 +4449,12 @@ class Chi(MGXS): Return the cross section indexed according to increasing or decreasing energy groups (decreasing or increasing energies). Defaults to 'increasing'. - value : str - A string for the type of value to return - 'mean', 'std_dev', or - 'rel_err' are accepted. Defaults to 'mean'. + value : {'mean', 'std_dev', 'rel_err'} + A string for the type of value to return. Defaults to 'mean'. Returns ------- - ndarray + numpy.ndarray A NumPy array of the multi-group cross section indexed in the order each group, subdomain and nuclide is listed in the parameters. @@ -2512,7 +4511,7 @@ class Chi(MGXS): xs_tally = nu_fission_out / nu_fission_in # Add the coarse energy filter back to the nu-fission tally - nu_fission_in.add_filter(energy_filter) + nu_fission_in.filters.append(energy_filter) xs = xs_tally.get_values(filters=filters, filter_bins=filter_bins, value=value) @@ -2560,10 +4559,10 @@ class Chi(MGXS): return xs def get_pandas_dataframe(self, groups='all', nuclides='all', - xs_type='macro', summary=None): + xs_type='macro', distribcell_paths=False): """Build a Pandas DataFrame for the MGXS data. - This method leverages the Tally.get_pandas_dataframe(...) method, but + This method leverages :meth:`openmc.Tally.get_pandas_dataframe`, but renames the columns with terminology appropriate for cross section data. Parameters @@ -2580,12 +4579,11 @@ class Chi(MGXS): xs_type: {'macro', 'micro'} Return macro or micro cross section in units of cm^-1 or barns. Defaults to 'macro'. - summary : None or Summary - An optional Summary object to be used to construct columns for - distribcell tally filters (default is None). The geometric - information in the Summary object is embedded into a multi-index - column with a geometric "path" to each distribcell intance. - NOTE: This option requires the OpenCG Python package. + distribcell_paths : bool, optional + Construct columns for distribcell tally filters (default is True). + The geometric information in the Summary object is embedded into + a Multi-index column with a geometric "path" to each distribcell + instance. Returns ------- @@ -2601,8 +4599,8 @@ class Chi(MGXS): """ # Build the dataframe using the parent class method - df = super(Chi, self).get_pandas_dataframe(groups, nuclides, - xs_type, summary) + df = super(Chi, self).get_pandas_dataframe( + groups, nuclides, xs_type, distribcell_paths=distribcell_paths) # If user requested micro cross sections, multiply by the atom # densities to cancel out division made by the parent class method diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py index 06b369c68..35b48d873 100644 --- a/openmc/mgxs_library.py +++ b/openmc/mgxs_library.py @@ -1,19 +1,19 @@ from collections import Iterable from numbers import Real, Integral from xml.etree import ElementTree as ET -import warnings import sys -if sys.version_info[0] >= 3: - basestring = str import numpy as np import openmc -from openmc.mgxs import EnergyGroups +import openmc.mgxs from openmc.checkvalue import check_type, check_value, check_greater_than, \ - check_iterable_type + check_iterable_type from openmc.clean_xml import * +if sys.version_info[0] >= 3: + basestring = str + # Supported incoming particle MGXS angular treatment representations _REPRESENTATIONS = ['isotropic', 'angle'] @@ -24,7 +24,7 @@ def ndarray_to_string(arr): Parameters ---------- - arr : ndarray + arr : numpy.ndarray Array to combine in to a string Returns @@ -87,8 +87,9 @@ class XSdata(object): ---------- name : str, optional Name of the mgxs data set. - - representation : {'isotropic', 'angle'} + energy_groups : openmc.mgxs.EnergyGroups + Energygroup structure + representation : {'isotropic', 'angle'}, optional Method used in generating the MGXS (isotropic or angle-dependent flux weighting). Defaults to 'isotropic' @@ -98,11 +99,17 @@ class XSdata(object): Unique identifier for the xsdata object alias : str Separate unique identifier for the xsdata object + zaid : int + 1000*(atomic number) + mass number. As an example, the zaid of U-235 + would be 92235. + awr : float + Atomic weight ratio of an isotope. That is, the ratio of the mass + of the isotope to the mass of a single neutron. kT : float - Temperature (in units of MeV) of this data set. - energy_groups : EnergyGroups + Temperature (in units of MeV). + energy_groups : openmc.mgxs.EnergyGroups Energy group structure - fissionable : boolean + fissionable : bool Whether or not this is a fissionable data set. scatt_type : {'legendre', 'histogram', or 'tabular'} Angular distribution representation (legendre, histogram, or tabular) @@ -115,14 +122,113 @@ class XSdata(object): Legendre polynomial form). Dict contains two keys: 'enable' and 'num_points'. 'enable' is a boolean and 'num_points' is the number of points to use, if 'enable' is True. + representation : {'isotropic', 'angle'} + Method used in generating the MGXS (isotropic or angle-dependent flux + weighting). + num_azimuthal : int + Number of equal width angular bins that the azimuthal angular domain is + subdivided into. This only applies when ``representation`` is "angle". + num_polar : int + Number of equal width angular bins that the polar angular domain is + subdivided into. This only applies when ``representation`` is "angle". + use_chi : bool + Whether or not a chi vector or nu-fission matrix was used. + vector_shape : iterable of int + Dimensionality of vector multi-group cross sections (e.g., the total + cross section). The return result depends on the value of + ``representation``. + matrix_shape : iterable of int + Dimensionality of matrix multi-group cross sections (e.g., the + fission matrix cross section). The return result depends on the + value of ``representation``. + pn_matrix_shape : iterable of int + Dimensionality of scattering matrix data (e.g., the + scattering matrix cross section). The return result depends on the + value of ``representation``. + total : numpy.ndarray + Group-wise total cross section ordered by increasing group index (i.e., + fast to thermal). If ``representation`` is "isotropic", then the length + of this list should equal the number of groups described in the + ``groups`` element. If ``representation`` is "angle", then the length + of this list should equal the number of groups times the number of + azimuthal angles times the number of polar angles, with the + inner-dimension being groups, intermediate-dimension being azimuthal + angles and outer-dimension being the polar angles. + absorption : numpy.ndarray + Group-wise absorption cross section ordered by increasing group index + (i.e., fast to thermal). If ``representation`` is "isotropic", then the + length of this list should equal the number of groups described in the + ``groups`` attribute. If ``representation`` is "angle", then the length + of this list should equal the number of groups times the number of + azimuthal angles times the number of polar angles, with the + inner-dimension being groups, intermediate-dimension being azimuthal + angles and outer-dimension being the polar angles. + scatter : numpy.ndarray + Scattering moment matrices presented with the columns representing + incoming group and rows representing the outgoing group. That is, + down-scatter will be above the diagonal of the resultant matrix. This + matrix is repeated for every Legendre order (in order of increasing + orders) if ``scatt_type`` is "legendre"; otherwise, this matrix is + repeated for every bin of the histogram or tabular representation. + Finally, if ``representation`` is "angle", the above is repeated for + every azimuthal angle and every polar angle, in that order. + multiplicity : numpy.ndarray + Ratio of neutrons produced in scattering collisions to the neutrons + which undergo scattering collisions; that is, the multiplicity provides + the code with a scaling factor to account for neutrons produced in + (n,xn) reactions. This information is assumed isotropic and therefore + does not need to be repeated for every Legendre moment or + histogram/tabular bin. This matrix follows the same arrangement as + described for the ``scatter`` attribute, with the exception of the data + needed to provide the scattering type information. + fission : numpy.ndarray + Group-wise fission cross section ordered by increasing group index + (i.e., fast to thermal). If ``representation`` is "isotropic", then the + length of this list should equal the number of groups described in the + ``groups`` attribute. If ``representation`` is "angle", then the length + of this list should equal the number of groups times the number of + azimuthal angles times the number of polar angles, with the + inner-dimension being groups, intermediate-dimension being azimuthal + angles and outer-dimension being the polar angles. + kappa_fission : numpy.ndarray + Group-wise kappa-fission cross section ordered by increasing group + index (i.e., fast to thermal). If ``representation`` is "isotropic", + then the length of this list should equal the number of groups in the + ``groups`` attribute. If ``representation`` is "angle", then the length + of this list should equal the number of groups times the number of + azimuthal angles times the number of polar angles, with the + inner-dimension being groups, intermediate-dimension being azimuthal + angles and outer-dimension being the polar angles. + chi : numpy.ndarray + Group-wise fission spectra ordered by increasing group index (i.e., + fast to thermal). This attribute should be used if making the common + approximation that the fission spectra does not depend on incoming + energy. If the user does not wish to make this approximation, then + this should not be provided and this information included in the + ``nu_fission`` element instead. If ``representation`` is "isotropic", + then the length of this list should equal the number of groups + in the ``groups`` element. If ``representation`` is "angle", then the + length of this list should equal the number of groups times the number + of azimuthal angles times the number of polar angles, with the + inner-dimension being groups, intermediate-dimension being azimuthal + angles and outer-dimension being the polar angles. + nu_fission : numpy.ndarray + Group-wise fission production cross section vector (i.e., if ``chi`` is + provided), or is the group-wise fission production matrix. If providing + the vector, it should be ordered the same as the ``fission`` data. If + providing the matrix, it should be ordered the same as the + ``multiplicity`` matrix. """ - def __init__(self, name, energy_groups, representation="isotropic"): + + def __init__(self, name, energy_groups, representation='isotropic'): # Initialize class attributes self._name = name self._energy_groups = energy_groups self._representation = representation self._alias = None + self._zaid = None + self._awr = None self._kT = None self._fissionable = False self._scatt_type = 'legendre' @@ -136,7 +242,7 @@ class XSdata(object): self._multiplicity = None self._fission = None self._nu_fission = None - self._k_fission = None + self._kappa_fission = None self._chi = None self._use_chi = None @@ -156,6 +262,14 @@ class XSdata(object): def alias(self): return self._alias + @property + def zaid(self): + return self._zaid + + @property + def awr(self): + return self._awr + @property def kT(self): return self._kT @@ -180,6 +294,10 @@ class XSdata(object): def num_azimuthal(self): return self._num_azimuthal + @property + def use_chi(self): + return self._use_chi + @property def total(self): return self._total @@ -205,8 +323,8 @@ class XSdata(object): return self._nu_fission @property - def k_fission(self): - return self._k_fission + def kappa_fission(self): + return self._kappa_fission @property def chi(self): @@ -220,6 +338,34 @@ class XSdata(object): else: return self._order + @property + def vector_shape(self): + if self.representation is 'isotropic': + return (self.energy_groups.num_groups,) + elif self.representation is 'angle': + return (self.num_polar, self.num_azimuthal, + self.energy_groups.num_groups) + + @property + def matrix_shape(self): + if self.representation is 'isotropic': + return (self.energy_groups.num_groups, + self.energy_groups.num_groups) + elif self.representation is 'angle': + return (self.num_polar, self.num_azimuthal, + self.energy_groups.num_groups, + self.energy_groups.num_groups) + + @property + def pn_matrix_shape(self): + if self.representation is 'isotropic': + return (self.num_orders, self.energy_groups.num_groups, + self.energy_groups.num_groups) + elif self.representation is 'angle': + return (self.num_polar, self.num_azimuthal, self.num_orders, + self.energy_groups.num_groups, + self.energy_groups.num_groups) + @name.setter def name(self, name): check_type('name for XSdata', name, basestring) @@ -228,15 +374,12 @@ class XSdata(object): @energy_groups.setter def energy_groups(self, energy_groups): # Check validity of energy_groups - check_type("energy_groups", energy_groups, EnergyGroups) + check_type('energy_groups', energy_groups, openmc.mgxs.EnergyGroups) - # Check that there is one or more groups - if ((energy_groups.num_groups is None) or - (energy_groups.num_groups < 1)): - - msg = 'energy_groups object incorrectly initialized.' + if energy_group.group_edges is None: + msg = 'Unable to assign an EnergyGroups object ' \ + 'with uninitialized group edges' raise ValueError(msg) - self._energy_groups = energy_groups @representation.setter @@ -253,37 +396,52 @@ class XSdata(object): else: self._alias = self._name + @zaid.setter + def zaid(self, zaid): + # Check type and value + check_type('zaid', zaid, Integral) + check_greater_than('zaid', zaid, 0) + self._zaid = zaid + + @awr.setter + def awr(self, awr): + # Check validity of type and that the awr value is > 0 + check_type('awr', awr, Real) + check_greater_than('awr', awr, 0.0) + self._awr = awr + @kT.setter def kT(self, kT): # Check validity of type and that the kT value is >= 0 - check_type("kT", kT, Real) - check_greater_than("kT", kT, 0.0, equality=True) + check_type('kT', kT, Real) + check_greater_than('kT', kT, 0.0, equality=True) self._kT = kT @scatt_type.setter def scatt_type(self, scatt_type): # check to see it is of a valid type and value - check_value("scatt_type", scatt_type, ['legendre', 'histogram', + check_value('scatt_type', scatt_type, ['legendre', 'histogram', 'tabular']) self._scatt_type = scatt_type @order.setter def order(self, order): # Check type and value - check_type("order", order, Integral) - check_greater_than("order", order, 0, equality=True) + check_type('order', order, Integral) + check_greater_than('order', order, 0, equality=True) self._order = order @tabular_legendre.setter def tabular_legendre(self, tabular_legendre): # Check to make sure this is a dict and it has our keys with the # right values. - check_type("tabular_legendre", tabular_legendre, dict) + check_type('tabular_legendre', tabular_legendre, dict) if 'enable' in tabular_legendre: enable = tabular_legendre['enable'] check_type('enable', enable, bool) else: - msg = "enable must be provided in tabular_legendre" + msg = 'The tabular_legendre dict must include a value keyed by ' \ + '"enable"' raise ValueError(msg) if 'num_points' in tabular_legendre: num_points = tabular_legendre['num_points'] @@ -299,200 +457,521 @@ class XSdata(object): @num_polar.setter def num_polar(self, num_polar): # Make sure we have positive ints - check_value("num_polar", num_polar, Integral) - check_greater_than("num_polar", num_polar, 0) + check_value('num_polar', num_polar, Integral) + check_greater_than('num_polar', num_polar, 0) self._num_polar = num_polar @num_azimuthal.setter def num_azimuthal(self, num_azimuthal): - check_value("num_azimuthal", num_azimuthal, Integral) - check_greater_than("num_azimuthal", num_azimuthal, 0) + check_value('num_azimuthal', num_azimuthal, Integral) + check_greater_than('num_azimuthal', num_azimuthal, 0) self._num_azimuthal = num_azimuthal + @use_chi.setter + def use_chi(self, use_chi): + check_type('use_chi', use_chi, bool) + self._use_chi = use_chi + @total.setter def total(self, total): - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups,) - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - # check we have a numpy list - check_type("total", total, np.ndarray, expected_iter_type=Real) - if total.shape == shape: - self._total = np.copy(total) - else: - msg = 'Shape of provided total "{0}" does not match shape ' \ - 'required, "{1}"'.format(total.shape, shape) - raise ValueError(msg) + check_type('total', total, Iterable, expected_iter_type=Real) + # Convert to a numpy array so we can easily get the shape for + # checking + nptotal = np.asarray(total) + check_value('total shape', nptotal.shape, [self.vector_shape]) + + self._total = nptotal @absorption.setter def absorption(self, absorption): - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups,) - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - # check we have a numpy list - check_type("absorption", absorption, np.ndarray, expected_iter_type=Real) - if absorption.shape == shape: - self._absorption = np.copy(absorption) - else: - msg = 'Shape of provided absorption "{0}" does not match shape ' \ - 'required, "{1}"'.format(absorption.shape, shape) - raise ValueError(msg) + check_type('absorption', absorption, Iterable, expected_iter_type=Real) + # Convert to a numpy array so we can easily get the shape for + # checking + npabsorption = np.asarray(absorption) + check_value('absorption shape', npabsorption.shape, + [self.vector_shape]) + + self._absorption = npabsorption @fission.setter def fission(self, fission): - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups,) - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - # check we have a numpy list - check_type("fission", fission, np.ndarray, expected_iter_type=Real) - if fission.shape == shape: - self._fission = np.copy(fission) - if np.sum(self._fission) > 0.0: - self._fissionable = True - else: - msg = 'Shape of provided fission "{0}" does not match shape ' \ - 'required, "{1}"'.format(fission.shape, shape) - raise ValueError(msg) + check_type('fission', fission, Iterable, expected_iter_type=Real) + # Convert to a numpy array so we can easily get the shape for + # checking + npfission = np.asarray(fission) + check_value('fission shape', npfission.shape, [self.vector_shape]) - @k_fission.setter - def k_fission(self, k_fission): - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups,) - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - # check we have a numpy list - check_type("k_fission", k_fission, np.ndarray, expected_iter_type=Real) - if k_fission.shape == shape: - self._k_fission = np.copy(k_fission) - if np.sum(self._k_fission) > 0.0: - self._fissionable = True - else: - msg = 'Shape of provided k_fission "{0}" does not match shape ' \ - 'required, "{1}"'.format(k_fission.shape, shape) - raise ValueError(msg) + self._fission = npfission + + if np.sum(self._fission) > 0.0: + self._fissionable = True + + @kappa_fission.setter + def kappa_fission(self, kappa_fission): + check_type('kappa_fission', kappa_fission, Iterable, + expected_iter_type=Real) + # Convert to a numpy array so we can easily get the shape for + # checking + npkappa_fission = np.asarray(kappa_fission) + check_value('kappa fission shape', npkappa_fission.shape, + [self.vector_shape]) + + self._kappa_fission = npkappa_fission + + if np.sum(self._kappa_fission) > 0.0: + self._fissionable = True @chi.setter def chi(self, chi): - if not self._use_chi: - msg = 'Providing chi when nu_fission already provided as matrix!' + if self.use_chi is not None: + if not self.use_chi: + msg = 'Providing "chi" when "nu-fission" already provided as a' \ + 'matrix' + raise ValueError(msg) + + check_type('chi', chi, Iterable, expected_iter_type=Real) + # Convert to a numpy array so we can easily get the shape for + # checking + npchi = np.asarray(chi) + # Check the shape + if npchi.shape != self.vector_shape: + msg = 'Provided chi iterable does not have the expected shape.' raise ValueError(msg) - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups,) - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - # check we have a numpy list - check_type("chi", chi, np.ndarray, expected_iter_type=Real) - if chi.shape == shape: - self._chi = np.copy(chi) - else: - msg = 'Shape of provided chi "{0}" does not match shape ' \ - 'required, "{1}"'.format(chi.shape, shape) - raise ValueError(msg) - if self._use_chi is not None: - self._use_chi = True + + self._chi = npchi + + if self.use_chi is not None: + self.use_chi = True @scatter.setter def scatter(self, scatter): - if self._representation is 'isotropic': - shape = (self.num_orders, self._energy_groups.num_groups, - self._energy_groups.num_groups) - max_depth = 3 - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, self.num_orders, - self._energy_groups.num_groups, - self._energy_groups.num_groups) - max_depth = 5 - # check we have a numpy list - check_iterable_type("scatter", scatter, expected_type=Real, - max_depth=max_depth) - if scatter.shape == shape: - self._scatter = np.copy(scatter) - else: - msg = 'Shape of provided scatter "{0}" does not match shape ' \ - 'required, "{1}"'.format(scatter.shape, shape) - raise ValueError(msg) + # Convert to a numpy array so we can easily get the shape for + # checking + npscatter = np.asarray(scatter) + check_iterable_type('scatter', npscatter, Real, + max_depth=len(npscatter.shape)) + check_value('scatter shape', npscatter.shape, [self.pn_matrix_shape]) + + self._scatter = npscatter @multiplicity.setter def multiplicity(self, multiplicity): - if self._representation is 'isotropic': - shape = (self._energy_groups.num_groups, - self._energy_groups.num_groups) - max_depth = 2 - elif self._representation is 'angle': - shape = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups, - self._energy_groups.num_groups) - max_depth = 4 - # check we have a numpy list - check_iterable_type("multiplicity", multiplicity, expected_type=Real, - max_depth=max_depth) - if multiplicity.shape == shape: - self._multiplicity = np.copy(multiplicity) - else: - msg = 'Shape of provided multiplicity "{0}" does not match shape ' \ - 'required, "{1}"'.format(multiplicity.shape, shape) - raise ValueError(msg) + # Convert to a numpy array so we can easily get the shape for + # checking + npmultiplicity = np.asarray(multiplicity) + check_iterable_type('multiplicity', npmultiplicity, Real, + max_depth=len(npmultiplicity.shape)) + check_value('multiplicity shape', npmultiplicity.shape, + [self.matrix_shape]) + + self._multiplicity = npmultiplicity @nu_fission.setter def nu_fission(self, nu_fission): + # The NuFissionXS class does not have the capability to produce + # a fission matrix and therefore if this path is pursued, we know + # chi must be used. # nu_fission can be given as a vector or a matrix # Vector is used when chi also exists. # Matrix is used when chi does not exist. # We have to check that the correct form is given, but only if # chi already has been set. If not, we just check that this is OK - # and set the use_chi flag. + # and set the use_chi flag accordingly - # First lets set our dimensions here since they get used repeatedly - # throughout this code. - if self._representation is 'isotropic': - shape_vec = (self._energy_groups.num_groups,) - shape_mat = (self._energy_groups.num_groups, - self._energy_groups.num_groups) - elif self._representation is 'angle': - shape_vec = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups) - shape_mat = (self._num_polar, self._num_azimuthal, - self._energy_groups.num_groups, - self._energy_groups.num_groups) + # Convert to a numpy array so we can easily get the shape for + # checking + npnu_fission = np.asarray(nu_fission) - # Begin by checking the case when chi has already been given and thus - # the rules for filling in nu_fission are set. - if self._use_chi is not None: - if self._use_chi: - shape = shape_vec + check_iterable_type('nu_fission', npnu_fission, Real, + max_depth=len(npnu_fission.shape)) + + if self.use_chi is not None: + if self.use_chi: + check_value('nu_fission shape', npnu_fission.shape, + [self.vector_shape]) else: - shape = shape_mat - if nu_fission.shape != shape: - msg = "Invalid Shape of Nu_fission!" - raise ValueError(msg) + check_value('nu_fission shape', npnu_fission.shape, + [self.matrix_shape]) else: - # Get shape of nu_fission so we can figure if we need chi or not - if nu_fission.shape == shape_vec: - self._use_chi = True - shape = shape_vec - elif nu_fission.shape == shape_mat: - self._use_chi = False - shape = shape_mat + check_value('nu_fission shape', npnu_fission.shape, + [self.vector_shape, self.matrix_shape]) + # Find out if we have a nu-fission matrix or vector + # and set a flag to allow other methods to check this later. + if npnu_fission.shape == self.vector_shape: + self.use_chi = True else: - msg = "Invalid Shape of Nu_fission!" - raise ValueError(msg) + self.use_chi = False - # check we have a numpy list - check_type("nu_fission", nu_fission, np.ndarray, expected_iter_type=Real) - self._nu_fission = np.copy(nu_fission) + self._nu_fission = npnu_fission if np.sum(self._nu_fission) > 0.0: self._fissionable = True + def set_total_mgxs(self, total, nuclide='total', xs_type='macro'): + """This method allows for an openmc.mgxs.TotalXS or + openmc.mgxs.TransportXS to be used to set the total cross section + for this XSdata object. + + Parameters + ---------- + total: openmc.mgxs.TotalXS or openmc.mgxs.TransportXS + MGXS Object containing the total or transport cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('total', total, (openmc.mgxs.TotalXS, + openmc.mgxs.TransportXS)) + check_value('energy_groups', total.energy_groups, [self.energy_groups]) + check_value('domain_type', total.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._total = total.get_xs(nuclides=nuclide, xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + def set_absorption_mgxs(self, absorption, nuclide='total', + xs_type='macro'): + """This method allows for an openmc.mgxs.AbsorptionXS + to be used to set the absorption cross section for this XSdata object. + + Parameters + ---------- + absorption: openmc.mgxs.AbsorptionXS + MGXS Object containing the absorption cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('absorption', absorption, openmc.mgxs.AbsorptionXS) + check_value('energy_groups', absorption.energy_groups, + [self.energy_groups]) + check_value('domain_type', absorption.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._absorption = absorption.get_xs(nuclides=nuclide, + xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + def set_fission_mgxs(self, fission, nuclide='total', xs_type='macro'): + """This method allows for an openmc.mgxs.FissionXS + to be used to set the fission cross section for this XSdata object. + + Parameters + ---------- + fission: openmc.mgxs.FissionXS + MGXS Object containing the fission cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('fission', fission, openmc.mgxs.FissionXS) + check_value('energy_groups', fission.energy_groups, + [self.energy_groups]) + check_value('domain_type', fission.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._fission = fission.get_xs(nuclides=nuclide, + xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + def set_nu_fission_mgxs(self, nu_fission, nuclide='total', + xs_type='macro'): + """This method allows for an openmc.mgxs.NuFissionXS + to be used to set the nu-fission cross section for this XSdata object. + + Parameters + ---------- + nu_fission: openmc.mgxs.NuFissionXS + MGXS Object containing the nu-fission cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('nu_fission', nu_fission, (openmc.mgxs.NuFissionXS, + openmc.mgxs.NuFissionMatrixXS)) + check_value('energy_groups', nu_fission.energy_groups, + [self.energy_groups]) + check_value('domain_type', nu_fission.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._nu_fission = nu_fission.get_xs(nuclides=nuclide, + xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + if isinstance(nu_fission, openmc.mgxs.NuFissionMatrixXS): + self.use_chi = False + else: + self.use_chi = True + + if np.sum(self._nu_fission) > 0.0: + self._fissionable = True + + def set_kappa_fission_mgxs(self, k_fission, nuclide='total', + xs_type='macro'): + """This method allows for an openmc.mgxs.KappaFissionXS + to be used to set the kappa-fission cross section for this XSdata + object. + + Parameters + ---------- + kappa_fission: openmc.mgxs.KappaFissionXS + MGXS Object containing the kappa-fission cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('k_fission', k_fission, openmc.mgxs.KappaFissionXS) + check_value('energy_groups', k_fission.energy_groups, + [self.energy_groups]) + check_value('domain_type', k_fission.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._kappa_fission = k_fission.get_xs(nuclides=nuclide, + xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + def set_chi_mgxs(self, chi, nuclide='total', xs_type='macro'): + """This method allows for an openmc.mgxs.Chi + to be used to set chi for this XSdata object. + + Parameters + ---------- + chi: openmc.mgxs.Chi + MGXS Object containing chi for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + if self.use_chi is not None: + if not self.use_chi: + msg = 'Providing chi when nu_fission already provided as a ' \ + 'matrix!' + raise ValueError(msg) + + check_type('chi', chi, openmc.mgxs.Chi) + check_value('energy_groups', chi.energy_groups, [self.energy_groups]) + check_value('domain_type', chi.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + self._chi = chi.get_xs(nuclides=nuclide, + xs_type=xs_type) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + if self.use_chi is not None: + self.use_chi = True + + def set_scatter_mgxs(self, scatter, nuclide='total', xs_type='macro'): + """This method allows for an openmc.mgxs.ScatterMatrixXS + to be used to set the scatter matrix cross section for this XSdata + object. If the XSdata.order attribute has not yet been set, then + it will be set based on the properties of scatter. + + Parameters + ---------- + scatter: openmc.mgxs.ScatterMatrixXS + MGXS Object containing the scatter matrix cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('scatter', scatter, openmc.mgxs.ScatterMatrixXS) + check_value('energy_groups', scatter.energy_groups, + [self.energy_groups]) + check_value('domain_type', scatter.domain_type, + ['universe', 'cell', 'material']) + + if (self.scatt_type != 'legendre'): + msg = 'Anisotropic scattering representations other than ' \ + 'Legendre expansions have not yet been implemented in ' \ + 'openmc.mgxs.' + raise ValueError(msg) + + # If the user has not defined XSdata.order, then we will set + # the order based on the data within scatter. + # Otherwise, we will check to see that XSdata.order to match + # the order of scatter + if self.order is None: + self.order = scatter.legendre_order + else: + check_value('legendre_order', scatter.legendre_order, + [self.order]) + + if self.representation is 'isotropic': + # Get the scattering orders in the outermost dimension + self._scatter = np.zeros((self.num_orders, + self.energy_groups.num_groups, + self.energy_groups.num_groups)) + for moment in range(self.num_orders): + self._scatter[moment, :, :] = scatter.get_xs(nuclides=nuclide, + xs_type=xs_type, + moment=moment) + + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + + def set_multiplicity_mgxs(self, nuscatter, scatter=None, nuclide='total', + xs_type='macro'): + """This method allows for either the direct use of only an + openmc.mgxs.MultiplicityMatrixXS OR an openmc.mgxs.NuScatterMatrixXS and + openmc.mgxs.ScatterMatrixXS to be used to set the scattering + multiplicity for this XSdata object. Multiplicity, + in OpenMC parlance, is a factor used to account for the production + of neutrons introduced by scattering multiplication reactions, i.e., + (n,xn) events. In this sense, the multiplication matrix is simply + defined as the ratio of the nu-scatter and scatter matrices. + + Parameters + ---------- + nuscatter: {openmc.mgxs.NuScatterMatrixXS, + openmc.mgxs.MultiplicityMatrixXS} + MGXS Object containing the matrix cross section for the domain + of interest. + scatter: openmc.mgxs.ScatterMatrixXS + MGXS Object containing the scattering matrix cross section + for the domain of interest. + nuclide : str + Individual nuclide (or 'total' if obtaining material-wise data) + to gather data for. Defaults to 'total'. + xs_type: {'macro', 'micro'} + Provide the macro or micro cross section in units of cm^-1 or + barns. Defaults to 'macro'. + + See also + -------- + openmc.mgxs.Library.create_mg_library() + openmc.mgxs.Library.get_xsdata + + """ + + check_type('nuscatter', nuscatter, (openmc.mgxs.NuScatterMatrixXS, + openmc.mgxs.MultiplicityMatrixXS)) + check_value('energy_groups', nuscatter.energy_groups, + [self.energy_groups]) + check_value('domain_type', nuscatter.domain_type, + ['universe', 'cell', 'material']) + if scatter is not None: + check_type('scatter', scatter, openmc.mgxs.ScatterMatrixXS) + if isinstance(nuscatter, openmc.mgxs.MultiplicityMatrixXS): + msg = 'Either an MultiplicityMatrixXS object must be passed ' \ + 'for "nuscatter" or the "scatter" argument must be ' \ + 'provided.' + raise ValueError(msg) + check_value('energy_groups', scatter.energy_groups, + [self.energy_groups]) + check_value('domain_type', scatter.domain_type, + ['universe', 'cell', 'material']) + + if self.representation is 'isotropic': + nuscatt = nuscatter.get_xs(nuclides=nuclide, + xs_type=xs_type, moment=0) + if isinstance(nuscatter, openmc.mgxs.MultiplicityMatrixXS): + self._multiplicity = nuscatt + else: + scatt = scatter.get_xs(nuclides=nuclide, + xs_type=xs_type, moment=0) + self._multiplicity = np.divide(nuscatt, scatt) + elif self.representation is 'angle': + msg = 'Angular-Dependent MGXS have not yet been implemented' + raise ValueError(msg) + self._multiplicity = np.nan_to_num(self._multiplicity) + def _get_xsdata_xml(self): - element = ET.Element("xsdata") - element.set("name", self._name) + element = ET.Element('xsdata') + element.set('name', self._name) if self._alias is not None: subelement = ET.SubElement(element, 'alias') @@ -502,6 +981,18 @@ class XSdata(object): subelement = ET.SubElement(element, 'kT') subelement.text = str(self._kT) + if self._zaid is not None: + subelement = ET.SubElement(element, 'zaid') + subelement.text = str(self._zaid) + + if self._awr is not None: + subelement = ET.SubElement(element, 'awr') + subelement.text = str(self._awr) + + if self._kT is not None: + subelement = ET.SubElement(element, 'kT') + subelement.text = str(self._kT) + if self._fissionable is not None: subelement = ET.SubElement(element, 'fissionable') subelement.text = str(self._fissionable) @@ -529,7 +1020,8 @@ class XSdata(object): if self._tabular_legendre is not None: subelement = ET.SubElement(element, 'tabular_legendre') subelement.set('enable', str(self._tabular_legendre['enable'])) - subelement.set('num_points', str(self._tabular_legendre['num_points'])) + subelement.set('num_points', + str(self._tabular_legendre['num_points'])) if self._total is not None: subelement = ET.SubElement(element, 'total') @@ -552,9 +1044,9 @@ class XSdata(object): subelement = ET.SubElement(element, 'fission') subelement.text = ndarray_to_string(self._fission) - if self._k_fission is not None: + if self._kappa_fission is not None: subelement = ET.SubElement(element, 'k_fission') - subelement.text = ndarray_to_string(self._k_fission) + subelement.text = ndarray_to_string(self._kappa_fission) if self._nu_fission is not None: subelement = ET.SubElement(element, 'nu_fission') @@ -567,9 +1059,10 @@ class XSdata(object): return element -class MGXSLibraryFile(object): +class MGXSLibrary(object): """Multi-Group Cross Sections file used for an OpenMC simulation. - Corresponds directly to the MG version of the cross_sections.xml input file. + Corresponds directly to the MG version of the cross_sections.xml input + file. Attributes ---------- @@ -577,18 +1070,15 @@ class MGXSLibraryFile(object): Energy group structure. inverse_velocities : Iterable of Real Inverse of velocities, units of sec/cm - filename : str - XML file to write to. - xsdatas : Iterable of XSdata + xsdatas : Iterable of openmc.XSdata Iterable of multi-Group cross section data objects """ def __init__(self, energy_groups): - # Initialize MGXSLibraryFile class attributes self._xsdatas = [] self._energy_groups = energy_groups self._inverse_velocities = None - self._cross_sections_file = ET.Element("cross_sections") + self._cross_sections_file = ET.Element('cross_sections') @property def inverse_velocities(self): @@ -607,7 +1097,7 @@ class MGXSLibraryFile(object): @energy_groups.setter def energy_groups(self, energy_groups): - check_type("energy groups", energy_groups, EnergyGroups) + check_type('energy groups', energy_groups, openmc.mgxs.EnergyGroups) self._energy_groups = energy_groups def add_xsdata(self, xsdata): @@ -615,20 +1105,16 @@ class MGXSLibraryFile(object): Parameters ---------- - xsdata : XSdata + xsdata : openmc.XSdata MGXS information to add """ - - # Check the type if not isinstance(xsdata, XSdata): msg = 'Unable to add a non-XSdata "{0}" to the ' \ - 'MGXSLibraryFile'.format(xsdata) + 'MGXSLibrary instance'.format(xsdata) raise ValueError(msg) - - # Make sure energy groups match. if xsdata.energy_groups != self._energy_groups: - msg = 'Energy groups of XSdata do not match that of MGXSLibraryFile!' + msg = 'Energy groups of XSdata do not match that of MGXSLibrary.' raise ValueError(msg) self._xsdatas.append(xsdata) @@ -638,15 +1124,11 @@ class MGXSLibraryFile(object): Parameters ---------- - xsdatas : tuple or list of XSdata + xsdatas : tuple or list of openmc.XSdata XSdatas to add """ - - if not isinstance(xsdatas, Iterable): - msg = 'Unable to create OpenMC xsdatas.xml file from "{0}" which ' \ - 'is not iterable'.format(xsdatas) - raise ValueError(msg) + check_iterable_type('xsdatas', xsdatas, XSdata) for xsdata in xsdatas: self.add_xsdata(xsdata) @@ -656,33 +1138,33 @@ class MGXSLibraryFile(object): Parameters ---------- - xsdata : XSdata + xsdata : openmc.XSdata XSdata to remove """ if not isinstance(xsdata, XSdata): msg = 'Unable to remove a non-XSdata "{0}" from the ' \ - 'XSdatasFile'.format(xsdata) + 'MGXSLibrary instance'.format(xsdata) raise ValueError(msg) self._xsdatas.remove(xsdata) def _create_groups_subelement(self): if self._energy_groups is not None: - element = ET.SubElement(self._cross_sections_file, "groups") + element = ET.SubElement(self._cross_sections_file, 'groups') element.text = str(self._energy_groups.num_groups) def _create_group_structure_subelement(self): if self._energy_groups is not None: element = ET.SubElement(self._cross_sections_file, - "group_structure") + 'group_structure') element.text = ' '.join(map(str, self._energy_groups.group_edges)) def _create_inverse_velocities_subelement(self): if self._inverse_velocities is not None: element = ET.SubElement(self._cross_sections_file, - "inverse_velocities") + 'inverse_velocities') element.text = ' '.join(map(str, self._inverse_velocities)) def _create_xsdata_subelements(self): @@ -690,14 +1172,14 @@ class MGXSLibraryFile(object): xml_element = xsdata._get_xsdata_xml() self._cross_sections_file.append(xml_element) - def export_to_xml(self, filename='mg_cross_sections.xml'): - """Create an mg_cross_sections.xml file that can be used for a + def export_to_xml(self, filename='mgxs.xml'): + """Create an mgxs.xml file that can be used for a simulation. Parameters ---------- filename : str, optional - filename of file, default is mg_cross_sections.xml + filename of file, default is mgxs.xml """ @@ -716,7 +1198,4 @@ class MGXSLibraryFile(object): # Write the XML Tree to the xsdatas.xml file tree = ET.ElementTree(self._cross_sections_file) tree.write(filename, xml_declaration=True, - encoding='utf-8', method="xml") - - - + encoding='utf-8', method='xml') diff --git a/openmc/opencg_compatible.py b/openmc/opencg_compatible.py index 0bda48c16..b112ed327 100644 --- a/openmc/opencg_compatible.py +++ b/openmc/opencg_compatible.py @@ -1,4 +1,5 @@ import copy +import operator import numpy as np @@ -9,8 +10,7 @@ except ImportError: raise ImportError(msg) import openmc -from openmc.region import Intersection -from openmc.surface import Halfspace +import openmc.checkvalue as cv # A dictionary of all OpenMC Materials created @@ -79,10 +79,7 @@ def get_opencg_material(openmc_material): """ - if not isinstance(openmc_material, openmc.Material): - msg = 'Unable to create an OpenCG Material from "{0}" ' \ - 'which is not an OpenMC Material'.format(openmc_material) - raise ValueError(msg) + cv.check_type('openmc_material', openmc_material, openmc.Material) global OPENCG_MATERIALS material_id = openmc_material.id @@ -119,10 +116,7 @@ def get_openmc_material(opencg_material): """ - if not isinstance(opencg_material, opencg.Material): - msg = 'Unable to create an OpenMC Material from "{0}" ' \ - 'which is not an OpenCG Material'.format(opencg_material) - raise ValueError(msg) + cv.check_type('opencg_material', opencg_material, opencg.Material) global OPENMC_MATERIALS material_id = opencg_material.id @@ -165,10 +159,7 @@ def is_opencg_surface_compatible(opencg_surface): """ - if not isinstance(opencg_surface, opencg.Surface): - msg = 'Unable to check if OpenCG Surface is compatible' \ - 'since "{0}" is not a Surface'.format(opencg_surface) - raise ValueError(msg) + cv.check_type('opencg_surface', opencg_surface, opencg.Surface) if opencg_surface.type in ['x-squareprism', 'y-squareprism', 'z-squareprism']: @@ -192,10 +183,7 @@ def get_opencg_surface(openmc_surface): """ - if not isinstance(openmc_surface, openmc.Surface): - msg = 'Unable to create an OpenCG Surface from "{0}" ' \ - 'which is not an OpenMC Surface'.format(openmc_surface) - raise ValueError(msg) + cv.check_type('openmc_surface', openmc_surface, openmc.Surface) global OPENCG_SURFACES surface_id = openmc_surface.id @@ -278,10 +266,7 @@ def get_openmc_surface(opencg_surface): """ - if not isinstance(opencg_surface, opencg.Surface): - msg = 'Unable to create an OpenMC Surface from "{0}" which ' \ - 'is not an OpenCG Surface'.format(opencg_surface) - raise ValueError(msg) + cv.check_type('opencg_surface', opencg_surface, opencg.Surface) global openmc_surface surface_id = opencg_surface.id @@ -369,10 +354,7 @@ def get_compatible_opencg_surfaces(opencg_surface): """ - if not isinstance(opencg_surface, opencg.Surface): - msg = 'Unable to create an OpenMC Surface from "{0}" which ' \ - 'is not an OpenCG Surface'.format(opencg_surface) - raise ValueError(msg) + cv.check_type('opencg_surface', opencg_surface, opencg.Surface) global OPENMC_SURFACES surface_id = opencg_surface.id @@ -410,9 +392,9 @@ def get_compatible_opencg_surfaces(opencg_surface): surfaces = [left, right, bottom, top] elif opencg_surface.type == 'z-squareprism': - x0 = opencg_surface.x0['x0'] - y0 = opencg_surface.y0['y0'] - R = opencg_surface.r['R'] + x0 = opencg_surface.x0 + y0 = opencg_surface.y0 + R = opencg_surface.r # Create a list of the four planes we need left = opencg.XPlane(name=name, boundary=boundary, x0=x0-R) @@ -451,10 +433,7 @@ def get_opencg_cell(openmc_cell): """ - if not isinstance(openmc_cell, openmc.Cell): - msg = 'Unable to create an OpenCG Cell from "{0}" which ' \ - 'is not an OpenMC Cell'.format(openmc_cell) - raise ValueError(msg) + cv.check_type('openmc_cell', openmc_cell, openmc.Cell) global OPENCG_CELLS cell_id = openmc_cell.id @@ -469,9 +448,9 @@ def get_opencg_cell(openmc_cell): fill = openmc_cell.fill - if (openmc_cell.fill_type == 'material'): + if openmc_cell.fill_type == 'material': opencg_cell.fill = get_opencg_material(fill) - elif (openmc_cell.fill_type == 'universe'): + elif openmc_cell.fill_type == 'universe': opencg_cell.fill = get_opencg_universe(fill) else: opencg_cell.fill = get_opencg_lattice(fill) @@ -487,13 +466,13 @@ def get_opencg_cell(openmc_cell): # half-spaces, i.e., no complex cells. region = openmc_cell.region if region is not None: - if isinstance(region, Halfspace): + if isinstance(region, openmc.Halfspace): surface = region.surface halfspace = -1 if region.side == '-' else 1 opencg_cell.add_surface(get_opencg_surface(surface), halfspace) - elif isinstance(region, Intersection): + elif isinstance(region, openmc.Intersection): for node in region.nodes: - if not isinstance(node, Halfspace): + if not isinstance(node, openmc.Halfspace): raise NotImplementedError("Complex cells not yet " "supported in OpenCG.") surface = node.surface @@ -533,20 +512,10 @@ def get_compatible_opencg_cells(opencg_cell, opencg_surface, halfspace): OpenMC """ - if not isinstance(opencg_cell, opencg.Cell): - msg = 'Unable to create compatible OpenMC Cell from "{0}" which ' \ - 'is not an OpenCG Cell'.format(opencg_cell) - raise ValueError(msg) - elif not isinstance(opencg_surface, opencg.Surface): - msg = 'Unable to create compatible OpenMC Cell since "{0}" is ' \ - 'not an OpenCG Surface'.format(opencg_surface) - raise ValueError(msg) - - elif halfspace not in [-1, +1]: - msg = 'Unable to create compatible Cell since "{0}"' \ - 'is not a +/-1 halfspace'.format(halfspace) - raise ValueError(msg) + cv.check_type('opencg_cell', opencg_cell, opencg.Cell) + cv.check_type('opencg_surface', opencg_surface, opencg.Surface) + cv.check_value('halfspace', halfspace, (-1, +1)) # Initialize an empty list for the new compatible cells compatible_cells = [] @@ -558,7 +527,7 @@ def get_compatible_opencg_cells(opencg_cell, opencg_surface, halfspace): # Get the compatible Surfaces (XPlanes and YPlanes) compatible_surfaces = get_compatible_opencg_surfaces(opencg_surface) - opencg_cell.removeSurface(opencg_surface) + opencg_cell.remove_surface(opencg_surface) # If Cell is inside SquarePrism, add "inside" of Surface halfspaces if halfspace == -1: @@ -575,7 +544,7 @@ def get_compatible_opencg_cells(opencg_cell, opencg_surface, halfspace): num_clones = 8 for clone_id in range(num_clones): - # Create a cloned OpenCG Cell with Surfaces compatible with OpenMC + # Create cloned OpenCG Cell with Surfaces compatible with OpenMC clone = opencg_cell.clone() compatible_cells.append(clone) @@ -625,7 +594,7 @@ def get_compatible_opencg_cells(opencg_cell, opencg_surface, halfspace): # Remove redundant Surfaces from the Cells for cell in compatible_cells: - cell.removeRedundantSurfaces() + cell.remove_redundant_surfaces() # Return the list of OpenMC compatible OpenCG Cells return compatible_cells @@ -641,10 +610,7 @@ def make_opencg_cells_compatible(opencg_universe): """ - if not isinstance(opencg_universe, opencg.Universe): - msg = 'Unable to make compatible OpenCG Cells for "{0}" which ' \ - 'is not an OpenCG Universe'.format(opencg_universe) - raise ValueError(msg) + cv.check_type('opencg_universe', opencg_universe, opencg.Universe) # Check all OpenCG Cells in this Universe for compatibility with OpenMC opencg_cells = opencg_universe.cells @@ -672,7 +638,7 @@ def make_opencg_cells_compatible(opencg_universe): surface, halfspace) # Remove the non-compatible OpenCG Cell from the Universe - opencg_universe.removeCell(opencg_cell) + opencg_universe.remove_cell(opencg_cell) # Add the compatible OpenCG Cells to the Universe opencg_universe.add_cells(cells) @@ -700,10 +666,7 @@ def get_openmc_cell(opencg_cell): """ - if not isinstance(opencg_cell, opencg.Cell): - msg = 'Unable to create an OpenMC Cell from "{0}" which ' \ - 'is not an OpenCG Cell'.format(opencg_cell) - raise ValueError(msg) + cv.check_type('opencg_cell', opencg_cell, opencg.Cell) global OPENMC_CELLS cell_id = opencg_cell.id @@ -718,9 +681,9 @@ def get_openmc_cell(opencg_cell): fill = opencg_cell.fill - if (opencg_cell.type == 'universe'): + if opencg_cell.type == 'universe': openmc_cell.fill = get_openmc_universe(fill) - elif (opencg_cell.type == 'lattice'): + elif opencg_cell.type == 'lattice': openmc_cell.fill = get_openmc_lattice(fill) else: openmc_cell.fill = get_openmc_material(fill) @@ -733,12 +696,13 @@ def get_openmc_cell(opencg_cell): translation = np.asarray(opencg_cell.translation, dtype=np.float64) openmc_cell.translation = translation - surfaces = opencg_cell.surfaces - - for surface_id in surfaces: - surface = surfaces[surface_id][0] - halfspace = surfaces[surface_id][1] - openmc_cell.add_surface(get_openmc_surface(surface), halfspace) + surfaces = [] + operators = [] + for surface, halfspace in opencg_cell.surfaces.values(): + surfaces.append(get_openmc_surface(surface)) + operators.append(operator.neg if halfspace == -1 else operator.pos) + openmc_cell.region = openmc.Intersection( + *[op(s) for op, s in zip(operators, surfaces)]) # Add the OpenMC Cell to the global collection of all OpenMC Cells OPENMC_CELLS[cell_id] = openmc_cell @@ -764,10 +728,7 @@ def get_opencg_universe(openmc_universe): """ - if not isinstance(openmc_universe, openmc.Universe): - msg = 'Unable to create an OpenCG Universe from "{0}" which ' \ - 'is not an OpenMC Universe'.format(openmc_universe) - raise ValueError(msg) + cv.check_type('openmc_universe', openmc_universe, openmc.Universe) global OPENCG_UNIVERSES universe_id = openmc_universe.id @@ -811,10 +772,7 @@ def get_openmc_universe(opencg_universe): """ - if not isinstance(opencg_universe, opencg.Universe): - msg = 'Unable to create an OpenMC Universe from "{0}" which ' \ - 'is not an OpenCG Universe'.format(opencg_universe) - raise ValueError(msg) + cv.check_type('opencg_universe', opencg_universe, opencg.Universe) global OPENMC_UNIVERSES universe_id = opencg_universe.id @@ -861,10 +819,7 @@ def get_opencg_lattice(openmc_lattice): """ - if not isinstance(openmc_lattice, openmc.Lattice): - msg = 'Unable to create an OpenCG Lattice from "{0}" which ' \ - 'is not an OpenMC Lattice'.format(openmc_lattice) - raise ValueError(msg) + cv.check_type('openmc_lattice', openmc_lattice, openmc.Lattice) global OPENCG_LATTICES lattice_id = openmc_lattice.id @@ -906,8 +861,8 @@ def get_opencg_lattice(openmc_lattice): universes = new_universes # Initialize an empty array for the OpenCG nested Universes in this Lattice - universe_array = np.ndarray(tuple(np.array(dimension)[::-1]), - dtype=opencg.Universe) + universe_array = np.empty(tuple(np.array(dimension)[::-1]), + dtype=opencg.Universe) # Create OpenCG Universes for each unique nested Universe in this Lattice unique_universes = openmc_lattice.get_unique_universes() @@ -958,10 +913,7 @@ def get_openmc_lattice(opencg_lattice): """ - if not isinstance(opencg_lattice, opencg.Lattice): - msg = 'Unable to create an OpenMC Lattice from "{0}" which ' \ - 'is not an OpenCG Lattice'.format(opencg_lattice) - raise ValueError(msg) + cv.check_type('opencg_lattice', opencg_lattice, opencg.Lattice) global OPENMC_LATTICES lattice_id = opencg_lattice.id @@ -977,8 +929,8 @@ def get_openmc_lattice(opencg_lattice): outer = opencg_lattice.outside # Initialize an empty array for the OpenMC nested Universes in this Lattice - universe_array = np.ndarray(tuple(np.array(dimension)[::-1]), - dtype=openmc.Universe) + universe_array = np.empty(tuple(np.array(dimension)[::-1]), + dtype=openmc.Universe) # Create OpenMC Universes for each unique nested Universe in this Lattice unique_universes = opencg_lattice.get_unique_universes() @@ -1001,7 +953,6 @@ def get_openmc_lattice(opencg_lattice): np.array(dimension, dtype=np.float64))) / -2.0 openmc_lattice = openmc.RectLattice(lattice_id=lattice_id) - openmc_lattice.dimension = dimension openmc_lattice.pitch = width openmc_lattice.universes = universe_array openmc_lattice.lower_left = lower_left @@ -1032,10 +983,7 @@ def get_opencg_geometry(openmc_geometry): """ - if not isinstance(openmc_geometry, openmc.Geometry): - msg = 'Unable to get OpenCG geometry from "{0}" which is ' \ - 'not an OpenMC Geometry object'.format(openmc_geometry) - raise ValueError(msg) + cv.check_type('openmc_geometry', openmc_geometry, openmc.Geometry) # Clear dictionaries and auto-generated IDs OPENMC_SURFACES.clear() @@ -1053,6 +1001,7 @@ def get_opencg_geometry(openmc_geometry): opencg_geometry = opencg.Geometry() opencg_geometry.root_universe = opencg_root_universe opencg_geometry.initialize_cell_offsets() + opencg_geometry.assign_auto_ids() return opencg_geometry @@ -1072,10 +1021,7 @@ def get_openmc_geometry(opencg_geometry): """ - if not isinstance(opencg_geometry, opencg.Geometry): - msg = 'Unable to get OpenMC geometry from "{0}" which is ' \ - 'not an OpenCG Geometry object'.format(opencg_geometry) - raise ValueError(msg) + cv.check_type('opencg_geometry', opencg_geometry, opencg.Geometry) # Deep copy the goemetry since it may be modified to make all Surfaces # compatible with OpenMC's specifications diff --git a/openmc/particle_restart.py b/openmc/particle_restart.py index 72bf3ac3d..7a27db2f6 100644 --- a/openmc/particle_restart.py +++ b/openmc/particle_restart.py @@ -37,6 +37,11 @@ class Particle(object): def __init__(self, filename): import h5py + if h5py.__version__ == '2.6.0': + raise ImportError("h5py 2.6.0 has a known bug which makes it " + "incompatible with OpenMC's HDF5 files. " + "Please switch to a different version.") + self._f = h5py.File(filename, 'r') # Ensure filetype and revision are correct diff --git a/openmc/plots.py b/openmc/plots.py index 636ca225c..9167e55d5 100644 --- a/openmc/plots.py +++ b/openmc/plots.py @@ -2,6 +2,7 @@ from collections import Iterable from numbers import Real, Integral from xml.etree import ElementTree as ET import sys +import warnings import numpy as np @@ -125,7 +126,7 @@ class Plot(object): return self._background @property - def mask_componenets(self): + def mask_components(self): return self._mask_components @property @@ -227,7 +228,7 @@ class Plot(object): self._col_spec = col_spec - @mask_componenets.setter + @mask_components.setter def mask_components(self, mask_components): cv.check_type('plot mask_components', mask_components, Iterable, Integral) for component in mask_components: @@ -275,7 +276,7 @@ class Plot(object): The random number seed used to generate the color scheme """ - + cv.check_type('geometry', geometry, openmc.Geometry) cv.check_type('seed', seed, Integral) cv.check_greater_than('seed', seed, 1, equality=True) @@ -401,44 +402,90 @@ class Plot(object): return element -class PlotsFile(object): - """Plots file used for an OpenMC simulation. Corresponds directly to the - plots.xml input file. +class Plots(cv.CheckedList): + """Collection of Plots used for an OpenMC simulation. + + This class corresponds directly to the plots.xml input file. It can be + thought of as a normal Python list where each member is a :class:`Plot`. It + behaves like a list as the following example demonstrates: + + >>> xz_plot = openmc.Plot() + >>> big_plot = openmc.Plot() + >>> small_plot = openmc.Plot() + >>> p = openmc.Plots((xz_plot, big_plot)) + >>> p.append(small_plot) + >>> small_plot = p.pop() + + Parameters + ---------- + plots : Iterable of openmc.Plot + Plots to add to the collection """ - def __init__(self): - # Initialize PlotsFile class attributes - self._plots = [] + def __init__(self, plots=None): + super(Plots, self).__init__(Plot, 'plots collection') self._plots_file = ET.Element("plots") + if plots is not None: + self += plots def add_plot(self, plot): """Add a plot to the file. + .. deprecated:: 0.8 + Use :meth:`Plots.append` instead. + Parameters ---------- - plot : Plot + plot : openmc.Plot Plot to add """ + warnings.warn("Plots.add_plot(...) has been deprecated and may be " + "removed in a future version. Use Plots.append(...) " + "instead.", DeprecationWarning) + self.append(plot) - if not isinstance(plot, Plot): - msg = 'Unable to add a non-Plot "{0}" to the PlotsFile'.format(plot) - raise ValueError(msg) + def append(self, plot): + """Append plot to collection - self._plots.append(plot) + Parameters + ---------- + plot : openmc.Plot + Plot to append + + """ + super(Plots, self).append(plot) + + def insert(self, index, plot): + """Insert plot before index + + Parameters + ---------- + index : int + Index in list + plot : openmc.Plot + Plot to insert + + """ + super(Plots, self).insert(index, plot) def remove_plot(self, plot): """Remove a plot from the file. + .. deprecated:: 0.8 + Use :meth:`Plots.remove` instead. + Parameters ---------- - plot : Plot + plot : openmc.Plot Plot to remove """ - - self._plots.remove(plot) + warnings.warn("Plots.remove_plot(...) has been deprecated and may be " + "removed in a future version. Use Plots.remove(...) " + "instead.", DeprecationWarning) + self.remove(plot) def colorize(self, geometry, seed=1): """Generate a consistent color scheme for each domain in each plot. @@ -456,7 +503,7 @@ class PlotsFile(object): """ - for plot in self._plots: + for plot in self: plot.colorize(geometry, seed) @@ -482,11 +529,11 @@ class PlotsFile(object): """ - for plot in self._plots: + for plot in self: plot.highlight_domains(geometry, domains, seed, alpha, background) def _create_plot_subelements(self): - for plot in self._plots: + for plot in self: xml_element = plot.get_plot_xml() if len(plot._name) > 0: diff --git a/openmc/region.py b/openmc/region.py index 7589184aa..9e1011271 100644 --- a/openmc/region.py +++ b/openmc/region.py @@ -9,10 +9,11 @@ from openmc.checkvalue import check_type class Region(object): """Region of space that can be assigned to a cell. - Region is an abstract base class that is inherited by Halfspace, - Intersection, Union, and Complement. Each of those respective classes are - typically not instantiated directly but rather are created through operators - of the Surface and Region classes. + Region is an abstract base class that is inherited by + :class:`openmc.Halfspace`, :class:`openmc.Intersection`, + :class:`openmc.Union`, and :class:`openmc.Complement`. Each of those + respective classes are typically not instantiated directly but rather are + created through operators of the Surface and Region classes. """ @@ -27,6 +28,10 @@ class Region(object): def __invert__(self): return Complement(self) + @abstractmethod + def __contains__(self, point): + return False + @abstractmethod def __str__(self): return '' @@ -201,11 +206,11 @@ class Intersection(Region): """Intersection of two or more regions. Instances of Intersection are generally created via the __and__ operator - applied to two instances of Region. This is illustrated in the following - example: + applied to two instances of :class:`openmc.Region`. This is illustrated in + the following example: - >>> equator = openmc.surface.ZPlane(z0=0.0) - >>> earth = openmc.surface.Sphere(R=637.1e6) + >>> equator = openmc.ZPlane(z0=0.0) + >>> earth = openmc.Sphere(R=637.1e6) >>> northern_hemisphere = -earth & +equator >>> southern_hemisphere = -earth & -equator >>> type(northern_hemisphere) @@ -213,12 +218,12 @@ class Intersection(Region): Parameters ---------- - *nodes + \*nodes Regions to take the intersection of Attributes ---------- - nodes : tuple of Region + nodes : list of openmc.Region Regions to take the intersection of bounding_box : tuple of numpy.array Lower-left and upper-right coordinates of an axis-aligned bounding box @@ -228,6 +233,26 @@ class Intersection(Region): def __init__(self, *nodes): self.nodes = list(nodes) + def __iter__(self): + for n in self.nodes: + yield n + + def __contains__(self, point): + """Check whether a point is contained in the region. + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates, :math:`(x',y',z')`, of the point + + Returns + ------- + bool + Whether the point is in the region + + """ + return all(point in n for n in self.nodes) + def __str__(self): return '(' + ' '.join(map(str, self.nodes)) + ')' @@ -255,21 +280,22 @@ class Union(Region): """Union of two or more regions. Instances of Union are generally created via the __or__ operator applied to - two instances of Region. This is illustrated in the following example: + two instances of :class:`openmc.Region`. This is illustrated in the + following example: - >>> s1 = openmc.surface.ZPlane(z0=0.0) - >>> s2 = openmc.surface.Sphere(R=637.1e6) + >>> s1 = openmc.ZPlane(z0=0.0) + >>> s2 = openmc.Sphere(R=637.1e6) >>> type(-s2 | +s1) Parameters ---------- - *nodes + \*nodes Regions to take the union of Attributes ---------- - nodes : tuple of Region + nodes : tuple of openmc.Region Regions to take the union of bounding_box : tuple of numpy.array Lower-left and upper-right coordinates of an axis-aligned bounding box @@ -279,6 +305,26 @@ class Union(Region): def __init__(self, *nodes): self.nodes = list(nodes) + def __iter__(self): + for n in self.nodes: + yield n + + def __contains__(self, point): + """Check whether a point is contained in the region. + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates, :math:`(x',y',z')`, of the point + + Returns + ------- + bool + Whether the point is in the region + + """ + return any(point in n for n in self.nodes) + def __str__(self): return '(' + ' | '.join(map(str, self.nodes)) + ')' @@ -305,13 +351,13 @@ class Union(Region): class Complement(Region): """Complement of a region. - The Complement of an existing Region can be created by using the __invert__ - operator as the following example demonstrates: + The Complement of an existing :class:`openmc.Region` can be created by using + the __invert__ operator as the following example demonstrates: - >>> xl = openmc.surface.XPlane(x0=-10.0) - >>> xr = openmc.surface.XPlane(x0=10.0) - >>> yl = openmc.surface.YPlane(y0=-10.0) - >>> yr = openmc.surface.YPlane(y0=10.0) + >>> xl = openmc.XPlane(x0=-10.0) + >>> xr = openmc.XPlane(x0=10.0) + >>> yl = openmc.YPlane(y0=-10.0) + >>> yr = openmc.YPlane(y0=10.0) >>> inside_box = +xl & -xr & +yl & -yl >>> outside_box = ~inside_box >>> type(outside_box) @@ -319,12 +365,12 @@ class Complement(Region): Parameters ---------- - node : Region + node : openmc.Region Region to take the complement of Attributes ---------- - node : Region + node : openmc.Region Regions to take the complement of bounding_box : tuple of numpy.array Lower-left and upper-right coordinates of an axis-aligned bounding box @@ -334,6 +380,22 @@ class Complement(Region): def __init__(self, node): self.node = node + def __contains__(self, point): + """Check whether a point is contained in the region. + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates, :math:`(x',y',z')`, of the point + + Returns + ------- + bool + Whether the point is in the region + + """ + return point not in self.node + def __str__(self): return '~' + str(self.node) diff --git a/openmc/settings.py b/openmc/settings.py index cb0207e71..e64935d7a 100644 --- a/openmc/settings.py +++ b/openmc/settings.py @@ -9,13 +9,14 @@ import numpy as np from openmc.clean_xml import * from openmc.checkvalue import (check_type, check_length, check_value, check_greater_than, check_less_than) +from openmc import Nuclide from openmc.source import Source if sys.version_info[0] >= 3: basestring = str -class SettingsFile(object): +class Settings(object): """Settings file used for an OpenMC simulation. Corresponds directly to the settings.xml input file. @@ -37,7 +38,7 @@ class SettingsFile(object): type are 'variance', 'std_dev', and 'rel_err'. The threshold value should be a float indicating the variance, standard deviation, or relative error used. - source : Iterable of openmc.source.Source + source : Iterable of openmc.Source Distribution of source sites in space, angle, and energy output : dict Dictionary indicating what files to output. Valid keys are 'summary', @@ -69,9 +70,10 @@ class SettingsFile(object): deviation. cross_sections : str Indicates the path to an XML cross section listing file (usually named - cross_sections.xml). If it is not set, the :envvar:`CROSS_SECTIONS` - environment variable will be used for continuous-energy calculations - and :envvar:`MG_CROSS_SECTIONS` will be used for multi-group + cross_sections.xml). If it is not set, the + :envvar:`OPENMC_CROSS_SECTIONS` environment variable will be used for + continuous-energy calculations and + :envvar:`OPENMC_MG_CROSS_SECTIONS` will be used for multi-group calculations to find the path to the XML cross section file. energy_grid : {'nuclide', 'logarithm', 'material-union'} Set the method used to search energy grids. @@ -125,6 +127,8 @@ class SettingsFile(object): Coordinates of the lower-left point of the UFS mesh ufs_upper_right : tuple or list Coordinates of the upper-right point of the UFS mesh + resonance_scattering : ResonanceScattering or iterable of ResonanceScattering + The elastic scattering model to use for resonant isotopes """ @@ -205,6 +209,8 @@ class SettingsFile(object): self._run_mode_subelement = None self._source_element = None + self._resonance_scattering = None + @property def run_mode(self): return self._run_mode @@ -393,9 +399,13 @@ class SettingsFile(object): def dd_count_interactions(self): return self._dd_count_interactions + @property + def resonance_scattering(self): + return self._resonance_scattering + @run_mode.setter def run_mode(self, run_mode): - if 'run_mode' not in ['eigenvalue', 'fixed source']: + if run_mode not in ['eigenvalue', 'fixed source']: msg = 'Unable to set run mode to "{0}". Only "eigenvalue" ' \ 'and "fixed source" are supported."'.format(run_mode) raise ValueError(msg) @@ -764,6 +774,16 @@ class SettingsFile(object): self._dd_count_interactions = interactions + @resonance_scattering.setter + def resonance_scattering(self, res): + if isinstance(res, Iterable): + check_type('resonance_scattering', res, Iterable, + ResonanceScattering) + self._resonance_scattering = res + else: + check_type('resonance_scattering', res, ResonanceScattering) + self._resonance_scattering = [res] + def _create_run_mode_subelement(self): if self.run_mode == 'eigenvalue': @@ -1043,6 +1063,17 @@ class SettingsFile(object): subelement = ET.SubElement(element, "count_interactions") subelement.text = str(self._dd_count_interactions).lower() + def _create_resonance_scattering_element(self): + if self.resonance_scattering is None: return + + element = ET.SubElement(self._settings_file, "resonance_scattering") + + for r in self.resonance_scattering: + if r.nuclide.name != r.nuclide_0K.name: + raise ValueError("The nuclide and nuclide_0K attributes of " + "a ResonantScattering object must have identical names.") + r.create_xml_subelement(element) + def export_to_xml(self): """Create a settings.xml file that can be used for a simulation. @@ -1079,6 +1110,7 @@ class SettingsFile(object): self._create_track_subelement() self._create_ufs_subelement() self._create_dd_subelement() + self._create_resonance_scattering_element() # Clean the indentation in the file to be user-readable clean_xml_indentation(self._settings_file) @@ -1087,3 +1119,104 @@ class SettingsFile(object): tree = ET.ElementTree(self._settings_file) tree.write("settings.xml", xml_declaration=True, encoding='utf-8', method="xml") + + +class ResonanceScattering(object): + """Specification of the elastic scattering model for resonant isotopes + + Attributes + ---------- + nuclide : openmc.Nuclide + The nuclide affected by this resonance scattering treatment. + nuclide_0K : openmc.Nuclide + This should be the same isotope as the nuclide attribute above, but it + should have an xs attribute that identifies 0 Kelvin data. + method : str + The method used to sample outgoing scattering energies. Valid options + are 'ARES', 'CXS' (constant cross section), 'DBRC' (Doppler broadening + rejection correction), and 'WCM' (weight correction method). + E_min : float + The minimum energy above which the specified method is applied. By + default, CXS will be used below E_min. + E_max : float + The maximum energy below which the specified method is applied. By + default, the asymptotic target-at-rest model is applied above E_max. + + """ + + def __init__(self): + self._nuclide = None + self._nuclide_0K = None + self._method = None + self._E_min = None + self._E_max = None + + @property + def nuclide(self): + return self._nuclide + + @property + def nuclide_0K(self): + return self._nuclide_0K + + @property + def method(self): + return self._method + + @property + def E_min(self): + return self._E_min + + @property + def E_max(self): + return self._E_max + + @nuclide.setter + def nuclide(self, nuc): + check_type('nuclide', nuc, Nuclide) + if nuc.zaid == None: raise ValueError("The nuclide must have an " + "explicitly defined zaid attribute.") + self._nuclide = nuc + + @nuclide_0K.setter + def nuclide_0K(self, nuc): + check_type('nuclide_0K', nuc, Nuclide) + if nuc.zaid == None: raise ValueError("The nuclide_0K must have an " + "explicitly defined zaid attribute.") + self._nuclide_0K = nuc + + @method.setter + def method(self, m): + check_value('method', m, ('ARES', 'CXS', 'DBRC', 'WCM')) + self._method = m + + @E_min.setter + def E_min(self, E): + check_type('E_min', E, Real) + check_greater_than('E_min', E, 0, True) + self._E_min = E + + @E_max.setter + def E_max(self, E): + check_type('E_max', E, Real) + check_greater_than('E_max', E, 0, True) + self._E_max = E + + def create_xml_subelement(self, xml_element): + scatterer = ET.SubElement(xml_element, "scatterer") + subelement = ET.SubElement(scatterer, 'nuclide') + subelement.text = self.nuclide.name + if self.method is not None: + subelement = ET.SubElement(scatterer, 'method') + subelement.text = self.method + subelement = ET.SubElement(scatterer, 'xs_label') + subelement.text = str(self.nuclide.zaid) + '.' + str(self.nuclide.xs) + subelement = ET.SubElement(scatterer, 'xs_label_0K') + subelement.text = str(self.nuclide_0K.zaid) + '.' \ + + str(self.nuclide_0K.xs) + if self.E_min is not None: + subelement = ET.SubElement(scatterer, 'E_min') + subelement.text = str(self.E_min) + if self.E_max is not None: + subelement = ET.SubElement(scatterer, 'E_max') + subelement.text = str(self.E_max) diff --git a/openmc/statepoint.py b/openmc/statepoint.py index 003b08818..0baa63158 100644 --- a/openmc/statepoint.py +++ b/openmc/statepoint.py @@ -1,5 +1,8 @@ import sys import re +import os +import warnings + import numpy as np import openmc @@ -14,63 +17,74 @@ class StatePoint(object): of a given batch). Statepoints can be used to analyze tally results as well as restart a simulation. + Parameters + ---------- + filename : str + Path to file to load + autolink : bool, optional + Whether to automatically link in metadata from a summary.h5 + file. Defaults to True. + Attributes ---------- cmfd_on : bool Indicate whether CMFD is active - cmfd_balance : ndarray + cmfd_balance : numpy.ndarray Residual neutron balance for each batch cmfd_dominance Dominance ratio for each batch - cmfd_entropy : ndarray + cmfd_entropy : numpy.ndarray Shannon entropy of CMFD fission source for each batch - cmfd_indices : ndarray + cmfd_indices : numpy.ndarray Number of CMFD mesh cells and energy groups. The first three indices correspond to the x-, y-, and z- spatial directions and the fourth index is the number of energy groups. - cmfd_srccmp : ndarray + cmfd_srccmp : numpy.ndarray Root-mean-square difference between OpenMC and CMFD fission source for each batch - cmfd_src : ndarray + cmfd_src : numpy.ndarray CMFD fission source distribution over all mesh cells and energy groups. - current_batch : Integral + current_batch : int Number of batches simulated date_and_time : str Date and time when simulation began - entropy : ndarray + entropy : numpy.ndarray Shannon entropy of fission source at each batch gen_per_batch : Integral Number of fission generations per batch - global_tallies : ndarray of compound datatype + global_tallies : numpy.ndarray of compound datatype Global tallies for k-effective estimates and leakage. The compound datatype has fields 'name', 'sum', 'sum_sq', 'mean', and 'std_dev'. k_combined : list Combined estimator for k-effective and its uncertainty - k_col_abs : Real + k_col_abs : float Cross-product of collision and absorption estimates of k-effective - k_col_tra : Real + k_col_tra : float Cross-product of collision and tracklength estimates of k-effective - k_abs_tra : Real + k_abs_tra : float Cross-product of absorption and tracklength estimates of k-effective - k_generation : ndarray + k_generation : numpy.ndarray Estimate of k-effective for each batch/generation meshes : dict Dictionary whose keys are mesh IDs and whose values are Mesh objects - n_batches : Integral + n_batches : int Number of batches - n_inactive : Integral + n_inactive : int Number of inactive batches - n_particles : Integral + n_particles : int Number of particles per generation - n_realizations : Integral + n_realizations : int Number of tally realizations path : str Working directory for simulation run_mode : str Simulation run mode, e.g. 'k-eigenvalue' - seed : Integral + runtime : dict + Dictionary whose keys are strings describing various runtime metrics + and whose values are time values in seconds. + seed : int Pseudorandom number generator seed - source : ndarray of compound datatype + source : numpy.ndarray of compound datatype Array of source sites. The compound datatype has fields 'wgt', 'xyz', 'uvw', and 'E' corresponding to the weight, position, direction, and energy of the source site. @@ -85,13 +99,18 @@ class StatePoint(object): Indicate whether user-defined tallies are present version: tuple of Integral Version of OpenMC - summary : None or openmc.summary.Summary + summary : None or openmc.Summary A summary object if the statepoint has been linked with a summary file """ - def __init__(self, filename): + def __init__(self, filename, autolink=True): import h5py + if h5py.__version__ == '2.6.0': + raise ImportError("h5py 2.6.0 has a known bug which makes it " + "incompatible with OpenMC's HDF5 files. " + "Please switch to a different version.") + self._f = h5py.File(filename, 'r') # Ensure filetype and revision are correct @@ -101,8 +120,9 @@ class StatePoint(object): raise IOError('{} is not a statepoint file.'.format(filename)) except AttributeError: raise IOError('Could not read statepoint file. This most likely ' - 'means the statepoint file was produced by a different ' - 'version of OpenMC than the one you are using.') + 'means the statepoint file was produced by a ' + 'different version of OpenMC than the one you are ' + 'using.') if self._f['revision'].value != 15: raise IOError('Statepoint file has a file revision of {} ' 'which is not consistent with the revision this ' @@ -112,10 +132,17 @@ class StatePoint(object): # Set flags for what data has been read self._meshes_read = False self._tallies_read = False - self._summary = False + self._summary = None self._global_tallies = None self._sparse = False + # Automatically link in a summary file if one exists + if autolink: + path_summary = os.path.join(os.path.dirname(filename), 'summary.h5') + if os.path.exists(path_summary): + su = openmc.Summary(path_summary) + self.link_with_summary(su) + def close(self): self._f.close() @@ -311,6 +338,11 @@ class StatePoint(object): def run_mode(self): return self._f['run_mode'].value.decode() + @property + def runtime(self): + return {name: dataset.value + for name, dataset in self._f['runtime'].items()} + @property def seed(self): return self._f['seed'].value @@ -389,7 +421,7 @@ class StatePoint(object): new_filter.mesh = self.meshes[key] # Add Filter to the Tally - tally.add_filter(new_filter) + tally.filters.append(new_filter) # Read Nuclide bins nuclide_names = \ @@ -398,7 +430,7 @@ class StatePoint(object): # Add all Nuclides to the Tally for name in nuclide_names: nuclide = openmc.Nuclide(name.decode().strip()) - tally.add_nuclide(nuclide) + tally.nuclides.append(nuclide) scores = self._f['{0}{1}/score_bins'.format( base, tally_key)].value @@ -425,7 +457,7 @@ class StatePoint(object): pattern = r'-n$|-pn$|-yn$' score = re.sub(pattern, '-' + moments[j].decode(), score) - tally.add_score(score) + tally.scores.append(score) # Add Tally to the global dictionary of all Tallies tally.sparse = self.sparse @@ -470,13 +502,18 @@ class StatePoint(object): self.tallies[tally_id].sparse = self.sparse def get_tally(self, scores=[], filters=[], nuclides=[], - name=None, id=None, estimator=None): + name=None, id=None, estimator=None, exact_filters=False, + exact_nuclides=False, exact_scores=False): """Finds and returns a Tally object with certain properties. This routine searches the list of Tallies and returns the first Tally found which satisfies all of the input parameters. - NOTE: The input parameters do not need to match the complete Tally - specification and may only represent a subset of the Tally's properties. + + NOTE: If any of the "exact" parameters are False (default), the input + parameters do not need to match the complete Tally specification and + may only represent a subset of the Tally's properties. If an "exact" + parameter is True then number of scores, filters, or nuclides in the + parameters must precisely match those of any matching Tally. Parameters ---------- @@ -492,10 +529,22 @@ class StatePoint(object): The id specified for the Tally (default is None). estimator: str, optional The type of estimator ('tracklength', 'analog'; default is None). + exact_filters : bool + If True, the number of filters in the parameters must be identical + to those in the matching Tally. If False (default), the filters in + the parameters may be a subset of those in the matching Tally. + exact_nuclides : bool + If True, the number of nuclides in the parameters must be identical + to those in the matching Tally. If False (default), the nuclides in + the parameters may be a subset of those in the matching Tally. + exact_scores : bool + If True, the number of scores in the parameters must be identical + to those in the matching Tally. If False (default), the scores + in the parameters may be a subset of those in the matching Tally. Returns ------- - tally : Tally + tally : openmc.Tally A tally matching the specified criteria Raises @@ -520,7 +569,15 @@ class StatePoint(object): continue # Determine if Tally has queried estimator - if estimator and not estimator == test_tally.estimator: + if estimator and estimator != test_tally.estimator: + continue + + # The number of filters, nuclides and scores must exactly match + if exact_scores and len(scores) != test_tally.num_scores: + continue + if exact_nuclides and len(nuclides) != test_tally.num_nuclides: + continue + if exact_filters and len(filters) != test_tally.num_filters: continue # Determine if Tally has the queried score(s) @@ -592,7 +649,7 @@ class StatePoint(object): Parameters ---------- - summary : Summary + summary : openmc.Summary A Summary object. Raises @@ -603,17 +660,24 @@ class StatePoint(object): """ + if self.summary is not None: + warnings.warn('A Summary object has already been linked.', + RuntimeWarning) + return + if not isinstance(summary, openmc.summary.Summary): msg = 'Unable to link statepoint with "{0}" which ' \ 'is not a Summary object'.format(summary) raise ValueError(msg) for tally_id, tally in self.tallies.items(): - # Get the Tally name from the summary file - tally.name = summary.tallies[tally_id].name + summary_tally = summary.tallies[tally_id] + tally.name = summary_tally.name tally.with_summary = True for tally_filter in tally.filters: + summary_filter = summary_tally.find_filter(tally_filter.type) + if tally_filter.type == 'surface': surface_ids = [] for bin in tally_filter.bins: @@ -626,6 +690,10 @@ class StatePoint(object): distribcell_ids.append(summary.cells[bin].id) tally_filter.bins = distribcell_ids + if tally_filter.type == 'distribcell': + tally_filter.distribcell_paths = \ + summary_filter.distribcell_paths + if tally_filter.type == 'universe': universe_ids = [] for bin in tally_filter.bins: diff --git a/openmc/stats/multivariate.py b/openmc/stats/multivariate.py index 29258ee8d..e4eadd7aa 100644 --- a/openmc/stats/multivariate.py +++ b/openmc/stats/multivariate.py @@ -22,12 +22,12 @@ class UnitSphere(object): Parameters ---------- - reference_uvw : Iterable of Real + reference_uvw : Iterable of float Direction from which polar angle is measured Attributes ---------- - reference_uvw : Iterable of Real + reference_uvw : Iterable of float Direction from which polar angle is measured """ @@ -62,19 +62,19 @@ class PolarAzimuthal(UnitSphere): Parameters ---------- - mu : Univariate + mu : openmc.stats.Univariate Distribution of the cosine of the polar angle - phi : Univariate + phi : openmc.stats.Univariate Distribution of the azimuthal angle in radians - reference_uvw : Iterable of Real + reference_uvw : Iterable of float Direction from which polar angle is measured. Defaults to the positive z-direction. Attributes ---------- - mu : Univariate + mu : openmc.stats.Univariate Distribution of the cosine of the polar angle - phi : Univariate + phi : openmc.stats.Univariate Distribution of the azimuthal angle in radians """ @@ -142,7 +142,7 @@ class Monodirectional(UnitSphere): Parameters ---------- - reference_uvw : Iterable of Real + reference_uvw : Iterable of float Direction from which polar angle is measured. Defaults to the positive x-direction. @@ -186,20 +186,20 @@ class CartesianIndependent(Spatial): Parameters ---------- - x : Univariate + x : openmc.stats.Univariate Distribution of x-coordinates - y : Univariate + y : openmc.stats.Univariate Distribution of y-coordinates - z : Univariate + z : openmc.stats.Univariate Distribution of z-coordinates Attributes ---------- - x : Univariate + x : openmc.stats.Univariate Distribution of x-coordinates - y : Univariate + y : openmc.stats.Univariate Distribution of y-coordinates - z : Univariate + z : openmc.stats.Univariate Distribution of z-coordinates """ @@ -252,9 +252,9 @@ class Box(Spatial): Parameters ---------- - lower_left : Iterable of Real + lower_left : Iterable of float Lower-left coordinates of cuboid - upper_right : Iterable of Real + upper_right : Iterable of float Upper-right coordinates of cuboid only_fissionable : bool, optional Whether spatial sites should only be accepted if they occur in @@ -262,9 +262,9 @@ class Box(Spatial): Attributes ---------- - lower_left : Iterable of Real + lower_left : Iterable of float Lower-left coordinates of cuboid - upper_right : Iterable of Real + upper_right : Iterable of float Upper-right coordinates of cuboid only_fissionable : bool, optional Whether spatial sites should only be accepted if they occur in @@ -328,17 +328,17 @@ class Point(Spatial): Parameters ---------- - xyz : Iterable of Real - Cartesian coordinates of location + xyz : Iterable of float, optional + Cartesian coordinates of location. Defaults to (0., 0., 0.). Attributes ---------- - xyz : Iterable of Real + xyz : Iterable of float Cartesian coordinates of location """ - def __init__(self, xyz): + def __init__(self, xyz=(0., 0., 0.)): super(Point, self).__init__() self.xyz = xyz diff --git a/openmc/stats/univariate.py b/openmc/stats/univariate.py index 04e70bd00..af9b9b301 100644 --- a/openmc/stats/univariate.py +++ b/openmc/stats/univariate.py @@ -37,16 +37,16 @@ class Discrete(Univariate): Parameters ---------- - x : Iterable of Real + x : Iterable of float Values of the random variable - p : Iterable of Real + p : Iterable of float Discrete probability for each value Attributes ---------- - x : Iterable of Real + x : Iterable of float Values of the random variable - p : Iterable of Real + p : Iterable of float Discrete probability for each value """ @@ -66,14 +66,14 @@ class Discrete(Univariate): @x.setter def x(self, x): - if cv._isinstance(x, Real): + if isinstance(x, Real): x = [x] cv.check_type('discrete values', x, Iterable, Real) self._x = x @p.setter def p(self, p): - if cv._isinstance(p, Real): + if isinstance(p, Real): p = [p] cv.check_type('discrete probabilities', p, Iterable, Real) for pk in p: @@ -243,9 +243,9 @@ class Tabular(Univariate): Parameters ---------- - x : Iterable of Real + x : Iterable of float Tabulated values of the random variable - p : Iterable of Real + p : Iterable of float Tabulated probabilities interpolation : {'histogram', 'linear-linear'}, optional Indicate whether the density function is constant between tabulated @@ -253,9 +253,9 @@ class Tabular(Univariate): Attributes ---------- - x : Iterable of Real + x : Iterable of float Tabulated values of the random variable - p : Iterable of Real + p : Iterable of float Tabulated probabilities interpolation : {'histogram', 'linear-linear'}, optional Indicate whether the density function is constant between tabulated diff --git a/openmc/summary.py b/openmc/summary.py index 0d232fb07..d5259247f 100644 --- a/openmc/summary.py +++ b/openmc/summary.py @@ -26,6 +26,10 @@ class Summary(object): # Python API so we'll only try to import h5py if the user actually inits # a Summary object. import h5py + if h5py.__version__ == '2.6.0': + raise ImportError("h5py 2.6.0 has a known bug which makes it " + "incompatible with OpenMC's HDF5 files. " + "Please switch to a different version.") openmc.reset_auto_ids() @@ -38,8 +42,10 @@ class Summary(object): self._opencg_geometry = None self._read_metadata() + self._read_nuclides() self._read_geometry() self._read_tallies() + self._f.close() @property def openmc_geometry(self): @@ -55,8 +61,8 @@ class Summary(object): def _read_metadata(self): # Read OpenMC version self.version = [self._f['version_major'].value, - self._f['version_minor'].value, - self._f['version_release'].value] + self._f['version_minor'].value, + self._f['version_release'].value] # Read date and time self.date_and_time = self._f['date_and_time'][...] @@ -65,11 +71,23 @@ class Summary(object): self.n_batches = self._f['n_batches'].value self.n_particles = self._f['n_particles'].value - self.n_active = self._f['n_active'].value - self.n_inactive = self._f['n_inactive'].value - self.gen_per_batch = self._f['gen_per_batch'].value + if 'n_inactive' in self._f: + self.n_active = self._f['n_active'].value + self.n_inactive = self._f['n_inactive'].value + self.gen_per_batch = self._f['gen_per_batch'].value self.n_procs = self._f['n_procs'].value + def _read_nuclides(self): + self.nuclides = {} + n_nuclides = self._f['nuclides/n_nuclides_total'].value + names = self._f['nuclides/names'].value + awrs = self._f['nuclides/awrs'].value + zaids = self._f['nuclides/zaids'].value + for n in range(n_nuclides): + name = names[n].decode() + name = name[:name.find('.')] + self.nuclides[name] = (zaids[n], awrs[n]) + def _read_geometry(self): # Read in and initialize the Materials and Geometry self._read_materials() @@ -266,7 +284,7 @@ class Summary(object): rotation = \ self._f['geometry/cells'][key]['rotation'][...] rotation = np.asarray(rotation, dtype=np.int) - cell.rotation = rotation + cell._rotation = rotation # Store Cell fill information for after Universe/Lattice creation self._cell_fills[index] = (fill_type, fill) @@ -344,7 +362,6 @@ class Summary(object): # Create the Lattice lattice = openmc.RectLattice(lattice_id=lattice_id, name=name) - lattice.dimension = tuple(dimension) lattice.lower_left = lower_left lattice.pitch = pitch @@ -354,7 +371,7 @@ class Summary(object): # Build array of Universe pointers for the Lattice universes = \ - np.ndarray(tuple(universe_ids.shape), dtype=openmc.Universe) + np.empty(tuple(universe_ids.shape), dtype=openmc.Universe) for z in range(universe_ids.shape[0]): for y in range(universe_ids.shape[1]): @@ -378,19 +395,17 @@ class Summary(object): self.lattices[index] = lattice if lattice_type == 'hexagonal': - n_rings = self._f['geometry/lattices'][key]['n_rings'][0] - n_axial = self._f['geometry/lattices'][key]['n_axial'][0] + n_rings = self._f['geometry/lattices'][key]['n_rings'].value + n_axial = self._f['geometry/lattices'][key]['n_axial'].value center = self._f['geometry/lattices'][key]['center'][...] pitch = self._f['geometry/lattices'][key]['pitch'][...] - outer = self._f['geometry/lattices'][key]['outer'][0] + outer = self._f['geometry/lattices'][key]['outer'].value universe_ids = self._f[ 'geometry/lattices'][key]['universes'][...] # Create the Lattice lattice = openmc.HexLattice(lattice_id=lattice_id, name=name) - lattice.num_rings = n_rings - lattice.num_axial = n_axial lattice.center = center lattice.pitch = pitch @@ -403,12 +418,12 @@ class Summary(object): # (x, alpha, z) to the Python API's format of a ragged nested # list of (z, ring, theta). universes = [] - for z in range(lattice.num_axial): + for z in range(n_axial): # Add a list for this axial level. universes.append([]) - x = lattice.num_rings - 1 - a = 2*lattice.num_rings - 2 - for r in range(lattice.num_rings - 1, 0, -1): + x = n_rings - 1 + a = 2*n_rings - 2 + for r in range(n_rings - 1, 0, -1): # Add a list for this ring. universes[-1].append([]) @@ -482,13 +497,13 @@ class Summary(object): # Retrieve the object corresponding to the fill type and ID if fill_type == 'normal': if isinstance(fill_id, Iterable): - fill = [self.get_material_by_id(mat) if mat > 0 else 'void' + fill = [self.get_material_by_id(mat) if mat > 0 else None for mat in fill_id] else: if fill_id > 0: fill = self.get_material_by_id(fill_id) else: - fill = 'void' + fill = None elif fill_type == 'universe': fill = self.get_universe_by_id(fill_id) else: @@ -542,7 +557,7 @@ class Summary(object): # If this is a moment, use generic moment order pattern = r'-n$|-pn$|-yn$' score = re.sub(pattern, '-' + moments[j].decode(), score) - tally.add_score(score) + tally.scores.append(score) # Read filter metadata num_filters = self._f['{0}/n_filters'.format(subbase)].value @@ -562,8 +577,14 @@ class Summary(object): new_filter = openmc.Filter(filter_type, bins) new_filter.num_bins = num_bins + # Read in distribcell paths + if filter_type == 'distribcell': + paths = self._f['{0}/paths'.format(subsubbase)][...] + paths = [str(path.decode()) for path in paths] + new_filter.distribcell_paths = paths + # Add Filter to the Tally - tally.add_filter(new_filter) + tally.filters.append(new_filter) # Add Tally to the global dictionary of all Tallies self.tallies[tally_id] = tally @@ -578,7 +599,7 @@ class Summary(object): Returns ------- - material : openmc.material.Material + material : openmc.Material Material with given id """ @@ -599,7 +620,7 @@ class Summary(object): Returns ------- - surface : openmc.surface.Surface + surface : openmc.Surface Surface with given id """ @@ -620,7 +641,7 @@ class Summary(object): Returns ------- - cell : openmc.universe.Cell + cell : openmc.Cell Cell with given id """ @@ -641,7 +662,7 @@ class Summary(object): Returns ------- - universe : openmc.universe.Universe + universe : openmc.Universe Universe with given id """ @@ -662,7 +683,7 @@ class Summary(object): Returns ------- - lattice : openmc.universe.Lattice + lattice : openmc.Lattice Lattice with given id """ diff --git a/openmc/surface.py b/openmc/surface.py index 8dc45209b..76f0d82e7 100644 --- a/openmc/surface.py +++ b/openmc/surface.py @@ -2,11 +2,12 @@ from abc import ABCMeta from numbers import Real, Integral from xml.etree import ElementTree as ET import sys +from math import sqrt import numpy as np from openmc.checkvalue import check_type, check_value, check_greater_than -from openmc.region import Region +from openmc.region import Region, Intersection if sys.version_info[0] >= 3: basestring = str @@ -23,8 +24,11 @@ def reset_auto_surface_id(): class Surface(object): - """A two-dimensional surface that can be used define regions of space with an - associated boundary condition. + """An implicit surface with an associated boundary condition. + + An implicit surface is defined as the set of zeros of a function of the + three Cartesian coordinates. Surfaces in OpenMC are limited to a set of + algebraic surfaces, i.e., surfaces that are polynomial in x, y, and z. Parameters ---------- @@ -34,7 +38,9 @@ class Surface(object): boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. + freely pass through the surface. Note that periodic boundary conditions + can only be applied to x-, y-, and z-planes, and only axis-aligned + periodicity is supported. name : str, optional Name of the surface. If not specified, the name will be the empty string. @@ -44,19 +50,18 @@ class Surface(object): boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} Boundary condition that defines the behavior for particles hitting the surface. - coeffs : dict + coefficients : dict Dictionary of surface coefficients id : int Unique identifier for the surface name : str Name of the surface type : str - Type of the surface, e.g. 'x-plane' + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', name=''): - # Initialize class attributes self.id = surface_id self.name = name self._type = '' @@ -65,7 +70,7 @@ class Surface(object): # A dictionary of the quadratic surface coefficients # Key - coefficeint name # Value - coefficient value - self._coeffs = {} + self._coefficients = {} # An ordered list of the coefficient names to export to XML in the # proper order @@ -84,12 +89,13 @@ class Surface(object): string += '{0: <16}{1}{2}\n'.format('\tType', '=\t', self._type) string += '{0: <16}{1}{2}\n'.format('\tBoundary', '=\t', self._boundary_type) - coeffs = '{0: <16}'.format('\tCoefficients') + '\n' + coefficients = '{0: <16}'.format('\tCoefficients') + '\n' - for coeff in self._coeffs: - coeffs += '{0: <16}{1}{2}\n'.format(coeff, '=\t', self._coeffs[coeff]) + for coeff in self._coefficients: + coefficients += '{0: <16}{1}{2}\n'.format( + coeff, '=\t', self._coefficients[coeff]) - string += coeffs + string += coefficients return string @@ -110,8 +116,8 @@ class Surface(object): return self._boundary_type @property - def coeffs(self): - return self._coeffs + def coefficients(self): + return self._coefficients @id.setter def id(self, surface_id): @@ -153,10 +159,10 @@ class Surface(object): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -173,8 +179,9 @@ class Surface(object): element.set("name", str(self._name)) element.set("type", self._type) - element.set("boundary", self._boundary_type) - element.set("coeffs", ' '.join([str(self._coeffs.setdefault(key, 0.0)) + if self.boundary_type != 'transmission': + element.set("boundary", self.boundary_type) + element.set("coeffs", ' '.join([str(self._coefficients.setdefault(key, 0.0)) for key in self._coeff_keys])) return element @@ -185,22 +192,22 @@ class Plane(Surface): Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - A : float - The 'A' parameter for the plane - B : float - The 'B' parameter for the plane - C : float - The 'C' parameter for the plane - D : float - The 'D' parameter for the plane - name : str + A : float, optional + The 'A' parameter for the plane. Defaults to 1. + B : float, optional + The 'B' parameter for the plane. Defaults to 0. + C : float, optional + The 'C' parameter for the plane. Defaults to 0. + D : float, optional + The 'D' parameter for the plane. Defaults to 0. + name : str, optional Name of the plane. If not specified, the name will be the empty string. Attributes @@ -213,115 +220,165 @@ class Plane(Surface): The 'C' parameter for the plane d : float The 'D' parameter for the plane + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + periodic_surface : openmc.Surface + If a periodic boundary condition is used, the surface with which this + one is periodic with + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - A=None, B=None, C=None, D=None, name=''): - # Initialize Plane class attributes + A=1., B=0., C=0., D=0., name=''): super(Plane, self).__init__(surface_id, boundary_type, name=name) self._type = 'plane' self._coeff_keys = ['A', 'B', 'C', 'D'] - self._coeffs['A'] = 1. - self._coeffs['B'] = 0. - self._coeffs['C'] = 0. - self._coeffs['D'] = 0. - - if A is not None: - self.a = A - - if B is not None: - self.b = B - - if C is not None: - self.c = C - - if D is not None: - self.d = D + self._periodic_surface = None + self.a = A + self.b = B + self.c = C + self.d = D @property def a(self): - return self.coeffs['A'] + return self.coefficients['A'] @property def b(self): - return self.coeffs['B'] + return self.coefficients['B'] @property def c(self): - return self.coeffs['C'] + return self.coefficients['C'] @property def d(self): - return self.coeffs['D'] + return self.coefficients['D'] + + @property + def periodic_surface(self): + return self._periodic_surface @a.setter def a(self, A): check_type('A coefficient', A, Real) - self._coeffs['A'] = A + self._coefficients['A'] = A @b.setter def b(self, B): check_type('B coefficient', B, Real) - self._coeffs['B'] = B + self._coefficients['B'] = B @c.setter def c(self, C): check_type('C coefficient', C, Real) - self._coeffs['C'] = C + self._coefficients['C'] = C @d.setter def d(self, D): check_type('D coefficient', D, Real) - self._coeffs['D'] = D + self._coefficients['D'] = D + + @periodic_surface.setter + def periodic_surface(self, periodic_surface): + check_type('periodic surface', periodic_surface, Plane) + self._periodic_surface = periodic_surface + periodic_surface._periodic_surface = self + + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`Ax' + By' + Cz' - d` + + """ + + x, y, z = point + return self.a*x + self.b*y + self.c*z - self.d + + def create_xml_subelement(self): + element = super(Plane, self).create_xml_subelement() + + # Add periodic surface pair information + if self.boundary_type == 'periodic': + if self.periodic_surface is not None: + element.set("periodic_surface_id", str(self.periodic_surface.id)) + return element class XPlane(Plane): - """A plane perpendicular to the x axis, i.e. a surface of the form :math:`x - - x_0 = 0` + """A plane perpendicular to the x axis of the form :math:`x - x_0 = 0` Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. - x0 : float - Location of the plane - name : str + freely pass through the surface. Only axis-aligned periodicity is + supported, i.e., x-planes can only be paired with x-planes. + x0 : float, optional + Location of the plane. Defaults to 0. + name : str, optional Name of the plane. If not specified, the name will be the empty string. Attributes ---------- x0 : float Location of the plane + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + Boundary condition that defines the behavior for particles hitting the + surface. + periodic_surface : openmc.Surface + If a periodic boundary condition is used, the surface with which this + one is periodic with + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, name=''): - # Initialize XPlane class attributes + x0=0., name=''): super(XPlane, self).__init__(surface_id, boundary_type, name=name) self._type = 'x-plane' self._coeff_keys = ['x0'] - self._coeffs['x0'] = 0. - - if x0 is not None: - self.x0 = x0 + self.x0 = x0 @property def x0(self): - return self.coeffs['x0'] + return self.coefficients['x0'] @x0.setter def x0(self, x0): check_type('x0 coefficient', x0, Real) - self._coeffs['x0'] = x0 + self._coefficients['x0'] = x0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -338,10 +395,10 @@ class XPlane(Plane): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -354,52 +411,80 @@ class XPlane(Plane): return (np.array([self.x0, -np.inf, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`x' - x_0` + + """ + return point[0] - self.x0 + class YPlane(Plane): - """A plane perpendicular to the y axis, i.e. a surface of the form :math:`y - - y_0 = 0` + """A plane perpendicular to the y axis of the form :math:`y - y_0 = 0` Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. - y0 : float + freely pass through the surface. Only axis-aligned periodicity is + supported, i.e., x-planes can only be paired with x-planes. + y0 : float, optional Location of the plane - name : str + name : str, optional Name of the plane. If not specified, the name will be the empty string. Attributes ---------- y0 : float Location of the plane + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + Boundary condition that defines the behavior for particles hitting the + surface. + periodic_surface : openmc.Surface + If a periodic boundary condition is used, the surface with which this + one is periodic with + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - y0=None, name=''): + y0=0., name=''): # Initialize YPlane class attributes super(YPlane, self).__init__(surface_id, boundary_type, name=name) self._type = 'y-plane' self._coeff_keys = ['y0'] - self._coeffs['y0'] = 0. - - if y0 is not None: - self.y0 = y0 + self.y0 = y0 @property def y0(self): - return self.coeffs['y0'] + return self.coefficients['y0'] @y0.setter def y0(self, y0): check_type('y0 coefficient', y0, Real) - self._coeffs['y0'] = y0 + self._coefficients['y0'] = y0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -416,10 +501,10 @@ class YPlane(Plane): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -432,52 +517,80 @@ class YPlane(Plane): return (np.array([-np.inf, self.y0, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`y' - y_0` + + """ + return point[1] - self.y0 + class ZPlane(Plane): - """A plane perpendicular to the z axis, i.e. a surface of the form :math:`z - - z_0 = 0` + """A plane perpendicular to the z axis of the form :math:`z - z_0 = 0` Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. - z0 : float - Location of the plane - name : str + freely pass through the surface. Only axis-aligned periodicity is + supported, i.e., x-planes can only be paired with x-planes. + z0 : float, optional + Location of the plane. Defaults to 0. + name : str, optional Name of the plane. If not specified, the name will be the empty string. Attributes ---------- z0 : float Location of the plane + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + Boundary condition that defines the behavior for particles hitting the + surface. + periodic_surface : openmc.Surface + If a periodic boundary condition is used, the surface with which this + one is periodic with + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - z0=None, name=''): + z0=0., name=''): # Initialize ZPlane class attributes super(ZPlane, self).__init__(surface_id, boundary_type, name=name) self._type = 'z-plane' self._coeff_keys = ['z0'] - self._coeffs['z0'] = 0. - - if z0 is not None: - self.z0 = z0 + self.z0 = z0 @property def z0(self): - return self.coeffs['z0'] + return self.coefficients['z0'] @z0.setter def z0(self, z0): check_type('z0 coefficient', z0, Real) - self._coeffs['z0'] = z0 + self._coefficients['z0'] = z0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -494,10 +607,10 @@ class ZPlane(Plane): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -510,22 +623,39 @@ class ZPlane(Plane): return (np.array([-np.inf, -np.inf, self.z0]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`z' - z_0` + + """ + return point[2] - self.z0 + class Cylinder(Surface): """A cylinder whose length is parallel to the x-, y-, or z-axis. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - R : float - Radius of the cylinder - name : str + R : float, optional + Radius of the cylinder. Defaults to 1. + name : str, optional Name of the cylinder. If not specified, the name will be the empty string. @@ -533,52 +663,59 @@ class Cylinder(Surface): ---------- r : float Radius of the cylinder + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ __metaclass__ = ABCMeta def __init__(self, surface_id=None, boundary_type='transmission', - R=None, name=''): - # Initialize Cylinder class attributes + R=1., name=''): super(Cylinder, self).__init__(surface_id, boundary_type, name=name) self._coeff_keys = ['R'] - self._coeffs['R'] = 1. - - if R is not None: - self.r = R + self.r = R @property def r(self): - return self.coeffs['R'] + return self.coefficients['R'] @r.setter def r(self, R): check_type('R coefficient', R, Real) - self._coeffs['R'] = R + self._coefficients['R'] = R class XCylinder(Cylinder): - """An infinite cylinder whose length is parallel to the x-axis. This is a - quadratic surface of the form :math:`(y - y_0)^2 + (z - z_0)^2 = R^2`. + """An infinite cylinder whose length is parallel to the x-axis of the form + :math:`(y - y_0)^2 + (z - z_0)^2 = R^2`. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - y0 : float - y-coordinate of the center of the cylinder - z0 : float - z-coordinate of the center of the cylinder - R : float - Radius of the cylinder - name : str + y0 : float, optional + y-coordinate of the center of the cylinder. Defaults to 0. + z0 : float, optional + z-coordinate of the center of the cylinder. Defaults to 0. + R : float, optional + Radius of the cylinder. Defaults to 0. + name : str, optional Name of the cylinder. If not specified, the name will be the empty string. @@ -588,42 +725,46 @@ class XCylinder(Cylinder): y-coordinate of the center of the cylinder z0 : float z-coordinate of the center of the cylinder + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - y0=None, z0=None, R=None, name=''): - # Initialize XCylinder class attributes + y0=0., z0=0., R=1., name=''): super(XCylinder, self).__init__(surface_id, boundary_type, R, name=name) self._type = 'x-cylinder' self._coeff_keys = ['y0', 'z0', 'R'] - self._coeffs['y0'] = 0. - self._coeffs['z0'] = 0. - - if y0 is not None: - self.y0 = y0 - - if z0 is not None: - self.z0 = z0 + self.y0 = y0 + self.z0 = z0 @property def y0(self): - return self.coeffs['y0'] + return self.coefficients['y0'] @property def z0(self): - return self.coeffs['z0'] + return self.coefficients['z0'] @y0.setter def y0(self, y0): check_type('y0 coefficient', y0, Real) - self._coeffs['y0'] = y0 + self._coefficients['y0'] = y0 @z0.setter def z0(self, z0): check_type('z0 coefficient', z0, Real) - self._coeffs['z0'] = z0 + self._coefficients['z0'] = z0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -641,10 +782,10 @@ class XCylinder(Cylinder): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -657,27 +798,46 @@ class XCylinder(Cylinder): return (np.array([-np.inf, -np.inf, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(y' - y_0)^2 + (z' - z_0)^2 - R^2` + + """ + y = point[1] - self.y0 + z = point[2] - self.z0 + return y**2 + z**2 - self.r**2 + class YCylinder(Cylinder): - """An infinite cylinder whose length is parallel to the y-axis. This is a - quadratic surface of the form :math:`(x - x_0)^2 + (z - z_0)^2 = R^2`. + """An infinite cylinder whose length is parallel to the y-axis of the form + :math:`(x - x_0)^2 + (z - z_0)^2 = R^2`. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the center of the cylinder - z0 : float - z-coordinate of the center of the cylinder - R : float - Radius of the cylinder - name : str + x0 : float, optional + x-coordinate of the center of the cylinder. Defaults to 0. + z0 : float, optional + z-coordinate of the center of the cylinder. Defaults to 0. + R : float, optional + Radius of the cylinder. Defaults to 1. + name : str, optional Name of the cylinder. If not specified, the name will be the empty string. @@ -687,42 +847,46 @@ class YCylinder(Cylinder): x-coordinate of the center of the cylinder z0 : float z-coordinate of the center of the cylinder + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, z0=None, R=None, name=''): - # Initialize YCylinder class attributes + x0=0., z0=0., R=1., name=''): super(YCylinder, self).__init__(surface_id, boundary_type, R, name=name) self._type = 'y-cylinder' self._coeff_keys = ['x0', 'z0', 'R'] - self._coeffs['x0'] = 0. - self._coeffs['z0'] = 0. - - if x0 is not None: - self.x0 = x0 - - if z0 is not None: - self.z0 = z0 + self.x0 = x0 + self.z0 = z0 @property def x0(self): - return self.coeffs['x0'] + return self.coefficients['x0'] @property def z0(self): - return self.coeffs['z0'] + return self.coefficients['z0'] @x0.setter def x0(self, x0): check_type('x0 coefficient', x0, Real) - self._coeffs['x0'] = x0 + self._coefficients['x0'] = x0 @z0.setter def z0(self, z0): check_type('z0 coefficient', z0, Real) - self._coeffs['z0'] = z0 + self._coefficients['z0'] = z0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -740,10 +904,10 @@ class YCylinder(Cylinder): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -756,27 +920,46 @@ class YCylinder(Cylinder): return (np.array([-np.inf, -np.inf, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(x' - x_0)^2 + (z' - z_0)^2 - R^2` + + """ + x = point[0] - self.x0 + z = point[2] - self.z0 + return x**2 + z**2 - self.r**2 + class ZCylinder(Cylinder): - """An infinite cylinder whose length is parallel to the z-axis. This is a - quadratic surface of the form :math:`(x - x_0)^2 + (y - y_0)^2 = R^2`. + """An infinite cylinder whose length is parallel to the z-axis of the form + :math:`(x - x_0)^2 + (y - y_0)^2 = R^2`. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the center of the cylinder - y0 : float - y-coordinate of the center of the cylinder - R : float - Radius of the cylinder - name : str + x0 : float, optional + x-coordinate of the center of the cylinder. Defaults to 0. + y0 : float, optional + y-coordinate of the center of the cylinder. Defaults to 0. + R : float, optional + Radius of the cylinder. Defaults to 1. + name : str, optional Name of the cylinder. If not specified, the name will be the empty string. @@ -786,42 +969,46 @@ class ZCylinder(Cylinder): x-coordinate of the center of the cylinder y0 : float y-coordinate of the center of the cylinder + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, R=None, name=''): - # Initialize ZCylinder class attributes + x0=0., y0=0., R=1., name=''): super(ZCylinder, self).__init__(surface_id, boundary_type, R, name=name) self._type = 'z-cylinder' self._coeff_keys = ['x0', 'y0', 'R'] - self._coeffs['x0'] = 0. - self._coeffs['y0'] = 0. - - if x0 is not None: - self.x0 = x0 - - if y0 is not None: - self.y0 = y0 + self.x0 = x0 + self.y0 = y0 @property def x0(self): - return self.coeffs['x0'] + return self.coefficients['x0'] @property def y0(self): - return self.coeffs['y0'] + return self.coefficients['y0'] @x0.setter def x0(self, x0): check_type('x0 coefficient', x0, Real) - self._coeffs['x0'] = x0 + self._coefficients['x0'] = x0 @y0.setter def y0(self, y0): check_type('y0 coefficient', y0, Real) - self._coeffs['y0'] = y0 + self._coefficients['y0'] = y0 def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -839,10 +1026,10 @@ class ZCylinder(Cylinder): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -855,28 +1042,47 @@ class ZCylinder(Cylinder): return (np.array([-np.inf, -np.inf, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(x' - x_0)^2 + (y' - y_0)^2 - R^2` + + """ + x = point[0] - self.x0 + y = point[1] - self.y0 + return x**2 + y**2 - self.r**2 + class Sphere(Surface): """A sphere of the form :math:`(x - x_0)^2 + (y - y_0)^2 + (z - z_0)^2 = R^2`. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the center of the sphere - y0 : float - y-coordinate of the center of the sphere - z0 : float - z-coordinate of the center of the sphere - R : float - Radius of the sphere - name : str + x0 : float, optional + x-coordinate of the center of the sphere. Defaults to 0. + y0 : float, optional + y-coordinate of the center of the sphere. Defaults to 0. + z0 : float, optional + z-coordinate of the center of the sphere. Defaults to 0. + R : float, optional + Radius of the sphere. Defaults to 1. + name : str, optional Name of the sphere. If not specified, the name will be the empty string. Attributes @@ -889,68 +1095,66 @@ class Sphere(Surface): z-coordinate of the center of the sphere R : float Radius of the sphere + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, z0=None, R=None, name=''): - # Initialize Sphere class attributes + x0=0., y0=0., z0=0., R=1., name=''): super(Sphere, self).__init__(surface_id, boundary_type, name=name) self._type = 'sphere' self._coeff_keys = ['x0', 'y0', 'z0', 'R'] - self._coeffs['x0'] = 0. - self._coeffs['y0'] = 0. - self._coeffs['z0'] = 0. - self._coeffs['R'] = 1. - - if x0 is not None: - self.x0 = x0 - - if y0 is not None: - self.y0 = y0 - - if z0 is not None: - self.z0 = z0 - - if R is not None: - self.r = R + self.x0 = x0 + self.y0 = y0 + self.z0 = z0 + self.r = R @property def x0(self): - return self.coeffs['x0'] + return self.coefficients['x0'] @property def y0(self): - return self.coeffs['y0'] + return self.coefficients['y0'] @property def z0(self): - return self.coeffs['z0'] + return self.coefficients['z0'] @property def r(self): - return self.coeffs['R'] + return self.coefficients['R'] @x0.setter def x0(self, x0): check_type('x0 coefficient', x0, Real) - self._coeffs['x0'] = x0 + self._coefficients['x0'] = x0 @y0.setter def y0(self, y0): check_type('y0 coefficient', y0, Real) - self._coeffs['y0'] = y0 + self._coefficients['y0'] = y0 @z0.setter def z0(self, z0): check_type('z0 coefficient', z0, Real) - self._coeffs['z0'] = z0 + self._coefficients['z0'] = z0 @r.setter def r(self, R): check_type('R coefficient', R, Real) - self._coeffs['R'] = R + self._coefficients['R'] = R def bounding_box(self, side): """Determine an axis-aligned bounding box. @@ -967,10 +1171,10 @@ class Sphere(Surface): Returns ------- - numpy.array + numpy.ndarray Lower-left coordinates of the axis-aligned bounding box for the desired half-space - numpy.array + numpy.ndarray Upper-right coordinates of the axis-aligned bounding box for the desired half-space @@ -985,27 +1189,47 @@ class Sphere(Surface): return (np.array([-np.inf, -np.inf, -np.inf]), np.array([np.inf, np.inf, np.inf])) + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(x' - x_0)^2 + (y' - y_0)^2 + (z' - z_0)^2 - R^2` + + """ + x = point[0] - self.x0 + y = point[1] - self.y0 + z = point[2] - self.z0 + return x**2 + y**2 + z**2 - self.r**2 + class Cone(Surface): """A conical surface parallel to the x-, y-, or z-axis. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the apex + x0 : float, optional + x-coordinate of the apex. Defaults to 0. y0 : float - y-coordinate of the apex + y-coordinate of the apex. Defaults to 0. z0 : float - z-coordinate of the apex + z-coordinate of the apex. Defaults to 0. R2 : float - Parameter related to the aperature + Parameter related to the aperature. Defaults to 1. name : str Name of the cone. If not specified, the name will be the empty string. @@ -1019,69 +1243,67 @@ class Cone(Surface): z-coordinate of the apex R2 : float Parameter related to the aperature + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ __metaclass__ = ABCMeta def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, z0=None, R2=None, name=''): - # Initialize Cone class attributes + x0=0., y0=0., z0=0., R2=1., name=''): super(Cone, self).__init__(surface_id, boundary_type, name=name) self._coeff_keys = ['x0', 'y0', 'z0', 'R2'] - self._coeffs['x0'] = 0. - self._coeffs['y0'] = 0. - self._coeffs['z0'] = 0. - self._coeffs['R2'] = 1. - - if x0 is not None: - self.x0 = x0 - - if y0 is not None: - self.y0 = y0 - - if z0 is not None: - self.z0 = z0 - - if R2 is not None: - self.r2 = R2 + self.x0 = x0 + self.y0 = y0 + self.z0 = z0 + self.r2 = R2 @property def x0(self): - return self.coeffs['x0'] + return self.coefficients['x0'] @property def y0(self): - return self.coeffs['y0'] + return self.coefficients['y0'] @property def z0(self): - return self.coeffs['z0'] + return self.coefficients['z0'] @property def r2(self): - return self.coeffs['r2'] + return self.coefficients['r2'] @x0.setter def x0(self, x0): check_type('x0 coefficient', x0, Real) - self._coeffs['x0'] = x0 + self._coefficients['x0'] = x0 @y0.setter def y0(self, y0): check_type('y0 coefficient', y0, Real) - self._coeffs['y0'] = y0 + self._coefficients['y0'] = y0 @z0.setter def z0(self, z0): check_type('z0 coefficient', z0, Real) - self._coeffs['z0'] = z0 + self._coefficients['z0'] = z0 @r2.setter def r2(self, R2): check_type('R^2 coefficient', R2, Real) - self._coeffs['R2'] = R2 + self._coefficients['R2'] = R2 class XCone(Cone): @@ -1090,22 +1312,22 @@ class XCone(Cone): Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the apex - y0 : float - y-coordinate of the apex - z0 : float - z-coordinate of the apex - R2 : float - Parameter related to the aperature - name : str + x0 : float, optional + x-coordinate of the apex. Defaults to 0. + y0 : float, optional + y-coordinate of the apex. Defaults to 0. + z0 : float, optional + z-coordinate of the apex. Defaults to 0. + R2 : float, optional + Parameter related to the aperature. Defaults to 1. + name : str, optional Name of the cone. If not specified, the name will be the empty string. Attributes @@ -1118,17 +1340,47 @@ class XCone(Cone): z-coordinate of the apex R2 : float Parameter related to the aperature + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, z0=None, R2=None, name=''): - # Initialize XCone class attributes + x0=0., y0=0., z0=0., R2=1., name=''): super(XCone, self).__init__(surface_id, boundary_type, x0, y0, z0, R2, name=name) self._type = 'x-cone' + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(y' - y_0)^2 + (z' - z_0)^2 - R^2(x' - x_0)^2` + + """ + x = point[0] - self.x0 + y = point[1] - self.y0 + z = point[2] - self.z0 + return y**2 + z**2 - self.r2*x**2 + class YCone(Cone): """A cone parallel to the y-axis of the form :math:`(x - x_0)^2 + (z - z_0)^2 = @@ -1136,22 +1388,22 @@ class YCone(Cone): Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the apex - y0 : float - y-coordinate of the apex - z0 : float - z-coordinate of the apex - R2 : float - Parameter related to the aperature - name : str + x0 : float, optional + x-coordinate of the apex. Defaults to 0. + y0 : float, optional + y-coordinate of the apex. Defaults to 0. + z0 : float, optional + z-coordinate of the apex. Defaults to 0. + R2 : float, optional + Parameter related to the aperature. Defaults to 1. + name : str, optional Name of the cone. If not specified, the name will be the empty string. Attributes @@ -1164,17 +1416,47 @@ class YCone(Cone): z-coordinate of the apex R2 : float Parameter related to the aperature + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, z0=None, R2=None, name=''): - # Initialize YCone class attributes + x0=0., y0=0., z0=0., R2=1., name=''): super(YCone, self).__init__(surface_id, boundary_type, x0, y0, z0, R2, name=name) self._type = 'y-cone' + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(x' - x_0)^2 + (z' - z_0)^2 - R^2(y' - y_0)^2` + + """ + x = point[0] - self.x0 + y = point[1] - self.y0 + z = point[2] - self.z0 + return x**2 + z**2 - self.r2*y**2 + class ZCone(Cone): """A cone parallel to the x-axis of the form :math:`(x - x_0)^2 + (y - y_0)^2 = @@ -1182,22 +1464,22 @@ class ZCone(Cone): Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - x0 : float - x-coordinate of the apex - y0 : float - y-coordinate of the apex - z0 : float - z-coordinate of the apex - R2 : float - Parameter related to the aperature - name : str + x0 : float, optional + x-coordinate of the apex. Defaults to 0. + y0 : float, optional + y-coordinate of the apex. Defaults to 0. + z0 : float, optional + z-coordinate of the apex. Defaults to 0. + R2 : float, optional + Parameter related to the aperature. Defaults to 1. + name : str, optional Name of the cone. If not specified, the name will be the empty string. Attributes @@ -1210,164 +1492,212 @@ class ZCone(Cone): z-coordinate of the apex R2 : float Parameter related to the aperature + boundary_type : {'transmission, 'vacuum', 'reflective'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - x0=None, y0=None, z0=None, R2=None, name=''): - # Initialize ZCone class attributes + x0=0., y0=0., z0=0., R2=1., name=''): super(ZCone, self).__init__(surface_id, boundary_type, x0, y0, z0, R2, name=name) self._type = 'z-cone' + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`(x' - x_0)^2 + (y' - y_0)^2 - R^2(z' - z_0)^2` + + """ + x = point[0] - self.x0 + y = point[1] - self.y0 + z = point[2] - self.z0 + return x**2 + y**2 - self.r2*z**2 + class Quadric(Surface): - """A sphere of the form :math:`Ax^2 + By^2 + Cz^2 + Dxy + Eyz + Fxz + Gx + Hy + - Jz + K`. + """A surface of the form :math:`Ax^2 + By^2 + Cz^2 + Dxy + Eyz + Fxz + Gx + Hy + + Jz + K = 0`. Parameters ---------- - surface_id : int + surface_id : int, optional Unique identifier for the surface. If not specified, an identifier will automatically be assigned. - boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles freely pass through the surface. - a, b, c, d, e, f, g, h, j, k : float - coefficients for the surface - name : str + a, b, c, d, e, f, g, h, j, k : float, optional + coefficients for the surface. All default to 0. + name : str, optional Name of the sphere. If not specified, the name will be the empty string. Attributes ---------- a, b, c, d, e, f, g, h, j, k : float coefficients for the surface + boundary_type : {'transmission, 'vacuum', 'reflective', 'periodic'} + Boundary condition that defines the behavior for particles hitting the + surface. + coefficients : dict + Dictionary of surface coefficients + id : int + Unique identifier for the surface + name : str + Name of the surface + type : str + Type of the surface """ def __init__(self, surface_id=None, boundary_type='transmission', - a=None, b=None, c=None, d=None, e=None, f=None, g=None, - h=None, j=None, k=None, name=''): - # Initialize Quadric class attributes + a=0., b=0., c=0., d=0., e=0., f=0., g=0., + h=0., j=0., k=0., name=''): super(Quadric, self).__init__(surface_id, boundary_type, name=name) self._type = 'quadric' self._coeff_keys = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'j', 'k'] - for key in self._coeff_keys: - self._coeffs[key] = 0. - - if a is not None: - self.a = a - if b is not None: - self.b = b - if c is not None: - self.c = c - if d is not None: - self.d = d - if e is not None: - self.e = e - if f is not None: - self.f = f - if g is not None: - self.g = g - if h is not None: - self.h = h - if j is not None: - self.j = j - if k is not None: - self.k = k + self.a = a + self.b = b + self.c = c + self.d = d + self.e = e + self.f = f + self.g = g + self.h = h + self.j = j + self.k = k @property def a(self): - return self.coeffs['a'] + return self.coefficients['a'] @property def b(self): - return self.coeffs['b'] + return self.coefficients['b'] @property def c(self): - return self.coeffs['c'] + return self.coefficients['c'] @property def d(self): - return self.coeffs['d'] + return self.coefficients['d'] @property def e(self): - return self.coeffs['e'] + return self.coefficients['e'] @property def f(self): - return self.coeffs['f'] + return self.coefficients['f'] @property def g(self): - return self.coeffs['g'] + return self.coefficients['g'] @property def h(self): - return self.coeffs['h'] + return self.coefficients['h'] @property def j(self): - return self.coeffs['j'] + return self.coefficients['j'] @property def k(self): - return self.coeffs['k'] + return self.coefficients['k'] @a.setter def a(self, a): check_type('a coefficient', a, Real) - self._coeffs['a'] = a + self._coefficients['a'] = a @b.setter def b(self, b): check_type('b coefficient', b, Real) - self._coeffs['b'] = b + self._coefficients['b'] = b @c.setter def c(self, c): check_type('c coefficient', c, Real) - self._coeffs['c'] = c + self._coefficients['c'] = c @d.setter def d(self, d): check_type('d coefficient', d, Real) - self._coeffs['d'] = d + self._coefficients['d'] = d @e.setter def e(self, e): check_type('e coefficient', e, Real) - self._coeffs['e'] = e + self._coefficients['e'] = e @f.setter def f(self, f): check_type('f coefficient', f, Real) - self._coeffs['f'] = f + self._coefficients['f'] = f @g.setter def g(self, g): check_type('g coefficient', g, Real) - self._coeffs['g'] = g + self._coefficients['g'] = g @h.setter def h(self, h): check_type('h coefficient', h, Real) - self._coeffs['h'] = h + self._coefficients['h'] = h @j.setter def j(self, j): check_type('j coefficient', j, Real) - self._coeffs['j'] = j + self._coefficients['j'] = j @k.setter def k(self, k): check_type('k coefficient', k, Real) - self._coeffs['k'] = k + self._coefficients['k'] = k + + def evaluate(self, point): + """Evaluate the surface equation at a given point. + + Parameters + ---------- + point : 3-tuple of float + The Cartesian coordinates, :math:`(x',y',z')`, at which the surface + equation should be evaluated. + + Returns + ------- + float + :math:`Ax'^2 + By'^2 + Cz'^2 + Dx'y' + Ey'z' + Fx'z' + Gx' + Hy' + + Jz' + K = 0` + + """ + x, y, z = point + return x*(self.a*x + self.d*y + self.g) + \ + y*(self.b*y + self.e*z + self.h) + \ + z*(self.c*z + self.f*x + self.j) + self.k class Halfspace(Region): @@ -1383,7 +1713,7 @@ class Halfspace(Region): can be created from an existing Surface through the __neg__ and __pos__ operators, as the following example demonstrates: - >>> sphere = openmc.surface.Sphere(surface_id=1, R=10.0) + >>> sphere = openmc.Sphere(surface_id=1, R=10.0) >>> inside_sphere = -sphere >>> outside_sphere = +sphere >>> type(inside_sphere) @@ -1391,18 +1721,18 @@ class Halfspace(Region): Parameters ---------- - surface : Surface + surface : openmc.Surface Surface which divides Euclidean space. side : {'+', '-'} Indicates whether the positive or negative half-space is used. Attributes ---------- - surface : Surface + surface : openmc.Surface Surface which divides Euclidean space. side : {'+', '-'} Indicates whether the positive or negative half-space is used. - bounding_box : tuple of numpy.array + bounding_box : tuple of numpy.ndarray Lower-left and upper-right coordinates of an axis-aligned bounding box """ @@ -1414,6 +1744,24 @@ class Halfspace(Region): def __invert__(self): return -self.surface if self.side == '+' else +self.surface + def __contains__(self, point): + """Check whether a point is contained in the half-space. + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates, :math:`(x',y',z')`, of the point + + Returns + ------- + bool + Whether the point is in the half-space + + """ + + val = self.surface.evaluate(point) + return val >= 0. if self.side == '+' else val < 0. + @property def surface(self): return self._surface @@ -1439,3 +1787,45 @@ class Halfspace(Region): def __str__(self): return '-' + str(self.surface.id) if self.side == '-' \ else str(self.surface.id) + + +def make_hexagon_region(edge_length=1., orientation='y'): + """Create a hexagon region from six surface planes. + + Parameters + ---------- + edge_length : float + Length of a side of the hexagon in cm + orientation : {'x', 'y'} + An 'x' orientation means that two sides of the hexagon are parallel to + the x-axis and a 'y' orientation means that two sides of the hexagon are + parallel to the y-axis. + + Returns + ------- + openmc.Region + The inside of a hexagonal prism + + """ + + l = edge_length + + if orientation == 'y': + right = XPlane(x0=sqrt(3.)/2.*l) + left = XPlane(x0=-sqrt(3.)/2.*l) + c = sqrt(3.)/3. + ur = Plane(A=c, B=1., D=l) # y = -x/sqrt(3) + a + ul = Plane(A=-c, B=1., D=l) # y = x/sqrt(3) + a + lr = Plane(A=-c, B=1., D=-l) # y = x/sqrt(3) - a + ll = Plane(A=c, B=1., D=-l) # y = -x/sqrt(3) - a + return Intersection(-right, +left, -ur, -ul, +lr, +ll) + + elif orientation == 'x': + top = YPlane(y0=sqrt(3.)/2.*l) + bottom = YPlane(y0=-sqrt(3.)/2.*l) + c = sqrt(3.) + ur = Plane(A=c, B=1., D=c*l) # y = -sqrt(3)*(x - a) + lr = Plane(A=-c, B=1., D=-c*l) # y = sqrt(3)*(x + a) + ll = Plane(A=c, B=1., D=-c*l) # y = -sqrt(3)*(x + a) + ul = Plane(A=-c, B=1., D=c*l) # y = sqrt(3)*(x + a) + return Intersection(-top, +bottom, -ur, +lr, +ll, -ul) diff --git a/openmc/tallies.py b/openmc/tallies.py index fb66eb77f..38aa0bf12 100644 --- a/openmc/tallies.py +++ b/openmc/tallies.py @@ -1,14 +1,15 @@ from __future__ import division -from collections import Iterable, defaultdict +from collections import Iterable, MutableSequence, defaultdict import copy from functools import partial import os import pickle import itertools from numbers import Integral, Real -from xml.etree import ElementTree as ET import sys +import warnings +from xml.etree import ElementTree as ET import numpy as np @@ -18,10 +19,10 @@ from openmc.filter import _FILTER_TYPES import openmc.checkvalue as cv from openmc.clean_xml import * - if sys.version_info[0] >= 3: basestring = str + # "Static" variable for auto-generated Tally IDs AUTO_TALLY_ID = 10000 @@ -32,6 +33,12 @@ AUTO_TALLY_ID = 10000 # specified axis. _PRODUCT_TYPES = ['tensor', 'entrywise'] +# The following indicate acceptable types when setting Tally.scores, +# Tally.nuclides, and Tally.filters +_SCORE_CLASSES = (basestring, CrossScore, AggregateScore) +_NUCLIDE_CLASSES = (basestring, Nuclide, CrossNuclide, AggregateNuclide) +_FILTER_CLASSES = (Filter, CrossFilter, AggregateFilter) + def reset_auto_tally_id(): global AUTO_TALLY_ID @@ -44,7 +51,7 @@ class Tally(object): Parameters ---------- - tally_id : Integral, optional + tally_id : int, optional Unique identifier for the tally. If none is specified, an identifier will automatically be assigned name : str, optional @@ -52,43 +59,43 @@ class Tally(object): Attributes ---------- - id : Integral + id : int Unique identifier for the tally name : str Name of the tally - filters : list of openmc.filter.Filter + filters : list of openmc.Filter List of specified filters for the tally - nuclides : list of openmc.nuclide.Nuclide + nuclides : list of openmc.Nuclide List of nuclides to score results for scores : list of str List of defined scores, e.g. 'flux', 'fission', etc. estimator : {'analog', 'tracklength', 'collision'} Type of estimator for the tally - triggers : list of openmc.trigger.Trigger + triggers : list of openmc.Trigger List of tally triggers - num_scores : Integral + num_scores : int Total number of scores, accounting for the fact that a single user-specified score, e.g. scatter-P3 or flux-Y2,2, might have multiple bins - num_filter_bins : Integral + num_filter_bins : int Total number of filter bins accounting for all filters - num_bins : Integral + num_bins : int Total number of bins for the tally - shape : 3-tuple of Integral - The shape of the tally data array ordered as the number of filter bins, + shape : 3-tuple of int + The shape of the tally data array ordered as the number of filter bins, nuclide bins and score bins - num_realizations : Integral + num_realizations : int Total number of realizations with_summary : bool Whether or not a Summary has been linked - sum : ndarray + sum : numpy.ndarray An array containing the sum of each independent realization for each bin - sum_sq : ndarray + sum_sq : numpy.ndarray An array containing the sum of each independent realization squared for each bin - mean : ndarray + mean : numpy.ndarray An array containing the sample mean for each bin - std_dev : ndarray + std_dev : numpy.ndarray An array containing the sample standard deviation for each bin derived : bool Whether or not the tally is derived from one or more other tallies @@ -102,11 +109,11 @@ class Tally(object): # Initialize Tally class attributes self.id = tally_id self.name = name - self._filters = [] - self._nuclides = [] - self._scores = [] + self._filters = cv.CheckedList(_FILTER_CLASSES, 'tally filters') + self._nuclides = cv.CheckedList(_NUCLIDE_CLASSES, 'tally nuclides') + self._scores = cv.CheckedList(_SCORE_CLASSES, 'tally scores') self._estimator = None - self._triggers = [] + self._triggers = cv.CheckedList(Trigger, 'tally triggers') self._num_realizations = 0 self._with_summary = False @@ -145,19 +152,19 @@ class Tally(object): clone._filters = [] for self_filter in self.filters: - clone.add_filter(copy.deepcopy(self_filter, memo)) + clone.filters.append(copy.deepcopy(self_filter, memo)) clone._nuclides = [] for nuclide in self.nuclides: - clone.add_nuclide(copy.deepcopy(nuclide, memo)) + clone.nuclides.append(copy.deepcopy(nuclide, memo)) clone._scores = [] for score in self.scores: - clone.add_score(score) + clone.scores.append(score) clone._triggers = [] for trigger in self.triggers: - clone.add_trigger(trigger) + clone.triggers.append(trigger) memo[id(self)] = clone @@ -307,6 +314,10 @@ class Tally(object): if not self._results_read: import h5py + if h5py.__version__ == '2.6.0': + raise ImportError("h5py 2.6.0 has a known bug which makes it " + "incompatible with OpenMC's HDF5 files. " + "Please switch to a different version.") # Open the HDF5 statepoint file f = h5py.File(self._sp_filename, 'r') @@ -423,23 +434,30 @@ class Tally(object): ['analog', 'tracklength', 'collision']) self._estimator = estimator + @triggers.setter + def triggers(self, triggers): + cv.check_type('tally triggers', triggers, MutableSequence) + self._triggers = cv.CheckedList(Trigger, 'tally triggers', triggers) + def add_trigger(self, trigger): """Add a tally trigger to the tally + .. deprecated:: 0.8 + Use the Tally.triggers property directly, i.e., + Tally.triggers.append(...) + Parameters ---------- - trigger : openmc.trigger.Trigger + trigger : openmc.Trigger Trigger to add """ - if not isinstance(trigger, Trigger): - msg = 'Unable to add a tally trigger for Tally ID="{0}" to ' \ - 'since "{1}" is not a Trigger'.format(self.id, trigger) - raise ValueError(msg) - - if trigger not in self.triggers: - self.triggers.append(trigger) + warnings.warn('Tally.add_trigger(...) has been deprecated and may be ' + 'removed in a future version. Tally triggers should be ' + 'defined using the triggers property directly.', + DeprecationWarning) + self.triggers.append(trigger) @id.setter def id(self, tally_id): @@ -460,9 +478,60 @@ class Tally(object): else: self._name = '' + @filters.setter + def filters(self, filters): + cv.check_type('tally filters', filters, MutableSequence) + + # If the filter is already in the Tally, raise an error + for i, f in enumerate(filters[:-1]): + if f in filters[i+1:]: + msg = 'Unable to add a duplicate filter "{0}" to Tally ID="{1}" ' \ + 'since duplicate filters are not supported in the OpenMC ' \ + 'Python API'.format(f, self.id) + raise ValueError(msg) + + self._filters = cv.CheckedList(_FILTER_CLASSES, 'tally filters', filters) + + @nuclides.setter + def nuclides(self, nuclides): + cv.check_type('tally nuclides', nuclides, MutableSequence) + + # If the nuclide is already in the Tally, raise an error + for i, nuclide in enumerate(nuclides[:-1]): + if nuclide in nuclides[i+1:]: + msg = 'Unable to add a duplicate nuclide "{0}" to Tally ID="{1}" ' \ + 'since duplicate nuclides are not supported in the OpenMC ' \ + 'Python API'.format(nuclide, self.id) + raise ValueError(msg) + + self._nuclides = cv.CheckedList(_NUCLIDE_CLASSES, 'tally nuclides', + nuclides) + + @scores.setter + def scores(self, scores): + cv.check_type('tally scores', scores, MutableSequence) + + for i, score in enumerate(scores[:-1]): + # If the score is already in the Tally, raise an error + if score in scores[i+1:]: + msg = 'Unable to add a duplicate score "{0}" to Tally ID="{1}" ' \ + 'since duplicate scores are not supported in the OpenMC ' \ + 'Python API'.format(score, self.id) + raise ValueError(msg) + + # If score is a string, strip whitespace + if isinstance(score, basestring): + scores[i] = score.strip() + + self._scores = cv.CheckedList(_SCORE_CLASSES, 'tally scores', scores) + def add_filter(self, new_filter): """Add a filter to the tally + .. deprecated:: 0.8 + Use the Tally.filters property directly, i.e., + Tally.filters.append(...) + Parameters ---------- new_filter : Filter, CrossFilter or AggregateFilter @@ -475,23 +544,19 @@ class Tally(object): """ - if not isinstance(new_filter, (Filter, CrossFilter, AggregateFilter)): - msg = 'Unable to add Filter "{0}" to Tally ID="{1}" since it is ' \ - 'not a Filter object'.format(new_filter, self.id) - raise ValueError(msg) - - # If the filter is already in the Tally, raise an error - if new_filter in self.filters: - msg = 'Unable to add a duplicate filter "{0}" to Tally ID="{1}" ' \ - 'since duplicate filters are not supported in the OpenMC ' \ - 'Python API'.format(new_filter, self.id) - raise ValueError(msg) - - self._filters.append(new_filter) + warnings.warn('Tally.add_filter(...) has been deprecated and may be ' + 'removed in a future version. Tally filters should be ' + 'defined using the filters property directly.', + DeprecationWarning) + self.filters.append(new_filter) def add_nuclide(self, nuclide): """Specify that scores for a particular nuclide should be accumulated + .. deprecated:: 0.8 + Use the Tally.nuclides property directly, i.e., + Tally.nuclides.append(...) + Parameters ---------- nuclide : str, Nuclide, CrossNuclide or AggregateNuclide @@ -504,24 +569,19 @@ class Tally(object): """ - if not isinstance(nuclide, (basestring, Nuclide, - CrossNuclide, AggregateNuclide)): - msg = 'Unable to add nuclide "{0}" to Tally ID="{1}" since it is ' \ - 'not a Nuclide object'.format(nuclide) - raise ValueError(msg) - - # If the nuclide is already in the Tally, raise an error - if nuclide in self.nuclides: - msg = 'Unable to add a duplicate nuclide "{0}" to Tally ID="{1}" ' \ - 'since duplicate nuclides are not supported in the OpenMC ' \ - 'Python API'.format(nuclide, self.id) - raise ValueError(msg) - - self._nuclides.append(nuclide) + warnings.warn('Tally.add_nuclide(...) has been deprecated and may be ' + 'removed in a future version. Tally nuclides should be ' + 'defined using the nuclides property directly.', + DeprecationWarning) + self.nuclides.append(nuclide) def add_score(self, score): """Specify a quantity to be scored + .. deprecated:: 0.8 + Use the Tally.scores property directly, i.e., + Tally.scores.append(...) + Parameters ---------- score : str, CrossScore or AggregateScore @@ -533,24 +593,11 @@ class Tally(object): """ - if not isinstance(score, (basestring, CrossScore, AggregateScore)): - msg = 'Unable to add score "{0}" to Tally ID="{1}" since it is ' \ - 'not a string'.format(score, self.id) - raise ValueError(msg) - - # If the score is already in the Tally, raise an error - if score in self.scores: - msg = 'Unable to add a duplicate score "{0}" to Tally ID="{1}" ' \ - 'since duplicate scores are not supported in the OpenMC ' \ - 'Python API'.format(score, self.id) - raise ValueError(msg) - - # Normal score strings - if isinstance(score, basestring): - self._scores.append(score.strip()) - # CrossScores and AggrgateScore - else: - self._scores.append(score) + warnings.warn('Tally.add_score(...) has been deprecated and may be ' + 'removed in a future version. Tally scores should be ' + 'defined using the scores property directly.', + DeprecationWarning) + self.scores.append(score) @num_realizations.setter def num_realizations(self, num_realizations): @@ -645,7 +692,7 @@ class Tally(object): Parameters ---------- - old_filter : openmc.filter.Filter + old_filter : openmc.Filter Filter to remove """ @@ -662,7 +709,7 @@ class Tally(object): Parameters ---------- - nuclide : openmc.nuclide.Nuclide + nuclide : openmc.Nuclide Nuclide to remove """ @@ -684,7 +731,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally Tally to check for mergeable filters """ @@ -737,7 +784,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally Tally to check for mergeable nuclides """ @@ -774,7 +821,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally Tally to check for mergeable scores """ @@ -784,9 +831,7 @@ class Tally(object): # Search for each of this tally's scores in the other tally for score in self.scores: - if score not in other.scores: - all_scores_match = False - else: + if score in other.scores: no_scores_match = False # Search for each of the other tally's scores in this tally @@ -815,7 +860,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally Tally to check for merging """ @@ -860,12 +905,12 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally Tally to merge with this one Returns ------- - merged_tally : Tally + merged_tally : openmc.Tally Merged tallies """ @@ -917,7 +962,7 @@ class Tally(object): # Add unique nuclides from other tally to merged tally for nuclide in other.nuclides: if nuclide not in merged_tally.nuclides: - merged_tally.add_nuclide(nuclide) + merged_tally.nuclides.append(nuclide) # If two tallies can be merged along score bins if merge_scores and not equal_scores: @@ -927,11 +972,11 @@ class Tally(object): # Add unique scores from other tally to merged tally for score in other.scores: if score not in merged_tally.scores: - merged_tally.add_score(score) + merged_tally.scores.append(score) # Add triggers from other tally to merged tally for trigger in other.triggers: - merged_tally.add_trigger(trigger) + merged_tally.triggers.append(trigger) # If results have not been read, then return tally for input generation if self._results_read is None: @@ -1108,7 +1153,7 @@ class Tally(object): Returns ------- - filter_found : openmc.filter.Filter + filter_found : openmc.Filter Filter from this tally with matching type, or None if no matching Filter is found @@ -1142,7 +1187,7 @@ class Tally(object): ---------- filter_type : str The type of Filter (e.g., 'cell', 'energy', etc.) - filter_bin : Integral or tuple + filter_bin : int or tuple The bin is an integer ID for 'material', 'surface', 'cell', 'cellborn', and 'universe' Filters. The bin is an integer for the cell instance ID for 'distribcell' Filters. The bin is a 2-tuple of @@ -1268,7 +1313,7 @@ class Tally(object): Returns ------- - ndarray + numpy.ndarray A NumPy array of the filter indices """ @@ -1350,7 +1395,7 @@ class Tally(object): Returns ------- - ndarray + numpy.ndarray A NumPy array of the nuclide indices """ @@ -1384,7 +1429,7 @@ class Tally(object): Returns ------- - ndarray + numpy.ndarray A NumPy array of the score indices """ @@ -1446,7 +1491,7 @@ class Tally(object): Returns ------- - float or ndarray + float or numpy.ndarray A scalar or NumPy array of the Tally data indexed in the order each filter, nuclide and score is listed in the parameters. @@ -1495,8 +1540,8 @@ class Tally(object): return data - def get_pandas_dataframe(self, filters=True, nuclides=True, - scores=True, summary=None, float_format='{:.2e}'): + def get_pandas_dataframe(self, filters=True, nuclides=True, scores=True, + distribcell_paths=True, float_format='{:.2e}'): """Build a Pandas DataFrame for the Tally data. This method constructs a Pandas DataFrame object for the Tally data @@ -1514,13 +1559,12 @@ class Tally(object): Include columns with nuclide bin information (default is True). scores : bool Include columns with score bin information (default is True). - summary : None or Summary - An optional Summary object to be used to construct columns for - distribcell tally filters (default is None). The geometric - information in the Summary object is embedded into a Multi-index - column with a geometric "path" to each distribcell intance. - NOTE: This option requires the OpenCG Python package. - float_format : string + distribcell_paths : bool, optional + Construct columns for distribcell tally filters (default is True). + The geometric information in the Summary object is embedded into a + Multi-index column with a geometric "path" to each distribcell + instance. + float_format : str All floats in the DataFrame will be formatted using the given format string before printing. @@ -1545,14 +1589,6 @@ class Tally(object): msg = 'The Tally ID="{0}" has no data to return'.format(self.id) raise KeyError(msg) - # If using Summary, ensure StatePoint.link_with_summary(...) was called - if summary and not self.with_summary: - msg = 'The Tally ID="{0}" has not been linked with the Summary. ' \ - 'Call the StatePoint.link_with_summary(...) method ' \ - 'before using Tally.get_pandas_dataframe(...) with ' \ - 'Summary info'.format(self.id) - raise KeyError(msg) - # Initialize a pandas dataframe for the tally data import pandas as pd df = pd.DataFrame() @@ -1565,7 +1601,8 @@ class Tally(object): # Append each Filter's DataFrame to the overall DataFrame for self_filter in self.filters: - filter_df = self_filter.get_pandas_dataframe(data_size, summary) + filter_df = self_filter.get_pandas_dataframe( + data_size, distribcell_paths) df = pd.concat([df, filter_df], axis=1) # Include DataFrame column for nuclides if user requested it @@ -1594,7 +1631,7 @@ class Tally(object): for score in self.scores: if isinstance(score, (basestring, CrossScore)): - scores.append(score) + scores.append(str(score)) elif isinstance(score, AggregateScore): scores.append(score.name) column_name = '{0}(score)'.format(score.aggregate_op) @@ -1640,8 +1677,8 @@ class Tally(object): The tally data in OpenMC is stored as a 3D array with the dimensions corresponding to filters, nuclides and scores. As a result, tally data - can be opaque for a user to directly index (i.e., without use of the - Tally.get_values(...) method) since one must know how to properly use + can be opaque for a user to directly index (i.e., without use of + :meth:`openmc.Tally.get_values`) since one must know how to properly use the number of bins and strides for each filter to index into the first (filter) dimension. @@ -1661,7 +1698,7 @@ class Tally(object): Returns ------- - ndarray + numpy.ndarray The tally data array indexed by filters, nuclides and scores. """ @@ -1839,7 +1876,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally The tally on the right hand side of the hybrid product binary_op : {'+', '-', '*', '/', '^'} The binary operation in the hybrid product @@ -1861,7 +1898,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new Tally that is the hybrid product with this one. Raises @@ -1981,33 +2018,33 @@ class Tally(object): # Add filters to the new tally if filter_product == 'entrywise': for self_filter in self_copy.filters: - new_tally.add_filter(self_filter) + new_tally.filters.append(self_filter) else: all_filters = [self_copy.filters, other_copy.filters] for self_filter, other_filter in itertools.product(*all_filters): new_filter = CrossFilter(self_filter, other_filter, binary_op) - new_tally.add_filter(new_filter) + new_tally.filters.append(new_filter) # Add nuclides to the new tally if nuclide_product == 'entrywise': for self_nuclide in self_copy.nuclides: - new_tally.add_nuclide(self_nuclide) + new_tally.nuclides.append(self_nuclide) else: all_nuclides = [self_copy.nuclides, other_copy.nuclides] for self_nuclide, other_nuclide in itertools.product(*all_nuclides): new_nuclide = \ CrossNuclide(self_nuclide, other_nuclide, binary_op) - new_tally.add_nuclide(new_nuclide) + new_tally.nuclides.append(new_nuclide) # Add scores to the new tally if score_product == 'entrywise': for self_score in self_copy.scores: - new_tally.add_score(self_score) + new_tally.scores.append(self_score) else: all_scores = [self_copy.scores, other_copy.scores] for self_score, other_score in itertools.product(*all_scores): new_score = CrossScore(self_score, other_score, binary_op) - new_tally.add_score(new_score) + new_tally.scores.append(new_score) # Update the new tally's filter strides new_tally._update_filter_strides() @@ -2039,7 +2076,7 @@ class Tally(object): Parameters ---------- - other : Tally + other : openmc.Tally The tally to outer product with this tally filter_product : {'entrywise'} The type of product to be performed between filter data. Currently, @@ -2070,14 +2107,14 @@ class Tally(object): filter_copy = copy.deepcopy(other_filter) other._mean = np.repeat(other.mean, filter_copy.num_bins, axis=0) other._std_dev = np.repeat(other.std_dev, filter_copy.num_bins, axis=0) - other.add_filter(filter_copy) + other.filters.append(filter_copy) # Add filters present in other but not in self to self for self_filter in self_missing_filters: filter_copy = copy.deepcopy(self_filter) self._mean = np.repeat(self.mean, filter_copy.num_bins, axis=0) self._std_dev = np.repeat(self.std_dev, filter_copy.num_bins, axis=0) - self.add_filter(filter_copy) + self.filters.append(filter_copy) # Align other filters with self filters for i, self_filter in enumerate(self.filters): @@ -2100,7 +2137,7 @@ class Tally(object): np.tile(other.std_dev, (1, self.num_nuclides, 1)) # Add nuclides to each tally such that each tally contains the complete - # set of nuclides necessary to perform an entrywise product. New + # set of nuclides necessary to perform an entrywise product. New # nuclides added to a tally will have all their scores set to zero. else: @@ -2116,7 +2153,7 @@ class Tally(object): np.insert(other.mean, other.num_nuclides, 0, axis=1) other._std_dev = \ np.insert(other.std_dev, other.num_nuclides, 0, axis=1) - other.add_nuclide(nuclide) + other.nuclides.append(nuclide) # Add nuclides present in other but not in self to self for nuclide in self_missing_nuclides: @@ -2124,7 +2161,7 @@ class Tally(object): np.insert(self.mean, self.num_nuclides, 0, axis=1) self._std_dev = \ np.insert(self.std_dev, self.num_nuclides, 0, axis=1) - self.add_nuclide(nuclide) + self.nuclides.append(nuclide) # Align other nuclides with self nuclides for i, nuclide in enumerate(self.nuclides): @@ -2157,13 +2194,13 @@ class Tally(object): for score in other_missing_scores: other._mean = np.insert(other.mean, other.num_scores, 0, axis=2) other._std_dev = np.insert(other.std_dev, other.num_scores, 0, axis=2) - other.add_score(score) + other.scores.append(score) # Add scores present in other but not in self to self for score in self_missing_scores: self._mean = np.insert(self.mean, self.num_scores, 0, axis=2) self._std_dev = np.insert(self.std_dev, self.num_scores, 0, axis=2) - self.add_score(score) + self.scores.append(score) # Align other scores with self scores for i, score in enumerate(self.scores): @@ -2421,12 +2458,12 @@ class Tally(object): Parameters ---------- - other : Tally or Real + other : openmc.Tally or float The tally or scalar value to add to this tally Returns ------- - Tally + openmc.Tally A new derived tally which is the sum of this tally and the other tally or scalar value in the addition. @@ -2461,12 +2498,9 @@ class Tally(object): new_tally.with_summary = self.with_summary new_tally.num_realization = self.num_realizations - for self_filter in self.filters: - new_tally.add_filter(self_filter) - for nuclide in self.nuclides: - new_tally.add_nuclide(nuclide) - for score in self.scores: - new_tally.add_score(score) + new_tally.filters = copy.deepcopy(self.filters) + new_tally.nuclides = copy.deepcopy(self.nuclides) + new_tally.scores = copy.deepcopy(self.scores) # If this tally operand is sparse, sparsify the new tally new_tally.sparse = self.sparse @@ -2496,12 +2530,12 @@ class Tally(object): Parameters ---------- - other : Tally or Real + other : openmc.Tally or float The tally or scalar value to subtract from this tally Returns ------- - Tally + openmc.Tally A new derived tally which is the difference of this tally and the other tally or scalar value in the subtraction. @@ -2535,12 +2569,9 @@ class Tally(object): new_tally.with_summary = self.with_summary new_tally.num_realization = self.num_realizations - for self_filter in self.filters: - new_tally.add_filter(self_filter) - for nuclide in self.nuclides: - new_tally.add_nuclide(nuclide) - for score in self.scores: - new_tally.add_score(score) + new_tally.filters = copy.deepcopy(self.filters) + new_tally.nuclides = copy.deepcopy(self.nuclides) + new_tally.scores = copy.deepcopy(self.scores) # If this tally operand is sparse, sparsify the new tally new_tally.sparse = self.sparse @@ -2571,12 +2602,12 @@ class Tally(object): Parameters ---------- - other : Tally or Real + other : openmc.Tally or float The tally or scalar value to multiply with this tally Returns ------- - Tally + openmc.Tally A new derived tally which is the product of this tally and the other tally or scalar value in the multiplication. @@ -2610,12 +2641,9 @@ class Tally(object): new_tally.with_summary = self.with_summary new_tally.num_realization = self.num_realizations - for self_filter in self.filters: - new_tally.add_filter(self_filter) - for nuclide in self.nuclides: - new_tally.add_nuclide(nuclide) - for score in self.scores: - new_tally.add_score(score) + new_tally.filters = copy.deepcopy(self.filters) + new_tally.nuclides = copy.deepcopy(self.nuclides) + new_tally.scores = copy.deepcopy(self.scores) # If this tally operand is sparse, sparsify the new tally new_tally.sparse = self.sparse @@ -2646,12 +2674,12 @@ class Tally(object): Parameters ---------- - other : Tally or Real + other : openmc.Tally or float The tally or scalar value to divide this tally by Returns ------- - Tally + openmc.Tally A new derived tally which is the dividend of this tally and the other tally or scalar value in the division. @@ -2685,12 +2713,9 @@ class Tally(object): new_tally.with_summary = self.with_summary new_tally.num_realization = self.num_realizations - for self_filter in self.filters: - new_tally.add_filter(self_filter) - for nuclide in self.nuclides: - new_tally.add_nuclide(nuclide) - for score in self.scores: - new_tally.add_score(score) + new_tally.filters = copy.deepcopy(self.filters) + new_tally.nuclides = copy.deepcopy(self.nuclides) + new_tally.scores = copy.deepcopy(self.scores) # If this tally operand is sparse, sparsify the new tally new_tally.sparse = self.sparse @@ -2724,12 +2749,12 @@ class Tally(object): Parameters ---------- - power : Tally or Real + power : openmc.Tally or float The tally or scalar value exponent Returns ------- - Tally + openmc.Tally A new derived tally which is this tally raised to the power of the other tally or scalar value in the exponentiation. @@ -2764,12 +2789,9 @@ class Tally(object): new_tally.with_summary = self.with_summary new_tally.num_realization = self.num_realizations - for self_filter in self.filters: - new_tally.add_filter(self_filter) - for nuclide in self.nuclides: - new_tally.add_nuclide(nuclide) - for score in self.scores: - new_tally.add_score(score) + new_tally.filters = copy.deepcopy(self.filters) + new_tally.nuclides = copy.deepcopy(self.nuclides) + new_tally.scores = copy.deepcopy(self.scores) # If original tally was sparse, sparsify the exponentiated tally new_tally.sparse = self.sparse @@ -2788,12 +2810,12 @@ class Tally(object): Parameters ---------- - other : Integer or Real + other : float The scalar value to add to this tally Returns ------- - Tally + openmc.Tally A new derived tally of this tally added with the scalar value. """ @@ -2807,12 +2829,12 @@ class Tally(object): Parameters ---------- - other : Integer or Real + other : float The scalar value to subtract this tally from Returns ------- - Tally + openmc.Tally A new derived tally of this tally subtracted from the scalar value. """ @@ -2826,12 +2848,12 @@ class Tally(object): Parameters ---------- - other : Integer or Real + other : float The scalar value to multiply with this tally Returns ------- - Tally + openmc.Tally A new derived tally of this tally multiplied by the scalar value. """ @@ -2845,12 +2867,12 @@ class Tally(object): Parameters ---------- - other : Integer or Real + other : float The scalar value to divide by this tally Returns ------- - Tally + openmc.Tally A new derived tally of the scalar value divided by this tally. """ @@ -2862,7 +2884,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new derived tally which is the absolute value of this tally. """ @@ -2876,7 +2898,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new derived tally which is the negated value of this tally. """ @@ -2918,7 +2940,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new tally which encapsulates the subset of data requested in the order each filter, nuclide and score is listed in the parameters. @@ -3041,7 +3063,7 @@ class Tally(object): filter_type : str A filter type string (e.g., 'cell', 'energy') corresponding to the filter bins to sum across - filter_bins : Iterable of Integral or tuple + filter_bins : Iterable of int or tuple A list of the filter bins corresponding to the filter_type parameter Each bin in the list is the integer ID for 'material', 'surface', 'cell', 'cellborn', and 'universe' Filters. Each bin is an integer @@ -3059,7 +3081,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new tally which encapsulates the sum of data requested. """ @@ -3110,11 +3132,11 @@ class Tally(object): if not remove_filter: filter_sum = \ AggregateFilter(self_filter, [tuple(filter_bins)], 'sum') - tally_sum.add_filter(filter_sum) + tally_sum.filters.append(filter_sum) # Add a copy of each filter not summed across to the tally sum else: - tally_sum.add_filter(copy.deepcopy(self_filter)) + tally_sum.filters.append(copy.deepcopy(self_filter)) # Add a copy of this tally's filters to the tally sum else: @@ -3132,7 +3154,7 @@ class Tally(object): # Add AggregateNuclide to the tally sum nuclide_sum = AggregateNuclide(nuclides, 'sum') - tally_sum.add_nuclide(nuclide_sum) + tally_sum.nuclides.append(nuclide_sum) # Add a copy of this tally's nuclides to the tally sum else: @@ -3150,7 +3172,7 @@ class Tally(object): # Add AggregateScore to the tally sum score_sum = AggregateScore(scores, 'sum') - tally_sum.add_score(score_sum) + tally_sum.scores.append(score_sum) # Add a copy of this tally's scores to the tally sum else: @@ -3189,7 +3211,7 @@ class Tally(object): filter_type : str A filter type string (e.g., 'cell', 'energy') corresponding to the filter bins to average across - filter_bins : Iterable of Integral or tuple + filter_bins : Iterable of int or tuple A list of the filter bins corresponding to the filter_type parameter Each bin in the list is the integer ID for 'material', 'surface', 'cell', 'cellborn', and 'universe' Filters. Each bin is an integer @@ -3207,7 +3229,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new tally which encapsulates the average of data requested. """ @@ -3259,11 +3281,11 @@ class Tally(object): if not remove_filter: filter_sum = \ AggregateFilter(self_filter, [tuple(filter_bins)], 'avg') - tally_avg.add_filter(filter_sum) + tally_avg.filters.append(filter_sum) # Add a copy of each filter not averaged across to the tally avg else: - tally_avg.add_filter(copy.deepcopy(self_filter)) + tally_avg.filters.append(copy.deepcopy(self_filter)) # Add a copy of this tally's filters to the tally avg else: @@ -3282,7 +3304,7 @@ class Tally(object): # Add AggregateNuclide to the tally avg nuclide_avg = AggregateNuclide(nuclides, 'avg') - tally_avg.add_nuclide(nuclide_avg) + tally_avg.nuclides.append(nuclide_avg) # Add a copy of this tally's nuclides to the tally avg else: @@ -3301,7 +3323,7 @@ class Tally(object): # Add AggregateScore to the tally avg score_sum = AggregateScore(scores, 'avg') - tally_avg.add_score(score_sum) + tally_avg.scores.append(score_sum) # Add a copy of this tally's scores to the tally avg else: @@ -3340,7 +3362,7 @@ class Tally(object): Returns ------- - Tally + openmc.Tally A new derived Tally with data diagaonalized along the new filter. """ @@ -3354,7 +3376,7 @@ class Tally(object): # Add the new filter to a copy of this Tally new_tally = copy.deepcopy(self) - new_tally.add_filter(new_filter) + new_tally.filters.append(new_filter) # Determine "base" indices along the new "diagonal", and the factor # by which the "base" indices should be repeated to account for all @@ -3391,76 +3413,121 @@ class Tally(object): return new_tally -class TalliesFile(object): - """Tallies file used for an OpenMC simulation. Corresponds directly to the - tallies.xml input file. +class Tallies(cv.CheckedList): + """Collection of Tallies used for an OpenMC simulation. + + This class corresponds directly to the tallies.xml input file. It can be + thought of as a normal Python list where each member is a :class:`Tally`. It + behaves like a list as the following example demonstrates: + + >>> t1 = openmc.Tally() + >>> t2 = openmc.Tally() + >>> t3 = openmc.Tally() + >>> tallies = openmc.Tallies([t1]) + >>> tallies.append(t2) + >>> tallies += [t3] + + Parameters + ---------- + tallies : Iterable of openmc.Tally + Tallies to add to the collection """ - def __init__(self): - # Initialize TalliesFile class attributes - self._tallies = [] - self._meshes = [] + def __init__(self, tallies=None): + super(Tallies, self).__init__(Tally, 'tallies collection') self._tallies_file = ET.Element("tallies") - - @property - def tallies(self): - return self._tallies - - @property - def meshes(self): - return self._meshes + if tallies is not None: + self += tallies def add_tally(self, tally, merge=False): - """Add a tally to the file + """Append tally to collection + + .. deprecated:: 0.8 + Use :meth:`Tallies.append` instead. Parameters ---------- - tally : Tally - Tally to add to file - + tally : openmc.Tally + Tally to add merge : bool Indicate whether the tally should be merged with an existing tally, if possible. Defaults to False. """ + warnings.warn("Tallies.add_tally(...) has been deprecated and may be " + "removed in a future version. Use Tallies.append(...) " + "instead.", DeprecationWarning) + self.append(tally, merge) + def append(self, tally, merge=False): + """Append tally to collection + + Parameters + ---------- + tally : openmc.Tally + Tally to append + merge : bool + Indicate whether the tally should be merged with an existing tally, + if possible. Defaults to False. + + """ if not isinstance(tally, Tally): - msg = 'Unable to add a non-Tally "{0}" to the TalliesFile'.format(tally) - raise ValueError(msg) + msg = 'Unable to add a non-Tally "{0}" to the ' \ + 'Tallies instance'.format(tally) + raise TypeError(msg) if merge: merged = False # Look for a tally to merge with this one - for i, tally2 in enumerate(self._tallies): + for i, tally2 in enumerate(self): # If a mergeable tally is found if tally2.can_merge(tally): - # Replace tally 2 with the merged tally + # Replace tally2 with the merged tally merged_tally = tally2.merge(tally) - self._tallies[i] = merged_tally + self[i] = merged_tally merged = True break - # If not mergeable tally was found, simply add this tally + # If no mergeable tally was found, simply add this tally if not merged: - self._tallies.append(tally) + super(Tallies, self).append(tally) else: - self._tallies.append(tally) + super(Tallies, self).append(tally) - def remove_tally(self, tally): - """Remove a tally from the file + def insert(self, index, item): + """Insert tally before index Parameters ---------- - tally : Tally + index : int + Index in list + item : openmc.Tally + Tally to insert + + """ + super(Tallies, self).insert(index, item) + + def remove_tally(self, tally): + """Remove a tally from the collection + + .. deprecated:: 0.8 + Use :meth:`Tallies.remove` instead. + + Parameters + ---------- + tally : openmc.Tally Tally to remove """ + warnings.warn("Tallies.remove_tally(...) has been deprecated and may " + "be removed in a future version. Use Tallies.remove(...) " + "instead.", DeprecationWarning) - self._tallies.remove(tally) + self.remove(tally) def merge_tallies(self): """Merge any mergeable tallies together. Note that n-way merges are @@ -3468,8 +3535,8 @@ class TalliesFile(object): """ - for i, tally1 in enumerate(self._tallies): - for j, tally2 in enumerate(self._tallies): + for i, tally1 in enumerate(self): + for j, tally2 in enumerate(self): # Do not merge the same tally with itself if i == j: continue @@ -3478,10 +3545,10 @@ class TalliesFile(object): if tally1.can_merge(tally2): # Replace tally 1 with the merged tally merged_tally = tally1.merge(tally2) - self._tallies[i] = merged_tally + self[i] = merged_tally # Remove tally 2 since it is no longer needed - self._tallies.pop(j) + self.pop(j) # Continue iterating from the first loop break @@ -3489,43 +3556,54 @@ class TalliesFile(object): def add_mesh(self, mesh): """Add a mesh to the file + .. deprecated:: 0.8 + Meshes that appear in a tally are automatically added to the + collection. + Parameters ---------- - mesh : openmc.mesh.Mesh + mesh : openmc.Mesh Mesh to add to the file """ - if not isinstance(mesh, Mesh): - msg = 'Unable to add a non-Mesh "{0}" to the TalliesFile'.format(mesh) - raise ValueError(msg) - - self._meshes.append(mesh) + warnings.warn("Tallies.add_mesh(...) has been deprecated and may be " + "removed in a future version. Meshes that appear in a " + "tally are automatically added to the collection.", + DeprecationWarning) def remove_mesh(self, mesh): """Remove a mesh from the file + .. deprecated:: 0.8 + Meshes do not need to be managed explicitly. + Parameters ---------- - mesh : openmc.mesh.Mesh + mesh : openmc.Mesh Mesh to remove from the file """ - - self._meshes.remove(mesh) + warnings.warn("Tallies.remove_mesh(...) has been deprecated and may be " + "removed in a future version. Meshes do not need to be " + "managed explicitly.", DeprecationWarning) def _create_tally_subelements(self): - for tally in self._tallies: + for tally in self: xml_element = tally.get_tally_xml() self._tallies_file.append(xml_element) def _create_mesh_subelements(self): - for mesh in self._meshes: - if len(mesh._name) > 0: - self._tallies_file.append(ET.Comment(mesh._name)) + already_written = set() + for tally in self: + for f in tally.filters: + if f.type == 'mesh' and f.mesh not in already_written: + if len(f.mesh.name) > 0: + self._tallies_file.append(ET.Comment(f.mesh.name)) - xml_element = mesh.get_mesh_xml() - self._tallies_file.append(xml_element) + xml_element = f.mesh.get_mesh_xml() + self._tallies_file.append(xml_element) + already_written.add(f.mesh) def export_to_xml(self): """Create a tallies.xml file that can be used for a simulation. diff --git a/openmc/trigger.py b/openmc/trigger.py index bcac8c31c..b8383bd27 100644 --- a/openmc/trigger.py +++ b/openmc/trigger.py @@ -1,8 +1,10 @@ from numbers import Real from xml.etree import ElementTree as ET import sys +import warnings +from collections import Iterable -from openmc.checkvalue import check_type, check_value +import openmc.checkvalue as cv if sys.version_info[0] >= 3: basestring = str @@ -46,9 +48,7 @@ class Trigger(object): clone._trigger_type = self._trigger_type clone._threshold = self._threshold - clone._scores = [] - for score in self._scores: - clone.add_score(score) + clone.scores = self.scores memo[id(self)] = clone @@ -88,15 +88,26 @@ class Trigger(object): @trigger_type.setter def trigger_type(self, trigger_type): - check_value('tally trigger type', trigger_type, + cv.check_value('tally trigger type', trigger_type, ['variance', 'std_dev', 'rel_err']) self._trigger_type = trigger_type @threshold.setter def threshold(self, threshold): - check_type('tally trigger threshold', threshold, Real) + cv.check_type('tally trigger threshold', threshold, Real) self._threshold = threshold + @scores.setter + def scores(self, scores): + cv.check_type('trigger scores', scores, Iterable, basestring) + + # Set scores making sure not to have duplicates + self._scores = [] + for score in scores: + if score not in self._scores: + self._scores.append(score) + + def add_score(self, score): """Add a score to the list of scores to be checked against the trigger. @@ -107,16 +118,11 @@ class Trigger(object): """ - if not isinstance(score, basestring): - msg = 'Unable to add score "{0}" to tally trigger since ' \ - 'it is not a string'.format(score) - raise ValueError(msg) - - # If the score is already in the Tally, don't add it again - if score in self._scores: - return - else: - self._scores.append(score) + warnings.warn('Trigger.add_score(...) has been deprecated and may be ' + 'removed in a future version. Tally trigger scores should ' + 'be defined using the scores property directly.', + DeprecationWarning) + self.scores.append(score) def get_trigger_xml(self, element): """Return XML representation of the trigger diff --git a/openmc/universe.py b/openmc/universe.py index 74c438615..7f32d68a9 100644 --- a/openmc/universe.py +++ b/openmc/universe.py @@ -1,7 +1,7 @@ -import abc from collections import OrderedDict, Iterable -from numbers import Real, Integral +from numbers import Integral from xml.etree import ElementTree as ET +import random import sys import warnings @@ -9,451 +9,14 @@ import numpy as np import openmc import openmc.checkvalue as cv -from openmc.surface import Halfspace -from openmc.region import Region, Intersection, Complement if sys.version_info[0] >= 3: basestring = str - -# DeprecationWarning filter for the Cell.add_surface(...) method -warnings.simplefilter('always', DeprecationWarning) - -# A static variable for auto-generated Cell IDs -AUTO_CELL_ID = 10000 - # A dictionary for storing IDs of cell elements that have already been written, # used to optimize the writing process WRITTEN_IDS = {} - -def reset_auto_cell_id(): - global AUTO_CELL_ID - AUTO_CELL_ID = 10000 - - -class Cell(object): - """A region of space defined as the intersection of half-space created by - quadric surfaces. - - Parameters - ---------- - cell_id : int, optional - Unique identifier for the cell. If not specified, an identifier will - automatically be assigned. - name : str, optional - Name of the cell. If not specified, the name is the empty string. - - Attributes - ---------- - id : int - Unique identifier for the cell - name : str - Name of the cell - fill : Material or Universe or Lattice or 'void' or iterable of Material - Indicates what the region of space is filled with - region : openmc.region.Region - Region of space that is assigned to the cell. - rotation : ndarray - If the cell is filled with a universe, this array specifies the angles - in degrees about the x, y, and z axes that the filled universe should be - rotated. - translation : ndarray - If the cell is filled with a universe, this array specifies a vector - that is used to translate (shift) the universe. - offsets : ndarray - Array of offsets used for distributed cell searches - distribcell_index : int - Index of this cell in distribcell arrays - - """ - - def __init__(self, cell_id=None, name=''): - # Initialize Cell class attributes - self.id = cell_id - self.name = name - self._fill = None - self._type = None - self._region = None - self._rotation = None - self._translation = None - self._offsets = None - self._distribcell_index = None - - def __eq__(self, other): - if not isinstance(other, Cell): - return False - elif self.id != other.id: - return False - elif self.name != other.name: - return False - elif self.fill != other.fill: - return False - elif self.region != other.region: - return False - elif self.rotation != other.rotation: - return False - elif self.translation != other.translation: - return False - else: - return True - - def __ne__(self, other): - return not self == other - - def __hash__(self): - return hash(repr(self)) - - def __repr__(self): - string = 'Cell\n' - string += '{0: <16}{1}{2}\n'.format('\tID', '=\t', self._id) - string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) - - if isinstance(self._fill, openmc.Material): - string += '{0: <16}{1}{2}\n'.format('\tMaterial', '=\t', - self._fill._id) - elif isinstance(self._fill, Iterable): - string += '{0: <16}{1}'.format('\tMaterial', '=\t') - string += '[' - string += ', '.join(['void' if m == 'void' else str(m.id) - for m in self.fill]) - string += ']\n' - elif isinstance(self._fill, (Universe, Lattice)): - string += '{0: <16}{1}{2}\n'.format('\tFill', '=\t', - self._fill._id) - else: - string += '{0: <16}{1}{2}\n'.format('\tFill', '=\t', self._fill) - - string += '{0: <16}{1}{2}\n'.format('\tRegion', '=\t', self._region) - - string += '{0: <16}{1}{2}\n'.format('\tRotation', '=\t', - self._rotation) - string += '{0: <16}{1}{2}\n'.format('\tTranslation', '=\t', - self._translation) - string += '{0: <16}{1}{2}\n'.format('\tOffset', '=\t', self._offsets) - string += '{0: <16}{1}{2}\n'.format('\tDistribcell index', '=\t', - self._distribcell_index) - - return string - - @property - def id(self): - return self._id - - @property - def name(self): - return self._name - - @property - def fill(self): - return self._fill - - @property - def fill_type(self): - if isinstance(self.fill, openmc.Material): - return 'material' - elif isinstance(self.fill, openmc.Universe): - return 'universe' - elif isinstance(self.fill, openmc.Lattice): - return 'lattice' - else: - return None - - @property - def region(self): - return self._region - - @property - def rotation(self): - return self._rotation - - @property - def translation(self): - return self._translation - - @property - def offsets(self): - return self._offsets - - @property - def distribcell_index(self): - return self._distribcell_index - - @id.setter - def id(self, cell_id): - if cell_id is None: - global AUTO_CELL_ID - self._id = AUTO_CELL_ID - AUTO_CELL_ID += 1 - else: - cv.check_type('cell ID', cell_id, Integral) - cv.check_greater_than('cell ID', cell_id, 0, equality=True) - self._id = cell_id - - @name.setter - def name(self, name): - if name is not None: - cv.check_type('cell name', name, basestring) - self._name = name - else: - self._name = '' - - @fill.setter - def fill(self, fill): - if isinstance(fill, basestring): - if fill.strip().lower() == 'void': - self._type = 'void' - else: - msg = 'Unable to set Cell ID="{0}" to use a non-Material or ' \ - 'Universe fill "{1}"'.format(self._id, fill) - raise ValueError(msg) - - elif isinstance(fill, openmc.Material): - self._type = 'normal' - - elif isinstance(fill, Iterable): - cv.check_type('cell.fill', fill, Iterable, - (openmc.Material, basestring)) - self._type = 'normal' - - elif isinstance(fill, Universe): - self._type = 'fill' - - elif isinstance(fill, Lattice): - self._type = 'lattice' - - else: - msg = 'Unable to set Cell ID="{0}" to use a non-Material or ' \ - 'Universe fill "{1}"'.format(self._id, fill) - raise ValueError(msg) - - self._fill = fill - - @rotation.setter - def rotation(self, rotation): - cv.check_type('cell rotation', rotation, Iterable, Real) - cv.check_length('cell rotation', rotation, 3) - self._rotation = rotation - - @translation.setter - def translation(self, translation): - cv.check_type('cell translation', translation, Iterable, Real) - cv.check_length('cell translation', translation, 3) - self._translation = translation - - @offsets.setter - def offsets(self, offsets): - cv.check_type('cell offsets', offsets, Iterable) - self._offsets = offsets - - @region.setter - def region(self, region): - cv.check_type('cell region', region, Region) - self._region = region - - @distribcell_index.setter - def distribcell_index(self, ind): - cv.check_type('distribcell index', ind, Integral) - self._distribcell_index = ind - - def add_surface(self, surface, halfspace): - """Add a half-space to the list of half-spaces whose intersection defines the - cell. - - Parameters - ---------- - surface : openmc.surface.Surface - Quadric surface dividing space - halfspace : {-1, 1} - Indicate whether the negative or positive half-space is to be used - - """ - - warnings.warn("Cell.add_surface(...) has been deprecated and may be " - "removed in a future version. The region for a Cell " - "should be defined using the region property directly.", - DeprecationWarning) - - if not isinstance(surface, openmc.Surface): - msg = 'Unable to add Surface "{0}" to Cell ID="{1}" since it is ' \ - 'not a Surface object'.format(surface, self._id) - raise ValueError(msg) - - if halfspace not in [-1, +1]: - msg = 'Unable to add Surface "{0}" to Cell ID="{1}" with halfspace ' \ - '"{2}" since it is not +/-1'.format(surface, self._id, halfspace) - raise ValueError(msg) - - # If no region has been assigned, simply use the half-space. Otherwise, - # take the intersection of the current region and the half-space - # specified - region = +surface if halfspace == 1 else -surface - if self.region is None: - self.region = region - else: - if isinstance(self.region, Intersection): - self.region.nodes.append(region) - else: - self.region = Intersection(self.region, region) - - def get_cell_instance(self, path, distribcell_index): - # Get the current element and remove it from the list - cell_id = path[0] - path = path[1:] - - # If the Cell is filled by a Material - if self._type == 'normal' or self._type == 'void': - offset = 0 - - # If the Cell is filled by a Universe - elif self._type == 'fill': - offset = self.offsets[distribcell_index-1] - offset += self.fill.get_cell_instance(path, distribcell_index) - - # If the Cell is filled by a Lattice - else: - offset = self.fill.get_cell_instance(path, distribcell_index) - - return offset - - def get_all_nuclides(self): - """Return all nuclides contained in the cell - - Returns - ------- - nuclides : dict - Dictionary whose keys are nuclide names and values are 2-tuples of - (nuclide, density) - - """ - - nuclides = OrderedDict() - - if self._type != 'void': - nuclides.update(self._fill.get_all_nuclides()) - - return nuclides - - def get_all_cells(self): - """Return all cells that are contained within this one if it is filled with a - universe or lattice - - Returns - ------- - cells : dict - Dictionary whose keys are cell IDs and values are Cell instances - - """ - - cells = OrderedDict() - - if self._type == 'fill' or self._type == 'lattice': - cells.update(self._fill.get_all_cells()) - - return cells - - def get_all_materials(self): - """Return all materials that are contained within the cell - - Returns - ------- - materials : dict - Dictionary whose keys are material IDs and values are Material instances - - """ - - materials = OrderedDict() - if self.fill_type == 'material': - materials[self.fill.id] = self.fill - - # Append all Cells in each Cell in the Universe to the dictionary - cells = self.get_all_cells() - for cell_id, cell in cells.items(): - materials.update(cell.get_all_materials()) - - return materials - - def get_all_universes(self): - """Return all universes that are contained within this one if any of - its cells are filled with a universe or lattice. - - Returns - ------- - universes : dict - Dictionary whose keys are universe IDs and values are Universe - instances - - """ - - universes = OrderedDict() - - if self._type == 'fill': - universes[self._fill._id] = self._fill - universes.update(self._fill.get_all_universes()) - elif self._type == 'lattice': - universes.update(self._fill.get_all_universes()) - - return universes - - def create_xml_subelement(self, xml_element): - element = ET.Element("cell") - element.set("id", str(self.id)) - - if len(self._name) > 0: - element.set("name", str(self.name)) - - if isinstance(self.fill, basestring): - element.set("material", "void") - - elif isinstance(self.fill, openmc.Material): - element.set("material", str(self.fill.id)) - - elif isinstance(self.fill, Iterable): - element.set("material", ' '.join([m if m == 'void' else str(m.id) - for m in self.fill])) - - elif isinstance(self.fill, (Universe, Lattice)): - element.set("fill", str(self.fill.id)) - self.fill.create_xml_subelement(xml_element) - - else: - element.set("fill", str(self.fill)) - self.fill.create_xml_subelement(xml_element) - - if self.region is not None: - # Set the region attribute with the region specification - element.set("region", str(self.region)) - - # Only surfaces that appear in a region are added to the geometry - # file, so the appropriate check is performed here. First we create - # a function which is called recursively to navigate through the CSG - # tree. When it reaches a leaf (a Halfspace), it creates a - # element for the corresponding surface if none has been created - # thus far. - def create_surface_elements(node, element): - if isinstance(node, Halfspace): - path = './surface[@id=\'{0}\']'.format(node.surface.id) - if xml_element.find(path) is None: - surface_subelement = node.surface.create_xml_subelement() - xml_element.append(surface_subelement) - elif isinstance(node, Complement): - create_surface_elements(node.node, element) - else: - for subnode in node.nodes: - create_surface_elements(subnode, element) - - # Call the recursive function from the top node - create_surface_elements(self.region, xml_element) - - if self.translation is not None: - element.set("translation", ' '.join(map(str, self.translation))) - - if self.rotation is not None: - element.set("rotation", ' '.join(map(str, self.rotation))) - - return element - - # A static variable for auto-generated Lattice (Universe) IDs AUTO_UNIVERSE_ID = 10000 @@ -473,6 +36,8 @@ class Universe(object): automatically be assigned name : str, optional Name of the universe. If not specified, the name is the empty string. + cells : Iterable of openmc.Cell, optional + Cells to add to the universe. By default no cells are added. Attributes ---------- @@ -480,12 +45,13 @@ class Universe(object): Unique identifier of the universe name : str Name of the universe - cells : dict - Dictionary whose keys are cell IDs and values are Cell instances + cells : collections.OrderedDict + Dictionary whose keys are cell IDs and values are :class:`Cell` + instances """ - def __init__(self, universe_id=None, name=''): + def __init__(self, universe_id=None, name='', cells=None): # Initialize Cell class attributes self.id = universe_id self.name = name @@ -497,7 +63,9 @@ class Universe(object): # Keys - Cell IDs # Values - Offsets self._cell_offsets = OrderedDict() - self._num_regions = 0 + + if cells is not None: + self.add_cells(cells) def __eq__(self, other): if not isinstance(other, Universe): @@ -523,8 +91,6 @@ class Universe(object): string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) string += '{0: <16}{1}{2}\n'.format('\tCells', '=\t', list(self._cells.keys())) - string += '{0: <16}{1}{2}\n'.format('\t# Regions', '=\t', - self._num_regions) return string @property @@ -558,17 +124,129 @@ class Universe(object): else: self._name = '' + def find(self, point): + """Find cells/universes/lattices which contain a given point + + Parameters + ---------- + point : 3-tuple of float + Cartesian coordinates of the point + + Returns + ------- + list + Sequence of universes, cells, and lattices which are traversed to + find the given point + + """ + p = np.asarray(point) + for cell in self._cells.values(): + if p in cell: + if cell.fill_type in ('material', 'distribmat', 'void'): + return [self, cell] + elif cell.fill_type == 'universe': + if cell.translation is not None: + p -= cell.translation + if cell.rotation is not None: + p[:] = cell.rotation_matrix.dot(p) + return [self, cell] + cell.fill.find(p) + else: + return [self, cell] + cell.fill.find(p) + return [] + + def plot(self, center=(0., 0., 0.), width=(1., 1.), pixels=(200, 200), + basis='xy', color_by='cell', seed=None): + """Display a slice plot of the universe. + + Parameters + ---------- + center : Iterable of float + Coordinates at the center of the plot + width : Iterable of float + Width of the plot in each basis direction + pixels : Iterable of int + Number of pixels to use in each basis direction + basis : {'xy', 'xz', 'yz'} + The basis directions for the plot + color_by : {'cell', 'material'} + Indicate whether the plot should be colored by cell or by material + seed : hashable object or None + Hashable object which is used to seed the random number generator + used to select colors. If None, the generator is seeded from the + current time. + + """ + import matplotlib.pyplot as plt + + # Seed the random number generator + if seed is not None: + random.seed(seed) + + if basis == 'xy': + x_min = center[0] - 0.5*width[0] + x_max = center[0] + 0.5*width[0] + y_min = center[1] - 0.5*width[1] + y_max = center[1] + 0.5*width[1] + elif basis == 'yz': + # The x-axis will correspond to physical y and the y-axis will correspond to physical z + x_min = center[1] - 0.5*width[0] + x_max = center[1] + 0.5*width[0] + y_min = center[2] - 0.5*width[1] + y_max = center[2] + 0.5*width[1] + elif basis == 'xz': + # The y-axis will correspond to physical z + x_min = center[0] - 0.5*width[0] + x_max = center[0] + 0.5*width[0] + y_min = center[2] - 0.5*width[1] + y_max = center[2] + 0.5*width[1] + + # Determine locations to determine cells at + x_coords = np.linspace(x_min, x_max, pixels[0], endpoint=False) + \ + 0.5*(x_max - x_min)/pixels[0] + y_coords = np.linspace(y_max, y_min, pixels[1], endpoint=False) - \ + 0.5*(y_max - y_min)/pixels[1] + + colors = {} + img = np.zeros(pixels + (4,)) # Use RGBA form + for i, x in enumerate(x_coords): + for j, y in enumerate(y_coords): + if basis == 'xy': + path = self.find((x, y, center[2])) + elif basis == 'yz': + path = self.find((center[0], x, y)) + elif basis == 'xz': + path = self.find((x, center[1], y)) + + if len(path) > 0: + try: + if color_by == 'cell': + uid = path[-1].id + elif color_by == 'material': + if path[-1].fill_type == 'material': + uid = path[-1].fill.id + else: + continue + except AttributeError: + continue + if uid not in colors: + colors[uid] = (random.random(), random.random(), + random.random(), 1.0) + img[j,i,:] = colors[uid] + + plt.imshow(img, extent=(x_min, x_max, y_min, y_max)) + plt.show() + def add_cell(self, cell): """Add a cell to the universe. Parameters ---------- - cell : Cell + cell : openmc.Cell Cell to add """ - if not isinstance(cell, Cell): + if not isinstance(cell, openmc.Cell): msg = 'Unable to add a Cell to Universe ID="{0}" since "{1}" is not ' \ 'a Cell'.format(self._id, cell) raise ValueError(msg) @@ -583,7 +261,7 @@ class Universe(object): Parameters ---------- - cells : array-like of Cell + cells : Iterable of openmc.Cell Cells to add """ @@ -601,12 +279,12 @@ class Universe(object): Parameters ---------- - cell : Cell + cell : openmc.Cell Cell to remove """ - if not isinstance(cell, Cell): + if not isinstance(cell, openmc.Cell): msg = 'Unable to remove a Cell from Universe ID="{0}" since "{1}" is ' \ 'not a Cell'.format(self._id, cell) raise ValueError(msg) @@ -621,11 +299,19 @@ class Universe(object): self._cells.clear() def get_cell_instance(self, path, distribcell_index): - # Get the current element and remove it from the list - path = path[1:] - # Get the Cell ID - cell_id = path[0] + # Pop off the root Universe ID from the path + next_index = path.index('-') + path = path[next_index+2:] + + # Extract the Cell ID from the path + if '-' in path: + next_index = path.index('-') + cell_id = int(path[:next_index]) + path = path[next_index+2:] + else: + cell_id = int(path) + path = '' # Make a recursive call to the Cell within this Universe offset = self.cells[cell_id].get_cell_instance(path, distribcell_index) @@ -638,7 +324,7 @@ class Universe(object): Returns ------- - nuclides : dict + nuclides : collections.OrderedDict Dictionary whose keys are nuclide names and values are 2-tuples of (nuclide, density) @@ -657,8 +343,9 @@ class Universe(object): Returns ------- - cells : dict - Dictionary whose keys are cell IDs and values are Cell instances + cells : collections.OrderedDict + Dictionary whose keys are cell IDs and values are :class:`Cell` + instances """ @@ -678,8 +365,9 @@ class Universe(object): Returns ------- - materials : dict - Dictionary whose keys are material IDs and values are Material instances + materials : Collections.OrderedDict + Dictionary whose keys are material IDs and values are + :class:`Material` instances """ @@ -697,9 +385,9 @@ class Universe(object): Returns ------- - universes : dict - Dictionary whose keys are universe IDs and values are Universe - instances + universes : collections.OrderedDict + Dictionary whose keys are universe IDs and values are + :class:`Universe` instances """ @@ -729,849 +417,3 @@ class Universe(object): # Append the Universe ID to the subelement and add to Element cell_subelement.set("universe", str(self._id)) xml_element.append(cell_subelement) - - -class Lattice(object): - """A repeating structure wherein each element is a universe. - - Parameters - ---------- - lattice_id : int, optional - Unique identifier for the lattice. If not specified, an identifier will - automatically be assigned. - name : str, optional - Name of the lattice. If not specified, the name is the empty string. - - Attributes - ---------- - id : int - Unique identifier for the lattice - name : str - Name of the lattice - pitch : float - Pitch of the lattice in cm - outer : int - The unique identifier of a universe to fill all space outside the - lattice - universes : ndarray of Universe - An array of universes filling each element of the lattice - - """ - - # This is an abstract class which cannot be instantiated - __metaclass__ = abc.ABCMeta - - def __init__(self, lattice_id=None, name=''): - # Initialize Lattice class attributes - self.id = lattice_id - self.name = name - self._pitch = None - self._outer = None - self._universes = None - - def __eq__(self, other): - if not isinstance(other, Lattice): - return False - elif self.id != other.id: - return False - elif self.name != other.name: - return False - elif self.pitch != other.pitch: - return False - elif self.outer != other.outer: - return False - elif self.universes != other.universes: - return False - else: - return True - - def __ne__(self, other): - return not self == other - - @property - def id(self): - return self._id - - @property - def name(self): - return self._name - - @property - def pitch(self): - return self._pitch - - @property - def outer(self): - return self._outer - - @property - def universes(self): - return self._universes - - @id.setter - def id(self, lattice_id): - if lattice_id is None: - global AUTO_UNIVERSE_ID - self._id = AUTO_UNIVERSE_ID - AUTO_UNIVERSE_ID += 1 - else: - cv.check_type('lattice ID', lattice_id, Integral) - cv.check_greater_than('lattice ID', lattice_id, 0, equality=True) - self._id = lattice_id - - @name.setter - def name(self, name): - if name is not None: - cv.check_type('lattice name', name, basestring) - self._name = name - else: - self._name = '' - - @outer.setter - def outer(self, outer): - cv.check_type('outer universe', outer, Universe) - self._outer = outer - - @universes.setter - def universes(self, universes): - cv.check_iterable_type('lattice universes', universes, Universe, - min_depth=2, max_depth=3) - self._universes = np.asarray(universes) - - def get_unique_universes(self): - """Determine all unique universes in the lattice - - Returns - ------- - universes : dict - Dictionary whose keys are universe IDs and values are Universe - instances - - """ - - univs = OrderedDict() - for k in range(len(self._universes)): - for j in range(len(self._universes[k])): - if isinstance(self._universes[k][j], Universe): - u = self._universes[k][j] - univs[u._id] = u - else: - for i in range(len(self._universes[k][j])): - u = self._universes[k][j][i] - assert isinstance(u, Universe) - univs[u._id] = u - - if self.outer is not None: - univs[self.outer._id] = self.outer - - return univs - - def get_all_nuclides(self): - """Return all nuclides contained in the lattice - - Returns - ------- - nuclides : dict - Dictionary whose keys are nuclide names and values are 2-tuples of - (nuclide, density) - - """ - - nuclides = OrderedDict() - - # Get all unique Universes contained in each of the lattice cells - unique_universes = self.get_unique_universes() - - # Append all Universes containing each cell to the dictionary - for universe_id, universe in unique_universes.items(): - nuclides.update(universe.get_all_nuclides()) - - return nuclides - - def get_all_cells(self): - """Return all cells that are contained within the lattice - - Returns - ------- - cells : dict - Dictionary whose keys are cell IDs and values are Cell instances - - """ - - cells = OrderedDict() - unique_universes = self.get_unique_universes() - - for universe_id, universe in unique_universes.items(): - cells.update(universe.get_all_cells()) - - return cells - - def get_all_materials(self): - """Return all materials that are contained within the lattice - - Returns - ------- - materials : dict - Dictionary whose keys are material IDs and values are Material instances - - """ - - materials = OrderedDict() - - # Append all Cells in each Cell in the Universe to the dictionary - cells = self.get_all_cells() - for cell_id, cell in cells.items(): - materials.update(cell.get_all_materials()) - - return materials - - def get_all_universes(self): - """Return all universes that are contained within the lattice - - Returns - ------- - universes : dict - Dictionary whose keys are universe IDs and values are Universe - instances - - """ - - # Initialize a dictionary of all Universes contained by the Lattice - # in each nested Universe level - all_universes = OrderedDict() - - # Get all unique Universes contained in each of the lattice cells - unique_universes = self.get_unique_universes() - - # Add the unique Universes filling each Lattice cell - all_universes.update(unique_universes) - - # Append all Universes containing each cell to the dictionary - for universe_id, universe in unique_universes.items(): - all_universes.update(universe.get_all_universes()) - - return all_universes - - -class RectLattice(Lattice): - """A lattice consisting of rectangular prisms. - - Parameters - ---------- - lattice_id : int, optional - Unique identifier for the lattice. If not specified, an identifier will - automatically be assigned. - name : str, optional - Name of the lattice. If not specified, the name is the empty string. - - Attributes - ---------- - id : int - Unique identifier for the lattice - name : str - Name of the lattice - dimension : array-like of int - An array of two or three integers representing the number of lattice - cells in the x- and y- (and z-) directions, respectively. - lower_left : array-like of float - The coordinates of the lower-left corner of the lattice. If the lattice - is two-dimensional, only the x- and y-coordinates are specified. - - """ - - def __init__(self, lattice_id=None, name=''): - super(RectLattice, self).__init__(lattice_id, name) - - # Initialize Lattice class attributes - self._dimension = None - self._lower_left = None - self._offsets = None - - def __eq__(self, other): - if not isinstance(other, RectLattice): - return False - elif not super(RectLattice, self).__eq__(other): - return False - elif self.dimension != other.dimension: - return False - elif self.lower_left != other.lower_left: - return False - else: - return True - - def __ne__(self, other): - return not self == other - - def __hash__(self): - return hash(repr(self)) - - def __repr__(self): - string = 'RectLattice\n' - string += '{0: <16}{1}{2}\n'.format('\tID', '=\t', self._id) - string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) - string += '{0: <16}{1}{2}\n'.format('\tDimension', '=\t', - self._dimension) - string += '{0: <16}{1}{2}\n'.format('\tLower Left', '=\t', - self._lower_left) - string += '{0: <16}{1}{2}\n'.format('\tPitch', '=\t', self._pitch) - - if self._outer is not None: - string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', - self._outer._id) - else: - string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', - self._outer) - - string += '{0: <16}\n'.format('\tUniverses') - - # Lattice nested Universe IDs - column major for Fortran - for i, universe in enumerate(np.ravel(self._universes)): - string += '{0} '.format(universe._id) - - # Add a newline character every time we reach end of row of cells - if (i+1) % self._dimension[-1] == 0: - string += '\n' - - string = string.rstrip('\n') - - if self._offsets is not None: - string += '{0: <16}\n'.format('\tOffsets') - - # Lattice cell offsets - for i, offset in enumerate(np.ravel(self._offsets)): - string += '{0} '.format(offset) - - # Add a newline character when we reach end of row of cells - if (i+1) % self._dimension[-1] == 0: - string += '\n' - - string = string.rstrip('\n') - - return string - - @property - def dimension(self): - return self._dimension - - @property - def lower_left(self): - return self._lower_left - - @property - def offsets(self): - return self._offsets - - @dimension.setter - def dimension(self, dimension): - cv.check_type('lattice dimension', dimension, Iterable, Integral) - cv.check_length('lattice dimension', dimension, 2, 3) - for dim in dimension: - cv.check_greater_than('lattice dimension', dim, 0) - self._dimension = dimension - - @lower_left.setter - def lower_left(self, lower_left): - cv.check_type('lattice lower left corner', lower_left, Iterable, Real) - cv.check_length('lattice lower left corner', lower_left, 2, 3) - self._lower_left = lower_left - - @offsets.setter - def offsets(self, offsets): - cv.check_type('lattice offsets', offsets, Iterable) - self._offsets = offsets - - @Lattice.pitch.setter - def pitch(self, pitch): - cv.check_type('lattice pitch', pitch, Iterable, Real) - cv.check_length('lattice pitch', pitch, 2, 3) - for dim in pitch: - cv.check_greater_than('lattice pitch', dim, 0.0) - self._pitch = pitch - - def get_cell_instance(self, path, distribcell_index): - # Get the current element and remove it from the list - i = path[0] - path = path[1:] - - # For 2D Lattices - if len(self._dimension) == 2: - offset = self._offsets[i[3]-1, i[2]-1, i[1]-1, distribcell_index-1] - offset += self._universes[i[1]-1][i[2]-1].get_cell_instance(path, - distribcell_index) - - # For 3D Lattices - else: - offset = self._offsets[i[3]-1, i[2]-1, i[1]-1, distribcell_index-1] - offset += self._universes[i[3]-1][i[2]-1][i[1]-1].get_cell_instance( - path, distribcell_index) - - return offset - - def create_xml_subelement(self, xml_element): - - # Determine if XML element already contains subelement for this Lattice - path = './lattice[@id=\'{0}\']'.format(self._id) - test = xml_element.find(path) - - # If the element does contain the Lattice subelement, then return - if test is not None: - return - - lattice_subelement = ET.Element("lattice") - lattice_subelement.set("id", str(self._id)) - - if len(self._name) > 0: - lattice_subelement.set("name", str(self._name)) - - # Export the Lattice cell pitch - pitch = ET.SubElement(lattice_subelement, "pitch") - pitch.text = ' '.join(map(str, self._pitch)) - - # Export the Lattice outer Universe (if specified) - if self._outer is not None: - outer = ET.SubElement(lattice_subelement, "outer") - outer.text = '{0}'.format(self._outer._id) - self._outer.create_xml_subelement(xml_element) - - # Export Lattice cell dimensions - dimension = ET.SubElement(lattice_subelement, "dimension") - dimension.text = ' '.join(map(str, self._dimension)) - - # Export Lattice lower left - lower_left = ET.SubElement(lattice_subelement, "lower_left") - lower_left.text = ' '.join(map(str, self._lower_left)) - - # Export the Lattice nested Universe IDs - column major for Fortran - universe_ids = '\n' - - # 3D Lattices - if len(self._dimension) == 3: - for z in range(self._dimension[2]): - for y in range(self._dimension[1]): - for x in range(self._dimension[0]): - universe = self._universes[z][y][x] - - # Append Universe ID to the Lattice XML subelement - universe_ids += '{0} '.format(universe._id) - - # Create XML subelement for this Universe - universe.create_xml_subelement(xml_element) - - # Add newline character when we reach end of row of cells - universe_ids += '\n' - - # Add newline character when we reach end of row of cells - universe_ids += '\n' - - # 2D Lattices - else: - for y in range(self._dimension[1]): - for x in range(self._dimension[0]): - universe = self._universes[y][x] - - # Append Universe ID to Lattice XML subelement - universe_ids += '{0} '.format(universe._id) - - # Create XML subelement for this Universe - universe.create_xml_subelement(xml_element) - - # Add newline character when we reach end of row of cells - universe_ids += '\n' - - # Remove trailing newline character from Universe IDs string - universe_ids = universe_ids.rstrip('\n') - - universes = ET.SubElement(lattice_subelement, "universes") - universes.text = universe_ids - - # Append the XML subelement for this Lattice to the XML element - xml_element.append(lattice_subelement) - - -class HexLattice(Lattice): - """A lattice consisting of hexagonal prisms. - - Parameters - ---------- - lattice_id : int, optional - Unique identifier for the lattice. If not specified, an identifier will - automatically be assigned. - name : str, optional - Name of the lattice. If not specified, the name is the empty string. - - Attributes - ---------- - id : int - Unique identifier for the lattice - name : str - Name of the lattice - num_rings : int - Number of radial ring positions in the xy-plane - num_axial : int - Number of positions along the z-axis. - center : array-like of float - Coordinates of the center of the lattice. If the lattice does not have - axial sections then only the x- and y-coordinates are specified - - """ - - def __init__(self, lattice_id=None, name=''): - super(HexLattice, self).__init__(lattice_id, name) - - # Initialize Lattice class attributes - self._num_rings = None - self._num_axial = None - self._center = None - - def __eq__(self, other): - if not isinstance(other, HexLattice): - return False - elif not super(HexLattice, self).__eq__(other): - return False - elif self.num_rings != other.num_rings: - return False - elif self.num_axial != other.num_axial: - return False - elif self.center != other.center: - return False - else: - return True - - def __ne__(self, other): - return not self == other - - def __hash__(self): - return hash(repr(self)) - - def __repr__(self): - string = 'HexLattice\n' - string += '{0: <16}{1}{2}\n'.format('\tID', '=\t', self._id) - string += '{0: <16}{1}{2}\n'.format('\tName', '=\t', self._name) - string += '{0: <16}{1}{2}\n'.format('\t# Rings', '=\t', self._num_rings) - string += '{0: <16}{1}{2}\n'.format('\t# Axial', '=\t', self._num_axial) - string += '{0: <16}{1}{2}\n'.format('\tCenter', '=\t', - self._center) - string += '{0: <16}{1}{2}\n'.format('\tPitch', '=\t', self._pitch) - - if self._outer is not None: - string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', - self._outer._id) - else: - string += '{0: <16}{1}{2}\n'.format('\tOuter', '=\t', - self._outer) - - string += '{0: <16}\n'.format('\tUniverses') - - if self._num_axial is not None: - slices = [self._repr_axial_slice(x) for x in self._universes] - string += '\n'.join(slices) - - else: - string += self._repr_axial_slice(self._universes) - - return string - - @property - def num_rings(self): - return self._num_rings - - @property - def num_axial(self): - return self._num_axial - - @property - def center(self): - return self._center - - @num_rings.setter - def num_rings(self, num_rings): - cv.check_type('number of rings', num_rings, Integral) - cv.check_greater_than('number of rings', num_rings, 0) - self._num_rings = num_rings - - @num_axial.setter - def num_axial(self, num_axial): - cv.check_type('number of axial', num_axial, Integral) - cv.check_greater_than('number of axial', num_axial, 0) - self._num_axial = num_axial - - @center.setter - def center(self, center): - cv.check_type('lattice center', center, Iterable, Real) - cv.check_length('lattice center', center, 2, 3) - self._center = center - - @Lattice.pitch.setter - def pitch(self, pitch): - cv.check_type('lattice pitch', pitch, Iterable, Real) - cv.check_length('lattice pitch', pitch, 1, 2) - for dim in pitch: - cv.check_greater_than('lattice pitch', dim, 0) - self._pitch = pitch - - @Lattice.universes.setter - def universes(self, universes): - # Call Lattice.universes parent class setter property - Lattice.universes.fset(self, universes) - - # NOTE: This routine assumes that the user creates a "ragged" list of - # lists, where each sub-list corresponds to one ring of Universes. - # The sub-lists are ordered from outermost ring to innermost ring. - # The Universes within each sub-list are ordered from the "top" in a - # clockwise fashion. - - # Check to see if the given universes look like a 2D or a 3D array. - if isinstance(self._universes[0][0], Universe): - n_dims = 2 - - elif isinstance(self._universes[0][0][0], Universe): - n_dims = 3 - - else: - msg = 'HexLattice ID={0:d} does not appear to be either 2D or ' \ - '3D. Make sure set_universes was given a two-deep or ' \ - 'three-deep iterable of universes.'.format(self._id) - raise RuntimeError(msg) - - # Set the number of axial positions. - if n_dims == 3: - self.num_axial = len(self._universes) - else: - self._num_axial = None - - # Set the number of rings and make sure this number is consistent for - # all axial positions. - if n_dims == 3: - self.num_rings = len(self._universes) - for rings in self._universes: - if len(rings) != self._num_rings: - msg = 'HexLattice ID={0:d} has an inconsistent number of ' \ - 'rings per axial positon'.format(self._id) - raise ValueError(msg) - - else: - self.num_rings = len(self._universes) - - # Make sure there are the correct number of elements in each ring. - if n_dims == 3: - for axial_slice in self._universes: - # Check the center ring. - if len(axial_slice[-1]) != 1: - msg = 'HexLattice ID={0:d} has the wrong number of ' \ - 'elements in the innermost ring. Only 1 element is ' \ - 'allowed in the innermost ring.'.format(self._id) - raise ValueError(msg) - - # Check the outer rings. - for r in range(self._num_rings-1): - if len(axial_slice[r]) != 6*(self._num_rings - 1 - r): - msg = 'HexLattice ID={0:d} has the wrong number of ' \ - 'elements in ring number {1:d} (counting from the '\ - 'outermost ring). This ring should have {2:d} ' \ - 'elements.'.format(self._id, r, - 6*(self._num_rings - 1 - r)) - raise ValueError(msg) - - else: - axial_slice = self._universes - # Check the center ring. - if len(axial_slice[-1]) != 1: - msg = 'HexLattice ID={0:d} has the wrong number of ' \ - 'elements in the innermost ring. Only 1 element is ' \ - 'allowed in the innermost ring.'.format(self._id) - raise ValueError(msg) - - # Check the outer rings. - for r in range(self._num_rings-1): - if len(axial_slice[r]) != 6*(self._num_rings - 1 - r): - msg = 'HexLattice ID={0:d} has the wrong number of ' \ - 'elements in ring number {1:d} (counting from the '\ - 'outermost ring). This ring should have {2:d} ' \ - 'elements.'.format(self._id, r, - 6*(self._num_rings - 1 - r)) - raise ValueError(msg) - - def create_xml_subelement(self, xml_element): - # Determine if XML element already contains subelement for this Lattice - path = './hex_lattice[@id=\'{0}\']'.format(self._id) - test = xml_element.find(path) - - # If the element does contain the Lattice subelement, then return - if test is not None: - return - - lattice_subelement = ET.Element("hex_lattice") - lattice_subelement.set("id", str(self._id)) - - if len(self._name) > 0: - lattice_subelement.set("name", str(self._name)) - - # Export the Lattice cell pitch - pitch = ET.SubElement(lattice_subelement, "pitch") - pitch.text = ' '.join(map(str, self._pitch)) - - # Export the Lattice outer Universe (if specified) - if self._outer is not None: - outer = ET.SubElement(lattice_subelement, "outer") - outer.text = '{0}'.format(self._outer._id) - self._outer.create_xml_subelement(xml_element) - - lattice_subelement.set("n_rings", str(self._num_rings)) - - if self._num_axial is not None: - lattice_subelement.set("n_axial", str(self._num_axial)) - - # Export Lattice cell center - dimension = ET.SubElement(lattice_subelement, "center") - dimension.text = ' '.join(map(str, self._center)) - - # Export the Lattice nested Universe IDs. - - # 3D Lattices - if self._num_axial is not None: - slices = [] - for z in range(self._num_axial): - # Initialize the center universe. - universe = self._universes[z][-1][0] - universe.create_xml_subelement(xml_element) - - # Initialize the remaining universes. - for r in range(self._num_rings-1): - for theta in range(6*(self._num_rings - 1 - r)): - universe = self._universes[z][r][theta] - universe.create_xml_subelement(xml_element) - - # Get a string representation of the universe IDs. - slices.append(self._repr_axial_slice(self._universes[z])) - - # Collapse the list of axial slices into a single string. - universe_ids = '\n'.join(slices) - - # 2D Lattices - else: - # Initialize the center universe. - universe = self._universes[-1][0] - universe.create_xml_subelement(xml_element) - - # Initialize the remaining universes. - for r in range(self._num_rings - 1): - for theta in range(6*(self._num_rings - 1 - r)): - universe = self._universes[r][theta] - universe.create_xml_subelement(xml_element) - - # Get a string representation of the universe IDs. - universe_ids = self._repr_axial_slice(self._universes) - - universes = ET.SubElement(lattice_subelement, "universes") - universes.text = '\n' + universe_ids - - # Append the XML subelement for this Lattice to the XML element - xml_element.append(lattice_subelement) - - def _repr_axial_slice(self, universes): - """Return string representation for the given 2D group of universes. - - The 'universes' argument should be a list of lists of universes where - each sub-list represents a single ring. The first list should be the - outer ring. - """ - - # Find the largest universe ID and count the number of digits so we can - # properly pad the output string later. - largest_id = max([max([univ._id for univ in ring]) - for ring in universes]) - n_digits = len(str(largest_id)) - pad = ' '*n_digits - id_form = '{: ^' + str(n_digits) + 'd}' - - # Initialize the list for each row. - rows = [ [] for i in range(1 + 4 * (self._num_rings-1)) ] - middle = 2 * (self._num_rings - 1) - - # Start with the degenerate first ring. - universe = universes[-1][0] - rows[middle] = [id_form.format(universe._id)] - - # Add universes one ring at a time. - for r in range(1, self._num_rings): - # r_prime increments down while r increments up. - r_prime = self._num_rings - 1 - r - theta = 0 - y = middle + 2*r - - # Climb down the top-right. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].append(id_form.format(universe._id)) - - # Translate the indices. - y -= 1 - theta += 1 - - # Climb down the right. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].append(id_form.format(universe._id)) - - # Translate the indices. - y -= 2 - theta += 1 - - # Climb down the bottom-right. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].append(id_form.format(universe._id)) - - # Translate the indices. - y -= 1 - theta += 1 - - # Climb up the bottom-left. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].insert(0, id_form.format(universe._id)) - - # Translate the indices. - y += 1 - theta += 1 - - # Climb up the left. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].insert(0, id_form.format(universe._id)) - - # Translate the indices. - y += 2 - theta += 1 - - # Climb up the top-left. - for i in range(r): - # Add the universe. - universe = universes[r_prime][theta] - rows[y].insert(0, id_form.format(universe._id)) - - # Translate the indices. - y += 1 - theta += 1 - - # Flip the rows and join each row into a single string. - rows = [pad.join(x) for x in rows[::-1]] - - # Pad the beginning of the rows so they line up properly. - for y in range(self._num_rings - 1): - rows[y] = (self._num_rings - 1 - y)*pad + rows[y] - rows[-1 - y] = (self._num_rings - 1 - y)*pad + rows[-1 - y] - - for y in range(self._num_rings % 2, self._num_rings, 2): - rows[middle + y] = pad + rows[middle + y] - if y != 0: - rows[middle - y] = pad + rows[middle - y] - - # Join the rows together and return the string. - universe_ids = '\n'.join(rows) - return universe_ids diff --git a/setup.py b/setup.py index 87fdff68c..770f280ad 100644 --- a/setup.py +++ b/setup.py @@ -11,7 +11,7 @@ except ImportError: kwargs = {'name': 'openmc', 'version': '0.7.1', - 'packages': ['openmc', 'openmc.mgxs', 'openmc.stats'], + 'packages': ['openmc', 'openmc.data', 'openmc.mgxs', 'openmc.stats'], 'scripts': glob.glob('scripts/openmc-*'), # Metadata @@ -36,7 +36,7 @@ if have_setuptools: # Optional dependencies 'extras_require': { - 'pandas': ['pandas'], + 'pandas': ['pandas>=0.17.0'], 'sparse' : ['scipy'], 'vtk': ['vtk', 'silomesh'], 'validate': ['lxml'] diff --git a/src/ace.F90 b/src/ace.F90 index 5012c9b88..4a9f28705 100644 --- a/src/ace.F90 +++ b/src/ace.F90 @@ -1,23 +1,24 @@ module ace - use ace_header, only: Reaction + use angleenergy_header, only: AngleEnergy use constants use distribution_univariate, only: Uniform, Equiprobable, Tabular use endf, only: is_fission, is_disappearance + use endf_header, only: Constant1D, Tabulated1D, Polynomial use energy_distribution, only: TabularEquiprobable, LevelInelastic, & - ContinuousTabular, MaxwellEnergy, Evaporation, WattEnergy, NBodyPhaseSpace + ContinuousTabular, MaxwellEnergy, Evaporation, WattEnergy use error, only: fatal_error, warning - use fission, only: nu_total use global use list_header, only: ListInt use material_header, only: Material use nuclide_header use output, only: write_message + use product_header, only: ReactionProduct use sab_header use set_header, only: SetChar - use secondary_header, only: AngleEnergy use secondary_correlated, only: CorrelatedAngleEnergy use secondary_kalbach, only: KalbachMann + use secondary_nbody, only: NBodyPhaseSpace use secondary_uncorrelated, only: UncorrelatedAngleEnergy use string, only: to_str, to_lower @@ -54,7 +55,7 @@ contains character(12) :: name ! name of isotope, e.g. 92235.03c character(12) :: alias ! alias of nuclide, e.g. U-235.03c type(Material), pointer :: mat - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc type(SAlphaBeta), pointer :: sab type(SetChar) :: already_read @@ -225,10 +226,10 @@ contains ! Show which nuclide results in lowest energy for neutron transport do i = 1, n_nuclides_total - if (nuclides(i)%energy(nuclides(i)%n_grid) == energy_max_neutron) then + if (nuclides(i) % energy(nuclides(i) % n_grid) == energy_max_neutron) then call write_message("Maximum neutron transport energy: " // & trim(to_str(energy_max_neutron)) // " MeV for " // & - trim(adjustl(nuclides(i)%name)), 6) + trim(adjustl(nuclides(i) % name)), 6) exit end if end do @@ -265,7 +266,7 @@ contains character(10) :: mat ! material identifier character(70) :: comment ! comment for ACE table character(MAX_FILE_LEN) :: filename ! path to ACE cross section library - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc type(SAlphaBeta), pointer :: sab type(XsListing), pointer :: listing @@ -368,7 +369,7 @@ contains nuc % name = name nuc % awr = awr nuc % kT = kT - nuc % zaid = NXS(2) + nuc % zaid = listing % zaid end if ! read all blocks @@ -378,8 +379,8 @@ contains if (data_0K) then continue else - call read_nu_data(nuc) call read_reactions(nuc) + call read_nu_data(nuc) call read_energy_dist(nuc) call read_angular_dist(nuc) call read_unr_res(nuc) @@ -422,7 +423,7 @@ contains !=============================================================================== subroutine read_esz(nuc, data_0K) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc logical, intent(in) :: data_0K ! are we reading 0K data? integer :: NE ! number of energy points for total and elastic cross sections @@ -510,200 +511,211 @@ contains !=============================================================================== subroutine read_nu_data(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc - integer :: i ! loop index - integer :: JXS2 ! location for fission nu data - integer :: JXS24 ! location for delayed neutron data + integer :: i, j ! loop index + integer :: idx ! index in XSS integer :: KNU ! location for nu data integer :: LNU ! type of nu data (polynomial or tabular) - integer :: NC ! number of polynomial coefficients integer :: NR ! number of interpolation regions integer :: NE ! number of energies integer :: NPCR ! number of delayed neutron precursor groups - integer :: LED ! location of energy distribution locators - integer :: LDIS ! location of all energy distributions integer :: LOCC ! location of energy distributions for given MT integer :: LAW integer :: IDAT - integer :: lc ! locator - integer :: length ! length of data to allocate + real(8) :: total_group_probability + type(Tabulated1D) :: yield_delayed + type(Tabulated1D) :: group_probability - JXS2 = JXS(2) - JXS24 = JXS(24) - - if (JXS2 == 0) then - ! ======================================================================= - ! NO PROMPT/TOTAL NU DATA - nuc % nu_t_type = NU_NONE - nuc % nu_p_type = NU_NONE - - elseif (XSS(JXS2) > 0) then - ! ======================================================================= - ! PROMPT OR TOTAL NU DATA - KNU = JXS2 - LNU = int(XSS(KNU)) - if (LNU == 1) then - ! Polynomial data - nuc % nu_t_type = NU_POLYNOMIAL - nuc % nu_p_type = NU_NONE - - ! allocate determine how many coefficients for polynomial - NC = int(XSS(KNU+1)) - length = NC + 1 - elseif (LNU == 2) then - ! Tabular data - nuc % nu_t_type = NU_TABULAR - nuc % nu_p_type = NU_NONE - - ! determine number of interpolation regions and number of energies - NR = int(XSS(KNU+1)) - NE = int(XSS(KNU+2+2*NR)) - length = 2 + 2*NR + 2*NE - end if - - ! allocate space for nu data storage - allocate(nuc % nu_t_data(length)) - - ! read data -- for polynomial, this is the number of coefficients and the - ! coefficients themselves, and for tabular, this is interpolation data - ! and tabular E/nu - XSS_index = KNU + 1 - nuc % nu_t_data = get_real(length) - - elseif (XSS(JXS2) < 0) then - ! ======================================================================= - ! PROMPT AND TOTAL NU DATA -- read prompt data first - KNU = JXS2 + 1 - LNU = int(XSS(KNU)) - if (LNU == 1) then - ! Polynomial data - nuc % nu_p_type = NU_POLYNOMIAL - - ! allocate determine how many coefficients for polynomial - NC = int(XSS(KNU+1)) - length = NC + 1 - elseif (LNU == 2) then - ! Tabular data - nuc % nu_p_type = NU_TABULAR - - ! determine number of interpolation regions and number of energies - NR = int(XSS(KNU+1)) - NE = int(XSS(KNU+2+2*NR)) - length = 2 + 2*NR + 2*NE - end if - - ! allocate space for nu data storage - allocate(nuc % nu_p_data(length)) - - ! read data - XSS_index = KNU + 1 - nuc % nu_p_data = get_real(length) - - ! Now read total nu data - KNU = JXS2 + int(abs(XSS(JXS2))) + 1 - LNU = int(XSS(KNU)) - if (LNU == 1) then - ! Polynomial data - nuc % nu_t_type = NU_POLYNOMIAL - - ! allocate determine how many coefficients for polynomial - NC = int(XSS(KNU+1)) - length = NC + 1 - elseif (LNU == 2) then - ! Tabular data - nuc % nu_t_type = NU_TABULAR - - ! determine number of interpolation regions and number of energies - NR = int(XSS(KNU+1)) - NE = int(XSS(KNU+2+2*NR)) - length = 2 + 2*NR + 2*NE - end if - - ! allocate space for nu data storage - allocate(nuc % nu_t_data(length)) - - ! read data - XSS_index = KNU + 1 - nuc % nu_t_data = get_real(length) + if (JXS(2) == 0) then + ! Nuclide is not fissionable + return end if - if (JXS24 > 0) then - ! ======================================================================= - ! DELAYED NU DATA - - nuc % nu_d_type = NU_TABULAR - KNU = JXS24 - - ! determine size of tabular delayed nu data - NR = int(XSS(KNU+1)) - NE = int(XSS(KNU+2+2*NR)) - length = 2 + 2*NR + 2*NE - - ! allocate space for delayed nu data - allocate(nuc % nu_d_data(length)) - - ! read delayed nu data - XSS_index = KNU + 1 - nuc % nu_d_data = get_real(length) - - ! ======================================================================= - ! DELAYED NEUTRON ENERGY DISTRIBUTION - - ! Allocate space for secondary energy distribution + ! Determine number of delayed neutron precursors + if (JXS(24) > 0) then NPCR = NXS(8) + else + NPCR = 0 + end if + nuc % n_precursor = NPCR - ! Check to make sure nuclide does not have more than the maximum number - ! of delayed groups - if (NPCR > MAX_DELAYED_GROUPS) then - call fatal_error("Encountered nuclide with " // trim(to_str(NPCR)) & - // " delayed groups while the maximum number of delayed groups & - &set in constants.F90 is " // trim(to_str(MAX_DELAYED_GROUPS))) + ! Check to make sure nuclide does not have more than the maximum number + ! of delayed groups + if (NPCR > MAX_DELAYED_GROUPS) then + call fatal_error("Encountered nuclide with " // trim(to_str(NPCR)) & + // " delayed groups while the maximum number of delayed groups is " & + // trim(to_str(MAX_DELAYED_GROUPS))) + end if + + associate (rx => nuc % reactions(nuc % index_fission(1))) + ! Allocate space for prompt/delayed neutron products + allocate(rx % products(1 + NPCR)) + rx % products(:) % particle = NEUTRON + + if (XSS(JXS(2)) > 0) then + ! ======================================================================= + ! PROMPT OR TOTAL NU DATA + + ! If delayed data is present, then prompt data must be present. Otherwise + ! the product represents 'total' neutron emission + if (JXS(24) > 0) then + rx % products(1) % emission_mode = EMISSION_PROMPT + else + rx % products(1) % emission_mode = EMISSION_TOTAL + end if + + KNU = JXS(2) + LNU = nint(XSS(KNU)) + if (LNU == 1) then + ! Polynomial data + allocate(Polynomial :: rx % products(1) % yield) + + ! determine order of polynomial and read coefficients + select type (yield => rx % products(1) % yield) + type is (Polynomial) + call yield % from_ace(XSS, KNU + 1) + end select + + elseif (LNU == 2) then + ! Tabulated data + allocate(Tabulated1D :: rx % products(1) % yield) + + select type(yield => rx % products(1) % yield) + type is (Tabulated1D) + call yield % from_ace(XSS, KNU + 1) + end select + + end if + + elseif (XSS(JXS(2)) < 0) then + ! ======================================================================= + ! PROMPT AND TOTAL NU DATA + + rx % products(1) % emission_mode = EMISSION_PROMPT + + KNU = JXS(2) + 1 + LNU = nint(XSS(KNU)) + if (LNU == 1) then + ! Polynomial data + allocate(Polynomial :: rx % products(1) % yield) + + ! determine order of polynomial and read coefficients + select type (yield => rx % products(1) % yield) + type is (Polynomial) + call yield % from_ace(XSS, KNU + 1) + end select + + elseif (LNU == 2) then + ! Tabulated data + allocate(Tabulated1D :: rx % products(1) % yield) + + select type(yield => rx % products(1) % yield) + type is (Tabulated1D) + call yield % from_ace(XSS, KNU + 1) + end select + end if + + KNU = JXS(2) + nint(abs(XSS(JXS(2)))) + 1 + LNU = nint(XSS(KNU)) + if (LNU == 1) then + ! Polynomial data + allocate(Polynomial :: nuc % total_nu) + + ! determine order of polynomial and read coefficients + select type (yield => nuc % total_nu) + type is (Polynomial) + call yield % from_ace(XSS, KNU + 1) + end select + + elseif (LNU == 2) then + ! Tabulated data + allocate(Tabulated1D :: nuc % total_nu) + + select type(yield => nuc % total_nu) + type is (Tabulated1D) + call yield % from_ace(XSS, KNU + 1) + end select + end if end if - nuc % n_precursor = NPCR - allocate(nuc % nu_d_edist(NPCR)) + if (JXS(24) > 0) then + ! ======================================================================= + ! DELAYED NU DATA - LED = JXS(26) - LDIS = JXS(27) + ! Read total yield of delayed neutrons + call yield_delayed % from_ace(XSS, JXS(24) + 1) - ! Loop over all delayed neutron precursor groups - do i = 1, NPCR - ! find location of energy distribution data - LOCC = nint(XSS(LED + i - 1)) + idx = JXS(25) + total_group_probability = ZERO + do i = 1, NPCR + ! Set emission mode and decay rate + rx % products(1 + i) % emission_mode = EMISSION_DELAYED + rx % products(1 + i) % decay_rate = XSS(idx) - ! Determine law and location of data - LAW = nint(XSS(LDIS + LOCC)) - IDAT = nint(XSS(LDIS + LOCC + 1)) + ! Read probability for this precursor group + call group_probability % from_ace(XSS, idx + 1) - ! read energy distribution data - call get_energy_dist(nuc%nu_d_edist(i)%obj, LAW, LDIS, IDAT, & - ZERO, ZERO) + ! Set yield based on product of group probability and delayed yield + if (all(group_probability % y == group_probability % y(1))) then + allocate(Tabulated1D :: rx % products(1 + i) % yield) + select type (yield => rx % products(1 + i) % yield) + type is (Tabulated1D) + yield = yield_delayed + yield % y(:) = yield % y(:) * group_probability % y(1) + total_group_probability = total_group_probability + group_probability % y(1) + end select + else + call fatal_error("Delayed neutron with energy-dependent group & + &probability not implemented") + end if + + ! Advance position + NR = nint(XSS(idx + 1)) + NE = nint(XSS(idx + 2 + 2*NR)) + idx = idx + 3 + 2*(NR + NE) + + ! ======================================================================= + ! DELAYED NEUTRON ENERGY DISTRIBUTION + + ! Read energy distribution + LOCC = nint(XSS(JXS(26) + i - 1)) + + ! Determine law and location of data + LAW = nint(XSS(JXS(27) + LOCC)) + IDAT = nint(XSS(JXS(27) + LOCC + 1)) + + ! read energy distribution data + associate(p => rx % products(1 + i)) + allocate(p % applicability(1)) + allocate(p % distribution(1)) + call get_energy_dist(p % distribution(1) % obj, LAW, JXS(27), IDAT, & + ZERO, ZERO) + + select type (aedist => p % distribution(1) % obj) + type is (UncorrelatedAngleEnergy) + aedist % fission = .true. + end select + end associate + end do + + ! Renormalize delayed neutron yields to reflect fact that in ACE file, the + ! sum of the group probabilities is not exactly one + do i = 1, NPCR + select type (yield => rx % products(1 + i) % yield) + type is (Tabulated1D) + yield % y(:) = yield % y(:) / total_group_probability + end select + end do + end if + + ! Assign products to other fission reactions + do i = 2, nuc % n_fission + j = nuc % index_fission(i) + allocate(nuc % reactions(j) % products(1 + NPCR)) + nuc % reactions(j) % products(:) = rx % products(:) end do - - ! ======================================================================= - ! DELAYED NEUTRON PRECUSOR YIELDS AND CONSTANTS - - ! determine length of all precursor constants/yields/interp data - length = 0 - lc = JXS(25) - do i = 1, NPCR - NR = int(XSS(lc + length + 1)) - NE = int(XSS(lc + length + 2 + 2*NR)) - length = length + 3 + 2*NR + 2*NE - end do - - ! allocate space for precusor data - allocate(nuc % nu_d_precursor_data(length)) - - ! read delayed neutron precursor data - XSS_index = lc - nuc % nu_d_precursor_data = get_real(length) - - else - nuc % nu_d_type = NU_NONE - nuc % n_precursor = 0 - end if + end associate end subroutine read_nu_data @@ -714,7 +726,7 @@ contains !=============================================================================== subroutine read_reactions(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc integer :: i ! loop indices integer :: i_fission ! index in nuc % index_fission @@ -727,7 +739,7 @@ contains integer :: LOCA ! location of cross-section for given MT integer :: IE ! reaction's starting index on energy grid integer :: NE ! number of energies - integer :: NR ! number of interpolation regions + real(8) :: y type(ListInt) :: MTs LMT = JXS(3) @@ -746,13 +758,19 @@ contains ! sigma array is not allocated or stored for elastic scattering since it is ! already stored in nuc % elastic associate (rxn => nuc % reactions(1)) - rxn%MT = 2 - rxn%Q_value = ZERO - rxn%multiplicity = 1 - rxn%threshold = 1 - rxn%scatter_in_cm = .true. - allocate(rxn%secondary%distribution(1)) - allocate(UncorrelatedAngleEnergy :: rxn%secondary%distribution(1)%obj) + rxn % MT = 2 + rxn % Q_value = ZERO + allocate(rxn % products(1)) + rxn % products(1) % particle = NEUTRON + allocate(Constant1D :: rxn % products(1) % yield) + select type(yield => rxn % products(1) % yield) + type is (Constant1D) + yield % y = 1 + end select + rxn % threshold = 1 + rxn % scatter_in_cm = .true. + allocate(rxn % products(1) % distribution(1)) + allocate(UncorrelatedAngleEnergy :: rxn % products(1) % distribution(1) % obj) end associate ! Add contribution of elastic scattering to total cross section @@ -768,45 +786,35 @@ contains do i = 1, NMT associate (rxn => nuc % reactions(i+1)) ! read MT number, Q-value, and neutrons produced - rxn % MT = int(XSS(LMT + i - 1)) - rxn % Q_value = XSS(JXS4 + i - 1) - rxn % multiplicity = abs(nint(XSS(JXS5 + i - 1))) + rxn % MT = int(XSS(LMT + i - 1)) + rxn % Q_value = XSS(JXS4 + i - 1) rxn % scatter_in_cm = (nint(XSS(JXS5 + i - 1)) < 0) - ! Read energy-dependent multiplicities - if (rxn % multiplicity > 100) then - ! Set flag and allocate space for Tab1 to store yield - rxn % multiplicity_with_E = .true. - allocate(rxn % multiplicity_E) + if (.not. is_fission(rxn % MT)) then + allocate(rxn % products(1)) + rxn % products(1) % particle = NEUTRON - XSS_index = JXS(11) + rxn % multiplicity - 101 - NR = nint(XSS(XSS_index)) - rxn % multiplicity_E % n_regions = NR + y = abs(nint(XSS(JXS5 + i - 1))) + if (y > 100) then + ! Read energy-dependent multiplicities - ! allocate space for ENDF interpolation parameters - if (NR > 0) then - allocate(rxn % multiplicity_E % nbt(NR)) - allocate(rxn % multiplicity_E % int(NR)) + ! Set flag and allocate space for Tabulated1D to store yield + allocate(Tabulated1D :: rxn % products(1) % yield) + + ! Read yield function + select type (yield => rxn % products(1) % yield) + type is (Tabulated1D) + XSS_index = JXS(11) + int(y) - 101 + call yield % from_ace(XSS, XSS_index) + end select + else + ! Integral yield + allocate(Constant1D :: rxn % products(1) % yield) + select type (yield => rxn % products(1) % yield) + type is (Constant1D) + yield % y = y + end select end if - - ! read ENDF interpolation parameters - XSS_index = XSS_index + 1 - if (NR > 0) then - rxn % multiplicity_E % nbt = get_int(NR) - rxn % multiplicity_E % int = get_int(NR) - end if - - ! allocate space for yield data - XSS_index = XSS_index + 2*NR - NE = nint(XSS(XSS_index)) - rxn % multiplicity_E % n_pairs = NE - allocate(rxn % multiplicity_E % x(NE)) - allocate(rxn % multiplicity_E % y(NE)) - - ! read yield data - XSS_index = XSS_index + 1 - rxn % multiplicity_E % x = get_real(NE) - rxn % multiplicity_E % y = get_real(NE) end if ! read starting energy index @@ -894,7 +902,7 @@ contains !=============================================================================== subroutine read_angular_dist(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc integer :: LOCB ! location of angular distribution for given MT integer :: NE ! number of incoming energies @@ -923,42 +931,42 @@ contains ! "one" angular distribution, it is repeated as many times as there are ! energy distributions for this reaction since the ! UncorrelatedAngleEnergy type holds one angle and energy distribution. - do k = 1, size(rxn%secondary%distribution) - select type (aedist => rxn%secondary%distribution(k)%obj) + do k = 1, size(rxn % products(1) % distribution) + select type (aedist => rxn % products(1) % distribution(k) % obj) type is (UncorrelatedAngleEnergy) ! allocate space for incoming energies and locations NE = int(XSS(JXS(9) + LOCB - 1)) - allocate(aedist%angle%energy(NE)) - allocate(aedist%angle%distribution(NE)) + allocate(aedist % angle % energy(NE)) + allocate(aedist % angle % distribution(NE)) allocate(LC(NE)) ! read incoming energy grid and location of nucs XSS_index = JXS(9) + LOCB - aedist%angle%energy(:) = get_real(NE) + aedist % angle % energy(:) = get_real(NE) LC(:) = get_int(NE) ! determine dize of data block do j = 1, NE if (LC(j) == 0) then ! isotropic - allocate(Uniform :: aedist%angle%distribution(j)%obj) - select type (adist => aedist%angle%distribution(j)%obj) + allocate(Uniform :: aedist % angle % distribution(j) % obj) + select type (adist => aedist % angle % distribution(j) % obj) type is (Uniform) - adist%a = -ONE - adist%b = ONE + adist % a = -ONE + adist % b = ONE end select elseif (LC(j) > 0) then ! 32 equiprobable bins - allocate(Equiprobable :: aedist%angle%distribution(j)%obj) - select type (adist => aedist%angle%distribution(j)%obj) + allocate(Equiprobable :: aedist % angle % distribution(j) % obj) + select type (adist => aedist % angle % distribution(j) % obj) type is (Equiprobable) - allocate(adist%x(33)) + allocate(adist % x(33)) end select elseif (LC(j) < 0) then ! tabular distribution - allocate(Tabular :: aedist%angle%distribution(j)%obj) + allocate(Tabular :: aedist % angle % distribution(j) % obj) end if end do @@ -967,9 +975,9 @@ contains ! on-the-fly do j = 1, NE XSS_index = JXS(9) + abs(LC(j)) - 1 - select type(adist => aedist%angle%distribution(j)%obj) + select type(adist => aedist % angle % distribution(j) % obj) type is (Equiprobable) - adist%x(:) = get_real(33) + adist % x(:) = get_real(33) type is (Tabular) ! determine interpolation and number of points interp = nint(XSS(XSS_index)) @@ -977,10 +985,10 @@ contains ! Get probability density data XSS_index = XSS_index + 2 - allocate(adist%x(NP), adist%p(NP), adist%c(NP)) - adist%x(:) = get_real(NP) - adist%p(:) = get_real(NP) - adist%c(:) = get_real(NP) + allocate(adist % x(NP), adist % p(NP), adist % c(NP)) + adist % x(:) = get_real(NP) + adist % p(:) = get_real(NP) + adist % c(:) = get_real(NP) end select end do deallocate(LC) @@ -998,7 +1006,7 @@ contains !=============================================================================== subroutine read_energy_dist(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc integer :: i ! loop index integer :: n @@ -1017,9 +1025,9 @@ contains end do ! Allocate space for distributions and probability of validity - associate (secondary => nuc%reactions(i + 1)%secondary) - allocate(secondary%applicability(n)) - allocate(secondary%distribution(n)) + associate (p => nuc % reactions(i + 1) % products(1)) + allocate(p % applicability(n)) + allocate(p % distribution(n)) LNW = nint(XSS(JXS(10) + i - 1)) n = 0 @@ -1031,11 +1039,11 @@ contains IDAT = nint(XSS(JXS(11) + LNW + 1)) ! Read probability of law validity - call secondary%applicability(n)%from_ace(XSS, JXS(11) + LNW + 2) + call p % applicability(n) % from_ace(XSS, JXS(11) + LNW + 2) ! Read energy law data - call get_energy_dist(secondary%distribution(n)%obj, LAW, & - JXS(11), IDAT, nuc%awr, nuc%reactions(i + 1)%Q_value) + call get_energy_dist(p % distribution(n) % obj, LAW, & + JXS(11), IDAT, nuc % awr, nuc % reactions(i + 1) % Q_value) ! <<<<<<<<<<<<<<<<<<<<<<<<<<<< REMOVE THIS <<<<<<<<<<<<<<<<<<<<<<<<<<< ! Before the secondary distribution refactor, when the angle/energy @@ -1044,11 +1052,11 @@ contains ! distribution even when no angle distribution exists in the ACE file ! (isotropic is assumed). To preserve the RNG stream, we explicitly ! mark fission reactions so that we avoid the angle sampling. - if (any(nuc%reactions(i + 1)%MT == & + if (any(nuc % reactions(i + 1) % MT == & [N_FISSION, N_F, N_NF, N_2NF, N_3NF])) then - select type (aedist => secondary%distribution(n)%obj) + select type (aedist => p % distribution(n) % obj) type is (UncorrelatedAngleEnergy) - aedist%fission = .true. + aedist % fission = .true. end select end if ! <<<<<<<<<<<<<<<<<<<<<<<<<<<< REMOVE THIS <<<<<<<<<<<<<<<<<<<<<<<<<<< @@ -1089,6 +1097,8 @@ contains allocate(KalbachMann :: aedist) elseif (law == 61) then allocate(CorrelatedAngleEnergy :: aedist) + elseif (law == 66) then + allocate(NBodyPhaseSpace :: aedist) else allocate(UncorrelatedAngleEnergy :: aedist) end if @@ -1100,8 +1110,8 @@ contains select case (law) case (1) - allocate(TabularEquiprobable :: aedist%energy) - select type (edist => aedist%energy) + allocate(TabularEquiprobable :: aedist % energy) + select type (edist => aedist % energy) type is (TabularEquiprobable) NR = nint(XSS(XSS_index)) NE = nint(XSS(XSS_index + 1 + 2*NR)) @@ -1109,33 +1119,33 @@ contains call fatal_error("Multiple interpolation regions not yet supported & &for tabular equiprobable energy distributions.") end if - edist%n_region = NR + edist % n_region = NR ! Read incoming energies for which outgoing energies are tabulated - allocate(edist%energy_in(NE)) + allocate(edist % energy_in(NE)) XSS_index = XSS_index + 2 + 2*NR - edist%energy_in(:) = get_real(NE) + edist % energy_in(:) = get_real(NE) ! Read outgoing energy tables NP = nint(XSS(XSS_index)) - allocate(edist%energy_out(NP, NE)) + allocate(edist % energy_out(NP, NE)) XSS_index = XSS_index + 1 do i = 1, NE - edist%energy_out(:, i) = get_real(NP) + edist % energy_out(:, i) = get_real(NP) end do end select case (3) - allocate(LevelInelastic :: aedist%energy) - select type (edist => aedist%energy) + allocate(LevelInelastic :: aedist % energy) + select type (edist => aedist % energy) type is (LevelInelastic) - edist%threshold = XSS(XSS_index) - edist%mass_ratio = XSS(XSS_index + 1) + edist % threshold = XSS(XSS_index) + edist % mass_ratio = XSS(XSS_index + 1) end select case (4) - allocate(ContinuousTabular :: aedist%energy) - select type (edist => aedist%energy) + allocate(ContinuousTabular :: aedist % energy) + select type (edist => aedist % energy) type is (ContinuousTabular) NR = nint(XSS(XSS_index)) XSS_index = XSS_index + 1 @@ -1143,94 +1153,84 @@ contains call fatal_error("Multiple interpolation regions not yet supported & &for continuous tabular energy distributions.") end if - edist%n_region = NR + edist % n_region = NR ! Read breakpoints and interpolation parameters if (NR > 0) then - allocate(edist%breakpoints(NR)) - allocate(edist%interpolation(NR)) - edist%breakpoints(:) = get_int(NR) - edist%interpolation(:) = get_int(NR) + allocate(edist % breakpoints(NR)) + allocate(edist % interpolation(NR)) + edist % breakpoints(:) = get_int(NR) + edist % interpolation(:) = get_int(NR) end if ! Read incoming energies for which outgoing energies are tabulated and ! locators NE = nint(XSS(XSS_index)) XSS_index = XSS_index + 1 - allocate(edist%energy_in(NE)) + allocate(edist % energy(NE)) allocate(L(NE)) - edist%energy_in(:) = get_real(NE) + edist % energy(:) = get_real(NE) L(:) = get_int(NE) ! Read outgoing energy tables - allocate(edist%energy_out(NE)) + allocate(edist % distribution(NE)) do i = 1, NE ! Determine interpolation and number of discrete points XSS_index = LDIS + L(i) - 1 interp = nint(XSS(XSS_index)) - edist%energy_out(i)%interpolation = mod(interp, 10) - edist%energy_out(i)%n_discrete = (interp - & - edist%energy_out(i)%interpolation)/10 + edist % distribution(i) % interpolation = mod(interp, 10) + edist % distribution(i) % n_discrete = (interp - & + edist % distribution(i) % interpolation)/10 ! check for discrete lines present - if (edist%energy_out(i)%n_discrete > 0) then + if (edist % distribution(i) % n_discrete > 0) then call fatal_error("Discrete lines in continuous tabular & &distribution not yet supported") end if ! Determine number of points and allocate space NP = nint(XSS(XSS_index + 1)) - allocate(edist%energy_out(i)%e_out(NP)) - allocate(edist%energy_out(i)%p(NP)) - allocate(edist%energy_out(i)%c(NP)) + allocate(edist % distribution(i) % e_out(NP)) + allocate(edist % distribution(i) % p(NP)) + allocate(edist % distribution(i) % c(NP)) ! Read tabular PDF for outgoing energy XSS_index = XSS_index + 2 - edist%energy_out(i)%e_out(:) = get_real(NP) - edist%energy_out(i)%p(:) = get_real(NP) - edist%energy_out(i)%c(:) = get_real(NP) + edist % distribution(i) % e_out(:) = get_real(NP) + edist % distribution(i) % p(:) = get_real(NP) + edist % distribution(i) % c(:) = get_real(NP) end do deallocate(L) end select case (7) - allocate(MaxwellEnergy :: aedist%energy) - select type (edist => aedist%energy) + allocate(MaxwellEnergy :: aedist % energy) + select type (edist => aedist % energy) type is (MaxwellEnergy) - call edist%theta%from_ace(XSS, XSS_index) - edist%u = XSS(XSS_index + 2 + 2*edist%theta%n_regions + & - 2*edist%theta%n_pairs) + call edist % theta % from_ace(XSS, XSS_index) + edist % u = XSS(XSS_index + 2 + 2*edist % theta % n_regions + & + 2*edist % theta % n_pairs) end select case (9) - allocate(Evaporation :: aedist%energy) - select type(edist => aedist%energy) + allocate(Evaporation :: aedist % energy) + select type(edist => aedist % energy) type is (Evaporation) - call edist%theta%from_ace(XSS, XSS_index) - edist%u = XSS(XSS_index + 2 + 2*edist%theta%n_regions + & - 2*edist%theta%n_pairs) + call edist % theta % from_ace(XSS, XSS_index) + edist % u = XSS(XSS_index + 2 + 2*edist % theta % n_regions + & + 2*edist % theta % n_pairs) end select case (11) - allocate(WattEnergy :: aedist%energy) - select type(edist => aedist%energy) + allocate(WattEnergy :: aedist % energy) + select type(edist => aedist % energy) type is (WattEnergy) - call edist%a%from_ace(XSS, XSS_index) - XSS_index = XSS_index + 2 + 2*edist%a%n_regions + 2*edist%a%n_pairs - call edist%b%from_ace(XSS, XSS_index) - XSS_index = XSS_index + 2 + 2*edist%b%n_regions + 2*edist%b%n_pairs - edist%u = XSS(XSS_index) - end select - - case (66) - allocate(NBodyPhaseSpace :: aedist%energy) - select type(edist => aedist%energy) - type is (NBodyPhaseSpace) - edist%n_bodies = int(XSS(XSS_index)) - edist%mass_ratio = XSS(XSS_index + 1) - edist%A = awr - edist%Q = Q_value + call edist % a % from_ace(XSS, XSS_index) + XSS_index = XSS_index + 2 + 2*edist % a % n_regions + 2*edist % a % n_pairs + call edist % b % from_ace(XSS, XSS_index) + XSS_index = XSS_index + 2 + 2*edist % b % n_regions + 2*edist % b % n_pairs + edist % u = XSS(XSS_index) end select end select @@ -1245,45 +1245,45 @@ contains call fatal_error("Multiple interpolation regions not yet supported & &for Kalbach-Mann energy distributions.") end if - aedist%n_region = NR + aedist % n_region = NR ! Read incoming energies for which outgoing energies are tabulated and locators - allocate(aedist%energy_in(NE)) + allocate(aedist % energy(NE)) allocate(L(NE)) XSS_index = XSS_index + 2 + 2*NR - aedist%energy_in(:) = get_real(NE) + aedist % energy(:) = get_real(NE) L(:) = get_int(NE) ! Read outgoing energy tables - allocate(aedist%table(NE)) + allocate(aedist % distribution(NE)) do i = 1, NE ! Determine interpolation and number of discrete points XSS_index = LDIS + L(i) - 1 interp = nint(XSS(XSS_index)) - aedist%table(i)%interpolation = mod(interp, 10) - aedist%table(i)%n_discrete = (interp - aedist%table(i)%interpolation)/10 + aedist % distribution(i) % interpolation = mod(interp, 10) + aedist % distribution(i) % n_discrete = (interp - aedist % distribution(i) % interpolation)/10 ! check for discrete lines present - if (aedist%table(i)%n_discrete > 0) then + if (aedist % distribution(i) % n_discrete > 0) then call fatal_error("Discrete lines in Kalbach-Mann distribution not & &yet supported") end if ! Determine number of points and allocate space NP = nint(XSS(XSS_index + 1)) - allocate(aedist%table(i)%e_out(NP)) - allocate(aedist%table(i)%p(NP)) - allocate(aedist%table(i)%c(NP)) - allocate(aedist%table(i)%r(NP)) - allocate(aedist%table(i)%a(NP)) + allocate(aedist % distribution(i) % e_out(NP)) + allocate(aedist % distribution(i) % p(NP)) + allocate(aedist % distribution(i) % c(NP)) + allocate(aedist % distribution(i) % r(NP)) + allocate(aedist % distribution(i) % a(NP)) ! Read tabular PDF for outgoing energy XSS_index = XSS_index + 2 - aedist%table(i)%e_out(:) = get_real(NP) - aedist%table(i)%p(:) = get_real(NP) - aedist%table(i)%c(:) = get_real(NP) - aedist%table(i)%r(:) = get_real(NP) - aedist%table(i)%a(:) = get_real(NP) + aedist % distribution(i) % e_out(:) = get_real(NP) + aedist % distribution(i) % p(:) = get_real(NP) + aedist % distribution(i) % c(:) = get_real(NP) + aedist % distribution(i) % r(:) = get_real(NP) + aedist % distribution(i) % a(:) = get_real(NP) end do deallocate(L) @@ -1298,67 +1298,67 @@ contains call fatal_error("Multiple interpolation regions not yet supported & &for correlated angle-energy distributions.") end if - aedist%n_region = NR + aedist % n_region = NR ! Read incoming energies for which outgoing energies are tabulated and ! locators - allocate(aedist%energy_in(NE)) + allocate(aedist % energy(NE)) allocate(L(NE)) XSS_index = XSS_index + 2 + 2*NR - aedist%energy_in(:) = get_real(NE) + aedist % energy(:) = get_real(NE) L(:) = get_int(NE) ! Read outgoing energy tables - allocate(aedist%table(NE)) + allocate(aedist % distribution(NE)) do i = 1, NE ! Determine interpolation and number of discrete points XSS_index = LDIS + L(i) - 1 interp = nint(XSS(XSS_index)) - aedist%table(i)%interpolation = mod(interp, 10) - aedist%table(i)%n_discrete = (interp - aedist%table(i)%interpolation)/10 + aedist % distribution(i) % interpolation = mod(interp, 10) + aedist % distribution(i) % n_discrete = (interp - aedist % distribution(i) % interpolation)/10 ! check for discrete lines present - if (aedist%table(i)%n_discrete > 0) then + if (aedist % distribution(i) % n_discrete > 0) then call fatal_error("Discrete lines in correlated angle-energy & &distribution not yet supported") end if ! Determine number of points and allocate space NP = nint(XSS(XSS_index + 1)) - allocate(aedist%table(i)%e_out(NP)) - allocate(aedist%table(i)%p(NP)) - allocate(aedist%table(i)%c(NP)) + allocate(aedist % distribution(i) % e_out(NP)) + allocate(aedist % distribution(i) % p(NP)) + allocate(aedist % distribution(i) % c(NP)) allocate(LC(NP)) ! Read tabular PDF for outgoing energy XSS_index = XSS_index + 2 - aedist%table(i)%e_out(:) = get_real(NP) - aedist%table(i)%p(:) = get_real(NP) - aedist%table(i)%c(:) = get_real(NP) + aedist % distribution(i) % e_out(:) = get_real(NP) + aedist % distribution(i) % p(:) = get_real(NP) + aedist % distribution(i) % c(:) = get_real(NP) LC(:) = get_int(NP) ! allocate angular distributions for each incoming/outgoing energy - allocate(aedist%table(i)%angle(NP)) + allocate(aedist % distribution(i) % angle(NP)) do j = 1, NP if (LC(j) == 0) then ! isotropic - allocate(Uniform :: aedist%table(i)%angle(j)%obj) - select type (adist => aedist%table(i)%angle(j)%obj) + allocate(Uniform :: aedist % distribution(i) % angle(j) % obj) + select type (adist => aedist % distribution(i) % angle(j) % obj) type is (Uniform) - adist%a = -ONE - adist%b = ONE + adist % a = -ONE + adist % b = ONE end select elseif (LC(j) > 0) then ! tabular distribution - allocate(Tabular :: aedist%table(i)%angle(j)%obj) + allocate(Tabular :: aedist % distribution(i) % angle(j) % obj) end if end do ! read angular distributions do j = 1, NP XSS_index = LDIS + abs(LC(j)) - 1 - select type(adist => aedist%table(i)%angle(j)%obj) + select type(adist => aedist % distribution(i) % angle(j) % obj) type is (Tabular) ! determine interpolation and number of points interp = nint(XSS(XSS_index)) @@ -1366,10 +1366,10 @@ contains ! Get probability density data XSS_index = XSS_index + 2 - allocate(adist%x(NP), adist%p(NP), adist%c(NP)) - adist%x(:) = get_real(NP) - adist%p(:) = get_real(NP) - adist%c(:) = get_real(NP) + allocate(adist % x(NP), adist % p(NP), adist % c(NP)) + adist % x(:) = get_real(NP) + adist % p(:) = get_real(NP) + adist % c(:) = get_real(NP) end select end do deallocate(LC) @@ -1377,6 +1377,15 @@ contains end do deallocate(L) + + type is (NBodyPhaseSpace) + ! ======================================================================== + ! N-BODY PHASE SPACE DISTRIBUTION + + aedist % n_bodies = int(XSS(XSS_index)) + aedist % mass_ratio = XSS(XSS_index + 1) + aedist % A = awr + aedist % Q = Q_value end select end subroutine get_energy_dist @@ -1386,7 +1395,7 @@ contains !=============================================================================== subroutine read_unr_res(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc integer :: JXS23 ! location of URR data integer :: lc ! locator @@ -1466,7 +1475,6 @@ contains end if end subroutine read_unr_res - !=============================================================================== ! GENERATE_NU_FISSION precalculates the microscopic nu-fission cross section for ! a given nuclide. This is done so that the nu_total function does not need to @@ -1474,23 +1482,14 @@ contains !=============================================================================== subroutine generate_nu_fission(nuc) - type(NuclideCE), intent(inout) :: nuc + type(Nuclide), intent(inout) :: nuc integer :: i ! index on nuclide energy grid - real(8) :: E ! energy - real(8) :: nu ! # of neutrons per fission - do i = 1, nuc % n_grid - ! determine energy - E = nuc % energy(i) - - ! determine total nu at given energy - nu = nu_total(nuc, E) - - ! determine nu-fission microscopic cross section - nuc % nu_fission(i) = nu * nuc % fission(i) + do i = 1, size(nuc % energy) + nuc % nu_fission(i) = nuc % nu(nuc % energy(i), EMISSION_TOTAL) * & + nuc % fission(i) end do - end subroutine generate_nu_fission !=============================================================================== @@ -1667,26 +1666,4 @@ contains end function get_real -!=============================================================================== -! SAME_NUCLIDE_LIST creates a linked list for each nuclide containing the -! indices in the nuclides array of all other instances of that nuclide. For -! example, the same nuclide may exist at multiple temperatures resulting -! in multiple entries in the nuclides array for a single zaid number. -!=============================================================================== - - subroutine same_nuclide_list() - - integer :: i ! index in nuclides array - integer :: j ! index in nuclides array - - do i = 1, n_nuclides_total - do j = 1, n_nuclides_total - if (nuclides(i) % zaid == nuclides(j) % zaid) then - call nuclides(i) % nuc_list % push_back(j) - end if - end do - end do - - end subroutine same_nuclide_list - end module ace diff --git a/src/ace_header.F90 b/src/ace_header.F90 deleted file mode 100644 index ae5000e5a..000000000 --- a/src/ace_header.F90 +++ /dev/null @@ -1,58 +0,0 @@ -module ace_header - - use constants, only: MAX_FILE_LEN, ZERO - use dict_header, only: DictIntInt - use endf_header, only: Tab1 - use secondary_header, only: SecondaryDistribution, AngleEnergyContainer - use stl_vector, only: VectorInt - - implicit none - -!=============================================================================== -! REACTION contains the cross-section and secondary energy and angle -! distributions for a single reaction in a continuous-energy ACE-format table -!=============================================================================== - - type Reaction - integer :: MT ! ENDF MT value - real(8) :: Q_value ! Reaction Q value - integer :: multiplicity ! Number of secondary particles released - type(Tab1), pointer :: multiplicity_E => null() ! Energy-dependent neutron yield - integer :: threshold ! Energy grid index of threshold - logical :: scatter_in_cm ! scattering system in center-of-mass? - logical :: multiplicity_with_E = .false. ! Flag to indicate E-dependent multiplicity - real(8), allocatable :: sigma(:) ! Cross section values - type(SecondaryDistribution) :: secondary - - contains - procedure :: clear => reaction_clear ! Deallocates Reaction - end type Reaction - -!=============================================================================== -! URRDATA contains probability tables for the unresolved resonance range. -!=============================================================================== - - type UrrData - integer :: n_energy ! # of incident neutron energies - integer :: n_prob ! # of probabilities - integer :: interp ! inteprolation (2=lin-lin, 5=log-log) - integer :: inelastic_flag ! inelastic competition flag - integer :: absorption_flag ! other absorption flag - logical :: multiply_smooth ! multiply by smooth cross section? - real(8), allocatable :: energy(:) ! incident energies - real(8), allocatable :: prob(:,:,:) ! actual probabibility tables - end type UrrData - - contains - -!=============================================================================== -! REACTION_CLEAR resets and deallocates data in Reaction. -!=============================================================================== - - subroutine reaction_clear(this) - class(Reaction), intent(inout) :: this ! The Reaction object to clear - - if (associated(this % multiplicity_E)) deallocate(this % multiplicity_E) - end subroutine reaction_clear - -end module ace_header diff --git a/src/angleenergy_header.F90 b/src/angleenergy_header.F90 new file mode 100644 index 000000000..483bad856 --- /dev/null +++ b/src/angleenergy_header.F90 @@ -0,0 +1,29 @@ +module angleenergy_header + +!=============================================================================== +! ANGLEENERGY (abstract) defines a correlated or uncorrelated angle-energy +! distribution that is a function of incoming energy. Each derived type must +! implement a sample() subroutine that returns an outgoing energy and scattering +! cosine given an incoming energy. +!=============================================================================== + + type, abstract :: AngleEnergy + contains + procedure(angleenergy_sample_), deferred :: sample + end type AngleEnergy + + abstract interface + subroutine angleenergy_sample_(this, E_in, E_out, mu) + import AngleEnergy + class(AngleEnergy), intent(in) :: this + real(8), intent(in) :: E_in + real(8), intent(out) :: E_out + real(8), intent(out) :: mu + end subroutine angleenergy_sample_ + end interface + + type :: AngleEnergyContainer + class(AngleEnergy), allocatable :: obj + end type AngleEnergyContainer + +end module angleenergy_header diff --git a/src/cmfd_input.F90 b/src/cmfd_input.F90 index 2d9df4182..f69c09fe1 100644 --- a/src/cmfd_input.F90 +++ b/src/cmfd_input.F90 @@ -70,7 +70,7 @@ contains inquire(FILE=filename, EXIST=file_exists) if (.not. file_exists) then ! CMFD is optional unless it is in on from settings - if (cmfd_on) then + if (cmfd_run) then call fatal_error("No CMFD XML file, '" // trim(filename) // "' does not& & exist!") end if diff --git a/src/constants.F90 b/src/constants.F90 index 0c6f09cdd..4354cc423 100644 --- a/src/constants.F90 +++ b/src/constants.F90 @@ -37,7 +37,7 @@ module constants real(8), parameter :: FP_COINCIDENT = 1e-12_8 ! Maximum number of collisions/crossings - integer, parameter :: MAX_EVENTS = 10000 + integer, parameter :: MAX_EVENTS = 1000000 integer, parameter :: MAX_SAMPLE = 100000 ! Maximum number of secondary particles created @@ -223,6 +223,12 @@ module constants NU_POLYNOMIAL = 1, & ! Nu values given by polynomial NU_TABULAR = 2 ! Nu values given by tabular distribution + ! Secondary particle emission type + integer, parameter :: & + EMISSION_PROMPT = 1, & ! Prompt emission of secondary particle + EMISSION_DELAYED = 2, & ! Delayed emission of secondary particle + EMISSION_TOTAL = 3 ! Yield represents total emission (prompt + delayed) + ! Cross section filetypes integer, parameter :: & ASCII = 1, & ! ASCII cross section file @@ -273,7 +279,7 @@ module constants EVENT_ABSORB = 2 ! Tally score type - integer, parameter :: N_SCORE_TYPES = 22 + integer, parameter :: N_SCORE_TYPES = 20 integer, parameter :: & SCORE_FLUX = -1, & ! flux SCORE_TOTAL = -2, & ! total reaction rate @@ -283,20 +289,18 @@ module constants SCORE_SCATTER_PN = -6, & ! system for scoring 0th through nth moment SCORE_NU_SCATTER_N = -7, & ! arbitrary nu-scattering moment SCORE_NU_SCATTER_PN = -8, & ! system for scoring 0th through nth nu-scatter moment - SCORE_TRANSPORT = -9, & ! transport reaction rate - SCORE_N_1N = -10, & ! (n,1n) rate - SCORE_ABSORPTION = -11, & ! absorption rate - SCORE_FISSION = -12, & ! fission rate - SCORE_NU_FISSION = -13, & ! neutron production rate - SCORE_KAPPA_FISSION = -14, & ! fission energy production rate - SCORE_CURRENT = -15, & ! partial current - SCORE_FLUX_YN = -16, & ! angular moment of flux - SCORE_TOTAL_YN = -17, & ! angular moment of total reaction rate - SCORE_SCATTER_YN = -18, & ! angular flux-weighted scattering moment (0:N) - SCORE_NU_SCATTER_YN = -19, & ! angular flux-weighted nu-scattering moment (0:N) - SCORE_EVENTS = -20, & ! number of events - SCORE_DELAYED_NU_FISSION = -21, & ! delayed neutron production rate - SCORE_INVERSE_VELOCITY = -22 ! flux-weighted inverse velocity + SCORE_ABSORPTION = -9, & ! absorption rate + SCORE_FISSION = -10, & ! fission rate + SCORE_NU_FISSION = -11, & ! neutron production rate + SCORE_KAPPA_FISSION = -12, & ! fission energy production rate + SCORE_CURRENT = -13, & ! partial current + SCORE_FLUX_YN = -14, & ! angular moment of flux + SCORE_TOTAL_YN = -15, & ! angular moment of total reaction rate + SCORE_SCATTER_YN = -16, & ! angular flux-weighted scattering moment (0:N) + SCORE_NU_SCATTER_YN = -17, & ! angular flux-weighted nu-scattering moment (0:N) + SCORE_EVENTS = -18, & ! number of events + SCORE_DELAYED_NU_FISSION = -19, & ! delayed neutron production rate + SCORE_INVERSE_VELOCITY = -20 ! flux-weighted inverse velocity ! Maximum scattering order supported integer, parameter :: MAX_ANG_ORDER = 10 @@ -365,10 +369,11 @@ module constants ! ============================================================================ ! RANDOM NUMBER STREAM CONSTANTS - integer, parameter :: N_STREAMS = 3 - integer, parameter :: STREAM_TRACKING = 1 - integer, parameter :: STREAM_TALLIES = 2 - integer, parameter :: STREAM_SOURCE = 3 + integer, parameter :: N_STREAMS = 4 + integer, parameter :: STREAM_TRACKING = 1 + integer, parameter :: STREAM_TALLIES = 2 + integer, parameter :: STREAM_SOURCE = 3 + integer, parameter :: STREAM_URR_PTABLE = 4 ! ============================================================================ ! MISCELLANEOUS CONSTANTS diff --git a/src/cross_section.F90 b/src/cross_section.F90 index 4f5d2252c..fd8318c3b 100644 --- a/src/cross_section.F90 +++ b/src/cross_section.F90 @@ -1,16 +1,14 @@ module cross_section - use ace_header, only: Reaction, UrrData use constants use energy_grid, only: grid_method, log_spacing use error, only: fatal_error - use fission, only: nu_total use global use list_header, only: ListElemInt use material_header, only: Material use nuclide_header use particle_header, only: Particle - use random_lcg, only: prn + use random_lcg, only: prn, future_prn, prn_set_stream use sab_header, only: SAlphaBeta use search, only: binary_search @@ -148,7 +146,7 @@ contains integer :: i_low ! lower logarithmic mapping index integer :: i_high ! upper logarithmic mapping index real(8) :: f ! interp factor on nuclide energy grid - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc type(Material), pointer :: mat ! Set pointer to nuclide and material @@ -354,154 +352,136 @@ contains integer, intent(in) :: i_nuclide ! index into nuclides array real(8), intent(in) :: E ! energy - integer :: i ! loop index integer :: i_energy ! index for energy integer :: i_low ! band index at lower bounding energy integer :: i_up ! band index at upper bounding energy - integer :: same_nuc_idx ! index of same nuclide real(8) :: f ! interpolation factor real(8) :: r ! pseudo-random number real(8) :: elastic ! elastic cross section real(8) :: capture ! (n,gamma) cross section real(8) :: fission ! fission cross section real(8) :: inelastic ! inelastic cross section - logical :: same_nuc ! do we know the xs for this nuclide at this energy? - type(UrrData), pointer :: urr - type(NuclideCE), pointer :: nuc micro_xs(i_nuclide) % use_ptable = .true. - ! get pointer to probability table - nuc => nuclides(i_nuclide) - urr => nuc % urr_data + associate (nuc => nuclides(i_nuclide), urr => nuclides(i_nuclide) % urr_data) + ! determine energy table + i_energy = 1 + do + if (E < urr % energy(i_energy + 1)) exit + i_energy = i_energy + 1 + end do - ! determine energy table - i_energy = 1 - do - if (E < urr % energy(i_energy + 1)) exit - i_energy = i_energy + 1 - end do + ! determine interpolation factor on table + f = (E - urr % energy(i_energy)) / & + (urr % energy(i_energy + 1) - urr % energy(i_energy)) - ! determine interpolation factor on table - f = (E - urr % energy(i_energy)) / & - (urr % energy(i_energy + 1) - urr % energy(i_energy)) + ! sample probability table using the cumulative distribution - ! sample probability table using the cumulative distribution + ! Random numbers for xs calculation are sampled from a separated stream. + ! This guarantees the randomness and, at the same time, makes sure we reuse + ! random number for the same nuclide at different temperatures, therefore + ! preserving correlation of temperature in probability tables. + call prn_set_stream(STREAM_URR_PTABLE) + r = future_prn(int(nuc_zaid_dict % get_key(nuc % zaid), 8)) + call prn_set_stream(STREAM_TRACKING) - ! if we're dealing with a nuclide that we've previously encountered at - ! this energy but a different temperature, use the original random number to - ! preserve correlation of temperature in probability tables - same_nuc = .false. - do i = 1, nuc % nuc_list % size() - if (E /= ZERO .and. E == micro_xs(nuc % nuc_list % data(i)) % last_E) then - same_nuc = .true. - same_nuc_idx = i - exit - end if - end do + i_low = 1 + do + if (urr % prob(i_energy, URR_CUM_PROB, i_low) > r) exit + i_low = i_low + 1 + end do + i_up = 1 + do + if (urr % prob(i_energy + 1, URR_CUM_PROB, i_up) > r) exit + i_up = i_up + 1 + end do - if (same_nuc) then - r = micro_xs(nuc % nuc_list % data(same_nuc_idx)) % last_prn - else - r = prn() - micro_xs(i_nuclide) % last_prn = r - end if + ! determine elastic, fission, and capture cross sections from probability + ! table + if (urr % interp == LINEAR_LINEAR) then + elastic = (ONE - f) * urr % prob(i_energy, URR_ELASTIC, i_low) + & + f * urr % prob(i_energy + 1, URR_ELASTIC, i_up) + fission = (ONE - f) * urr % prob(i_energy, URR_FISSION, i_low) + & + f * urr % prob(i_energy + 1, URR_FISSION, i_up) + capture = (ONE - f) * urr % prob(i_energy, URR_N_GAMMA, i_low) + & + f * urr % prob(i_energy + 1, URR_N_GAMMA, i_up) + elseif (urr % interp == LOG_LOG) then + ! Get logarithmic interpolation factor + f = log(E / urr % energy(i_energy)) / & + log(urr % energy(i_energy + 1) / urr % energy(i_energy)) - i_low = 1 - do - if (urr % prob(i_energy, URR_CUM_PROB, i_low) > r) exit - i_low = i_low + 1 - end do - i_up = 1 - do - if (urr % prob(i_energy + 1, URR_CUM_PROB, i_up) > r) exit - i_up = i_up + 1 - end do - - ! determine elastic, fission, and capture cross sections from probability - ! table - if (urr % interp == LINEAR_LINEAR) then - elastic = (ONE - f) * urr % prob(i_energy, URR_ELASTIC, i_low) + & - f * urr % prob(i_energy + 1, URR_ELASTIC, i_up) - fission = (ONE - f) * urr % prob(i_energy, URR_FISSION, i_low) + & - f * urr % prob(i_energy + 1, URR_FISSION, i_up) - capture = (ONE - f) * urr % prob(i_energy, URR_N_GAMMA, i_low) + & - f * urr % prob(i_energy + 1, URR_N_GAMMA, i_up) - elseif (urr % interp == LOG_LOG) then - ! Get logarithmic interpolation factor - f = log(E / urr % energy(i_energy)) / & - log(urr % energy(i_energy + 1) / urr % energy(i_energy)) - - ! Calculate elastic cross section/factor - elastic = ZERO - if (urr % prob(i_energy, URR_ELASTIC, i_low) > ZERO .and. & - urr % prob(i_energy + 1, URR_ELASTIC, i_up) > ZERO) then - elastic = exp((ONE - f) * log(urr % prob(i_energy, URR_ELASTIC, & - i_low)) + f * log(urr % prob(i_energy + 1, URR_ELASTIC, & - i_up))) - end if - - ! Calculate fission cross section/factor - fission = ZERO - if (urr % prob(i_energy, URR_FISSION, i_low) > ZERO .and. & - urr % prob(i_energy + 1, URR_FISSION, i_up) > ZERO) then - fission = exp((ONE - f) * log(urr % prob(i_energy, URR_FISSION, & - i_low)) + f * log(urr % prob(i_energy + 1, URR_FISSION, & - i_up))) - end if - - ! Calculate capture cross section/factor - capture = ZERO - if (urr % prob(i_energy, URR_N_GAMMA, i_low) > ZERO .and. & - urr % prob(i_energy + 1, URR_N_GAMMA, i_up) > ZERO) then - capture = exp((ONE - f) * log(urr % prob(i_energy, URR_N_GAMMA, & - i_low)) + f * log(urr % prob(i_energy + 1, URR_N_GAMMA, & - i_up))) - end if - end if - - ! Determine treatment of inelastic scattering - inelastic = ZERO - if (urr % inelastic_flag > 0) then - ! Get index on energy grid and interpolation factor - i_energy = micro_xs(i_nuclide) % index_grid - f = micro_xs(i_nuclide) % interp_factor - - ! Determine inelastic scattering cross section - associate (rxn => nuc % reactions(nuc % urr_inelastic)) - if (i_energy >= rxn % threshold) then - inelastic = (ONE - f) * rxn % sigma(i_energy - rxn%threshold + 1) + & - f * rxn % sigma(i_energy - rxn%threshold + 2) + ! Calculate elastic cross section/factor + elastic = ZERO + if (urr % prob(i_energy, URR_ELASTIC, i_low) > ZERO .and. & + urr % prob(i_energy + 1, URR_ELASTIC, i_up) > ZERO) then + elastic = exp((ONE - f) * log(urr % prob(i_energy, URR_ELASTIC, & + i_low)) + f * log(urr % prob(i_energy + 1, URR_ELASTIC, & + i_up))) end if - end associate - end if - ! Multiply by smooth cross-section if needed - if (urr % multiply_smooth) then - elastic = elastic * micro_xs(i_nuclide) % elastic - capture = capture * (micro_xs(i_nuclide) % absorption - & - micro_xs(i_nuclide) % fission) - fission = fission * micro_xs(i_nuclide) % fission - end if + ! Calculate fission cross section/factor + fission = ZERO + if (urr % prob(i_energy, URR_FISSION, i_low) > ZERO .and. & + urr % prob(i_energy + 1, URR_FISSION, i_up) > ZERO) then + fission = exp((ONE - f) * log(urr % prob(i_energy, URR_FISSION, & + i_low)) + f * log(urr % prob(i_energy + 1, URR_FISSION, & + i_up))) + end if - ! Check for negative values - if (elastic < ZERO) elastic = ZERO - if (fission < ZERO) fission = ZERO - if (capture < ZERO) capture = ZERO + ! Calculate capture cross section/factor + capture = ZERO + if (urr % prob(i_energy, URR_N_GAMMA, i_low) > ZERO .and. & + urr % prob(i_energy + 1, URR_N_GAMMA, i_up) > ZERO) then + capture = exp((ONE - f) * log(urr % prob(i_energy, URR_N_GAMMA, & + i_low)) + f * log(urr % prob(i_energy + 1, URR_N_GAMMA, & + i_up))) + end if + end if - ! Set elastic, absorption, fission, and total cross sections. Note that the - ! total cross section is calculated as sum of partials rather than using the - ! table-provided value - micro_xs(i_nuclide) % elastic = elastic - micro_xs(i_nuclide) % absorption = capture + fission - micro_xs(i_nuclide) % fission = fission - micro_xs(i_nuclide) % total = elastic + inelastic + capture + fission + ! Determine treatment of inelastic scattering + inelastic = ZERO + if (urr % inelastic_flag > 0) then + ! Get index on energy grid and interpolation factor + i_energy = micro_xs(i_nuclide) % index_grid + f = micro_xs(i_nuclide) % interp_factor - ! Determine nu-fission cross section - if (nuc % fissionable) then - micro_xs(i_nuclide) % nu_fission = nu_total(nuc, E) * & - micro_xs(i_nuclide) % fission - end if + ! Determine inelastic scattering cross section + associate (rxn => nuc % reactions(nuc % urr_inelastic)) + if (i_energy >= rxn % threshold) then + inelastic = (ONE - f) * rxn % sigma(i_energy - rxn%threshold + 1) + & + f * rxn % sigma(i_energy - rxn%threshold + 2) + end if + end associate + end if + + ! Multiply by smooth cross-section if needed + if (urr % multiply_smooth) then + elastic = elastic * micro_xs(i_nuclide) % elastic + capture = capture * (micro_xs(i_nuclide) % absorption - & + micro_xs(i_nuclide) % fission) + fission = fission * micro_xs(i_nuclide) % fission + end if + + ! Check for negative values + if (elastic < ZERO) elastic = ZERO + if (fission < ZERO) fission = ZERO + if (capture < ZERO) capture = ZERO + + ! Set elastic, absorption, fission, and total cross sections. Note that the + ! total cross section is calculated as sum of partials rather than using the + ! table-provided value + micro_xs(i_nuclide) % elastic = elastic + micro_xs(i_nuclide) % absorption = capture + fission + micro_xs(i_nuclide) % fission = fission + micro_xs(i_nuclide) % total = elastic + inelastic + capture + fission + + ! Determine nu-fission cross section + if (nuc % fissionable) then + micro_xs(i_nuclide) % nu_fission = nuc % nu(E, EMISSION_TOTAL) * & + micro_xs(i_nuclide) % fission + end if + end associate end subroutine calculate_urr_xs @@ -533,9 +513,9 @@ contains !=============================================================================== pure function elastic_xs_0K(E, nuc) result(xs_out) - real(8), intent(in) :: E ! trial energy - type(NuclideCE), intent(in) :: nuc ! target nuclide at temperature - real(8) :: xs_out ! 0K xs at trial energy + real(8), intent(in) :: E ! trial energy + type(Nuclide), intent(in) :: nuc ! target nuclide at temperature + real(8) :: xs_out ! 0K xs at trial energy integer :: i_grid ! index on nuclide energy grid real(8) :: f ! interp factor on nuclide energy grid diff --git a/src/eigenvalue.F90 b/src/eigenvalue.F90 index e735bc8d8..9befbe3c3 100644 --- a/src/eigenvalue.F90 +++ b/src/eigenvalue.F90 @@ -10,7 +10,7 @@ module eigenvalue use math, only: t_percentile use mesh, only: count_bank_sites use mesh_header, only: RegularMesh - use random_lcg, only: prn, set_particle_seed, prn_skip + use random_lcg, only: prn, set_particle_seed, advance_prn_seed use search, only: binary_search use string, only: to_str @@ -99,7 +99,7 @@ contains call set_particle_seed(int((current_batch - 1)*gen_per_batch + & current_gen,8)) - call prn_skip(start) + call advance_prn_seed(start) ! Determine how many fission sites we need to sample from the source bank ! and the probability for selecting a site. diff --git a/src/endf.F90 b/src/endf.F90 index 64f26539a..ad5e97a03 100644 --- a/src/endf.F90 +++ b/src/endf.F90 @@ -34,10 +34,6 @@ contains string = "nu-scatter-n" case (SCORE_NU_SCATTER_PN) string = "nu-scatter-pn" - case (SCORE_TRANSPORT) - string = "transport" - case (SCORE_N_1N) - string = "n1n" case (SCORE_ABSORPTION) string = "absorption" case (SCORE_FISSION) diff --git a/src/endf_header.F90 b/src/endf_header.F90 index 7388ea2f5..e9a073f4e 100644 --- a/src/endf_header.F90 +++ b/src/endf_header.F90 @@ -1,12 +1,51 @@ module endf_header - implicit none + use constants, only: ZERO, HISTOGRAM, LINEAR_LINEAR, LINEAR_LOG, & + LOG_LINEAR, LOG_LOG + use search, only: binary_search + +implicit none + + type, abstract :: Function1D + contains + procedure(function1d_evaluate_), deferred :: evaluate + end type Function1D + + abstract interface + pure function function1d_evaluate_(this, x) result(y) + import Function1D + class(Function1D), intent(in) :: this + real(8), intent(in) :: x + real(8) :: y + end function function1d_evaluate_ + end interface !=============================================================================== -! TAB1 represents a one-dimensional interpolable function +! CONSTANT1D represents a constant one-dimensional function !=============================================================================== - type Tab1 + type, extends(Function1D) :: Constant1D + real(8) :: y + contains + procedure :: evaluate => constant1d_evaluate + end type Constant1D + +!=============================================================================== +! POLYNOMIAL represents a one-dimensional function expressed as a polynomial +!=============================================================================== + + type, extends(Function1D) :: Polynomial + real(8), allocatable :: coef(:) ! coefficients + contains + procedure :: evaluate => polynomial_evaluate + procedure :: from_ace => polynomial_from_ace + end type Polynomial + +!=============================================================================== +! TABULATED1D represents a one-dimensional interpolable function +!=============================================================================== + + type, extends(Function1D) :: Tabulated1D integer :: n_regions = 0 ! # of interpolation regions integer, allocatable :: nbt(:) ! values separating interpolation regions integer, allocatable :: int(:) ! interpolation scheme @@ -14,18 +53,78 @@ module endf_header real(8), allocatable :: x(:) ! values of abscissa real(8), allocatable :: y(:) ! values of ordinate contains - procedure :: from_ace - end type Tab1 + procedure :: from_ace => tabulated1d_from_ace + procedure :: evaluate => tabulated1d_evaluate + end type Tabulated1D contains - subroutine from_ace(this, xss, idx) - class(Tab1), intent(inout) :: this +!=============================================================================== +! Constant1D implementation +!=============================================================================== + + pure function constant1d_evaluate(this, x) result(y) + class(Constant1D), intent(in) :: this + real(8), intent(in) :: x + real(8) :: y + + y = this % y + end function constant1d_evaluate + +!=============================================================================== +! Polynomial implementation +!=============================================================================== + + subroutine polynomial_from_ace(this, xss, idx) + class(Polynomial), intent(inout) :: this + real(8), intent(in) :: xss(:) + integer, intent(in) :: idx + + integer :: nc ! number of coefficients (order - 1) + + ! Clear space + if (allocated(this % coef)) deallocate(this % coef) + + ! Determine number of coefficients + nc = nint(xss(idx)) + + ! Allocate space for and read coefficients + allocate(this % coef(nc)) + this % coef(:) = xss(idx + 1 : idx + nc) + end subroutine polynomial_from_ace + + pure function polynomial_evaluate(this, x) result(y) + class(Polynomial), intent(in) :: this + real(8), intent(in) :: x + real(8) :: y + + integer :: i + + ! Use Horner's rule to evaluate polynomial. Note that coefficients are + ! ordered in increasing powers of x. + y = ZERO + do i = size(this % coef), 1, -1 + y = y*x + this % coef(i) + end do + end function polynomial_evaluate + +!=============================================================================== +! Tabulated1D implementation +!=============================================================================== + + subroutine tabulated1d_from_ace(this, xss, idx) + class(Tabulated1D), intent(inout) :: this real(8), intent(in) :: xss(:) integer, intent(in) :: idx integer :: nr, ne + ! Clear space + if (allocated(this % nbt)) deallocate(this % nbt) + if (allocated(this % int)) deallocate(this % int) + if (allocated(this % x)) deallocate(this % x) + if (allocated(this % y)) deallocate(this % y) + ! Determine number of regions nr = nint(xss(idx)) this%n_regions = nr @@ -47,6 +146,81 @@ contains allocate(this%y(ne)) this%x(:) = xss(idx + 2*nr + 2 : idx + 2*nr + 1 + ne) this%y(:) = xss(idx + 2*nr + 2 + ne : idx + 2*nr + 1 + 2*ne) - end subroutine from_ace + end subroutine tabulated1d_from_ace + + pure function tabulated1d_evaluate(this, x) result(y) + class(Tabulated1D), intent(in) :: this + real(8), intent(in) :: x ! x value to find y at + real(8) :: y ! y(x) + + integer :: i ! bin in which to interpolate + integer :: j ! index for interpolation region + integer :: n_regions ! number of interpolation regions + integer :: n_pairs ! number of tabulated values + integer :: interp ! ENDF interpolation scheme + real(8) :: r ! interpolation factor + real(8) :: x0, x1 ! bounding x values + real(8) :: y0, y1 ! bounding y values + + ! determine number of interpolation regions and pairs + n_regions = this % n_regions + n_pairs = this % n_pairs + + ! find which bin the abscissa is in -- if the abscissa is outside the + ! tabulated range, the first or last point is chosen, i.e. no interpolation + ! is done outside the energy range + if (x < this % x(1)) then + y = this % y(1) + return + elseif (x > this % x(n_pairs)) then + y = this % y(n_pairs) + return + else + i = binary_search(this % x, n_pairs, x) + end if + + ! determine interpolation scheme + if (n_regions == 0) then + interp = LINEAR_LINEAR + elseif (n_regions == 1) then + interp = this % int(1) + elseif (n_regions > 1) then + do j = 1, n_regions + if (i < this % nbt(j)) then + interp = this % int(j) + exit + end if + end do + end if + + ! handle special case of histogram interpolation + if (interp == HISTOGRAM) then + y = this % y(i) + return + end if + + ! determine bounding values + x0 = this % x(i) + x1 = this % x(i + 1) + y0 = this % y(i) + y1 = this % y(i + 1) + + ! determine interpolation factor and interpolated value + select case (interp) + case (LINEAR_LINEAR) + r = (x - x0)/(x1 - x0) + y = y0 + r*(y1 - y0) + case (LINEAR_LOG) + r = log(x/x0)/log(x1/x0) + y = y0 + r*(y1 - y0) + case (LOG_LINEAR) + r = (x - x0)/(x1 - x0) + y = y0*exp(r*log(y1/y0)) + case (LOG_LOG) + r = log(x/x0)/log(x1/x0) + y = y0*exp(r*log(y1/y0)) + end select + + end function tabulated1d_evaluate end module endf_header diff --git a/src/energy_distribution.F90 b/src/energy_distribution.F90 index 8b2cc10c9..3a42bb73d 100644 --- a/src/energy_distribution.F90 +++ b/src/energy_distribution.F90 @@ -1,8 +1,7 @@ module energy_distribution use constants, only: ZERO, ONE, TWO, PI, HISTOGRAM, LINEAR_LINEAR - use endf_header, only: Tab1 - use interpolation, only: interpolate_tab1 + use endf_header, only: Tabulated1D use math, only: maxwell_spectrum, watt_spectrum use random_lcg, only: prn use search, only: binary_search @@ -83,8 +82,8 @@ module energy_distribution integer :: n_region integer, allocatable :: breakpoints(:) integer, allocatable :: interpolation(:) - real(8), allocatable :: energy_in(:) - type(CTTable), allocatable :: energy_out(:) + real(8), allocatable :: energy(:) + type(CTTable), allocatable :: distribution(:) contains procedure :: sample => continuous_sample end type ContinuousTabular @@ -95,7 +94,7 @@ module energy_distribution !=============================================================================== type, extends(EnergyDistribution) :: MaxwellEnergy - type(Tab1) :: theta ! incoming-energy-dependent parameter + type(Tabulated1D) :: theta ! incoming-energy-dependent parameter real(8) :: u ! restriction energy contains procedure :: sample => maxwellenergy_sample @@ -107,7 +106,7 @@ module energy_distribution !=============================================================================== type, extends(EnergyDistribution) :: Evaporation - type(Tab1) :: theta + type(Tabulated1D) :: theta real(8) :: u contains procedure :: sample => evaporation_sample @@ -119,28 +118,13 @@ module energy_distribution !=============================================================================== type, extends(EnergyDistribution) :: WattEnergy - type(Tab1) :: a - type(Tab1) :: b + type(Tabulated1D) :: a + type(Tabulated1D) :: b real(8) :: u contains procedure :: sample => watt_sample end type WattEnergy -!=============================================================================== -! NBODYPHASESPACE gives the energy distribution for particles emitted from -! neutron and charged-particle reactions. This corresponds to ACE law 66 and -! ENDF File 6, LAW=6. -!=============================================================================== - - type, extends(EnergyDistribution) :: NBodyPhaseSpace - integer :: n_bodies - real(8) :: mass_ratio - real(8) :: A - real(8) :: Q - contains - procedure :: sample => nbody_sample - end type NBodyPhaseSpace - contains function equiprobable_sample(this, E_in) result(E_out) @@ -202,6 +186,7 @@ contains end if end function equiprobable_sample + function level_inelastic_sample(this, E_in) result(E_out) class(LevelInelastic), intent(in) :: this real(8), intent(in) :: E_in @@ -210,6 +195,7 @@ contains E_out = this%mass_ratio*(E_in - this%threshold) end function level_inelastic_sample + function continuous_sample(this, E_in) result(E_out) class(ContinuousTabular), intent(in) :: this real(8), intent(in) :: E_in ! incoming energy @@ -238,17 +224,17 @@ contains ! Find energy bin and calculate interpolation factor -- if the energy is ! outside the range of the tabulated energies, choose the first or last bins - n_energy_in = size(this%energy_in) - if (E_in < this%energy_in(1)) then + n_energy_in = size(this%energy) + if (E_in < this%energy(1)) then i = 1 r = ZERO - elseif (E_in > this%energy_in(n_energy_in)) then + elseif (E_in > this%energy(n_energy_in)) then i = n_energy_in - 1 r = ONE else - i = binary_search(this%energy_in, n_energy_in, E_in) - r = (E_in - this%energy_in(i)) / & - (this%energy_in(i+1) - this%energy_in(i)) + i = binary_search(this%energy, n_energy_in, E_in) + r = (E_in - this%energy(i)) / & + (this%energy(i+1) - this%energy(i)) end if ! Sample between the ith and (i+1)th bin @@ -263,23 +249,23 @@ contains end if ! Interpolation for energy E1 and EK - n_energy_out = size(this%energy_out(i)%e_out) - E_i_1 = this%energy_out(i)%e_out(1) - E_i_K = this%energy_out(i)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i)%e_out) + E_i_1 = this%distribution(i)%e_out(1) + E_i_K = this%distribution(i)%e_out(n_energy_out) - n_energy_out = size(this%energy_out(i+1)%e_out) - E_i1_1 = this%energy_out(i+1)%e_out(1) - E_i1_K = this%energy_out(i+1)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i+1)%e_out) + E_i1_1 = this%distribution(i+1)%e_out(1) + E_i1_K = this%distribution(i+1)%e_out(n_energy_out) E_1 = E_i_1 + r*(E_i1_1 - E_i_1) E_K = E_i_K + r*(E_i1_K - E_i_K) ! Determine outgoing energy bin - n_energy_out = size(this%energy_out(l)%e_out) + n_energy_out = size(this%distribution(l)%e_out) r1 = prn() - c_k = this%energy_out(l)%c(1) + c_k = this%distribution(l)%c(1) do k = 1, n_energy_out - 1 - c_k1 = this%energy_out(l)%c(k+1) + c_k1 = this%distribution(l)%c(k+1) if (r1 < c_k1) exit c_k = c_k1 end do @@ -287,9 +273,9 @@ contains ! Check to make sure k is <= NP - 1 k = min(k, n_energy_out - 1) - E_l_k = this%energy_out(l)%e_out(k) - p_l_k = this%energy_out(l)%p(k) - if (this%energy_out(l)%interpolation == HISTOGRAM) then + E_l_k = this%distribution(l)%e_out(k) + p_l_k = this%distribution(l)%p(k) + if (this%distribution(l)%interpolation == HISTOGRAM) then ! Histogram interpolation if (p_l_k > ZERO) then E_out = E_l_k + (r1 - c_k)/p_l_k @@ -297,10 +283,10 @@ contains E_out = E_l_k end if - elseif (this%energy_out(l)%interpolation == LINEAR_LINEAR) then + elseif (this%distribution(l)%interpolation == LINEAR_LINEAR) then ! Linear-linear interpolation - E_l_k1 = this%energy_out(l)%e_out(k+1) - p_l_k1 = this%energy_out(l)%p(k+1) + E_l_k1 = this%distribution(l)%e_out(k+1) + p_l_k1 = this%distribution(l)%p(k+1) frac = (p_l_k1 - p_l_k)/(E_l_k1 - E_l_k) if (frac == ZERO) then @@ -321,6 +307,7 @@ contains end if end function continuous_sample + function maxwellenergy_sample(this, E_in) result(E_out) class(MaxwellEnergy), intent(in) :: this real(8), intent(in) :: E_in ! incoming energy @@ -329,7 +316,7 @@ contains real(8) :: theta ! Maxwell distribution parameter ! Get temperature corresponding to incoming energy - theta = interpolate_tab1(this%theta, E_in) + theta = this % theta % evaluate(E_in) do ! Sample maxwell fission spectrum @@ -349,9 +336,9 @@ contains real(8) :: x, y, v ! Get temperature corresponding to incoming energy - theta = interpolate_tab1(this%theta, E_in) + theta = this % theta % evaluate(E_in) - y = (E_in - this%U)/theta + y = (E_in - this%u)/theta v = 1 - exp(-y) ! Sample outgoing energy based on evaporation spectrum probability @@ -372,10 +359,10 @@ contains real(8) :: a, b ! Watt spectrum parameters ! Determine Watt parameter 'a' from tabulated function - a = interpolate_tab1(this%a, E_in) + a = this % a % evaluate(E_in) ! Determine Watt parameter 'b' from tabulated function - b = interpolate_tab1(this%b, E_in) + b = this % b % evaluate(E_in) do ! Sample energy-dependent Watt fission spectrum @@ -386,44 +373,4 @@ contains end do end function watt_sample - function nbody_sample(this, E_in) result(E_out) - class(NBodyPhaseSpace), intent(in) :: this - real(8), intent(in) :: E_in ! incoming energy - real(8) :: E_out ! sampled outgoing energy - - real(8) :: Ap ! total mass of particles in neutron masses - real(8) :: E_max ! maximum possible COM energy - real(8) :: x, y, v - real(8) :: r1, r2, r3, r4, r5, r6 - - ! Determine E_max parameter - Ap = this%mass_ratio - E_max = (Ap - ONE)/Ap * (this%A/(this%A + ONE)*E_in + this%Q) - - ! x is essentially a Maxwellian distribution - x = maxwell_spectrum(ONE) - - select case (this%n_bodies) - case (3) - y = maxwell_spectrum(ONE) - case (4) - r1 = prn() - r2 = prn() - r3 = prn() - y = -log(r1*r2*r3) - case (5) - r1 = prn() - r2 = prn() - r3 = prn() - r4 = prn() - r5 = prn() - r6 = prn() - y = -log(r1*r2*r3*r4) - log(r5) * cos(PI/TWO*r6)**2 - end select - - ! Now determine v and E_out - v = x/(x+y) - E_out = E_max * v - end function nbody_sample - end module energy_distribution diff --git a/src/energy_grid.F90 b/src/energy_grid.F90 index 248462f70..66419f83c 100644 --- a/src/energy_grid.F90 +++ b/src/energy_grid.F90 @@ -27,7 +27,7 @@ contains integer :: i ! index in nuclides array integer :: j ! index in materials array type(ListReal) :: list - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc type(Material), pointer :: mat call write_message("Creating unionized energy grid...", 5) @@ -70,7 +70,7 @@ contains real(8) :: E_max ! Maximum energy in MeV real(8) :: E_min ! Minimum energy in MeV real(8), allocatable :: umesh(:) ! Equally log-spaced energy grid - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc ! Set minimum/maximum energies E_max = energy_max_neutron @@ -179,7 +179,7 @@ contains integer :: index_e ! index on union energy grid real(8) :: union_energy ! energy on union grid real(8) :: energy ! energy on nuclide grid - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc type(Material), pointer :: mat do k = 1, n_materials diff --git a/src/fission.F90 b/src/fission.F90 deleted file mode 100644 index 77ee64178..000000000 --- a/src/fission.F90 +++ /dev/null @@ -1,161 +0,0 @@ -module fission - - use nuclide_header, only: NuclideCE - use constants - use error, only: fatal_error - use interpolation, only: interpolate_tab1 - use search, only: binary_search - - implicit none - -contains - -!=============================================================================== -! NU_TOTAL calculates the total number of neutrons emitted per fission for a -! given nuclide and incoming neutron energy -!=============================================================================== - - pure function nu_total(nuc, E) result(nu) - type(NuclideCE), intent(in) :: nuc ! nuclide from which to find nu - real(8), intent(in) :: E ! energy of incoming neutron - real(8) :: nu ! number of total neutrons emitted per fission - - integer :: i ! loop index - integer :: NC ! number of polynomial coefficients - real(8) :: c ! polynomial coefficient - - if (nuc % nu_t_type == NU_NONE) then - nu = ERROR_REAL - elseif (nuc % nu_t_type == NU_POLYNOMIAL) then - ! determine number of coefficients - NC = int(nuc % nu_t_data(1)) - - ! sum up polynomial in energy - nu = ZERO - do i = 0, NC - 1 - c = nuc % nu_t_data(i+2) - nu = nu + c * E**i - end do - elseif (nuc % nu_t_type == NU_TABULAR) then - ! use ENDF interpolation laws to determine nu - nu = interpolate_tab1(nuc % nu_t_data, E) - end if - - end function nu_total - -!=============================================================================== -! NU_PROMPT calculates the total number of prompt neutrons emitted per fission -! for a given nuclide and incoming neutron energy -!=============================================================================== - - pure function nu_prompt(nuc, E) result(nu) - type(NuclideCE), intent(in) :: nuc ! nuclide from which to find nu - real(8), intent(in) :: E ! energy of incoming neutron - real(8) :: nu ! number of prompt neutrons emitted per fission - - integer :: i ! loop index - integer :: NC ! number of polynomial coefficients - real(8) :: c ! polynomial coefficient - - if (nuc % nu_p_type == NU_NONE) then - ! since no prompt or delayed data is present, this means all neutron - ! emission is prompt -- WARNING: This currently returns zero. The calling - ! routine needs to know this situation is occurring since we don't want - ! to call nu_total unnecessarily if it has already been called. - nu = ZERO - elseif (nuc % nu_p_type == NU_POLYNOMIAL) then - ! determine number of coefficients - NC = int(nuc % nu_p_data(1)) - - ! sum up polynomial in energy - nu = ZERO - do i = 0, NC - 1 - c = nuc % nu_p_data(i+2) - nu = nu + c * E**i - end do - elseif (nuc % nu_p_type == NU_TABULAR) then - ! use ENDF interpolation laws to determine nu - nu = interpolate_tab1(nuc % nu_p_data, E) - end if - - end function nu_prompt - -!=============================================================================== -! NU_DELAYED calculates the total number of delayed neutrons emitted per fission -! for a given nuclide and incoming neutron energy -!=============================================================================== - - pure function nu_delayed(nuc, E) result(nu) - type(NuclideCE), intent(in) :: nuc ! nuclide from which to find nu - real(8), intent(in) :: E ! energy of incoming neutron - real(8) :: nu ! number of delayed neutrons emitted per fission - - if (nuc % nu_d_type == NU_NONE) then - ! since no prompt or delayed data is present, this means all neutron - ! emission is prompt -- WARNING: This currently returns zero. The calling - ! routine needs to know this situation is occurring since we don't want - ! to call nu_delayed unnecessarily if it has already been called. - nu = ZERO - elseif (nuc % nu_d_type == NU_TABULAR) then - ! use ENDF interpolation laws to determine nu - nu = interpolate_tab1(nuc % nu_d_data, E) - end if - - end function nu_delayed - -!=============================================================================== -! YIELD_DELAYED calculates the fractional yield of delayed neutrons emitted for -! a given nuclide and incoming neutron energy in a given delayed group. -!=============================================================================== - - pure function yield_delayed(nuc, E, g) result(yield) - type(NuclideCE), intent(in) :: nuc ! nuclide from which to find nu - real(8), intent(in) :: E ! energy of incoming neutron - real(8) :: yield ! delayed neutron precursor yield - integer, intent(in) :: g ! the delayed neutron precursor group - integer :: d ! precursor group - integer :: lc ! index before start of energies/nu values - integer :: NR ! number of interpolation regions - integer :: NE ! number of energies tabulated - - yield = ZERO - - if (g > nuc % n_precursor .or. g < 1) then - ! if the precursor group is outside the range of precursor groups for - ! the input nuclide, return ZERO. - yield = ZERO - else if (nuc % nu_d_type == NU_NONE) then - ! since no prompt or delayed data is present, this means all neutron - ! emission is prompt -- WARNING: This currently returns zero. The calling - ! routine needs to know this situation is occurring since we don't want - ! to call yield_delayed unnecessarily if it has already been called. - yield = ZERO - else if (nuc % nu_d_type == NU_TABULAR) then - - lc = 1 - - ! loop over delayed groups and determine the yield for the desired group - do d = 1, nuc % n_precursor - - ! determine number of interpolation regions and energies - NR = int(nuc % nu_d_precursor_data(lc + 1)) - NE = int(nuc % nu_d_precursor_data(lc + 2 + 2*NR)) - - ! check if this is the desired group - if (d == g) then - - ! determine delayed neutron precursor yield for group g - yield = interpolate_tab1(nuc % nu_d_precursor_data( & - lc+1:lc+2+2*NR+2*NE), E) - - exit - end if - - ! advance pointer - lc = lc + 2 + 2*NR + 2*NE + 1 - end do - end if - - end function yield_delayed - -end module fission diff --git a/src/geometry.F90 b/src/geometry.F90 index 8a38f982b..21c8baa6b 100644 --- a/src/geometry.F90 +++ b/src/geometry.F90 @@ -378,6 +378,7 @@ contains real(8) :: v ! y-component of direction real(8) :: w ! z-component of direction real(8) :: norm ! "norm" of surface normal + real(8) :: xyz(3) ! Saved global coordinate integer :: i_surface ! index in surfaces logical :: found ! particle found in universe? class(Surface), pointer :: surf @@ -432,12 +433,13 @@ contains ! Score surface currents since reflection causes the direction of the ! particle to change -- artificially move the particle slightly back in - ! case the surface crossing in coincident with a mesh boundary + ! case the surface crossing is coincident with a mesh boundary if (active_current_tallies % size() > 0) then + xyz = p % coord(1) % xyz p % coord(1) % xyz = p % coord(1) % xyz - TINY_BIT * p % coord(1) % uvw call score_surface_current(p) - p % coord(1) % xyz = p % coord(1) % xyz + TINY_BIT * p % coord(1) % uvw + p % coord(1) % xyz = xyz end if ! Reflect particle off surface @@ -475,6 +477,70 @@ contains &// trim(to_str(surf%id))) end if return + elseif (surf % bc == BC_PERIODIC .and. run_mode /= MODE_PLOTTING) then + ! ======================================================================= + ! PERIODIC BOUNDARY + + ! Do not handle periodic boundary conditions on lower universes + if (p % n_coord /= 1) then + call handle_lost_particle(p, "Cannot transfer particle " & + // trim(to_str(p % id)) // " across surface in a lower universe.& + & Boundary conditions must be applied to universe 0.") + return + end if + + ! Score surface currents since reflection causes the direction of the + ! particle to change -- artificially move the particle slightly back in + ! case the surface crossing is coincident with a mesh boundary + + if (active_current_tallies % size() > 0) then + xyz = p % coord(1) % xyz + p % coord(1) % xyz = p % coord(1) % xyz - TINY_BIT * p % coord(1) % uvw + call score_surface_current(p) + p % coord(1) % xyz = xyz + end if + + select type (surf) + type is (SurfaceXPlane) + select type (opposite => surfaces(surf % i_periodic) % obj) + type is (SurfaceXPlane) + p % coord(1) % xyz(1) = opposite % x0 + end select + + type is (SurfaceYPlane) + select type (opposite => surfaces(surf % i_periodic) % obj) + type is (SurfaceYPlane) + p % coord(1) % xyz(2) = opposite % y0 + end select + + type is (SurfaceZPlane) + select type (opposite => surfaces(surf % i_periodic) % obj) + type is (SurfaceZPlane) + p % coord(1) % xyz(3) = opposite % z0 + end select + end select + + ! Reassign particle's surface + p % surface = sign(surf % i_periodic, p % surface) + + ! Figure out what cell particle is in now + p % n_coord = 1 + call find_cell(p, found) + if (.not. found) then + call handle_lost_particle(p, "Couldn't find particle after hitting & + &periodic boundary on surface " // trim(to_str(surf%id)) // ".") + return + end if + + ! Set previous coordinate going slightly past surface crossing + p % last_xyz = p % coord(1) % xyz + TINY_BIT * p % coord(1) % uvw + + ! Diagnostic message + if (verbosity >= 10 .or. trace) then + call write_message(" Hit periodic boundary on surface " & + // trim(to_str(surf%id))) + end if + return end if ! ========================================================================== diff --git a/src/geometry_header.F90 b/src/geometry_header.F90 index 1adda3ea3..30f82f706 100644 --- a/src/geometry_header.F90 +++ b/src/geometry_header.F90 @@ -1,6 +1,6 @@ module geometry_header - use constants, only: HALF, TWO, THREE + use constants, only: HALF, TWO, THREE, INFINITY implicit none @@ -201,20 +201,22 @@ contains real(8), intent(in) :: global_xyz(3) integer :: i_xyz(3) - real(8) :: xyz(3) ! global_xyz alias + real(8) :: xyz(3) ! global xyz relative to the center real(8) :: alpha ! Skewed coord axis real(8) :: xyz_t(3) ! Local xyz - real(8) :: dists(4) ! Squared distances from cell centers + real(8) :: d, d_min ! Squared distance from cell centers integer :: i, j, k ! Iterators - integer :: loc(1) ! Minimum distance index + integer :: k_min ! Minimum distance index - xyz = global_xyz + xyz(1) = global_xyz(1) - this % center(1) + xyz(2) = global_xyz(2) - this % center(2) ! Index z direction. if (this % is_3d) then - i_xyz(3) = ceiling((xyz(3) - this % center(3))/this % pitch(2) + HALF)& - + this % n_axial/2 + xyz(3) = global_xyz(3) - this % center(3) + i_xyz(3) = ceiling(xyz(3)/this % pitch(2) + HALF*this % n_axial) else + xyz(3) = global_xyz(3) i_xyz(3) = 1 end if @@ -233,28 +235,33 @@ contains ! the four possible cells. Regular hexagonal tiles form a centroidal ! Voronoi tessellation so the global xyz should be in the hexagonal cell ! that it is closest to the center of. This method is used over a - ! method that uses the remainders of the floor divisions above becasue it + ! method that uses the remainders of the floor divisions above because it ! provides better finite precision performance. Squared distances are ! used becasue they are more computationally efficient than normal ! distances. k = 1 - do i=0,1 - do j=0,1 - xyz_t = this % get_local_xyz(xyz, i_xyz + (/j, i, 0/)) - dists(k) = xyz_t(1)**2 + xyz_t(2)**2 + d_min = INFINITY + do i = 0, 1 + do j = 0, 1 + xyz_t = this % get_local_xyz(global_xyz, i_xyz + [j, i, 0]) + d = xyz_t(1)**2 + xyz_t(2)**2 + if (d < d_min) then + d_min = d + k_min = k + end if k = k + 1 end do end do ! Select the minimum squared distance which corresponds to the cell the ! coordinates are in. - loc = minloc(dists) - if (loc(1) == 2) then - i_xyz = i_xyz + (/1, 0, 0/) - else if (loc(1) == 3) then - i_xyz = i_xyz + (/0, 1, 0/) - else if (loc(1) == 4) then - i_xyz = i_xyz + (/1, 1, 0/) + if (k_min == 2) then + i_xyz(1) = i_xyz(1) + 1 + else if (k_min == 3) then + i_xyz(2) = i_xyz(2) + 1 + else if (k_min == 4) then + i_xyz(1) = i_xyz(1) + 1 + i_xyz(2) = i_xyz(2) + 1 end if end function get_inds_hex @@ -303,7 +310,7 @@ contains (i_xyz(1) - this % n_rings) * this % pitch(1) / TWO) if (this % is_3d) then local_xyz(3) = xyz(3) - this % center(3) & - + (this % n_axial/2 - i_xyz(3) + 1) * this % pitch(2) + + (HALF*this % n_axial - i_xyz(3) + HALF) * this % pitch(2) else local_xyz(3) = xyz(3) end if diff --git a/src/global.F90 b/src/global.F90 index 2abbe4212..bb7bf50ef 100644 --- a/src/global.F90 +++ b/src/global.F90 @@ -5,9 +5,9 @@ module global use constants use dict_header, only: DictCharInt, DictIntInt use geometry_header, only: Cell, Universe, Lattice, LatticeContainer - use macroxs_header, only: MacroXSContainer use material_header, only: Material use mesh_header, only: RegularMesh + use mgxs_header, only: Mgxs, MgxsContainer use nuclide_header use plot_header, only: ObjectPlot use sab_header, only: SAlphaBeta @@ -86,7 +86,7 @@ module global ! CONTINUOUS-ENERGY CROSS SECTION RELATED VARIABLES ! Cross section arrays - type(NuclideCE), allocatable, target :: nuclides(:) ! Nuclide cross-sections + type(Nuclide), allocatable, target :: nuclides(:) ! Nuclide cross-sections type(SAlphaBeta), allocatable, target :: sab_tables(:) ! S(a,b) tables integer :: n_sab_tables ! Number of S(a,b) thermal scattering tables @@ -104,14 +104,18 @@ module global ! What to assume for expanding natural elements integer :: default_expand = ENDF_BVII1 + ! Total amount of nuclide ZAID and dictionary of nuclide ZAID and index + integer(8) :: n_nuc_zaid_total + type(DictIntInt) :: nuc_zaid_dict + ! ============================================================================ ! MULTI-GROUP CROSS SECTION RELATED VARIABLES ! Cross section arrays - type(NuclideMGContainer), allocatable, target :: nuclides_MG(:) + type(MgxsContainer), allocatable, target :: nuclides_MG(:) ! Cross section caches - type(MacroXSContainer), target, allocatable :: macro_xs(:) + type(MgxsContainer), target, allocatable :: macro_xs(:) ! Number of energy groups integer :: energy_groups diff --git a/src/hdf5_interface.F90 b/src/hdf5_interface.F90 index 01e50d983..ce934baa4 100644 --- a/src/hdf5_interface.F90 +++ b/src/hdf5_interface.F90 @@ -64,14 +64,28 @@ module hdf5_interface module procedure read_tally_result_2D end interface read_dataset + interface read_attribute + module procedure read_attribute_double + module procedure read_attribute_double_1D + module procedure read_attribute_double_2D + module procedure read_attribute_integer + module procedure read_attribute_integer_1D + module procedure read_attribute_integer_2D + module procedure read_attribute_string + end interface read_attribute + public :: write_dataset public :: read_dataset + public :: read_attribute public :: file_create public :: file_open public :: file_close public :: create_group public :: open_group public :: close_group + public :: open_dataset + public :: close_dataset + public :: get_shape public :: write_attribute_string contains @@ -243,6 +257,44 @@ contains end if end subroutine close_group +!=============================================================================== +! OPEN_DATASET opens an existing HDF5 dataset +!=============================================================================== + + function open_dataset(group_id, name) result(dataset_id) + integer(HID_T), intent(in) :: group_id + character(*), intent(in) :: name ! name of dataset + integer(HID_T) :: dataset_id + + logical :: exists ! does the dataset exist + integer :: hdf5_err ! HDF5 error code + + ! Check if group exists + call h5ltpath_valid_f(group_id, trim(name), .true., exists, hdf5_err) + + ! open group if it exists + if (exists) then + call h5dopen_f(group_id, trim(name), dataset_id, hdf5_err) + else + call fatal_error("The dataset '" // trim(name) // "' does not exist.") + end if + end function open_dataset + +!=============================================================================== +! CLOSE_GROUP closes HDF5 temp_group +!=============================================================================== + + subroutine close_dataset(dataset_id) + integer(HID_T), intent(inout) :: dataset_id + + integer :: hdf5_err ! HDF5 error code + + call h5dclose_f(dataset_id, hdf5_err) + if (hdf5_err < 0) then + call fatal_error("Unable to close HDF5 dataset.") + end if + end subroutine close_dataset + !=============================================================================== ! WRITE_DOUBLE writes double precision scalar data !=============================================================================== @@ -293,19 +345,27 @@ contains ! READ_DOUBLE reads double precision scalar data !=============================================================================== - subroutine read_double(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name for data - real(8), intent(inout), target :: buffer ! read data to here - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double(buffer, obj_id, name, indep) + real(8), target, intent(inout) :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O - integer :: hdf5_err - integer :: data_xfer_mode + integer :: hdf5_err + integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle - type(c_ptr) :: f_ptr + integer(HID_T) :: dset_id + type(c_ptr) :: f_ptr + + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) + else + dset_id = obj_id + end if ! Set up collective vs. independent I/O data_xfer_mode = H5FD_MPIO_COLLECTIVE_F @@ -313,21 +373,20 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) end if - call h5dclose_f(dset, hdf5_err) + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_double !=============================================================================== @@ -396,35 +455,46 @@ contains ! READ_DOUBLE_1D reads double precision 1-D array data !=============================================================================== - subroutine read_double_1D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_1D(buffer, obj_id, name, indep) + real(8), target, intent(inout) :: buffer(:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(1) - dims(:) = shape(buffer) - if (present(indep)) then - call read_double_1D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_double_1D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_double_1D_explicit(dset_id, dims, buffer, indep) + else + call read_double_1D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_double_1D - subroutine read_double_1D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(1) - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(dims(1)) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_1D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(1) + real(8), target, intent(inout) :: buffer(dims(1)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -433,21 +503,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_double_1D_explicit !=============================================================================== @@ -516,35 +583,46 @@ contains ! READ_DOUBLE_2D reads double precision 2-D array data !=============================================================================== - subroutine read_double_2D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_2D(buffer, obj_id, name, indep) + real(8), target, intent(inout) :: buffer(:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(2) - dims(:) = shape(buffer) - if (present(indep)) then - call read_double_2D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_double_2D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_double_2D_explicit(dset_id, dims, buffer, indep) + else + call read_double_2D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_double_2D - subroutine read_double_2D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(2) - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(dims(1),dims(2)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_2D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(2) + real(8), target, intent(inout) :: buffer(dims(1),dims(2)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -553,21 +631,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_double_2D_explicit !=============================================================================== @@ -636,35 +711,46 @@ contains ! READ_DOUBLE_3D reads double precision 3-D array data !=============================================================================== - subroutine read_double_3D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(:,:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_3D(buffer, obj_id, name, indep) + real(8), target, intent(inout) :: buffer(:,:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(3) - dims(:) = shape(buffer) - if (present(indep)) then - call read_double_3D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_double_3D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_double_3D_explicit(dset_id, dims, buffer, indep) + else + call read_double_3D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_double_3D - subroutine read_double_3D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(3) - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(dims(1),dims(2),dims(3)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_3D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(3) + real(8), target, intent(inout) :: buffer(dims(1),dims(2),dims(3)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -673,21 +759,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_double_3D_explicit !=============================================================================== @@ -756,35 +839,46 @@ contains ! READ_DOUBLE_4D reads double precision 4-D array data !=============================================================================== - subroutine read_double_4D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(:,:,:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_4D(buffer, obj_id, name, indep) + real(8), target, intent(inout) :: buffer(:,:,:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(4) - dims(:) = shape(buffer) - if (present(indep)) then - call read_double_4D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_double_4D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_double_4D_explicit(dset_id, dims, buffer, indep) + else + call read_double_4D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_double_4D - subroutine read_double_4D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(4) - character(*), intent(in) :: name ! name of data - real(8), intent(inout), target :: buffer(dims(1),dims(2),dims(3),dims(4)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_double_4D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(4) + real(8), target, intent(inout) :: buffer(dims(1),dims(2),dims(3),dims(4)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -793,21 +887,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_double_4D_explicit !=============================================================================== @@ -860,19 +951,27 @@ contains ! READ_INTEGER reads integer precision scalar data !=============================================================================== - subroutine read_integer(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name for data - integer, intent(inout), target :: buffer ! read data to here - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer(buffer, obj_id, name, indep) + integer, target, intent(inout) :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O - integer :: hdf5_err - integer :: data_xfer_mode + integer :: hdf5_err + integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle - type(c_ptr) :: f_ptr + integer(HID_T) :: dset_id + type(c_ptr) :: f_ptr + + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) + else + dset_id = obj_id + end if ! Set up collective vs. independent I/O data_xfer_mode = H5FD_MPIO_COLLECTIVE_F @@ -880,21 +979,20 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) end if - call h5dclose_f(dset, hdf5_err) + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_integer !=============================================================================== @@ -963,35 +1061,46 @@ contains ! READ_INTEGER_1D reads integer precision 1-D array data !=============================================================================== - subroutine read_integer_1D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_1D(buffer, obj_id, name, indep) + integer, target, intent(inout) :: buffer(:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(1) - dims(:) = shape(buffer) - if (present(indep)) then - call read_integer_1D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_integer_1D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_integer_1D_explicit(dset_id, dims, buffer, indep) + else + call read_integer_1D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_integer_1D - subroutine read_integer_1D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(1) - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(dims(1)) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_1D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(1) + integer, target, intent(inout) :: buffer(dims(1)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -1000,21 +1109,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_integer_1D_explicit !=============================================================================== @@ -1083,35 +1189,46 @@ contains ! READ_INTEGER_2D reads integer precision 2-D array data !=============================================================================== - subroutine read_integer_2D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_2D(buffer, obj_id, name, indep) + integer, target, intent(inout) :: buffer(:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(2) - dims(:) = shape(buffer) - if (present(indep)) then - call read_integer_2D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_integer_2D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_integer_2D_explicit(dset_id, dims, buffer, indep) + else + call read_integer_2D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_integer_2D - subroutine read_integer_2D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(2) - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(dims(1),dims(2)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_2D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(2) + integer, target, intent(inout) :: buffer(dims(1),dims(2)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -1120,21 +1237,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_integer_2D_explicit !=============================================================================== @@ -1203,35 +1317,46 @@ contains ! READ_INTEGER_3D reads integer precision 3-D array data !=============================================================================== - subroutine read_integer_3D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(:,:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_3D(buffer, obj_id, name, indep) + integer, target, intent(inout) :: buffer(:,:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(3) - dims(:) = shape(buffer) - if (present(indep)) then - call read_integer_3D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_integer_3D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_integer_3D_explicit(dset_id, dims, buffer, indep) + else + call read_integer_3D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_integer_3D - subroutine read_integer_3D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(3) - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(dims(1),dims(2),dims(3)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_3D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(3) + integer, target, intent(inout) :: buffer(dims(1),dims(2),dims(3)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -1240,21 +1365,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_integer_3D_explicit !=============================================================================== @@ -1323,35 +1445,46 @@ contains ! READ_INTEGER_4D reads integer precision 4-D array data !=============================================================================== - subroutine read_integer_4D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(:,:,:,:) ! data to write - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_4D(buffer, obj_id, name, indep) + integer, target, intent(inout) :: buffer(:,:,:,:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(4) - dims(:) = shape(buffer) - if (present(indep)) then - call read_integer_4D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_integer_4D_explicit(group_id, dims, name, buffer) + dset_id = obj_id end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_integer_4D_explicit(dset_id, dims, buffer, indep) + else + call read_integer_4D_explicit(dset_id, dims, buffer) + end if + + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_integer_4D - subroutine read_integer_4D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(4) - character(*), intent(in) :: name ! name of data - integer, intent(inout), target :: buffer(dims(1),dims(2),dims(3),dims(4)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_integer_4D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(4) + integer, target, intent(inout) :: buffer(dims(1),dims(2),dims(3),dims(4)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle type(c_ptr) :: f_ptr ! Set up collective vs. independent I/O @@ -1360,21 +1493,18 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5dread_f(dset_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) end if - - call h5dclose_f(dset, hdf5_err) end subroutine read_integer_4D_explicit !=============================================================================== @@ -1427,19 +1557,27 @@ contains ! READ_LONG reads long integer scalar data !=============================================================================== - subroutine read_long(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name for data - integer(8), intent(inout), target :: buffer ! read data to here - logical, intent(in), optional :: indep ! independent I/O + subroutine read_long(buffer, obj_id, name, indep) + integer(8), target, intent(inout) :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O - integer :: hdf5_err - integer :: data_xfer_mode + integer :: hdf5_err + integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle - type(c_ptr) :: f_ptr + integer(HID_T) :: dset_id + type(c_ptr) :: f_ptr + + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) + else + dset_id = obj_id + end if ! Set up collective vs. independent I/O data_xfer_mode = H5FD_MPIO_COLLECTIVE_F @@ -1447,21 +1585,20 @@ contains if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - call h5dopen_f(group_id, trim(name), dset, hdf5_err) f_ptr = c_loc(buffer) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, hdf5_integer8_t, f_ptr, hdf5_err, xfer_prp=plist) + call h5dread_f(dset_id, hdf5_integer8_t, f_ptr, hdf5_err, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, hdf5_integer8_t, f_ptr, hdf5_err) + call h5dread_f(dset_id, hdf5_integer8_t, f_ptr, hdf5_err) end if - call h5dclose_f(dset, hdf5_err) + if (present(name)) call h5dclose_f(dset_id, hdf5_err) end subroutine read_long !=============================================================================== @@ -1529,37 +1666,42 @@ contains ! READ_STRING reads string data !=============================================================================== - subroutine read_string(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name ! name for data - character(*), intent(inout), target :: buffer ! read data to here - logical, intent(in), optional :: indep ! independent I/O + subroutine read_string(buffer, obj_id, name, indep) + character(*), target, intent(inout) :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle - integer(HID_T) :: dspace ! data or file space handle + integer(HID_T) :: dset_id + integer(HID_T) :: space_id integer(HID_T) :: filetype integer(HID_T) :: memtype integer(SIZE_T) :: size integer(SIZE_T) :: n type(c_ptr) :: f_ptr + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) + else + dset_id = obj_id + end if + ! Set up collective vs. independent I/O data_xfer_mode = H5FD_MPIO_COLLECTIVE_F if (present(indep)) then if (indep) data_xfer_mode = H5FD_MPIO_INDEPENDENT_F end if - ! Get dataset and dataspace - call h5dopen_f(group_id, trim(name), dset, hdf5_err) - call h5dget_space_f(dset, dspace, hdf5_err) + ! Get dataspace + call h5dget_space_f(dset_id, space_id, hdf5_err) ! Make sure buffer is large enough - call h5dget_type_f(dset, filetype, hdf5_err) + call h5dget_type_f(dset_id, filetype, hdf5_err) call h5tget_size_f(filetype, size, hdf5_err) if (size > len(buffer) + 1) then call fatal_error("Character buffer is not long enough to & @@ -1574,20 +1716,21 @@ contains ! Get pointer to start of string f_ptr = c_loc(buffer(1:1)) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, memtype, f_ptr, hdf5_err, mem_space_id=dspace, & - xfer_prp=plist) + call h5dread_f(dset_id, memtype, f_ptr, hdf5_err, & + mem_space_id=space_id, xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, memtype, f_ptr, hdf5_err, mem_space_id=dspace) + call h5dread_f(dset_id, memtype, f_ptr, hdf5_err, mem_space_id=space_id) end if - call h5dclose_f(dset, hdf5_err) - call h5sclose_f(dspace, hdf5_err) + if (present(name)) call h5dclose_f(dset_id, hdf5_err) + + call h5sclose_f(space_id, hdf5_err) call h5tclose_f(filetype, hdf5_err) call h5tclose_f(memtype, hdf5_err) end subroutine read_string @@ -1674,36 +1817,45 @@ contains ! READ_STRING_1D reads string 1-D array data !=============================================================================== - subroutine read_string_1D(group_id, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - character(*), intent(in) :: name - character(*), intent(inout), target :: buffer(:) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_string_1D(buffer, obj_id, name, indep) + character(*), target, intent(inout) :: buffer(:) + integer(HID_T), intent(in) :: obj_id + character(*), optional, intent(in) :: name + logical, optional, intent(in) :: indep ! independent I/O + integer :: hdf5_err + integer(HID_T) :: dset_id integer(HSIZE_T) :: dims(1) - dims(:) = shape(buffer) - if (present(indep)) then - call read_string_1D_explicit(group_id, dims, name, buffer, indep) + ! If 'name' argument is passed, obj_id is interpreted to be a group and + ! 'name' is the name of the dataset we should read from + if (present(name)) then + call h5dopen_f(obj_id, trim(name), dset_id, hdf5_err) else - call read_string_1D_explicit(group_id, dims, name, buffer) + dset_id = obj_id + end if + + dims(:) = shape(buffer) + + if (present(indep)) then + call read_string_1D_explicit(dset_id, dims, buffer, indep) + else + call read_string_1D_explicit(dset_id, dims, buffer) end if end subroutine read_string_1D - subroutine read_string_1D_explicit(group_id, dims, name, buffer, indep) - integer(HID_T), intent(in) :: group_id - integer(HSIZE_T), intent(in) :: dims(1) - character(*), intent(in) :: name - character(*), intent(inout), target :: buffer(dims(1)) - logical, intent(in), optional :: indep ! independent I/O + subroutine read_string_1D_explicit(dset_id, dims, buffer, indep) + integer(HID_T), intent(in) :: dset_id + integer(HSIZE_T), intent(in) :: dims(1) + character(*), target, intent(inout) :: buffer(dims(1)) + logical, optional, intent(in) :: indep ! independent I/O integer :: hdf5_err integer :: data_xfer_mode #ifdef PHDF5 integer(HID_T) :: plist ! property list #endif - integer(HID_T) :: dset ! data set handle - integer(HID_T) :: dspace ! data or file space handle + integer(HID_T) :: space_id integer(HID_T) :: filetype integer(HID_T) :: memtype integer(SIZE_T) :: size @@ -1717,11 +1869,10 @@ contains end if ! Get dataset and dataspace - call h5dopen_f(group_id, trim(name), dset, hdf5_err) - call h5dget_space_f(dset, dspace, hdf5_err) + call h5dget_space_f(dset_id, space_id, hdf5_err) ! Make sure buffer is large enough - call h5dget_type_f(dset, filetype, hdf5_err) + call h5dget_type_f(dset_id, filetype, hdf5_err) call h5tget_size_f(filetype, size, hdf5_err) if (size > len(buffer(1)) + 1) then call fatal_error("Character buffer is not long enough to & @@ -1736,20 +1887,19 @@ contains ! Get pointer to start of string f_ptr = c_loc(buffer(1)(1:1)) - if (using_mpio_device(group_id)) then + if (using_mpio_device(dset_id)) then #ifdef PHDF5 call h5pcreate_f(H5P_DATASET_XFER_F, plist, hdf5_err) call h5pset_dxpl_mpio_f(plist, data_xfer_mode, hdf5_err) - call h5dread_f(dset, memtype, f_ptr, hdf5_err, mem_space_id=dspace, & + call h5dread_f(dset_id, memtype, f_ptr, hdf5_err, mem_space_id=space_id, & xfer_prp=plist) call h5pclose_f(plist, hdf5_err) #endif else - call h5dread_f(dset, memtype, f_ptr, hdf5_err, mem_space_id=dspace) + call h5dread_f(dset_id, memtype, f_ptr, hdf5_err, mem_space_id=space_id) end if - call h5dclose_f(dset, hdf5_err) - call h5sclose_f(dspace, hdf5_err) + call h5sclose_f(space_id, hdf5_err) call h5tclose_f(filetype, hdf5_err) call h5tclose_f(memtype, hdf5_err) end subroutine read_string_1D_explicit @@ -1893,6 +2043,254 @@ contains call h5dclose_f(dset, hdf5_err) end subroutine read_tally_result_2D_explicit + subroutine read_attribute_double(buffer, obj_id, name) + real(8), intent(inout), target :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: attr_id + type(c_ptr) :: f_ptr + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_double + + subroutine read_attribute_double_1D(buffer, obj_id, name) + real(8), target, allocatable, intent(inout) :: buffer(:) + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: space_id + integer(HID_T) :: attr_id + integer(HSIZE_T) :: dims(1) + integer(HSIZE_T) :: maxdims(1) + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + + if (allocated(buffer)) then + dims(:) = shape(buffer) + else + call h5aget_space_f(attr_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + allocate(buffer(dims(1))) + call h5sclose_f(space_id, hdf5_err) + end if + + call read_attribute_double_1D_explicit(attr_id, dims, buffer) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_double_1D + + subroutine read_attribute_double_1D_explicit(attr_id, dims, buffer) + integer(HID_T), intent(in) :: attr_id + integer(HSIZE_T), intent(in) :: dims(1) + real(8), target, intent(inout) :: buffer(dims(1)) + + integer :: hdf5_err + type(c_ptr) :: f_ptr + + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + end subroutine read_attribute_double_1D_explicit + + subroutine read_attribute_double_2D(buffer, obj_id, name) + real(8), target, allocatable, intent(inout) :: buffer(:,:) + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: space_id + integer(HID_T) :: attr_id + integer(HSIZE_T) :: dims(2) + integer(HSIZE_T) :: maxdims(2) + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + + if (allocated(buffer)) then + dims(:) = shape(buffer) + else + call h5aget_space_f(attr_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + allocate(buffer(dims(1), dims(2))) + call h5sclose_f(space_id, hdf5_err) + end if + + call read_attribute_double_2D_explicit(attr_id, dims, buffer) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_double_2D + + subroutine read_attribute_double_2D_explicit(attr_id, dims, buffer) + integer(HID_T), intent(in) :: attr_id + integer(HSIZE_T), intent(in) :: dims(2) + real(8), target, intent(inout) :: buffer(dims(1),dims(2)) + + integer :: hdf5_err + type(c_ptr) :: f_ptr + + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_DOUBLE, f_ptr, hdf5_err) + end subroutine read_attribute_double_2D_explicit + + subroutine read_attribute_integer(buffer, obj_id, name) + integer, intent(inout), target :: buffer + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: attr_id + type(c_ptr) :: f_ptr + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_integer + + subroutine read_attribute_integer_1D(buffer, obj_id, name) + integer, target, allocatable, intent(inout) :: buffer(:) + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: space_id + integer(HID_T) :: attr_id + integer(HSIZE_T) :: dims(1) + integer(HSIZE_T) :: maxdims(1) + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + + if (allocated(buffer)) then + dims(:) = shape(buffer) + else + call h5aget_space_f(attr_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + allocate(buffer(dims(1))) + call h5sclose_f(space_id, hdf5_err) + end if + + call read_attribute_integer_1D_explicit(attr_id, dims, buffer) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_integer_1D + + subroutine read_attribute_integer_1D_explicit(attr_id, dims, buffer) + integer(HID_T), intent(in) :: attr_id + integer(HSIZE_T), intent(in) :: dims(1) + integer, target, intent(inout) :: buffer(dims(1)) + + integer :: hdf5_err + type(c_ptr) :: f_ptr + + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + end subroutine read_attribute_integer_1D_explicit + + subroutine read_attribute_integer_2D(buffer, obj_id, name) + integer, target, allocatable, intent(inout) :: buffer(:,:) + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name + + integer :: hdf5_err + integer(HID_T) :: space_id + integer(HID_T) :: attr_id + integer(HSIZE_T) :: dims(2) + integer(HSIZE_T) :: maxdims(2) + + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + + if (allocated(buffer)) then + dims(:) = shape(buffer) + else + call h5aget_space_f(attr_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + allocate(buffer(dims(1), dims(2))) + call h5sclose_f(space_id, hdf5_err) + end if + + call read_attribute_integer_2D_explicit(attr_id, dims, buffer) + call h5aclose_f(attr_id, hdf5_err) + end subroutine read_attribute_integer_2D + + subroutine read_attribute_integer_2D_explicit(attr_id, dims, buffer) + integer(HID_T), intent(in) :: attr_id + integer(HSIZE_T), intent(in) :: dims(2) + integer, target, intent(inout) :: buffer(dims(1),dims(2)) + + integer :: hdf5_err + type(c_ptr) :: f_ptr + + f_ptr = c_loc(buffer) + call h5aread_f(attr_id, H5T_NATIVE_INTEGER, f_ptr, hdf5_err) + end subroutine read_attribute_integer_2D_explicit + + subroutine read_attribute_string(buffer, obj_id, name) + character(*), intent(inout), target :: buffer ! read data to here + integer(HID_T), intent(in) :: obj_id + character(*), intent(in) :: name ! name for data + + integer :: hdf5_err + integer(HID_T) :: attr_id ! data set handle + integer(HID_T) :: filetype + integer(HID_T) :: memtype + integer(SIZE_T) :: i + integer(SIZE_T) :: size + character(kind=C_CHAR), allocatable, target :: temp_buffer(:) + type(c_ptr) :: f_ptr + + ! Get dataset and dataspace + call h5aopen_f(obj_id, trim(name), attr_id, hdf5_err) + + ! Make sure buffer is large enough + call h5aget_type_f(attr_id, filetype, hdf5_err) + call h5tget_size_f(filetype, size, hdf5_err) + allocate(temp_buffer(size)) + if (size > len(buffer)) then + call fatal_error("Character buffer is not long enough to & + &read HDF5 string.") + end if + + ! Get datatype in memory based on Fortran character + call h5tcopy_f(H5T_C_S1, memtype, hdf5_err) + call h5tset_size_f(memtype, size + 1, hdf5_err) + + ! Get pointer to start of string + f_ptr = c_loc(temp_buffer(1)) + + call h5aread_f(attr_id, memtype, f_ptr, hdf5_err) + buffer = '' + do i = 1, size + buffer(i:i) = temp_buffer(i) + end do + deallocate(temp_buffer) + + call h5aclose_f(attr_id, hdf5_err) + call h5tclose_f(filetype, hdf5_err) + call h5tclose_f(memtype, hdf5_err) + end subroutine read_attribute_string + + subroutine get_shape(obj_id, dims) + integer(HID_T), intent(in) :: obj_id + integer(HSIZE_T), intent(out) :: dims(:) + + integer :: hdf5_err + integer :: type + integer(HID_T) :: space_id + integer(HSIZE_T) :: maxdims(size(dims)) + + call h5iget_type_f(obj_id, type, hdf5_err) + if (type == H5I_DATASET_F) then + call h5dget_space_f(obj_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + call h5sclose_f(space_id, hdf5_err) + elseif (type == H5I_ATTR_F) then + call h5aget_space_f(obj_id, space_id, hdf5_err) + call h5sget_simple_extent_dims_f(space_id, dims, maxdims, hdf5_err) + call h5sclose_f(space_id, hdf5_err) + end if + end subroutine get_shape + function using_mpio_device(obj_id) result(mpio) integer(HID_T), intent(in) :: obj_id logical :: mpio diff --git a/src/initialize.F90 b/src/initialize.F90 index 52853f72f..8c4eabbc1 100644 --- a/src/initialize.F90 +++ b/src/initialize.F90 @@ -1,6 +1,6 @@ module initialize - use ace, only: read_ace_xs, same_nuclide_list + use ace, only: read_ace_xs use bank_header, only: Bank use constants use dict_header, only: DictIntInt, ElemKeyValueII @@ -16,7 +16,7 @@ module initialize hdf5_tallyresult_t, hdf5_integer8_t use input_xml, only: read_input_xml, cells_in_univ_dict, read_plots_xml use material_header, only: Material - use mgxs_data, only: read_mgxs, same_NuclideMG_list, create_macro_xs + use mgxs_data, only: read_mgxs, create_macro_xs use output, only: title, header, print_version, write_message, & print_usage, write_xs_summary, print_plot use random_lcg, only: initialize_prng @@ -122,13 +122,6 @@ contains end if call time_read_xs%stop() - ! Create linked lists for multiple instances of the same nuclide - if (run_CE) then - call same_nuclide_list() - else - call same_nuclidemg_list() - end if - ! Construct information needed for nuclear data if (run_CE) then ! Construct unionized or log energy grid for cross-sections @@ -382,7 +375,7 @@ contains ! Check what type of file this is file_id = file_open(argv(i), 'r', parallel=.true.) - call read_dataset(file_id, 'filetype', filetype) + call read_dataset(filetype, file_id, 'filetype') call file_close(file_id) ! Set path and flag for type of run @@ -408,7 +401,7 @@ contains ! Check file type is a source file file_id = file_open(argv(i), 'r', parallel=.true.) - call read_dataset(file_id, 'filetype', filetype) + call read_dataset(filetype, file_id, 'filetype') call file_close(file_id) if (filetype /= 'source') then call fatal_error("Second file after restart flag must be a & diff --git a/src/input_xml.F90 b/src/input_xml.F90 index 03ef8dcbc..e2add2027 100644 --- a/src/input_xml.F90 +++ b/src/input_xml.F90 @@ -92,18 +92,22 @@ contains type(NodeList), pointer :: node_scat_list => null() type(NodeList), pointer :: node_source_list => null() - ! Display output message - call write_message("Reading settings XML file...", 5) - ! Check if settings.xml exists filename = trim(path_input) // "settings.xml" inquire(FILE=filename, EXIST=file_exists) if (.not. file_exists) then - call fatal_error("Settings XML file '" // trim(filename) // "' does not & - &exist! In order to run OpenMC, you first need a set of input files;& - & at a minimum, this includes settings.xml, geometry.xml, and & - &materials.xml. Please consult the user's guide at & - &http://mit-crpg.github.io/openmc for further information.") + if (run_mode /= MODE_PLOTTING) then + call fatal_error("Settings XML file '" // trim(filename) // "' does & + ¬ exist! In order to run OpenMC, you first need a set of input & + &files; at a minimum, this includes settings.xml, geometry.xml, & + &and materials.xml. Please consult the user's guide at & + &http://mit-crpg.github.io/openmc for further information.") + else + ! The settings.xml file is optional if we just want to make a plot. + return + end if + else + call write_message("Reading settings XML file...", 5) end if ! Parse settings.xml file @@ -149,7 +153,7 @@ contains else call get_environment_variable("OPENMC_MG_CROSS_SECTIONS", env_variable) if (len_trim(env_variable) == 0) then - call fatal_error("No cross_sections.xml file was specified in & + call fatal_error("No mgxs.xml file was specified in & &settings.xml or in the OPENMC_MG_CROSS_SECTIONS environment & &variable. OpenMC needs such a file to identify where to & &find the cross section libraries. Please consult the user's & @@ -169,8 +173,12 @@ contains if (check_for_node(doc, "max_order")) then call get_node_value(doc, "max_order", max_order) else - ! Set to default of largest int, which means to use whatever is contained in library - max_order = huge(0) + ! Set to default of largest int - 1, which means to use whatever is + ! contained in library. + ! This is largest int - 1 because for legendre scattering, a value of + ! 1 is added to the order; adding 1 to huge(0) gets you the largest + ! negative integer, which is not what we want. + max_order = huge(0) - 1 end if else max_order = 0 @@ -1105,6 +1113,8 @@ contains integer :: universe_num integer :: n_cells_in_univ integer :: coeffs_reqd + integer :: i_xmin, i_xmax, i_ymin, i_ymax, i_zmin, i_zmax + real(8) :: xmin, xmax, ymin, ymax, zmin, zmax integer, allocatable :: temp_int_array(:) real(8) :: phi, theta, psi real(8), allocatable :: coeffs(:) @@ -1383,6 +1393,13 @@ contains call fatal_error("No surfaces found in geometry.xml!") end if + xmin = INFINITY + xmax = -INFINITY + ymin = INFINITY + ymax = -INFINITY + zmin = INFINITY + zmax = -INFINITY + ! Allocate cells array allocate(surfaces(n_surfaces)) @@ -1474,10 +1491,28 @@ contains select type(s) type is (SurfaceXPlane) s%x0 = coeffs(1) + + ! Determine outer surfaces + xmin = min(xmin, s % x0) + xmax = max(xmax, s % x0) + if (xmin == s % x0) i_xmin = i + if (xmax == s % x0) i_xmax = i type is (SurfaceYPlane) s%y0 = coeffs(1) + + ! Determine outer surfaces + ymin = min(ymin, s % y0) + ymax = max(ymax, s % y0) + if (ymin == s % y0) i_ymin = i + if (ymax == s % y0) i_ymax = i type is (SurfaceZPlane) s%z0 = coeffs(1) + + ! Determine outer surfaces + zmin = min(zmin, s % z0) + zmax = max(zmax, s % z0) + if (zmin == s % z0) i_zmin = i + if (zmax == s % z0) i_zmax = i type is (SurfacePlane) s%A = coeffs(1) s%B = coeffs(2) @@ -1544,11 +1579,19 @@ contains case ('reflective', 'reflect', 'reflecting') s%bc = BC_REFLECT boundary_exists = .true. + case ('periodic') + s%bc = BC_PERIODIC + boundary_exists = .true. + + ! Check for specification of periodic surface + if (check_for_node(node_surf, "periodic_surface_id")) then + call get_node_value(node_surf, "periodic_surface_id", & + s % i_periodic) + end if case default call fatal_error("Unknown boundary condition '" // trim(word) // & &"' specified on surface " // trim(to_str(s%id))) end select - ! Add surface to dictionary call surface_dict % add_key(s%id, i) end do @@ -1559,6 +1602,67 @@ contains call fatal_error("No boundary conditions were applied to any surfaces!") end if + ! Determine opposite side for periodic boundaries + do i = 1, size(surfaces) + if (surfaces(i) % obj % bc == BC_PERIODIC) then + select type (surf => surfaces(i) % obj) + type is (SurfaceXPlane) + if (surf % i_periodic == NONE) then + if (i == i_xmin) then + surf % i_periodic = i_xmax + elseif (i == i_xmax) then + surf % i_periodic = i_xmin + else + call fatal_error("Periodic boundary condition applied to & + &interior surface.") + end if + else + surf % i_periodic = surface_dict % get_key(surf % i_periodic) + end if + + type is (SurfaceYPlane) + if (surf % i_periodic == NONE) then + if (i == i_ymin) then + surf % i_periodic = i_ymax + elseif (i == i_ymax) then + surf % i_periodic = i_ymin + else + call fatal_error("Periodic boundary condition applied to & + &interior surface.") + end if + else + surf % i_periodic = surface_dict % get_key(surf % i_periodic) + end if + + type is (SurfaceZPlane) + if (surf % i_periodic == NONE) then + if (i == i_zmin) then + surf % i_periodic = i_zmax + elseif (i == i_zmax) then + surf % i_periodic = i_zmin + else + call fatal_error("Periodic boundary condition applied to & + &interior surface.") + end if + else + surf % i_periodic = surface_dict % get_key(surf % i_periodic) + end if + + class default + call fatal_error("Periodic boundary condition applied to & + &non-planar surface.") + end select + + ! Make sure opposite surface is also periodic + associate (surf => surfaces(i) % obj) + if (surfaces(surf % i_periodic) % obj % bc /= BC_PERIODIC) then + call fatal_error("Could not find matching surface for periodic & + &boundary on surface " // trim(to_str(surf % id)) // ".") + end if + end associate + end if + end do + ! ========================================================================== ! READ LATTICES FROM GEOMETRY.XML @@ -1891,21 +1995,23 @@ contains subroutine read_materials_xml() - integer :: i ! loop index for materials - integer :: j ! loop index for nuclides - integer :: k ! loop index for elements - integer :: n ! number of nuclides - integer :: n_sab ! number of sab tables for a material - integer :: n_nuc_ele ! number of nuclides in an element - integer :: index_list ! index in xs_listings array - integer :: index_nuclide ! index in nuclides - integer :: index_sab ! index in sab_tables - real(8) :: val ! value entered for density - real(8) :: temp_dble ! temporary double prec. real - logical :: file_exists ! does materials.xml exist? - logical :: sum_density ! density is taken to be sum of nuclide densities - character(12) :: name ! name of isotope, e.g. 92235.03c - character(12) :: alias ! alias of nuclide, e.g. U-235.03c + integer :: i ! loop index for materials + integer :: j ! loop index for nuclides + integer :: k ! loop index for elements + integer :: n ! number of nuclides + integer :: n_sab ! number of sab tables for a material + integer :: n_nuc_ele ! number of nuclides in an element + integer :: index_list ! index in xs_listings array + integer :: index_nuclide ! index in nuclides + integer :: index_nuc_zaid ! index in nuclide ZAID + integer :: index_sab ! index in sab_tables + real(8) :: val ! value entered for density + real(8) :: temp_dble ! temporary double prec. real + logical :: file_exists ! does materials.xml exist? + logical :: sum_density ! density is taken to be sum of nuclide densities + integer :: zaid ! ZAID of nuclide + character(12) :: name ! name of isotope, e.g. 92235.03c + character(12) :: alias ! alias of nuclide, e.g. U-235.03c character(MAX_WORD_LEN) :: units ! units on density character(MAX_LINE_LEN) :: filename ! absolute path to materials.xml character(MAX_LINE_LEN) :: temp_str ! temporary string when reading @@ -1955,6 +2061,7 @@ contains ! Initialize count for number of nuclides/S(a,b) tables index_nuclide = 0 + index_nuc_zaid = 0 index_sab = 0 do i = 1, n_materials @@ -2095,21 +2202,6 @@ contains end if end if - ! Check enforced isotropic lab scattering - if (check_for_node(node_nuc, "scattering")) then - call get_node_value(node_nuc, "scattering", temp_str) - if (adjustl(to_lower(temp_str)) == "iso-in-lab") then - call list_iso_lab % append(1) - else if (adjustl(to_lower(temp_str)) == "data") then - call list_iso_lab % append(0) - else - call fatal_error("Scattering must be isotropic in lab or follow& - & the ACE file data") - end if - else - call list_iso_lab % append(0) - end if - ! store full name call get_node_value(node_nuc, "name", temp_str) if (check_for_node(node_nuc, "xs")) & @@ -2154,6 +2246,23 @@ contains end if end if + ! Check enforced isotropic lab scattering + if (run_CE) then + if (check_for_node(node_nuc, "scattering")) then + call get_node_value(node_nuc, "scattering", temp_str) + if (adjustl(to_lower(temp_str)) == "iso-in-lab") then + call list_iso_lab % append(1) + else if (adjustl(to_lower(temp_str)) == "data") then + call list_iso_lab % append(0) + else + call fatal_error("Scattering must be isotropic in lab or follow& + & the ACE file data") + end if + else + call list_iso_lab % append(0) + end if + end if + ! store full name call get_node_value(node_nuc, "name", temp_str) if (check_for_node(node_nuc, "xs")) & @@ -2248,23 +2357,25 @@ contains n_nuc_ele = list_names % size() - n_nuc_ele ! Check enforced isotropic lab scattering - if (check_for_node(node_ele, "scattering")) then - call get_node_value(node_ele, "scattering", temp_str) - else - temp_str = "data" - end if - - ! Set ace or iso-in-lab scattering for each nuclide in element - do k = 1, n_nuc_ele - if (adjustl(to_lower(temp_str)) == "iso-in-lab") then - call list_iso_lab % append(1) - else if (adjustl(to_lower(temp_str)) == "data") then - call list_iso_lab % append(0) + if (run_CE) then + if (check_for_node(node_ele, "scattering")) then + call get_node_value(node_ele, "scattering", temp_str) else - call fatal_error("Scattering must be isotropic in lab or follow& - & the ACE file data") + temp_str = "data" end if - end do + + ! Set ace or iso-in-lab scattering for each nuclide in element + do k = 1, n_nuc_ele + if (adjustl(to_lower(temp_str)) == "iso-in-lab") then + call list_iso_lab % append(1) + else if (adjustl(to_lower(temp_str)) == "data") then + call list_iso_lab % append(0) + else + call fatal_error("Scattering must be isotropic in lab or follow& + & the ACE file data") + end if + end do + end if end do NATURAL_ELEMENTS @@ -2300,6 +2411,7 @@ contains index_list = xs_listing_dict % get_key(to_lower(name)) name = xs_listings(index_list) % name alias = xs_listings(index_list) % alias + zaid = xs_listings(index_list) % zaid ! If this nuclide hasn't been encountered yet, we need to add its name ! and alias to the nuclide_dict @@ -2313,6 +2425,12 @@ contains mat % nuclide(j) = nuclide_dict % get_key(to_lower(name)) end if + ! Construct dict of nuclide zaid + if (.not. nuc_zaid_dict % has_key(zaid)) then + index_nuc_zaid = index_nuc_zaid + 1 + call nuc_zaid_dict % add_key(zaid, index_nuc_zaid) + end if + ! Copy name and atom/weight percent mat % names(j) = name mat % atom_density(j) = list_density % get_item(j) @@ -2407,6 +2525,7 @@ contains ! Set total number of nuclides and S(a,b) tables n_nuclides_total = index_nuclide n_sab_tables = index_sab + n_nuc_zaid_total = index_nuc_zaid ! Close materials XML file call close_xmldoc(doc) @@ -2838,11 +2957,15 @@ contains allocate(t % filters(j) % real_bins(n_words)) call get_node_array(node_filt, "bins", t % filters(j) % real_bins) + ! We can save tallying time if we know that the tally bins + ! match the energy group structure. In that case, the matching bin + ! index is simply the group (after flipping for the different + ! ordering of the library and tallying systems). if (.not. run_CE) then - if (n_words /= energy_groups + 1) then - t % energy_matches_groups = .false. - else if (all(t % filters(j) % real_bins == energy_bins)) then - t % energy_matches_groups = .false. + if (n_words == energy_groups + 1) then + if (all(t % filters(j) % real_bins == & + energy_bins(energy_groups + 1:1:-1))) & + t % energy_matches_groups = .true. end if end if @@ -2857,11 +2980,15 @@ contains allocate(t % filters(j) % real_bins(n_words)) call get_node_array(node_filt, "bins", t % filters(j) % real_bins) + ! We can save tallying time if we know that the tally bins + ! match the energy group structure. In that case, the matching bin + ! index is simply the group (after flipping for the different + ! ordering of the library and tallying systems). if (.not. run_CE) then - if (n_words /= energy_groups + 1) then - t % energy_matches_groups = .false. - else if (all(t % filters(j) % real_bins == energy_bins)) then - t % energy_matches_groups = .false. + if (n_words == energy_groups + 1) then + if (all(t % filters(j) % real_bins == & + energy_bins(energy_groups + 1:1:-1))) & + t % energyout_matches_groups = .true. end if end if @@ -3320,27 +3447,22 @@ contains case ('nu-scatter') t % score_bins(j) = SCORE_NU_SCATTER - ! Set tally estimator to analog - t % estimator = ESTIMATOR_ANALOG - case ('scatter-n') - if (n_order == 0) then - t % score_bins(j) = SCORE_SCATTER - else - t % score_bins(j) = SCORE_SCATTER_N - ! Set tally estimator to analog + ! Set tally estimator to analog for CE mode + ! (MG mode has all data available without a collision being + ! necessary) + if (run_CE) then t % estimator = ESTIMATOR_ANALOG end if + + case ('scatter-n') + t % score_bins(j) = SCORE_SCATTER_N t % moment_order(j) = n_order + t % estimator = ESTIMATOR_ANALOG case ('nu-scatter-n') - ! Set tally estimator to analog - t % estimator = ESTIMATOR_ANALOG - if (n_order == 0) then - t % score_bins(j) = SCORE_NU_SCATTER - else - t % score_bins(j) = SCORE_NU_SCATTER_N - end if + t % score_bins(j) = SCORE_NU_SCATTER_N t % moment_order(j) = n_order + t % estimator = ESTIMATOR_ANALOG case ('scatter-pn') t % estimator = ESTIMATOR_ANALOG @@ -3371,18 +3493,12 @@ contains j = j + n_bins - 1 case('transport') - t % score_bins(j) = SCORE_TRANSPORT - - ! Set tally estimator to analog - t % estimator = ESTIMATOR_ANALOG - case ('diffusion') - call fatal_error("Diffusion score no longer supported for tallies, & + call fatal_error("Transport score no longer supported for tallies, & &please remove") - case ('n1n') - t % score_bins(j) = SCORE_N_1N - ! Set tally estimator to analog - t % estimator = ESTIMATOR_ANALOG + case ('n1n') + call fatal_error("n1n score no longer supported for tallies, & + &please remove") case ('n2n', '(n,2n)') t % score_bins(j) = N_2N @@ -4493,23 +4609,24 @@ contains subroutine read_mg_cross_sections_xml() integer :: i ! loop index - logical :: file_exists ! does cross_sections.xml exist? + logical :: file_exists ! does mgxs.xml exist? type(XsListing), pointer :: listing => null() type(Node), pointer :: doc => null() type(Node), pointer :: node_xsdata => null() type(NodeList), pointer :: node_xsdata_list => null() + real(8), allocatable :: rev_energy_bins(:) - ! Check if cross_sections.xml exists + ! Check if mgxs.xml exists inquire(FILE=path_cross_sections, EXIST=file_exists) if (.not. file_exists) then - ! Could not find cross_sections.xml file + ! Could not find mgxs.xml file call fatal_error("Cross sections XML file '" & // trim(path_cross_sections) // "' does not exist!") end if call write_message("Reading cross sections XML file...", 5) - ! Parse cross_sections.xml file + ! Parse mgxs.xml file call open_xmldoc(doc, path_cross_sections) if (check_for_node(doc, "groups")) then @@ -4519,6 +4636,7 @@ contains call fatal_error("groups element must exist!") end if + allocate(rev_energy_bins(energy_groups + 1)) allocate(energy_bins(energy_groups + 1)) if (check_for_node(doc, "group_structure")) then ! Get neutron group structure @@ -4527,6 +4645,9 @@ contains call fatal_error("group_structures element must exist!") end if + ! First reverse the order of energy_groups + energy_bins = energy_bins(energy_groups + 1:1:-1) + allocate(energy_bin_avg(energy_groups)) do i = 1, energy_groups energy_bin_avg(i) = HALF * (energy_bins(i) + energy_bins(i + 1)) @@ -4540,7 +4661,7 @@ contains ! If not given, estimate them by using average energy in group which is ! assumed to be the midpoint do i = 1, energy_groups - inverse_velocities(i) = & + inverse_velocities(i) = ONE / & (sqrt(TWO * energy_bin_avg(i) / (MASS_NEUTRON_MEV)) * & C_LIGHT * 100.0_8) end do @@ -4553,7 +4674,7 @@ contains ! Allocate xs_listings array if (n_listings == 0) then call fatal_error("At least one element must be present in & - &cross_sections.xml file!") + &mgxs.xml file!") else allocate(xs_listings(n_listings)) end if diff --git a/src/interpolation.F90 b/src/interpolation.F90 deleted file mode 100644 index 5f8787067..000000000 --- a/src/interpolation.F90 +++ /dev/null @@ -1,205 +0,0 @@ -module interpolation - - use constants - use endf_header, only: Tab1 - use search, only: binary_search - use string, only: to_str - - implicit none - - interface interpolate_tab1 - module procedure interpolate_tab1_array, interpolate_tab1_object - end interface interpolate_tab1 - -contains - -!=============================================================================== -! INTERPOLATE_TAB1_ARRAY interpolates a function between two points based on -! particular interpolation scheme. The data needs to be organized as a ENDF TAB1 -! type function containing the interpolation regions, break points, and -! tabulated x's and y's. -!=============================================================================== - - pure function interpolate_tab1_array(data, x, loc_start) result(y) - - real(8), intent(in) :: data(:) ! array of data - real(8), intent(in) :: x ! x value to find y at - integer, intent(in), optional :: loc_start ! starting location in data - real(8) :: y ! y(x) - - integer :: i ! bin in which to interpolate - integer :: j ! index for interpolation region - integer :: loc_0 ! starting location - integer :: n_regions ! number of interpolation regions - integer :: n_points ! number of tabulated values - integer :: interp ! ENDF interpolation scheme - integer :: loc_breakpoints ! location of breakpoints in data - integer :: loc_interp ! location of interpolation schemes in data - integer :: loc_x ! location of x's in data - integer :: loc_y ! location of y's in data - real(8) :: r ! interpolation factor - real(8) :: x0, x1 ! bounding x values - real(8) :: y0, y1 ! bounding y values - - ! determine starting location - if (present(loc_start)) then - loc_0 = loc_start - 1 - else - loc_0 = 0 - end if - - ! determine number of interpolation regions - n_regions = int(data(loc_0 + 1)) - - ! set locations for breakpoints and interpolation schemes - loc_breakpoints = loc_0 + 1 - loc_interp = loc_breakpoints + n_regions - - ! determine number of tabulated values - n_points = int(data(loc_interp + n_regions + 1)) - - ! set locations for x's and y's - loc_x = loc_interp + n_regions + 1 - loc_y = loc_x + n_points - - ! find which bin the abscissa is in -- if the abscissa is outside the - ! tabulated range, the first or last point is chosen, i.e. no interpolation - ! is done outside the energy range - if (x < data(loc_x + 1)) then - y = data(loc_y + 1) - return - elseif (x > data(loc_x + n_points)) then - y = data(loc_y + n_points) - return - else - i = binary_search(data(loc_x + 1:loc_x + n_points), n_points, x) - end if - - ! determine interpolation scheme - if (n_regions == 0) then - interp = LINEAR_LINEAR - elseif (n_regions == 1) then - interp = int(data(loc_interp + 1)) - elseif (n_regions > 1) then - do j = 1, n_regions - if (i < data(loc_breakpoints + j)) then - interp = int(data(loc_interp + j)) - exit - end if - end do - end if - - ! handle special case of histogram interpolation - if (interp == HISTOGRAM) then - y = data(loc_y + i) - return - end if - - ! determine bounding values - x0 = data(loc_x + i) - x1 = data(loc_x + i + 1) - y0 = data(loc_y + i) - y1 = data(loc_y + i + 1) - - ! determine interpolation factor and interpolated value - select case (interp) - case (LINEAR_LINEAR) - r = (x - x0)/(x1 - x0) - y = y0 + r*(y1 - y0) - case (LINEAR_LOG) - r = log(x/x0)/log(x1/x0) - y = y0 + r*(y1 - y0) - case (LOG_LINEAR) - r = (x - x0)/(x1 - x0) - y = y0*exp(r*log(y1/y0)) - case (LOG_LOG) - r = log(x/x0)/log(x1/x0) - y = y0*exp(r*log(y1/y0)) - end select - - end function interpolate_tab1_array - -!=============================================================================== -! INTERPOLATE_TAB1_OBJECT interpolates a function between two points based on -! particular interpolation scheme. The data needs to be organized as a ENDF TAB1 -! type function containing the interpolation regions, break points, and -! tabulated x's and y's. -!=============================================================================== - - pure function interpolate_tab1_object(obj, x) result(y) - - type(Tab1), intent(in) :: obj ! ENDF Tab1 interpolable function - real(8), intent(in) :: x ! x value to find y at - real(8) :: y ! y(x) - - integer :: i ! bin in which to interpolate - integer :: j ! index for interpolation region - integer :: n_regions ! number of interpolation regions - integer :: n_pairs ! number of tabulated values - integer :: interp ! ENDF interpolation scheme - real(8) :: r ! interpolation factor - real(8) :: x0, x1 ! bounding x values - real(8) :: y0, y1 ! bounding y values - - ! determine number of interpolation regions and pairs - n_regions = obj % n_regions - n_pairs = obj % n_pairs - - ! find which bin the abscissa is in -- if the abscissa is outside the - ! tabulated range, the first or last point is chosen, i.e. no interpolation - ! is done outside the energy range - if (x < obj % x(1)) then - y = obj % y(1) - return - elseif (x > obj % x(n_pairs)) then - y = obj % y(n_pairs) - return - else - i = binary_search(obj % x, n_pairs, x) - end if - - ! determine interpolation scheme - if (n_regions == 0) then - interp = LINEAR_LINEAR - elseif (n_regions == 1) then - interp = obj % int(1) - elseif (n_regions > 1) then - do j = 1, n_regions - if (i < obj % nbt(j)) then - interp = obj % int(j) - exit - end if - end do - end if - - ! handle special case of histogram interpolation - if (interp == HISTOGRAM) then - y = obj % y(i) - return - end if - - ! determine bounding values - x0 = obj % x(i) - x1 = obj % x(i + 1) - y0 = obj % y(i) - y1 = obj % y(i + 1) - - ! determine interpolation factor and interpolated value - select case (interp) - case (LINEAR_LINEAR) - r = (x - x0)/(x1 - x0) - y = y0 + r*(y1 - y0) - case (LINEAR_LOG) - r = log(x/x0)/log(x1/x0) - y = y0 + r*(y1 - y0) - case (LOG_LINEAR) - r = (x - x0)/(x1 - x0) - y = y0*exp(r*log(y1/y0)) - case (LOG_LOG) - r = log(x/x0)/log(x1/x0) - y = y0*exp(r*log(y1/y0)) - end select - - end function interpolate_tab1_object - -end module interpolation diff --git a/src/macroxs_header.F90 b/src/macroxs_header.F90 deleted file mode 100644 index 2a1234510..000000000 --- a/src/macroxs_header.F90 +++ /dev/null @@ -1,860 +0,0 @@ -module macroxs_header - - use constants, only: MAX_FILE_LEN, ZERO, ONE, TWO, PI - use list_header, only: ListInt - use material_header, only: material - use math, only: calc_pn, calc_rn, expand_harmonic, find_angle - use nuclide_header - use random_lcg, only: prn - use scattdata_header - - implicit none - -!=============================================================================== -! MACROXS_* contains cached macroscopic cross sections for the material a -! particle is traveling through -!=============================================================================== - - type, abstract :: MacroXS - ! Data Order - integer :: order - - contains - procedure(macroxs_init_), deferred :: init ! initializes object - procedure(macroxs_get_xs_), deferred :: get_xs ! Return xs - ! Sample the outgoing energy from a fission event - procedure(macroxs_sample_fission_), deferred :: sample_fission_energy - ! Sample the outgoing energy and angle from a scatter event - procedure(macroxs_sample_scatter_), deferred :: sample_scatter - ! Calculate the material specific MGXS data from the nuclides - procedure(macroxs_calculate_xs_), deferred :: calculate_xs - end type MacroXS - - abstract interface - subroutine macroxs_init_(this, mat, nuclides, groups, get_kfiss, get_fiss, & - max_order, scatt_type, legendre_mu_points, & - error_code, error_text) - import MacroXS, Material, NuclideMGContainer, MAX_LINE_LEN - class(MacroXS), intent(inout) :: this ! The MacroXS to initialize - type(Material), pointer, intent(in) :: mat ! base material - type(NuclideMGContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from - integer, intent(in) :: groups ! Number of E groups - logical, intent(in) :: get_kfiss ! Should we get kfiss data? - logical, intent(in) :: get_fiss ! Should we get fiss data? - integer, intent(in) :: max_order ! Maximum requested order - integer, intent(in) :: scatt_type ! Legendre or Tabular Scatt? - integer, intent(in) :: legendre_mu_points ! Treat as Leg or Tabular? - integer, intent(inout) :: error_code ! Code signifying error - character(MAX_LINE_LEN), intent(inout) :: error_text ! Error message to print - end subroutine macroxs_init_ - - function macroxs_get_xs_(this, g, xstype, gout, uvw) result(xs) - import MacroXS - class(MacroXS), intent(in) :: this ! The MacroXS to initialize - integer, intent(in) :: g ! Incoming Energy group - character(*) , intent(in) :: xstype ! Cross Section Type - integer, optional, intent(in) :: gout ! Outgoing Energy group - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - real(8) :: xs ! Resultant xs - end function macroxs_get_xs_ - - function macroxs_sample_fission_(this, gin, uvw) result(gout) - import MacroXS - class(MacroXS), intent(in) :: this ! Data to work with - integer, intent(in) :: gin ! Incoming energy group - real(8), intent(in) :: uvw(3) ! Particle Direction - integer :: gout ! Sampled outgoing group - - end function macroxs_sample_fission_ - - subroutine macroxs_sample_scatter_(this, uvw, gin, gout, mu, wgt) - import MacroXS - class(MacroXS), intent(in) :: this - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - integer, intent(in) :: gin ! Incoming neutron group - integer, intent(out) :: gout ! Sampled outgoin group - real(8), intent(out) :: mu ! Sampled change in angle - real(8), intent(inout) :: wgt ! Particle weight - end subroutine macroxs_sample_scatter_ - - subroutine macroxs_calculate_xs_(this, gin, uvw, xs) - import MacroXS, MaterialMacroXS - class(MacroXS), intent(in) :: this - integer, intent(in) :: gin ! Incoming neutron group - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - type(MaterialMacroXS), intent(inout) :: xs - end subroutine macroxs_calculate_xs_ - end interface - - type, extends(MacroXS) :: MacroXSIso - ! Microscopic cross sections - real(8), allocatable :: total(:) ! total cross section - real(8), allocatable :: absorption(:) ! absorption cross section - class(ScattData), allocatable :: scatter ! scattering information - real(8), allocatable :: nu_fission(:) ! nu-fission - real(8), allocatable :: k_fission(:) ! kappa-fission - real(8), allocatable :: fission(:) ! fission x/s - real(8), allocatable :: scattxs(:) ! scattering xs - real(8), allocatable :: chi(:,:) ! fission spectra - - contains - procedure :: init => macroxsiso_init ! inits object - procedure :: get_xs => macroxsiso_get_xs ! Returns xs - procedure :: sample_fission_energy => macroxsiso_sample_fission_energy - procedure :: sample_scatter => macroxsiso_sample_scatter - procedure :: calculate_xs => macroxsiso_calculate_xs - end type MacroXSIso - - type, extends(MacroXS) :: MacroXSAngle - ! Macroscopic cross sections - real(8), allocatable :: total(:,:,:) ! total cross section - real(8), allocatable :: absorption(:,:,:) ! absorption cross section - type(ScattDataContainer), allocatable :: scatter(:,:) ! scattering information - real(8), allocatable :: nu_fission(:,:,:) ! nu-fission - real(8), allocatable :: k_fission(:,:,:) ! kappa-fission - real(8), allocatable :: fission(:,:,:) ! fission x/s - real(8), allocatable :: chi(:,:,:,:) ! fission spectra - real(8), allocatable :: scattxs(:,:,:) ! scattering xs - real(8), allocatable :: polar(:) ! polar angles - real(8), allocatable :: azimuthal(:) ! azimuthal angles - - contains - procedure :: init => macroxsangle_init ! inits object - procedure :: get_xs => macroxsangle_get_xs ! Returns xs - procedure :: sample_fission_energy => macroxsangle_sample_fission_energy - procedure :: sample_scatter => macroxsangle_sample_scatter - procedure :: calculate_xs => macroxsangle_calculate_xs - end type MacroXSAngle - -!=============================================================================== -! MACROXSCONTAINER pointer array for storing MacroXS objects. -!=============================================================================== - - type MacroXSContainer - class(MacroXS), allocatable :: obj - end type MacroXSContainer - -contains - -!=============================================================================== -! MACROXS*_INIT sets the MacroXS Data -!=============================================================================== - - subroutine macroxsiso_init(this, mat, nuclides, groups, get_kfiss, get_fiss, & - max_order, scatt_type, legendre_mu_points, error_code, error_text) - class(MacroXSIso), intent(inout) :: this ! The MacroXS to initialize - type(Material), pointer, intent(in) :: mat ! base material - type(NuclideMGContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from - integer, intent(in) :: groups ! Number of E groups - logical, intent(in) :: get_kfiss ! Should we get kfiss data? - logical, intent(in) :: get_fiss ! Should we get fiss data? - integer, intent(in) :: max_order ! Maximum requested order - integer, intent(in) :: scatt_type ! How is data presented - integer, intent(in) :: legendre_mu_points ! Treat as Leg or Tabular? - integer, intent(inout) :: error_code ! Code signifying error - character(MAX_LINE_LEN), intent(inout) :: error_text ! Error message to print - - integer :: i ! loop index over nuclides - integer :: gin, gout ! group indices - real(8) :: atom_density ! atom density of a nuclide - integer :: imu - real(8) :: norm - integer :: mat_max_order, order, l - real(8), allocatable :: temp_mult(:,:) - real(8), allocatable :: temp_energy(:,:) - real(8), allocatable :: scatt_coeffs(:,:,:) - - ! Initialize error data - error_code = 0 - error_text = '' - - ! If we have tabular only data, then make sure all datasets have same size - if (scatt_type == ANGLE_HISTOGRAM) then - ! Check all scattering data of same size - order = nuclides(mat % nuclide(1)) % obj % order - do i = 2, mat % n_nuclides - if (order /= nuclides(mat % nuclide(i)) % obj % order) then - error_code = 1 - error_text = "All Histogram Scattering Entries Must Be Same Length!" - return - end if - end do - ! Ok, got our order, store it - this % order = order - - ! Allocate stuff for later - allocate(scatt_coeffs(order, groups, groups)) - scatt_coeffs = ZERO - allocate(ScattDataHistogram :: this % scatter) - - else if (scatt_type == ANGLE_TABULAR) then - ! Check all scattering data of same size - order = nuclides(mat % nuclide(1)) % obj % order - do i = 2, mat % n_nuclides - if (order /= nuclides(mat % nuclide(i)) % obj % order) then - error_code = 1 - error_text = "All Tabular Scattering Entries Must Be Same Length!" - return - end if - end do - ! Ok, got our order, store it - this % order = order - - ! Allocate stuff for later - allocate(scatt_coeffs(order, groups, groups)) - scatt_coeffs = ZERO - allocate(ScattDataTabular :: this % scatter) - - else if (scatt_type == ANGLE_LEGENDRE) then - ! Otherwise find the maximum scattering order - ! Need to determine the maximum scattering order of all data in this material - mat_max_order = 0 - do i = 1, mat % n_nuclides - if (nuclides(mat % nuclide(i)) % obj % order > mat_max_order) then - mat_max_order = nuclides(mat % nuclide(i)) % obj % order - end if - end do - - ! Now need to compare this material maximum scattering order with - ! the problem wide max scatt order and use whichever is lower - order = min(mat_max_order, max_order) - this % order = order + 1 - - ! Now we can allocate our scatt_coeffs object accordingly - allocate(scatt_coeffs(order + 1, groups, groups)) - scatt_coeffs = ZERO - if (legendre_mu_points == 1) then - allocate(ScattDataLegendre :: this % scatter) - else - allocate(ScattDataTabular :: this % scatter) - end if - end if - - ! Allocate and initialize data within macro_xs(i_mat) object - allocate(this % total(groups)) - this % total = ZERO - allocate(this % absorption(groups)) - this % absorption = ZERO - if (get_fiss) then - allocate(this % fission(groups)) - this % fission = ZERO - end if - if (get_kfiss) then - allocate(this % k_fission(groups)) - this % k_fission = ZERO - end if - allocate(this % nu_fission(groups)) - this % nu_fission = ZERO - allocate(this % chi(groups, groups)) - this % chi = ZERO - allocate(temp_energy(groups, groups)) - temp_energy = ZERO - allocate(temp_mult(groups, groups)) - temp_mult = ZERO - allocate(this % scattxs(groups)) - - ! Add contribution from each nuclide in material - do i = 1, mat % n_nuclides - ! Copy atom density of nuclide in material - atom_density = mat % atom_density(i) - - ! Perform our operations which depend upon the type - select type(nuc => nuclides(mat % nuclide(i)) % obj) - type is (NuclideIso) - - ! Add contributions to total, absorption, and fission data (if necessary) - this % total = this % total + atom_density * nuc % total - this % absorption = this % absorption + & - atom_density * nuc % absorption - if (nuc % fissionable) then - if (allocated(nuc % chi)) then - do gin = 1, groups - do gout = 1, groups - this % chi(gout,gin) = this % chi(gout,gin) + atom_density * & - nuc % chi(gout) * nuc % nu_fission(gin,1) - end do - end do - this % nu_fission = this % nu_fission + atom_density * & - nuc % nu_fission(:,1) - else - this % chi = this % chi + atom_density * nuc % nu_fission - do gin = 1, groups - this % nu_fission(gin) = this % nu_fission(gin) + atom_density * & - sum(nuc % nu_fission(:,gin)) - end do - end if - if (get_fiss) then - this % fission = this % fission + atom_density * nuc % fission - end if - if (get_kfiss) then - this % k_fission = this % k_fission + atom_density * nuc % k_fission - end if - end if - - ! Now time to do the scattering - do gin = 1, groups - do gout = 1, groups - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - ! Transfer matrix - temp_energy(gout,gin) = temp_energy(gout,gin) + atom_density * & - sum(nuc % scatter(gout,gin,:)) - - ! Determine the angular distribution - do imu = 1, order - scatt_coeffs(imu, gout, gin) = scatt_coeffs(imu, gout, gin) + & - nuc % scatter(gout,gin,imu) * & - atom_density - end do - - else if (scatt_type == ANGLE_LEGENDRE) then - ! Transfer matrix - temp_energy(gout,gin) = temp_energy(gout,gin) + atom_density * & - nuc % scatter(gout,gin,1) - - ! Determine the angular distribution coefficients so we can later - ! expand do the complete distribution - do l = 1, min(nuc % order, order) + 1 - scatt_coeffs(l, gout, gin) = scatt_coeffs(l, gout, gin) + & - nuc % scatter(gout,gin,l) * & - atom_density - end do - - end if - - ! Multiplicity matrix - temp_mult(gout,gin) = temp_mult(gout,gin) + atom_density * & - nuc % mult(gout,gin) - end do - end do - type is (NuclideAngle) - error_code = 1 - error_text = "Invalid Passing of NuclideAngle to MacroXSIso Object" - return - end select - end do - - ! Store the scattering xs - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - this % scattxs(:) = sum(sum(scatt_coeffs(:,:,:),dim=1),dim=1) - else if (scatt_type == ANGLE_LEGENDRE) then - this % scattxs(:) = sum(scatt_coeffs(1,:,:),dim=1) - end if - - ! Normalize the scatt_coeffs - do gin = 1, groups - do gout = 1, groups - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - norm = sum(scatt_coeffs(:,gout,gin)) - else if (scatt_type == ANGLE_LEGENDRE) then - norm = scatt_coeffs(1,gout,gin) - end if - if (norm /= ZERO) then - scatt_coeffs(:, gout, gin) = scatt_coeffs(:, gout,gin) / norm - end if - end do - ! Now normalize temp_energy (outgoing scattering energy probabilities) - norm = sum(temp_energy(:,gin)) - if (norm > ZERO) then - temp_energy(:,gin) = temp_energy(:,gin) / norm - end if - end do - - if (scatt_type == ANGLE_LEGENDRE .and. legendre_mu_points /= 1) then - call this % scatter % init(legendre_mu_points, temp_energy, temp_mult, & - scatt_coeffs) - else - call this % scatter % init(this % order, temp_energy, temp_mult, & - scatt_coeffs) - end if - - ! Now normalize chi - if (mat % fissionable) then - do gin = 1, groups - ! Normalize Chi - norm = sum(this % chi(:,gin)) - if (norm > ZERO) then - this % chi(:,gin) = this % chi(:,gin) / norm - end if - end do - end if - - ! Deallocate temporaries for the next material - deallocate(scatt_coeffs, temp_energy, temp_mult) - - end subroutine macroxsiso_init - - subroutine macroxsangle_init(this, mat, nuclides, groups, get_kfiss, get_fiss, & - max_order, scatt_type, legendre_mu_points, error_code, error_text) - class(MacroXSAngle), intent(inout) :: this ! The MacroXS to initialize - type(Material), pointer, intent(in) :: mat ! base material - type(NuclideMGContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from - integer, intent(in) :: groups ! Number of E groups - logical, intent(in) :: get_kfiss ! Should we get kfiss data? - logical, intent(in) :: get_fiss ! Should we get fiss data? - integer, intent(in) :: max_order ! Maximum requested order - integer, intent(in) :: scatt_type ! Legendre or Tabular Scatt? - integer, intent(in) :: legendre_mu_points ! Treat as Leg or Tabular? - integer, intent(inout) :: error_code ! Code signifying error - character(MAX_LINE_LEN), intent(inout) :: error_text ! Error message to print - - integer :: i ! loop index over nuclides - integer :: gin, gout ! group indices - real(8) :: atom_density ! atom density of a nuclide - integer :: ipol, iazi, npol, nazi - integer :: imu - real(8) :: norm - integer :: mat_max_order, order, l - real(8), allocatable :: temp_mult(:,:,:,:) - real(8), allocatable :: temp_energy(:,:,:,:) - real(8), allocatable :: scatt_coeffs(:,:,:,:,:) - - ! Initialize error data - error_code = 0 - error_text = '' - - ! Get the number of each polar and azi angles and make sure all the - ! NuclideAngle types have the same number of these angles - npol = -1 - nazi = -1 - do i = 1, mat % n_nuclides - select type(nuc => nuclides(mat % nuclide(i)) % obj) - type is (NuclideAngle) - if (npol == -1) then - npol = nuc % n_pol - nazi = nuc % n_azi - allocate(this % polar(npol)) - this % polar = nuc % polar - allocate(this % azimuthal(nazi)) - this % azimuthal = nuc % azimuthal - else - if ((npol /= nuc % n_pol) .or. (nazi /= nuc % n_azi)) then - error_code = 1 - error_text = "All Angular Data Must Be Same Length!" - end if - end if - end select - end do - - ! If we have tabular only data, then make sure all datasets have same size - if (scatt_type == ANGLE_HISTOGRAM) then - ! Check all scattering data of same size - order = nuclides(mat % nuclide(1)) % obj % order - do i = 2, mat % n_nuclides - if (order /= nuclides(mat % nuclide(i)) % obj % order) then - error_code = 1 - error_text = "All Histogram Scattering Entries Must Be Same Length!" - return - end if - end do - ! Ok, got our order, store it - this % order = order - - ! Allocate stuff for later - allocate(scatt_coeffs(order, groups, groups, nazi, npol)) - scatt_coeffs = ZERO - allocate(this % scatter(nazi, npol)) - do ipol = 1, npol - do iazi = 1, nazi - allocate(ScattDataHistogram :: this % scatter(iazi, ipol) % obj) - end do - end do - - else if (scatt_type == ANGLE_TABULAR) then - ! Check all scattering data of same size - order = nuclides(mat % nuclide(1)) % obj % order - do i = 2, mat % n_nuclides - if (order /= nuclides(mat % nuclide(i)) % obj % order) then - error_code = 1 - error_text = "All Tabular Scattering Entries Must Be Same Length!" - return - end if - end do - ! Ok, got our order, store it - this % order = order - - ! Allocate stuff for later - allocate(scatt_coeffs(order, groups, groups, nazi, npol)) - scatt_coeffs = ZERO - allocate(this % scatter(nazi, npol)) - do ipol = 1, npol - do iazi = 1, nazi - allocate(ScattDataTabular :: this % scatter(iazi, ipol) % obj) - end do - end do - - else if (scatt_type == ANGLE_LEGENDRE) then - ! Otherwise find the maximum scattering order - ! Need to determine the maximum scattering order of all data in this material - mat_max_order = 0 - do i = 1, mat % n_nuclides - if (nuclides(mat % nuclide(i)) % obj % order > mat_max_order) then - mat_max_order = nuclides(mat % nuclide(i)) % obj % order - end if - end do - - ! Now need to compare this material maximum scattering order with - ! the problem wide max scatt order and use whichever is lower - order = min(mat_max_order, max_order) - this % order = order + 1 - - ! Now we can allocate our scatt_coeffs object accordingly - allocate(scatt_coeffs(order + 1, groups, groups, nazi, npol)) - scatt_coeffs = ZERO - allocate(this % scatter(nazi, npol)) - do ipol = 1, npol - do iazi = 1, nazi - if (legendre_mu_points == 1) then - allocate(ScattDataLegendre :: this % scatter(iazi, ipol) % obj) - else - allocate(ScattDataTabular :: this % scatter(iazi, ipol) % obj) - end if - end do - end do - end if - - ! Allocate and initialize data within macro_xs(i_mat) object - allocate(this % total(groups,nazi,npol)) - this % total = ZERO - allocate(this % absorption(groups,nazi,npol)) - this % absorption = ZERO - if (get_fiss) then - allocate(this % fission(groups,nazi,npol)) - this % fission = ZERO - end if - if (get_kfiss) then - allocate(this % k_fission(groups,nazi,npol)) - this % k_fission = ZERO - end if - allocate(this % nu_fission(groups,nazi,npol)) - this % nu_fission = ZERO - allocate(this % chi(groups, groups, nazi, npol)) - this % chi = ZERO - allocate(temp_energy(groups,groups,nazi,npol)) - temp_energy = ZERO - allocate(temp_mult(groups,groups,nazi,npol)) - temp_mult = ZERO - allocate(this % scattxs(groups,nazi,npol)) - - ! Add contribution from each nuclide in material - do i = 1, mat % n_nuclides - ! Copy atom density of nuclide in material - atom_density = mat % atom_density(i) - - ! Perform our operations which depend upon the type - select type(nuc => nuclides(mat % nuclide(i)) % obj) - type is (NuclideIso) - error_code = 1 - error_text = "Invalid Passing of NuclideIso to MacroXSAngle Object" - return - type is (NuclideAngle) - ! Add contributions to total, absorption, and fission data (if necessary) - this % total = this % total + atom_density * nuc % total - this % absorption = this % absorption + & - atom_density * nuc % absorption - if (nuc % fissionable) then - if (allocated(nuc % chi)) then - do gin = 1, groups - do gout = 1, groups - this % chi(gout,gin,:,:) = this % chi(gout,gin,:,:) + atom_density * & - nuc % chi(gout,:,:) * nuc % nu_fission(gin,1,:,:) - end do - end do - this % nu_fission = this % nu_fission + atom_density * & - nuc % nu_fission(:,1,:,:) - else - this % chi = this % chi + atom_density * nuc % nu_fission - do gin = 1, groups - this % nu_fission(gin,:,:) = this % nu_fission(gin,:,:) + atom_density * & - sum(nuc % nu_fission(:,gin,:,:),dim=1) - end do - end if - if (get_fiss) then - this % fission = this % fission + atom_density * nuc % fission - end if - if (get_kfiss) then - this % k_fission = this % k_fission + atom_density * nuc % k_fission - end if - end if - - ! Now time to do the scattering - do gin = 1, groups - do gout = 1, groups - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - ! Transfer matrix - temp_energy(gout,gin,:,:) = temp_energy(gout,gin,:,:) + atom_density * & - sum(nuc % scatter(gout,gin,:,:,:),dim=1) - - ! Determine the angular distribution - do imu = 1, order - scatt_coeffs(imu,gout,gin,:,:) = scatt_coeffs(imu,gout,gin,:,:) + & - nuc % scatter(gout,gin,imu,:,:) * & - atom_density - end do - else if (scatt_type == ANGLE_LEGENDRE) then - ! Transfer matrix - temp_energy(gout,gin,:,:) = temp_energy(gout,gin,:,:) + atom_density * & - nuc % scatter(gout,gin,1,:,:) - - ! Determine the angular distribution coefficients so we can later - ! expand do the complete distribution - do l = 1, min(nuc % order, order) + 1 - scatt_coeffs(l, gout, gin,:,:) = scatt_coeffs(l, gout, gin,:,:) + & - nuc % scatter(gout,gin,l,:,:) * & - atom_density - end do - end if - - ! Multiplicity matrix - temp_mult(gout,gin,:,:) = temp_mult(gout,gin,:,:) + atom_density * & - nuc % mult(gout,gin,:,:) - end do - end do - end select - end do - - ! Store the scattering xs - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - this % scattxs(:,:,:) = sum(sum(scatt_coeffs(:,:,:,:,:),dim=1),dim=1) - else if (scatt_type == ANGLE_LEGENDRE) then - this % scattxs(:,:,:) = sum(scatt_coeffs(1,:,:,:,:),dim=1) - end if - - ! Normalize the scatt_coeffs - do ipol = 1, npol - do iazi = 1, nazi - do gin = 1, groups - do gout = 1, groups - if (scatt_type == ANGLE_HISTOGRAM .or. scatt_type == ANGLE_TABULAR) then - norm = sum(scatt_coeffs(:,gout,gin,iazi,ipol)) - else if (scatt_type == ANGLE_LEGENDRE) then - norm = scatt_coeffs(1,gout,gin,iazi,ipol) - end if - if (norm /= ZERO) then - scatt_coeffs(:,gout,gin,iazi,ipol) = & - scatt_coeffs(:,gout,gin,iazi,ipol) / norm - end if - end do - ! Now normalize temp_energy (outgoing scattering energy probabilities) - norm = sum(temp_energy(:,gin,iazi,ipol)) - if (norm > ZERO) then - temp_energy(:,gin,iazi,ipol) = temp_energy(:,gin,iazi,ipol) / norm - end if - end do - - if (scatt_type == ANGLE_LEGENDRE .and. legendre_mu_points /= 1) then - call this % scatter(iazi, ipol) % obj % init(legendre_mu_points, & - temp_energy(:,:,iazi,ipol), temp_mult(:,:,iazi,ipol), & - scatt_coeffs(:,:,:,iazi,ipol)) - else - call this % scatter(iazi, ipol) % obj % init(this % order, & - temp_energy(:,:,iazi,ipol), temp_mult(:,:,iazi,ipol), & - scatt_coeffs(:,:,:,iazi,ipol)) - end if - - end do - end do - - ! Now go through and normalize chi - if (mat % fissionable) then - do ipol = 1, npol - do iazi = 1, nazi - do gin = 1, groups - ! Normalize Chi - norm = sum(this % chi(:,gin,iazi,ipol)) - if (norm > ZERO) then - this % chi(:,gin,iazi,ipol) = this % chi(:,gin,iazi,ipol) / norm - end if - end do - end do - end do - end if - - ! Deallocate temporaries for the next material - deallocate(scatt_coeffs, temp_energy, temp_mult) - - end subroutine macroxsangle_init - -!=============================================================================== -! MACROXS_*_GET_XS returns the requested data type -!=============================================================================== - - function macroxsiso_get_xs(this, g, xstype, gout, uvw) result(xs) - class(MacroXSIso), intent(in) :: this ! The MacroXS to initialize - integer, intent(in) :: g ! Incoming Energy group - character(*) , intent(in) :: xstype ! Type of xs requested - integer, optional, intent(in) :: gout ! Outgoing Energy group - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - real(8) :: xs ! Requested x/s - - select case(xstype) - case('total') - xs = this % total(g) - case('absorption') - xs = this % absorption(g) - case('fission') - xs = this % fission(g) - case('k_fission') - xs = this % k_fission(g) - case('nu_fission') - xs = this % nu_fission(g) - case('scatter') - xs = this % scattxs(g) - case('mult') - if (present(gout)) then - xs = this % scatter % mult(gout,g) - else - xs = sum(this % scatter % mult(:,g)) - end if - end select - - end function macroxsiso_get_xs - - function macroxsangle_get_xs(this, g, xstype, gout,uvw) result(xs) - class(MacroXSAngle), intent(in) :: this ! The MacroXS to initialize - integer, intent(in) :: g ! Incoming Energy group - character(*) , intent(in) :: xstype ! Type of xs requested - integer, optional, intent(in) :: gout ! Outgoing Energy group - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - real(8) :: xs ! Requested x/s - - integer :: iazi, ipol - - if (present(uvw)) then - call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) - select case(xstype) - case('total') - xs = this % total(g,iazi,ipol) - case('absorption') - xs = this % absorption(g,iazi,ipol) - case('fission') - xs = this % fission(g,iazi,ipol) - case('k_fission') - xs = this % k_fission(g,iazi,ipol) - case('nu_fission') - xs = this % nu_fission(g,iazi,ipol) - case('scatter') - xs = this % scattxs(g,iazi,ipol) - case('mult') - if (present(gout)) then - xs = this % scatter(iazi,ipol) % obj % mult(gout,g) - else - xs = sum(this % scatter(iazi,ipol) % obj % mult(:,g)) - end if - end select - end if - - end function macroxsangle_get_xs - -!=============================================================================== -! MACROXS_*_SAMPLE_FISSION_ENERGY samples the outgoing energy from a fission -! event -!=============================================================================== - - function macroxsiso_sample_fission_energy(this, gin, uvw) result(gout) - class(MacroXSIso), intent(in) :: this ! Data to work with - integer, intent(in) :: gin ! Incoming energy group - real(8), intent(in) :: uvw(3) ! Particle Direction - integer :: gout ! Sampled outgoing group - real(8) :: xi ! Our random number - real(8) :: prob ! Running probability - - xi = prn() - prob = ZERO - gout = 0 - - do while (prob < xi) - gout = gout + 1 - prob = prob + this % chi(gout,gin) - end do - - end function macroxsiso_sample_fission_energy - - function macroxsangle_sample_fission_energy(this, gin, uvw) result(gout) - class(MacroXSAngle), intent(in) :: this ! Data to work with - integer, intent(in) :: gin ! Incoming energy group - real(8), intent(in) :: uvw(3) ! Particle Direction - integer :: gout ! Sampled outgoing group - real(8) :: xi ! Our random number - real(8) :: prob ! Running probability - integer :: iazi, ipol - - call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) - - xi = prn() - prob = ZERO - gout = 0 - - do while (prob < xi) - gout = gout + 1 - prob = prob + this % chi(gout,gin,iazi,ipol) - end do - - end function macroxsangle_sample_fission_energy - -!=============================================================================== -! MACROXS*_SAMPLE_SCATTER Selects outgoing energy and angle after a scatter -! event -!=============================================================================== - - subroutine macroxsiso_sample_scatter(this, uvw, gin, gout, mu, wgt) - class(MacroXSIso), intent(in) :: this - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - integer, intent(in) :: gin ! Incoming neutron group - integer, intent(out) :: gout ! Sampled outgoin group - real(8), intent(out) :: mu ! Sampled change in angle - real(8), intent(inout) :: wgt ! Particle weight - - call this % scatter % sample(gin, gout, mu, wgt) - - end subroutine macroxsiso_sample_scatter - - subroutine macroxsangle_sample_scatter(this, uvw, gin, gout, mu, wgt) - class(MacroXSAngle), intent(in) :: this - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - integer, intent(in) :: gin ! Incoming neutron group - integer, intent(out) :: gout ! Sampled outgoin group - real(8), intent(out) :: mu ! Sampled change in angle - real(8), intent(inout) :: wgt ! Particle weight - - integer :: iazi, ipol ! Angular indices - - call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) - call this % scatter(iazi,ipol) % obj % sample(gin,gout,mu,wgt) - - end subroutine macroxsangle_sample_scatter - -!=============================================================================== -! MACROXS*_CALCULATE_XS determines the multi-group macroscopic cross sections -! for the material the particle is currently traveling through. -!=============================================================================== - - subroutine macroxsiso_calculate_xs(this, gin, uvw, xs) - class(MacroXSIso), intent(in) :: this - integer, intent(in) :: gin ! Incoming neutron group - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - type(MaterialMacroXS), intent(inout) :: xs ! Resultant MacroXS Data - - xs % total = this % total(gin) - xs % elastic = this % scattxs(gin) - xs % absorption = this % absorption(gin) - xs % nu_fission = this % nu_fission(gin) - - end subroutine macroxsiso_calculate_xs - - subroutine macroxsangle_calculate_xs(this, gin, uvw, xs) - class(MacroXSAngle), intent(in) :: this - integer, intent(in) :: gin ! Incoming neutron group - real(8), intent(in) :: uvw(3) ! Incoming neutron direction - type(MaterialMacroXS), intent(inout) :: xs ! Resultant MacroXS Data - - integer :: iazi, ipol - - call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) - xs % total = this % total(gin, iazi, ipol) - xs % elastic = this % scattxs(gin, iazi, ipol) - xs % absorption = this % absorption(gin, iazi, ipol) - xs % nu_fission = this % nu_fission(gin, iazi, ipol) - - end subroutine macroxsangle_calculate_xs - -end module macroxs_header diff --git a/src/math.F90 b/src/math.F90 index f49220da7..c7ede8d2a 100644 --- a/src/math.F90 +++ b/src/math.F90 @@ -702,31 +702,4 @@ contains end function watt_spectrum - -!=============================================================================== -! find_angle finds the closest angle on the data grid and returns that index -!=============================================================================== - - pure subroutine find_angle(polar, azimuthal, uvw, i_azi, i_pol) - real(8), intent(in) :: polar(:) ! Polar angles [0,pi] - real(8), intent(in) :: azimuthal(:) ! Azi. angles [-pi,pi] - real(8), intent(in) :: uvw(3) ! Direction of motion - integer, intent(inout) :: i_pol ! Closest polar bin - integer, intent(inout) :: i_azi ! Closest azi bin - - real(8) :: my_pol, my_azi, dangle - - ! Convert uvw to polar and azi - - my_pol = acos(uvw(3)) - my_azi = atan2(uvw(2), uvw(1)) - - ! Search for equi-binned angles - dangle = PI / real(size(polar),8) - i_pol = floor(my_pol / dangle + ONE) - dangle = TWO * PI / real(size(azimuthal),8) - i_azi = floor((my_azi + PI) / dangle + ONE) - - end subroutine find_angle - end module math diff --git a/src/mgxs_data.F90 b/src/mgxs_data.F90 index 796269151..38d6ebc6c 100644 --- a/src/mgxs_data.F90 +++ b/src/mgxs_data.F90 @@ -3,9 +3,8 @@ module mgxs_data use constants use error, only: fatal_error use global - use macroxs_header use material_header, only: Material - use nuclide_header + use mgxs_header use output, only: write_message use set_header, only: SetChar use string, only: to_lower @@ -71,7 +70,8 @@ contains if (tallies(i) % score_bins(l) == SCORE_KAPPA_FISSION) then get_kfiss = .true. end if - if (tallies(i) % score_bins(l) == SCORE_FISSION) then + if (tallies(i) % score_bins(l) == SCORE_FISSION .or. & + tallies(i) % score_bins(l) == SCORE_NU_FISSION) then get_fiss = .true. end if end do @@ -118,17 +118,14 @@ contains ! Now allocate accordingly select case(representation) case(MGXS_ISOTROPIC) - allocate(NuclideIso :: nuclides_MG(i_nuclide) % obj) + allocate(MgxsIso :: nuclides_MG(i_nuclide) % obj) case(MGXS_ANGLE) - allocate(NuclideAngle :: nuclides_MG(i_nuclide) % obj) + allocate(MgxsAngle :: nuclides_MG(i_nuclide) % obj) end select ! Now read in the data specific to the type we just declared - call nuclides_MG(i_nuclide) % obj % init(node_xsdata, energy_groups, & - get_kfiss, get_fiss) - - ! Keep track of what listing is associated with this nuclide - nuclides_MG(i_nuclide) % obj % listing = i_listing + call nuclides_MG(i_nuclide) % obj % init_file(node_xsdata, & + energy_groups, get_kfiss, get_fiss, max_order, i_listing) ! Add name and alias to dictionary call already_read % add(name) @@ -161,59 +158,14 @@ contains end subroutine read_mgxs -!=============================================================================== -! SAME_NUCLIDEMG_LIST creates a linked list for each nuclide containing the -! indices in the nuclides array of all other instances of that nuclide. For -! example, the same nuclide may exist at multiple temperatures resulting -! in multiple entries in the nuclides array for a single zaid number. -!=============================================================================== - - subroutine same_nuclidemg_list() - - integer :: i ! index in nuclides array - integer :: j ! index in nuclides array - - do i = 1, n_nuclides_total - do j = 1, n_nuclides_total - if (nuclides_MG(i) % obj % zaid == nuclides_MG(j) % obj % zaid) then - call nuclides_MG(i) % obj % nuc_list % push_back(j) - end if - end do - end do - - end subroutine same_nuclidemg_list - !=============================================================================== ! CREATE_MACRO_XS generates the macroscopic x/s from the microscopic input data !=============================================================================== subroutine create_macro_xs() integer :: i_mat ! index in materials array - integer :: i ! loop index over nuclides - integer :: l ! Loop over score bins type(Material), pointer :: mat ! current material - logical :: get_kfiss, get_fiss - integer :: error_code - character(MAX_LINE_LEN) :: error_text integer :: scatt_type - integer :: legendre_mu_points - - ! Find out if we need fission & kappa fission - ! (i.e., are there any SCORE_FISSION or SCORE_KAPPA_FISSION tallies?) - get_kfiss = .false. - get_fiss = .false. - do i = 1, n_tallies - do l = 1, tallies(i) % n_score_bins - if (tallies(i) % score_bins(l) == SCORE_KAPPA_FISSION) then - get_kfiss = .true. - end if - if (tallies(i) % score_bins(l) == SCORE_FISSION) then - get_fiss = .true. - end if - end do - if (get_kfiss .and. get_fiss) & - exit - end do allocate(macro_xs(n_materials)) @@ -225,21 +177,15 @@ contains ! Therefore type(nuclides(mat % nuclide(1)) % obj) dictates type(macroxs) ! At the same time, we will find the scattering type, as that will dictate ! how we allocate the scatter object within macroxs - legendre_mu_points = nuclides_MG(mat % nuclide(1)) % obj % legendre_mu_points scatt_type = nuclides_MG(mat % nuclide(1)) % obj % scatt_type select type(nuc => nuclides_MG(mat % nuclide(1)) % obj) - type is (NuclideIso) - allocate(MacroXSIso :: macro_xs(i_mat) % obj) - type is (NuclideAngle) - allocate(MacroXSAngle :: macro_xs(i_mat) % obj) + type is (MgxsIso) + allocate(MgxsIso :: macro_xs(i_mat) % obj) + type is (MgxsAngle) + allocate(MgxsAngle :: macro_xs(i_mat) % obj) end select - - call macro_xs(i_mat) % obj % init(mat, nuclides_MG, energy_groups, & - get_kfiss, get_fiss, max_order, & - scatt_type, legendre_mu_points, & - error_code, error_text) - ! Handle any errors - if (error_code /= 0) call fatal_error(trim(error_text)) + call macro_xs(i_mat) % obj % combine(mat, nuclides_MG, energy_groups, & + max_order, scatt_type, i_mat) end do end subroutine create_macro_xs diff --git a/src/mgxs_header.F90 b/src/mgxs_header.F90 new file mode 100644 index 000000000..750a8df98 --- /dev/null +++ b/src/mgxs_header.F90 @@ -0,0 +1,1940 @@ +module mgxs_header + + use constants, only: MAX_FILE_LEN, ZERO, ONE, TWO, PI + use error, only: fatal_error + use, intrinsic :: ISO_FORTRAN_ENV, only: OUTPUT_UNIT + use list_header, only: ListInt + use material_header, only: material + use math, only: calc_pn, calc_rn, expand_harmonic, & + evaluate_legendre + use nuclide_header, only: MaterialMacroXS + use random_lcg, only: prn + use scattdata_header + use string + use xml_interface + +!=============================================================================== +! MGXS contains the base mgxs data for a nuclide/material +!=============================================================================== + + type, abstract :: Mgxs + character(len=104) :: name ! name of dataset, e.g. 92235.03c + integer :: zaid ! Z and A identifier, e.g. 92235 + real(8) :: awr ! Atomic Weight Ratio + integer :: listing ! index in xs_listings + real(8) :: kT ! temperature in MeV (k*T) + + ! Fission information + logical :: fissionable ! mgxs object is fissionable? + integer :: scatt_type ! either legendre, histogram, or tabular. + + contains + procedure(mgxs_init_file_), deferred :: init_file ! Initialize the data + procedure(mgxs_print_), deferred :: print ! Writes object info + procedure(mgxs_get_xs_), deferred :: get_xs ! Get the requested xs + procedure(mgxs_combine_), deferred :: combine ! initializes object + ! Sample the outgoing energy from a fission event + procedure(mgxs_sample_fission_), deferred :: sample_fission_energy + ! Sample the outgoing energy and angle from a scatter event + procedure(mgxs_sample_scatter_), deferred :: sample_scatter + ! Calculate the material specific MGXS data from the nuclides + procedure(mgxs_calculate_xs_), deferred :: calculate_xs + end type Mgxs + +!=============================================================================== +! MGXSCONTAINER pointer array for storing Nuclides +!=============================================================================== + + type MgxsContainer + class(Mgxs), pointer :: obj + end type MgxsContainer + +!=============================================================================== +! Interfaces for MGXS +!=============================================================================== + + abstract interface + subroutine mgxs_init_file_(this,node_xsdata,groups,get_kfiss,get_fiss, & + max_order,i_listing) + import Mgxs, Node + class(Mgxs), intent(inout) :: this ! Working Object + type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml + integer, intent(in) :: groups ! Number of Energy groups + logical, intent(in) :: get_kfiss ! Need Kappa-Fission? + logical, intent(in) :: get_fiss ! Should we get fiss data? + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: i_listing ! Index of listings array + end subroutine mgxs_init_file_ + + subroutine mgxs_print_(this, unit) + import Mgxs + class(Mgxs),intent(in) :: this + integer, optional, intent(in) :: unit + end subroutine mgxs_print_ + + pure function mgxs_get_xs_(this,xstype,gin,gout,uvw,mu) result(xs) + import Mgxs + class(Mgxs), intent(in) :: this + character(*), intent(in) :: xstype ! Cross Section Type + integer, intent(in) :: gin ! Incoming Energy group + integer, optional, intent(in) :: gout ! Outgoing Group + real(8), optional, intent(in) :: uvw(3) ! Requested Angle + real(8), optional, intent(in) :: mu ! Change in angle + real(8) :: xs ! Resultant xs + end function mgxs_get_xs_ + + pure function mgxs_calc_f_(this,gin,gout,mu,uvw,iazi,ipol) result(f) + import Mgxs + class(Mgxs), intent(in) :: this + integer, intent(in) :: gin ! Incoming Energy Group + integer, intent(in) :: gout ! Outgoing Energy Group + real(8), intent(in) :: mu ! Angle of interest + real(8), intent(in), optional :: uvw(3) ! Direction vector + integer, intent(in), optional :: iazi ! Incoming Energy Group + integer, intent(in), optional :: ipol ! Outgoing Energy Group + real(8) :: f ! Return value of f(mu) + + end function mgxs_calc_f_ + + subroutine mgxs_combine_(this,mat,nuclides,groups,max_order,scatt_type, & + i_listing) + import Mgxs, Material, MgxsContainer + class(Mgxs), intent(inout) :: this ! The Mgxs to initialize + type(Material), pointer, intent(in) :: mat ! base material + type(MgxsContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from + integer, intent(in) :: groups ! Number of E groups + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: scatt_type ! Legendre or Tabular Scatt? + integer, intent(in) :: i_listing ! Index in listings + end subroutine mgxs_combine_ + + function mgxs_sample_fission_(this, gin, uvw) result(gout) + import Mgxs + class(Mgxs), intent(in) :: this ! Data to work with + integer, intent(in) :: gin ! Incoming energy group + real(8), intent(in) :: uvw(3) ! Particle Direction + integer :: gout ! Sampled outgoing group + + end function mgxs_sample_fission_ + + subroutine mgxs_sample_scatter_(this, uvw, gin, gout, mu, wgt) + import Mgxs + class(Mgxs), intent(in) :: this + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + integer, intent(in) :: gin ! Incoming neutron group + integer, intent(out) :: gout ! Sampled outgoin group + real(8), intent(out) :: mu ! Sampled change in angle + real(8), intent(inout) :: wgt ! Particle weight + end subroutine mgxs_sample_scatter_ + + subroutine mgxs_calculate_xs_(this, gin, uvw, xs) + import Mgxs, MaterialMacroXS + class(Mgxs), intent(in) :: this + integer, intent(in) :: gin ! Incoming neutron group + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + type(MaterialMacroXS), intent(inout) :: xs ! Resultant Mgxs Data + end subroutine mgxs_calculate_xs_ + end interface + +!=============================================================================== +! MGXSISO contains the base MGXS data specifically for +! isotropically weighted MGXS +!=============================================================================== + + type, extends(Mgxs) :: MgxsIso + + ! Microscopic cross sections + real(8), allocatable :: total(:) ! total cross section + real(8), allocatable :: absorption(:) ! absorption cross section + class(ScattData), allocatable :: scatter ! scattering information + real(8), allocatable :: nu_fission(:) ! fission matrix (Gout x Gin) + real(8), allocatable :: k_fission(:) ! kappa-fission + real(8), allocatable :: fission(:) ! neutron production + real(8), allocatable :: chi(:, :) ! Fission Spectra + + contains + procedure :: init_file => mgxsiso_init_file ! Initialize Nuclidic MGXS Data + procedure :: print => mgxsiso_print ! Writes nuclide info + procedure :: get_xs => mgxsiso_get_xs ! Gets Size of Data w/in Object + procedure :: combine => mgxsiso_combine ! inits object + procedure :: sample_fission_energy => mgxsiso_sample_fission_energy + procedure :: sample_scatter => mgxsiso_sample_scatter + procedure :: calculate_xs => mgxsiso_calculate_xs + end type MgxsIso + +!=============================================================================== +! MGXSANGLE contains the base MGXS data specifically for +! angular flux weighted MGXS +!=============================================================================== + + type, extends(Mgxs) :: MgxsAngle + + ! Microscopic cross sections + real(8), allocatable :: total(:, :, :) ! total cross section + real(8), allocatable :: absorption(:, :, :) ! absorption cross section + type(ScattDataContainer), allocatable :: scatter(:, :) ! scattering information + real(8), allocatable :: nu_fission(:, :, :) ! fission matrix (Gout x Gin) + real(8), allocatable :: k_fission(:, :, :) ! kappa-fission + real(8), allocatable :: fission(:, :, :) ! neutron production + real(8), allocatable :: chi(:, :, :, :) ! Fission Spectra + ! In all cases, right-most indices are theta, phi + integer :: n_pol ! Number of polar angles + integer :: n_azi ! Number of azimuthal angles + real(8), allocatable :: polar(:) ! polar angles + real(8), allocatable :: azimuthal(:) ! azimuthal angles + + contains + procedure :: init_file => mgxsang_init_file ! Initialize Nuclidic MGXS Data + procedure :: print => mgxsang_print ! Writes nuclide info + procedure :: get_xs => mgxsang_get_xs ! Gets Size of Data w/in Object + procedure :: combine => mgxsang_combine ! inits object + procedure :: sample_fission_energy => mgxsang_sample_fission_energy + procedure :: sample_scatter => mgxsang_sample_scatter + procedure :: calculate_xs => mgxsang_calculate_xs + end type MgxsAngle + + contains + +!=============================================================================== +! MGXS*_INIT reads in the data from the XML file. At the point of entry +! the file would have been opened and metadata read. This routine begins with +! the xsdata object node itself. +!=============================================================================== + + subroutine mgxs_init_file(this, node_xsdata, i_listing) + class(Mgxs), intent(inout) :: this ! Working Object + type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml + integer, intent(in) :: i_listing ! Index in listings array + + character(MAX_LINE_LEN) :: temp_str + + ! Load the nuclide metadata + call get_node_value(node_xsdata, "name", this % name) + this % name = to_lower(this % name) + if (check_for_node(node_xsdata, "kT")) then + call get_node_value(node_xsdata, "kT", this % kT) + else + this % kT = ZERO + end if + if (check_for_node(node_xsdata, "zaid")) then + call get_node_value(node_xsdata, "zaid", this % zaid) + else + this % zaid = 0 + end if + if (check_for_node(node_xsdata, "awr")) then + call get_node_value(node_xsdata, "awr", this % awr) + else + this % awr = -ONE + end if + if (check_for_node(node_xsdata, "scatt_type")) then + call get_node_value(node_xsdata, "scatt_type", temp_str) + temp_str = trim(to_lower(temp_str)) + if (temp_str == 'legendre') then + this % scatt_type = ANGLE_LEGENDRE + else if (temp_str == 'histogram') then + this % scatt_type = ANGLE_HISTOGRAM + else if (temp_str == 'tabular') then + this % scatt_type = ANGLE_TABULAR + else + call fatal_error("Invalid scatt_type option!") + end if + else + this % scatt_type = ANGLE_LEGENDRE + end if + + if (check_for_node(node_xsdata, "fissionable")) then + call get_node_value(node_xsdata, "fissionable", temp_str) + temp_str = to_lower(temp_str) + if (trim(temp_str) == 'true' .or. trim(temp_str) == '1') then + this % fissionable = .true. + else + this % fissionable = .false. + end if + else + call fatal_error("Fissionable element must be set!") + end if + + ! Keep track of what listing is associated with this nuclide + this % listing = i_listing + + end subroutine mgxs_init_file + + subroutine mgxsiso_init_file(this, node_xsdata, groups, get_kfiss, get_fiss, & + max_order, i_listing) + class(MgxsIso), intent(inout) :: this ! Working Object + type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml + integer, intent(in) :: groups ! Number of Energy groups + logical, intent(in) :: get_kfiss ! Need Kappa-Fission? + logical, intent(in) :: get_fiss ! Need fiss data? + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: i_listing ! Index in listings array + + type(Node), pointer :: node_legendre_mu + character(MAX_LINE_LEN) :: temp_str + logical :: enable_leg_mu + real(8), allocatable :: temp_arr(:), temp_2d(:, :) + real(8), allocatable :: temp_mult(:, :) + real(8), allocatable :: scatt_coeffs(:, :, :) + real(8), allocatable :: input_scatt(:, :, :) + real(8), allocatable :: temp_scatt(:, :, :) + real(8) :: dmu, mu, norm + integer :: order, order_dim, gin, gout, l, arr_len + integer :: legendre_mu_points, imu + + ! Call generic data gathering routine (will populate the metadata) + call mgxs_init_file(this, node_xsdata, i_listing) + + ! Load the more specific data + allocate(this % nu_fission(groups)) + allocate(this % chi(groups,groups)) + if (this % fissionable) then + if (check_for_node(node_xsdata, "chi")) then + ! Chi was provided, that means they are giving chi and nu-fission + ! vectors + ! Get chi + allocate(temp_arr(groups)) + call get_node_array(node_xsdata, "chi", temp_arr) + do gin = 1, groups + do gout = 1, groups + this % chi(gout, gin) = temp_arr(gout) + end do + ! Normalize chi so its CDF goes to 1 + this % chi(:, gin) = this % chi(:, gin) / sum(this % chi(:, gin)) + end do + deallocate(temp_arr) + + ! Get nu_fission (as a vector) + if (check_for_node(node_xsdata, "nu_fission")) then + call get_node_array(node_xsdata, "nu_fission", this % nu_fission) + else + call fatal_error("If fissionable, must provide nu_fission!") + end if + + else + ! chi isnt provided but is within nu_fission, existing as a matrix + ! So, get nu_fission (as a matrix) + if (check_for_node(node_xsdata, "nu_fission")) then + allocate(temp_arr(groups*groups)) + call get_node_array(node_xsdata, "nu_fission", temp_arr) + allocate(temp_2d(groups, groups)) + temp_2d = reshape(temp_arr, (/groups, groups/)) + deallocate(temp_arr) + else + call fatal_error("If fissionable, must provide nu_fission!") + end if + + ! Set the vector nu-fission from the matrix nu-fission + do gin = 1, groups + this % nu_fission(gin) = sum(temp_2d(:, gin)) + end do + + ! Now pull out information needed for chi + this % chi(:, :) = temp_2d + ! Normalize chi so its CDF goes to 1 + do gin = 1, groups + this % chi(:, gin) = this % chi(:, gin) / sum(this % chi(:, gin)) + end do + deallocate(temp_2d) + end if + ! If we have a need* for the fission and kappa-fission x/s, get them + ! (*Need is defined as will be using it to tally) + if (get_fiss) then + allocate(this % fission(groups)) + if (check_for_node(node_xsdata, "fission")) then + call get_node_array(node_xsdata, "fission", this % fission) + else + call fatal_error("Fission data missing, required due to fission& + & tallies in tallies.xml file!") + end if + end if + if (get_kfiss) then + allocate(this % k_fission(groups)) + if (check_for_node(node_xsdata, "kappa_fission")) then + call get_node_array(node_xsdata, "kappa_fission", this % k_fission) + else + call fatal_error("kappa_fission data missing, required due to & + &kappa-fission tallies in tallies.xml file!") + end if + end if + else + this % nu_fission = ZERO + this % chi = ZERO + end if + + allocate(this % absorption(groups)) + if (check_for_node(node_xsdata, "absorption")) then + call get_node_array(node_xsdata, "absorption", this % absorption) + else + call fatal_error("Must provide absorption!") + end if + + ! Get multiplication data if present + allocate(temp_mult(groups, groups)) + if (check_for_node(node_xsdata, "multiplicity")) then + arr_len = get_arraysize_double(node_xsdata, "multiplicity") + if (arr_len == groups * groups) then + allocate(temp_arr(arr_len)) + call get_node_array(node_xsdata, "multiplicity", temp_arr) + temp_mult(:, :) = reshape(temp_arr, (/groups, groups/)) + deallocate(temp_arr) + else + call fatal_error("Multiplicity length not same as number of groups& + & squared!") + end if + else + temp_mult(:, :) = ONE + end if + + ! Get scattering treatment information + ! Tabular_legendre tells us if we are to treat the provided + ! Legendre polynomials as tabular data (if enable is true) or leaving + ! them as Legendres (if enable is false, or the default) + + ! Set the default (leave as Legendre polynomials) + enable_leg_mu = .false. + if (check_for_node(node_xsdata, "tabular_legendre")) then + call get_node_ptr(node_xsdata, "tabular_legendre", node_legendre_mu) + if (check_for_node(node_legendre_mu, "enable")) then + call get_node_value(node_legendre_mu, "enable", temp_str) + temp_str = trim(to_lower(temp_str)) + if (temp_str == 'true' .or. temp_str == '1') then + enable_leg_mu = .true. + elseif (temp_str == 'false' .or. temp_str == '0') then + enable_leg_mu = .false. + else + call fatal_error("Unrecognized tabular_legendre/enable: " & + // temp_str) + end if + end if + ! Ok, so if we need to convert to a tabular form, get the user provided + ! number of points + if (enable_leg_mu) then + if (check_for_node(node_legendre_mu, "num_points")) then + call get_node_value(node_legendre_mu, "num_points", & + legendre_mu_points) + if (legendre_mu_points <= 0) & + call fatal_error("num_points element must be positive& + & and non-zero!") + else + ! Set the default number of points (0.0625 spacing) + legendre_mu_points = 33 + end if + end if + end if + + ! Get the library's value for the order + if (check_for_node(node_xsdata, "order")) then + call get_node_value(node_xsdata, "order", order) + else + call fatal_error("Order must be provided!") + end if + + ! Before retrieving the data, store the dimensionality of the data in + ! order_dim. For Legendre data, we usually refer to it as Pn where + ! n is the order. However Pn has n+1 sets of points (since you need to + ! the count the P0 moment). Adjust for that. Histogram and Tabular + ! formats dont need this adjustment. + if (this % scatt_type == ANGLE_LEGENDRE) then + order_dim = order + 1 + else + order_dim = order + end if + + ! The input is gathered in the more user-friendly facing format of + ! Gout x Gin x Order. We will get it in that format in input_scatt, + ! but then need to convert it to a more useful ordering for processing + ! (Order x Gout x Gin). + allocate(input_scatt(groups, groups, order_dim)) + if (check_for_node(node_xsdata, "scatter")) then + allocate(temp_arr(groups * groups * order_dim)) + call get_node_array(node_xsdata, "scatter", temp_arr) + input_scatt = reshape(temp_arr, (/groups, groups, order_dim/)) + deallocate(temp_arr) + + ! Compare the number of orders given with the maximum order of the + ! problem. Strip off the supefluous orders if needed. + if (this % scatt_type == ANGLE_LEGENDRE) then + order = min(order_dim - 1, max_order) + order_dim = order + 1 + end if + allocate(temp_scatt(groups, groups, order_dim)) + temp_scatt(:, :, :) = input_scatt(:, :, 1:order_dim) + + ! Take input format (groups, groups, order) and convert to + ! the more useful format needed for scattdata: (order, groups, groups) + ! However, if scatt_type was ANGLE_LEGENDRE (i.e., the data was + ! provided as Legendre coefficients), and the user requested that + ! these legendres be converted to tabular form (note this is also + ! the default behavior), convert that now. + if (this % scatt_type == ANGLE_LEGENDRE .and. enable_leg_mu) then + ! Convert input parameters to what we need for the rest. + this % scatt_type = ANGLE_TABULAR + order_dim = legendre_mu_points + order = order_dim + dmu = TWO / real(order - 1, 8) + + allocate(scatt_coeffs(order_dim, groups, groups)) + do gin = 1, groups + do gout = 1, groups + norm = ZERO + do imu = 1, order_dim + if (imu == 1) then + mu = -ONE + else if (imu == order_dim) then + mu = ONE + else + mu = -ONE + real(imu - 1, 8) * dmu + end if + scatt_coeffs(imu, gout, gin) = & + evaluate_legendre(temp_scatt(gout, gin, :),mu) + ! Ensure positivity of distribution + if (scatt_coeffs(imu, gout, gin) < ZERO) & + scatt_coeffs(imu, gout, gin) = ZERO + ! And accrue the integral + if (imu > 1) then + norm = norm + HALF * dmu * & + (scatt_coeffs(imu - 1, gout, gin) + & + scatt_coeffs(imu, gout, gin)) + end if + end do + ! Now that we have the integral, lets ensure that the distribution + ! is normalized such that it preserves the original scattering xs + if (norm > ZERO) then + scatt_coeffs(:, gout, gin) = scatt_coeffs(:, gout, gin) * & + temp_scatt(gout, gin, 1) / norm + end if + end do + end do + else + ! Sticking with current representation, carry forward but change + ! the array ordering + allocate(scatt_coeffs(order_dim, groups, groups)) + do gin = 1, groups + do gout = 1, groups + do l = 1, order_dim + scatt_coeffs(l, gout, gin) = temp_scatt(gout, gin, l) + end do + end do + end do + end if + deallocate(temp_scatt) + else + call fatal_error("Must provide scatter!") + end if + + ! Allocate and initialize our ScattData Object. + if (this % scatt_type == ANGLE_HISTOGRAM) then + allocate(ScattDataHistogram :: this % scatter) + else if (this % scatt_type == ANGLE_TABULAR) then + allocate(ScattDataTabular :: this % scatter) + else if (this % scatt_type == ANGLE_LEGENDRE) then + allocate(ScattDataLegendre :: this % scatter) + end if + + ! Initialize the ScattData Object + call this % scatter % init(temp_mult, scatt_coeffs) + + ! Check sigA to ensure it is not 0 since it is + ! often divided by in the tally routines + ! (This may happen with Helium data) + do gin = 1, groups + if (this % absorption(gin) == ZERO) this % absorption(gin) = 1E-10_8 + end do + + ! Get, or infer, total xs data. + allocate(this % total(groups)) + if (check_for_node(node_xsdata, "total")) then + call get_node_array(node_xsdata, "total", this % total) + else + this % total(:) = this % absorption(:) + this % scatter % scattxs(:) + end if + + ! Deallocate temporaries for the next material + deallocate(input_scatt, scatt_coeffs, temp_mult) + + ! Finally, check sigT to ensure it is not 0 since it is + ! often divided by in the tally routines + do gin = 1, groups + if (this % total(gin) == ZERO) this % total(gin) = 1E-10_8 + end do + + + end subroutine mgxsiso_init_file + + subroutine mgxsang_init_file(this, node_xsdata, groups, get_kfiss, get_fiss, & + max_order, i_listing) + class(MgxsAngle), intent(inout) :: this ! Working Object + type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml + integer, intent(in) :: groups ! Number of Energy groups + logical, intent(in) :: get_kfiss ! Need Kappa-Fission? + logical, intent(in) :: get_fiss ! Should we get fiss data? + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: i_listing ! Index in listings array + + type(Node), pointer :: node_legendre_mu + character(MAX_LINE_LEN) :: temp_str + logical :: enable_leg_mu + real(8), allocatable :: temp_arr(:), temp_4d(:, :, :, :) + real(8), allocatable :: temp_mult(:, :, :, :) + real(8), allocatable :: scatt_coeffs(:, :, :, :, :) + real(8), allocatable :: input_scatt(:, :, :, :, :) + real(8), allocatable :: temp_scatt(:, :, :, :, :) + real(8) :: dmu, mu, norm, dangle + integer :: order, order_dim, gin, gout, l, arr_len + integer :: legendre_mu_points, imu, ipol, iazi + + ! Call generic data gathering routine (will populate the metadata) + call mgxs_init_file(this, node_xsdata, i_listing) + + if (check_for_node(node_xsdata, "num_polar")) then + call get_node_value(node_xsdata, "num_polar", this % n_pol) + else + call fatal_error("num_polar must be provided!") + end if + + if (check_for_node(node_xsdata, "num_azimuthal")) then + call get_node_value(node_xsdata, "num_azimuthal", this % n_azi) + else + call fatal_error("num_azimuthal must be provided!") + end if + + ! Load angle data, if present (else equally spaced) + allocate(this % polar(this % n_pol)) + allocate(this % azimuthal(this % n_azi)) + if (check_for_node(node_xsdata, "polar")) then + call fatal_error("User-Specified polar angle bins not yet supported!") + ! When this feature is supported, this line will be activated + call get_node_array(node_xsdata, "polar", this % polar) + else + dangle = PI / real(this % n_pol, 8) + do ipol = 1, this % n_pol + this % polar(ipol) = (real(ipol, 8) - HALF) * dangle + end do + end if + if (check_for_node(node_xsdata, "azimuthal")) then + call fatal_error("User-Specified azimuthal angle bins not yet supported!") + ! When this feature is supported, this line will be activated + call get_node_array(node_xsdata, "azimuthal", this % azimuthal) + else + dangle = TWO * PI / real(this % n_azi, 8) + do iazi = 1, this % n_azi + this % azimuthal(iazi) = -PI + (real(iazi, 8) - HALF) * dangle + end do + end if + + ! Load the more specific data + allocate(this % nu_fission(groups, this % n_azi, this % n_pol)) + allocate(this % chi(groups, groups, this % n_azi, this % n_pol)) + if (this % fissionable) then + if (check_for_node(node_xsdata, "chi")) then + ! Chi was provided, that means they are giving chi and nu-fission + ! vectors + ! Get chi + allocate(temp_arr(1 * groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "chi", temp_arr) + ! Initialize counter for temp_arr + l = 0 + gin = 1 + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gout = 1, groups + l = l + 1 + this % chi(gout, gin, iazi, ipol) = temp_arr(l) + end do + ! Normalize chi so its CDF goes to 1 + this % chi(:, gin, iazi, ipol) = & + this % chi(:, gin, iazi, ipol) / & + sum(this % chi(:, gin, iazi, ipol)) + end do + end do + + ! Now set all the other gin values + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 2, groups + this % chi(:, gin, iazi, ipol) = & + this % chi(:, 1, iazi, ipol) + end do + end do + end do + deallocate(temp_arr) + + ! Get nu_fission (as a vector) + if (check_for_node(node_xsdata, "nu_fission")) then + allocate(temp_arr(groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "nu_fission", temp_arr) + this % nu_fission(:, :, :) = reshape(temp_arr, (/groups, & + this % n_azi, this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("If fissionable, must provide nu_fission!") + end if + + else + ! chi isnt provided but is within nu_fission, existing as a matrix + ! So, get nu_fission (as a matrix) + if (check_for_node(node_xsdata, "nu_fission")) then + allocate(temp_arr(groups * groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "nu_fission", temp_arr) + allocate(temp_4d(groups, groups, this % n_azi,this % n_pol)) + temp_4d(:, :, :, :) = reshape(temp_arr, (/groups, groups, & + this % n_azi, this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("If fissionable, must provide nu_fission!") + end if + + ! Set the vector nu-fission from the matrix nu-fission + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 1, groups + this % nu_fission(gin, iazi, ipol) = & + sum(temp_4d(:, gin, iazi, ipol)) + end do + end do + end do + + ! Now pull out information needed for chi + this % chi = temp_4d + ! Normalize chi so its CDF goes to 1 + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 1, groups + this % chi(:, gin, iazi, ipol) = & + this % chi(:, gin, iazi, ipol) / & + sum(this % chi(:, gin, iazi, ipol)) + end do + end do + end do + deallocate(temp_4d) + end if + + ! If we have a need* for the fission and kappa-fission x/s, get them + ! (*Need is defined as will be using it to tally) + if (get_fiss) then + if (check_for_node(node_xsdata, "fission")) then + allocate(temp_arr(groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "fission", temp_arr) + allocate(this % fission(groups, this % n_azi, this % n_pol)) + this % fission(:, :, :) = reshape(temp_arr, (/groups, this % n_azi, & + this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("Fission data missing, required due to fission& + & tallies in tallies.xml file!") + end if + end if + if (get_kfiss) then + if (check_for_node(node_xsdata, "kappa_fission")) then + allocate(temp_arr(groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "kappa_fission", temp_arr) + allocate(this % k_fission(groups, this % n_azi, this % n_pol)) + this % k_fission(:, :, :) = reshape(temp_arr, (/groups, & + this % n_azi, this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("kappa_fission data missing, required due to & + &kappa-fission tallies in tallies.xml file!") + end if + end if + else + this % nu_fission(:, :, :) = ZERO + this % chi(:, :, :, :) = ZERO + end if + + if (check_for_node(node_xsdata, "absorption")) then + allocate(temp_arr(groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "absorption", temp_arr) + allocate(this % absorption(groups, this % n_azi, this % n_pol)) + this % absorption(:, :, :) = reshape(temp_arr, (/groups, this % n_azi, & + this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("Must provide absorption!") + end if + + ! Get multiplication data if present + allocate(temp_mult(groups,groups, this % n_azi, this % n_pol)) + if (check_for_node(node_xsdata, "multiplicity")) then + arr_len = get_arraysize_double(node_xsdata, "multiplicity") + if (arr_len == groups * groups * this % n_azi * this % n_pol) then + allocate(temp_arr(arr_len)) + call get_node_array(node_xsdata, "multiplicity", temp_arr) + temp_mult(:, :, :, :) = reshape(temp_arr, (/groups, groups, & + this % n_azi, this % n_pol/)) + deallocate(temp_arr) + else + call fatal_error("Multiplicity length not same as number of groups& + & squared!") + end if + else + temp_mult(:, :, :, :) = ONE + end if + + ! Get scattering treatment information + ! Tabular_legendre tells us if we are to treat the provided + ! Legendre polynomials as tabular data (if enable is true) or leaving + ! them as Legendres (if enable is false, or the default) + + ! Set the default (leave as Legendre polynomials) + enable_leg_mu = .false. + if (check_for_node(node_xsdata, "tabular_legendre")) then + call get_node_ptr(node_xsdata, "tabular_legendre", node_legendre_mu) + if (check_for_node(node_legendre_mu, "enable")) then + call get_node_value(node_legendre_mu, "enable", temp_str) + temp_str = trim(to_lower(temp_str)) + if (temp_str == 'true' .or. temp_str == '1') then + enable_leg_mu = .true. + elseif (temp_str == 'false' .or. temp_str == '0') then + enable_leg_mu = .false. + else + call fatal_error("Unrecognized tabular_legendre/enable: " & + // temp_str) + end if + end if + ! Ok, so if we need to convert to a tabular form, get the user provided + ! number of points + if (enable_leg_mu) then + if (check_for_node(node_legendre_mu, "num_points")) then + call get_node_value(node_legendre_mu, "num_points", & + legendre_mu_points) + if (legendre_mu_points <= 0) & + call fatal_error("num_points element must be positive& + & and non-zero!") + else + ! Set the default number of points (0.0625 spacing) + legendre_mu_points = 33 + end if + end if + end if + + ! Get the library's value for the order + if (check_for_node(node_xsdata, "order")) then + call get_node_value(node_xsdata, "order", order) + else + call fatal_error("Order must be provided!") + end if + + ! Before retrieving the data, store the dimensionality of the data in + ! order_dim. For Legendre data, we usually refer to it as Pn where + ! n is the order. However Pn has n+1 sets of points (since you need to + ! the count the P0 moment). Adjust for that. Histogram and Tabular + ! formats dont need this adjustment. + if (this % scatt_type == ANGLE_LEGENDRE) then + order_dim = order + 1 + else + order_dim = order + end if + + ! The input is gathered in the more user-friendly facing format of + ! Gout x Gin x Order x Azi x Pol. We will get it in that format in + ! input_scatt, but then need to convert it to a more useful ordering + ! for processing (Order x Gout x Gin x Azi x Pol). + allocate(input_scatt(groups, groups, order_dim, this % n_azi, & + this % n_pol)) + if (check_for_node(node_xsdata, "scatter")) then + allocate(temp_arr(groups * groups * order_dim * this % n_azi * & + this % n_pol)) + call get_node_array(node_xsdata, "scatter", temp_arr) + input_scatt(:, :, :, :, :) = reshape(temp_arr, (/groups, groups, & + order_dim, this % n_azi, this % n_pol/)) + deallocate(temp_arr) + + ! Compare the number of orders given with the maximum order of the + ! problem. Strip off the supefluous orders if needed. + if (this % scatt_type == ANGLE_LEGENDRE) then + order = min(order_dim - 1, max_order) + order_dim = order + 1 + end if + + allocate(temp_scatt(groups, groups, order_dim, this % n_azi, & + this % n_pol)) + temp_scatt(:, :, :, :, :) = input_scatt(:, :, 1:order_dim, :, :) + + ! Take input format (groups, groups, order) and convert to + ! the more useful format needed for scattdata: (order, groups, groups) + ! However, if scatt_type was ANGLE_LEGENDRE (i.e., the data was + ! provided as Legendre coefficients), and the user requested that + ! these legendres be converted to tabular form (note this is also + ! the default behavior), convert that now. + if (this % scatt_type == ANGLE_LEGENDRE .and. enable_leg_mu) then + + ! Convert input parameters to what we need for the rest. + this % scatt_type = ANGLE_TABULAR + order_dim = legendre_mu_points + order = order_dim + dmu = TWO / real(order - 1, 8) + + allocate(scatt_coeffs(order_dim, groups, groups, this % n_azi, & + this % n_pol)) + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 1, groups + do gout = 1, groups + norm = ZERO + do imu = 1, order_dim + if (imu == 1) then + mu = -ONE + else if (imu == order_dim) then + mu = ONE + else + mu = -ONE + real(imu - 1, 8) * dmu + end if + scatt_coeffs(imu, gout, gin, iazi, ipol) = & + evaluate_legendre(temp_scatt(gout, gin, :, iazi, ipol), mu) + ! Ensure positivity of distribution + if (scatt_coeffs(imu, gout, gin, iazi, ipol) < ZERO) & + scatt_coeffs(imu, gout, gin, iazi, ipol) = ZERO + ! And accrue the integral + if (imu > 1) then + norm = norm + HALF * dmu * & + (scatt_coeffs(imu - 1, gout, gin, iazi, ipol) + & + scatt_coeffs(imu, gout, gin, iazi, ipol)) + end if + end do + ! Now that we have the integral, lets ensure that the distribution + ! is normalized such that it preserves the original scattering xs + if (norm > ZERO) then + scatt_coeffs(:, gout, gin, iazi, ipol) = & + scatt_coeffs(:, gout, gin, iazi, ipol) * & + temp_scatt(gout, gin, 1, iazi, ipol) / norm + end if + end do + end do + end do + end do + else + ! Sticking with current representation, carry forward but change + ! the array ordering + allocate(scatt_coeffs(order_dim, groups, groups, this % n_azi, & + this % n_pol)) + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 1, groups + do gout = 1, groups + do l = 1, order_dim + scatt_coeffs(l, gout, gin, iazi, ipol) = & + temp_scatt(gout, gin, l, iazi, ipol) + end do + end do + end do + end do + end do + end if + deallocate(temp_scatt) + else + call fatal_error("Must provide scatter!") + end if + + allocate(this % scatter(this % n_azi, this % n_pol)) + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + ! Allocate and initialize our ScattData Object. + if (this % scatt_type == ANGLE_HISTOGRAM) then + allocate(ScattDataHistogram :: this % scatter(iazi, ipol) % obj) + else if (this % scatt_type == ANGLE_TABULAR) then + allocate(ScattDataTabular :: this % scatter(iazi, ipol) % obj) + else if (this % scatt_type == ANGLE_LEGENDRE) then + allocate(ScattDataLegendre :: this % scatter(iazi, ipol) % obj) + end if + + ! Initialize the ScattData Object + call this % scatter(iazi, ipol) % obj % init(& + temp_mult(:, :, iazi, ipol), & + scatt_coeffs(:, :, :, iazi, ipol)) + end do + end do + ! Deallocate temporaries for the next material + deallocate(input_scatt, scatt_coeffs, temp_mult) + + allocate(this % total(groups, this % n_azi, this % n_pol)) + if (check_for_node(node_xsdata, "total")) then + allocate(temp_arr(groups * this % n_azi * this % n_pol)) + call get_node_array(node_xsdata, "total", temp_arr) + this % total(:, :, :) = reshape(temp_arr, (/groups, this % n_azi, & + this % n_pol/)) + deallocate(temp_arr) + else + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + this % total(:, iazi, ipol) = this % absorption(:, iazi, ipol) + & + this % scatter(iazi, ipol) % obj % scattxs(:) + end do + end do + end if + + end subroutine mgxsang_init_file + +!=============================================================================== +! MGXS*_PRINT displays information about a continuous-energy neutron +! cross_section table and its reactions and secondary angle/energy distributions +!=============================================================================== + + subroutine mgxs_print(this, unit_) + class(Mgxs), intent(in) :: this + integer, intent(in) :: unit_ + + character(MAX_LINE_LEN) :: temp_str + + ! Basic nuclide information + write(unit_,*) 'MGXS Entry: ' // trim(this % name) + if (this % zaid > 0) then + write(unit_,*) ' ZAID = ' // trim(to_str(this % zaid)) + else if (this % zaid < 0) then + write(unit_,*) ' Material id = ' // trim(to_str(-this % zaid)) + end if + if (this % awr > ZERO) then + write(unit_,*) ' AWR = ' // trim(to_str(this % awr)) + end if + if (this % kT > ZERO) then + write(unit_,*) ' kT = ' // trim(to_str(this % kT)) + end if + if (this % scatt_type == ANGLE_LEGENDRE) then + temp_str = "Legendre" + write(unit_,*) ' Scattering Type = ' // trim(temp_str) + select type(this) + type is (MgxsIso) + temp_str = to_str(size(this % scatter % dist(1) % data,dim=1) - 1) + end select + write(unit_,*) ' Scattering Order = ' // trim(temp_str) + else if (this % scatt_type == ANGLE_HISTOGRAM) then + temp_str = "Histogram" + write(unit_,*) ' Scattering Type = ' // trim(temp_str) + select type(this) + type is (MgxsIso) + temp_str = to_str(size(this % scatter % dist(1) % data,dim=1)) + end select + write(unit_,*) ' Num. Distribution Bins = ' // trim(temp_str) + else if (this % scatt_type == ANGLE_TABULAR) then + temp_str = "Tabular" + write(unit_,*) ' Scattering Type = ' // trim(temp_str) + select type(this) + type is (MgxsIso) + temp_str = to_str(size(this % scatter % dist(1) % data,dim=1)) + end select + write(unit_,*) ' Num. Distribution Points = ' // trim(temp_str) + end if + write(unit_,*) ' Fissionable = ', this % fissionable + + end subroutine mgxs_print + + subroutine mgxsiso_print(this, unit) + + class(MgxsIso), intent(in) :: this + integer, optional, intent(in) :: unit + + integer :: unit_ ! unit to write to + integer :: size_total, size_scattmat, size_mgxs + integer :: gin + + ! set default unit for writing information + if (present(unit)) then + unit_ = unit + else + unit_ = OUTPUT_UNIT + end if + + ! Write Basic Nuclide Information + call mgxs_print(this, unit_) + + ! Determine size of mgxs and scattering matrices + size_scattmat = 0 + do gin = 1, size(this % scatter % energy) + size_scattmat = size_scattmat + & + 2 * size(this % scatter % energy(gin) % data) + & + size(this % scatter % dist(gin) % data) + end do + size_scattmat = size_scattmat + size(this % scatter % scattxs) + size_scattmat = size_scattmat * 8 + + size_mgxs = size(this % total) + size(this % absorption) + & + size(this % nu_fission) + size(this % k_fission) + & + size(this % fission) + size(this % chi) + size_mgxs = size_mgxs * 8 + + ! Calculate total memory + size_total = size_scattmat + size_mgxs + + ! Write memory used + write(unit_,*) ' Memory Requirements' + write(unit_,*) ' Cross sections = ' // trim(to_str(size_mgxs)) // ' bytes' + write(unit_,*) ' Scattering Matrices = ' // & + trim(to_str(size_scattmat)) // ' bytes' + write(unit_,*) ' Total = ' // trim(to_str(size_total)) // ' bytes' + + ! Blank line at end of nuclide + write(unit_,*) + + end subroutine mgxsiso_print + + subroutine mgxsang_print(this, unit) + + class(MgxsAngle), intent(in) :: this + integer, optional, intent(in) :: unit + + integer :: unit_ ! unit to write to + integer :: size_total, size_scattmat, size_mgxs + integer :: ipol, iazi, gin + + ! set default unit for writing information + if (present(unit)) then + unit_ = unit + else + unit_ = OUTPUT_UNIT + end if + + ! Write Basic Nuclide Information + call mgxs_print(this, unit_) + + write(unit_,*) ' # of Polar Angles = ' // trim(to_str(this % n_pol)) + write(unit_,*) ' # of Azimuthal Angles = ' // trim(to_str(this % n_azi)) + + ! Determine size of mgxs and scattering matrices + size_scattmat = 0 + do ipol = 1, this % n_pol + do iazi = 1, this % n_azi + do gin = 1, size(this % scatter(iazi, ipol) % obj % energy) + size_scattmat = size_scattmat + & + 2 * size(this % scatter(iazi, ipol) % obj % energy(gin) % data) + & + size(this % scatter(iazi, ipol) % obj % dist(gin) % data) + end do + size_scattmat = size_scattmat + & + size(this % scatter(iazi, ipol) % obj % scattxs) + end do + end do + size_scattmat = size_scattmat * 8 + + size_mgxs = size(this % total) + size(this % absorption) + & + size(this % nu_fission) + size(this % k_fission) + & + size(this % fission) + size(this % chi) + size_mgxs = size_mgxs * 8 + + ! Calculate total memory + size_total = size_scattmat + size_mgxs + + ! Write memory used + write(unit_,*) ' Memory Requirements' + write(unit_,*) ' Cross sections = ' // trim(to_str(size_mgxs)) // ' bytes' + write(unit_,*) ' Scattering Matrices = ' // & + trim(to_str(size_scattmat)) // ' bytes' + write(unit_,*) ' Total = ' // trim(to_str(size_total)) // ' bytes' + + ! Blank line at end of nuclide + write(unit_,*) + end subroutine mgxsang_print + +!=============================================================================== +! MGXS*_GET_XS returns the requested data cross section data +!=============================================================================== + + pure function mgxsiso_get_xs(this, xstype, gin, gout, uvw, mu) result(xs) + class(MgxsIso), intent(in) :: this ! The Mgxs to initialize + character(*) , intent(in) :: xstype ! Type of xs requested + integer, intent(in) :: gin ! Incoming Energy group + integer, optional, intent(in) :: gout ! Outgoing Energy group + real(8), optional, intent(in) :: uvw(3) ! Requested Angle + real(8), optional, intent(in) :: mu ! Change in angle + real(8) :: xs ! Requested x/s + + select case(xstype) + case('total') + xs = this % total(gin) + case('absorption') + xs = this % absorption(gin) + case('fission') + if (allocated(this % fission)) then + xs = this % fission(gin) + else + xs = ZERO + end if + case('kappa_fission') + if (allocated(this % k_fission)) then + xs = this % k_fission(gin) + else + xs = ZERO + end if + case('nu_fission') + xs = this % nu_fission(gin) + case('chi') + if (present(gout)) then + xs = this % chi(gout,gin) + else + ! Not sure youd want a 1 or a 0, but here you go! + xs = sum(this % chi(:, gin)) + end if + case('scatter') + if (present(gout)) then + if (gout < this % scatter % gmin(gin) .or. & + gout > this % scatter % gmax(gin)) then + xs = ZERO + else + xs = this % scatter % scattxs(gin) * & + this % scatter % energy(gin) % data(gout) + end if + else + xs = this % scatter % scattxs(gin) + end if + case('scatter/mult') + if (present(gout)) then + if (gout < this % scatter % gmin(gin) .or. & + gout > this % scatter % gmax(gin)) then + xs = ZERO + else + xs = this % scatter % scattxs(gin) * & + this % scatter % energy(gin) % data(gout) / & + this % scatter % mult(gin) % data(gout) + end if + else + xs = this % scatter % scattxs(gin) / & + (dot_product(this % scatter % mult(gin) % data, & + this % scatter % energy(gin) % data)) + end if + case('scatter*f_mu/mult','scatter*f_mu') + if (present(gout)) then + if (gout < this % scatter % gmin(gin) .or. & + gout > this % scatter % gmax(gin)) then + xs = ZERO + else + xs = this % scatter % scattxs(gin) * & + this % scatter % energy(gin) % data(gout) * & + this % scatter % calc_f(gin, gout, mu) + if (xstype == 'scatter*f_mu/mult') then + xs = xs / this % scatter % mult(gin) % data(gout) + end if + end if + else + xs = ZERO + ! TODO (Not likely needed) + ! (asking for f_mu without asking for a group or mu would mean the + ! user of this code wants the complete 1-outgoing group distribution + ! which Im not sure what they would do with that. + end if + case default + xs = ZERO + end select + + end function mgxsiso_get_xs + + pure function mgxsang_get_xs(this, xstype, gin, gout, uvw, mu) result(xs) + class(MgxsAngle), intent(in) :: this ! The Mgxs to initialize + character(*) , intent(in) :: xstype ! Type of xs requested + integer, intent(in) :: gin ! Incoming Energy group + integer, optional, intent(in) :: gout ! Outgoing Energy group + real(8), optional, intent(in) :: uvw(3) ! Requested Angle + real(8), optional, intent(in) :: mu ! Change in angle + real(8) :: xs ! Requested x/s + + integer :: iazi, ipol + + if (present(uvw)) then + call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) + select case(xstype) + case('total') + xs = this % total(gin, iazi, ipol) + case('absorption') + xs = this % absorption(gin, iazi, ipol) + case('fission') + if (allocated(this % fission)) then + xs = this % fission(gin, iazi, ipol) + else + xs = ZERO + end if + case('kappa_fission') + if (allocated(this % k_fission)) then + xs = this % k_fission(gin, iazi, ipol) + else + xs = ZERO + end if + case('nu_fission') + xs = this % nu_fission(gin, iazi, ipol) + case('chi') + if (present(gout)) then + xs = this % chi(gout, gin, iazi, ipol) + else + ! Not sure you would want a 1 or a 0, but here you go! + xs = sum(this % chi(:, gin, iazi, ipol)) + end if + case('scatter') + if (present(gout)) then + if (gout < this % scatter(iazi, ipol) % obj % gmin(gin) .or. & + gout > this % scatter(iazi, ipol) % obj % gmax(gin)) then + xs = ZERO + else + xs = this % scatter(iazi, ipol) % obj % scattxs(gin) * & + this % scatter(iazi, ipol) % obj % energy(gin) % data(gout) + end if + else + xs = this % scatter(iazi, ipol) % obj % scattxs(gin) + end if + case('scatter/mult') + if (present(gout)) then + if (gout < this % scatter(iazi, ipol) % obj % gmin(gin) .or. & + gout > this % scatter(iazi, ipol) % obj % gmax(gin)) then + xs = ZERO + else + xs = this % scatter(iazi, ipol) % obj % scattxs(gin) * & + this % scatter(iazi, ipol) % obj % energy(gin) % data(gout) / & + this % scatter(iazi, ipol) % obj % mult(gin) % data(gout) + end if + else + xs = this % scatter(iazi, ipol) % obj % scattxs(gin) / & + (dot_product(this % scatter(iazi, ipol) % obj % mult(gin) % data, & + this % scatter(iazi, ipol) % obj % energy(gin) % data)) + end if + case('scatter*f_mu/mult','scatter*f_mu') + if (present(gout)) then + if (gout < this % scatter(iazi, ipol) % obj % gmin(gin) .or. & + gout > this % scatter(iazi, ipol) % obj % gmax(gin)) then + xs = ZERO + else + xs = this % scatter(iazi, ipol) % obj % scattxs(gin) * & + this % scatter(iazi, ipol) % obj % energy(gin) % data(gout) + xs = xs * this % scatter(iazi, ipol) % obj % calc_f(gin, gout, mu) + if (xstype == 'scatter*f_mu/mult') then + xs = xs / & + this % scatter(iazi, ipol) % obj % mult(gin) % data(gout) + end if + end if + else + xs = ZERO + ! TODO (Not likely needed) + ! (asking for f_mu without asking for a group or mu would mean the + ! user of this code wants the complete 1-outgoing group distribution + ! which Im not sure what they would do with that. + end if + case default + xs = ZERO + end select + else + xs = ZERO + end if + + end function mgxsang_get_xs + +!=============================================================================== +! MACROXS*_COMBINE Builds a macroscopic Mgxs object from microscopic Mgxs +! objects +!=============================================================================== + + subroutine mgxs_combine(this, mat, scatt_type, i_listing) + class(Mgxs), intent(inout) :: this ! The Mgxs to initialize + type(Material), pointer, intent(in) :: mat ! base material + integer, intent(in) :: scatt_type ! How is data presented + integer, intent(in) :: i_listing ! Index in listings + + ! Fill in meta-data from material information + if (mat % name == "") then + this % name = trim(to_str(mat % id)) + else + this % name = mat % name + end if + this % zaid = -mat % id + this % listing = i_listing + this % fissionable = mat % fissionable + this % scatt_type = scatt_type + + ! The following info we should initialize, but we dont need it nor + ! does it have guaranteed meaning. + this % awr = -ONE + this % kT = -ONE + + end subroutine mgxs_combine + + subroutine mgxsiso_combine(this, mat, nuclides, groups, max_order, scatt_type, & + i_listing) + class(MgxsIso), intent(inout) :: this ! The Mgxs to initialize + type(Material), pointer, intent(in) :: mat ! base material + type(MgxsContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from + integer, intent(in) :: groups ! Number of E groups + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: scatt_type ! How is data presented + integer, intent(in) :: i_listing ! Index in listings + + integer :: i ! loop index over nuclides + integer :: gin, gout ! group indices + real(8) :: atom_density ! atom density of a nuclide + real(8) :: norm, nuscatt + integer :: mat_max_order, order, order_dim, nuc_order_dim + real(8), allocatable :: temp_mult(:, :), mult_num(:, :), mult_denom(:, :) + real(8), allocatable :: scatt_coeffs(:, :, :) + + ! Set the meta-data + call mgxs_combine(this, mat, scatt_type, i_listing) + + ! Determine the scattering type of our data and ensure all scattering orders + ! are the same. + select type(nuc => nuclides(mat % nuclide(1)) % obj) + type is (MgxsIso) + order = size(nuc % scatter % dist(1) % data, dim=1) + end select + ! If we have tabular only data, then make sure all datasets have same size + if (scatt_type == ANGLE_HISTOGRAM) then + ! Check all scattering data to ensure it is the same size + do i = 2, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsIso) + if (order /= size(nuc % scatter % dist(1) % data, dim=1)) & + call fatal_error("All histogram scattering entries must be& + & same length!") + end select + end do + ! Ok, got our order, store the dimensionality + order_dim = order + + ! Set our Scatter Object Type + allocate(ScattDataHistogram :: this % scatter) + + else if (scatt_type == ANGLE_TABULAR) then + ! Check all scattering data to ensure it is the same size + do i = 2, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsIso) + if (order /= size(nuc % scatter % dist(1) % data, dim=1)) & + call fatal_error("All tabular scattering entries must be& + & same length!") + end select + end do + ! Ok, got our order, store the dimensionality + order_dim = order + + ! Set our Scatter Object Type + allocate(ScattDataTabular :: this % scatter) + + else if (scatt_type == ANGLE_LEGENDRE) then + ! Need to determine the maximum scattering order of all data in this material + mat_max_order = 0 + do i = 1, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsIso) + if (size(nuc % scatter % dist(1) % data, dim=1) > mat_max_order) & + mat_max_order = size(nuc % scatter % dist(1) % data, dim=1) + end select + end do + + ! Now need to compare this material maximum scattering order with + ! the problem wide max scatt order and use whichever is lower + order = min(mat_max_order, max_order) + ! Ok, got our order, store the dimensionality + order_dim = order + 1 + + ! Set our Scatter Object Type + allocate(ScattDataLegendre :: this % scatter) + end if + + ! Allocate and initialize data needed for macro_xs(i_mat) object + allocate(this % total(groups)) + this % total(:) = ZERO + allocate(this % absorption(groups)) + this % absorption(:) = ZERO + allocate(this % fission(groups)) + this % fission(:) = ZERO + allocate(this % k_fission(groups)) + this % k_fission(:) = ZERO + allocate(this % nu_fission(groups)) + this % nu_fission(:) = ZERO + allocate(this % chi(groups,groups)) + this % chi(:, :) = ZERO + allocate(temp_mult(groups,groups)) + temp_mult(:, :) = ZERO + allocate(mult_num(groups,groups)) + mult_num(:, :) = ZERO + allocate(mult_denom(groups,groups)) + mult_denom(:, :) = ZERO + allocate(scatt_coeffs(order_dim,groups,groups)) + scatt_coeffs(:, :, :) = ZERO + + ! Add contribution from each nuclide in material + do i = 1, mat % n_nuclides + ! Copy atom density of nuclide in material + atom_density = mat % atom_density(i) + + ! Perform our operations which depend upon the type + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsIso) + ! Add contributions to total, absorption, and fission data (if necessary) + this % total(:) = this % total(:) + atom_density * nuc % total(:) + this % absorption(:) = this % absorption(:) + & + atom_density * nuc % absorption(:) + if (nuc % fissionable) then + this % chi(:, :) = this % chi(:, :) + atom_density * nuc % chi(:, :) + this % nu_fission(:) = this % nu_fission(:)+ atom_density * & + nuc % nu_fission(:) + if (allocated(nuc % fission)) then + this % fission(:) = this % fission(:) + atom_density * nuc % fission(:) + end if + if (allocated(nuc % k_fission)) then + this % k_fission(:) = this % k_fission(:) + atom_density * & + nuc % k_fission(:) + end if + end if + + ! Get the multiplication matrix + ! To combine from nuclidic data we need to use the final relationship + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / + ! sum_i(N_i*(nuscatt_{i,g,g'} / mult_{i,g,g'})) + ! Developed as follows: + ! mult_{gg'} = nuScatt{g,g'} / Scatt{g,g'} + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / sum(N_i*scatt_{i,g,g'}) + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / + ! sum_i(N_i*(nuscatt_{i,g,g'} / mult_{i,g,g'})) + ! nuscatt_{i,g,g'} can be reconstructed from scatter % energy and + ! scatter % scattxs + do gin = 1, groups + do gout = nuc % scatter % gmin(gin), nuc % scatter % gmax(gin) + nuscatt = nuc % scatter % scattxs(gin) * & + nuc % scatter % energy(gin) % data(gout) + mult_num(gout, gin) = mult_num(gout, gin) + atom_density * & + nuscatt + if (nuc % scatter % mult(gin) % data(gout) > ZERO) then + mult_denom(gout, gin) = mult_denom(gout,gin) + atom_density * & + nuscatt / nuc % scatter % mult(gin) % data(gout) + else + ! Avoid division by zero + mult_denom(gout, gin) = mult_denom(gout,gin) + atom_density + end if + end do + end do + + ! Get the complete scattering matrix + nuc_order_dim = size(nuc % scatter % dist(1) % data, dim=1) + scatt_coeffs(1:min(nuc_order_dim, order_dim), :, :) = & + scatt_coeffs(1:min(nuc_order_dim, order_dim), :, :) + & + atom_density * & + nuc % scatter % get_matrix(min(nuc_order_dim, order_dim)) + + type is (MgxsAngle) + call fatal_error("Invalid passing of MgxsAngle to MgxsIso object") + end select + end do + + ! Obtain temp_mult + do gin = 1, groups + do gout = 1, groups + if (mult_denom(gout, gin) > ZERO) then + temp_mult(gout, gin) = mult_num(gout, gin) / mult_denom(gout, gin) + else + temp_mult(gout, gin) = ONE + end if + end do + end do + + ! Initialize the ScattData Object + call this % scatter % init(temp_mult, scatt_coeffs) + + ! Now normalize chi + if (mat % fissionable) then + do gin = 1, groups + norm = sum(this % chi(:, gin)) + if (norm > ZERO) then + this % chi(:, gin) = this % chi(:, gin) / norm + end if + end do + end if + + ! Deallocate temporaries + deallocate(scatt_coeffs, temp_mult, mult_num, mult_denom) + + end subroutine mgxsiso_combine + + subroutine mgxsang_combine(this, mat, nuclides, groups, max_order, scatt_type, & + i_listing) + class(MgxsAngle), intent(inout) :: this ! The Mgxs to initialize + type(Material), pointer, intent(in) :: mat ! base material + type(MgxsContainer), intent(in) :: nuclides(:) ! List of nuclides to harvest from + integer, intent(in) :: groups ! Number of E groups + integer, intent(in) :: max_order ! Maximum requested order + integer, intent(in) :: scatt_type ! Legendre or Tabular Scatt? + integer, intent(in) :: i_listing ! Index in listings + + integer :: i ! loop index over nuclides + integer :: gin, gout ! group indices + real(8) :: atom_density ! atom density of a nuclide + integer :: ipol, iazi, n_pol, n_azi + real(8) :: norm, nuscatt + integer :: mat_max_order, order, order_dim, nuc_order_dim + real(8), allocatable :: temp_mult(:, :, :, :), mult_num(:, :, :, :) + real(8), allocatable :: mult_denom(:, :, :, :), scatt_coeffs(:, :, :, :, :) + + ! Set the meta-data + call mgxs_combine(this, mat, scatt_type, i_listing) + + ! Get the number of each polar and azi angles and make sure all the + ! NuclideAngle types have the same number of these angles + n_pol = -1 + n_azi = -1 + do i = 1, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsAngle) + if (n_pol == -1) then + n_pol = nuc % n_pol + n_azi = nuc % n_azi + allocate(this % polar(n_pol)) + this % polar(:) = nuc % polar(:) + allocate(this % azimuthal(n_azi)) + this % azimuthal(:) = nuc % azimuthal(:) + else + if ((n_pol /= nuc % n_pol) .or. (n_azi /= nuc % n_azi)) then + call fatal_error("All angular data must be same length!") + end if + end if + end select + end do + + ! Determine the scattering type of our data and ensure all scattering orders + ! are the same. + select type(nuc => nuclides(mat % nuclide(1)) % obj) + type is (MgxsAngle) + order = size(nuc % scatter(1,1) % obj % dist(1) % data, dim=1) + end select + ! If we have tabular only data, then make sure all datasets have same size + if (scatt_type == ANGLE_HISTOGRAM) then + ! Check all scattering data to ensure it is the same size + ! order = size(nuclides(mat % nuclide(1)) % obj % scatter % data,dim=1) + do i = 2, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsAngle) + if (order /= size(nuc % scatter(1,1) % obj % dist(1) % data, dim=1)) & + call fatal_error("All histogram scattering entries must be& + & same length!") + end select + end do + ! Ok, got our order, store the dimensionality + order_dim = order + + ! Set our Scatter Object Type + allocate(this % scatter(n_azi, n_pol)) + do ipol = 1, n_pol + do iazi = 1, n_azi + allocate(ScattDataHistogram :: this % scatter(iazi, ipol) % obj) + end do + end do + + else if (scatt_type == ANGLE_TABULAR) then + ! Check all scattering data to ensure it is the same size + do i = 2, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsAngle) + if (order /= size(nuc % scatter(1, 1) % obj % dist(1) % data, dim=1)) & + call fatal_error("All tabular scattering entries must be& + & same length!") + end select + end do + ! Ok, got our order, store the dimensionality + order_dim = order + + ! Set our Scatter Object Type + allocate(this % scatter(n_azi, n_pol)) + do ipol = 1, n_pol + do iazi = 1, n_azi + allocate(ScattDataTabular :: this % scatter(iazi, ipol) % obj) + end do + end do + + else if (scatt_type == ANGLE_LEGENDRE) then + ! Need to determine the maximum scattering order of all data in this material + mat_max_order = 0 + do i = 1, mat % n_nuclides + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsAngle) + if (size(nuc % scatter(1,1) % obj % dist(1) % data, dim=1) > mat_max_order) & + mat_max_order = size(nuc % scatter(1,1) % obj% dist(1) % data, dim=1) + end select + end do + + ! Now need to compare this material maximum scattering order with + ! the problem wide max scatt order and use whichever is lower + order = min(mat_max_order, max_order) + ! Ok, got our order, store the dimensionality + order_dim = order + 1 + + ! Set our Scatter Object Type + allocate(this % scatter(n_azi, n_pol)) + do ipol = 1, n_pol + do iazi = 1, n_azi + allocate(ScattDataLegendre :: this % scatter(iazi, ipol) % obj) + end do + end do + end if + + ! Allocate and initialize data within macro_xs(i_mat) object + allocate(this % total(groups, n_azi, n_pol)) + this % total(:, :, :) = ZERO + allocate(this % absorption(groups, n_azi, n_pol)) + this % absorption(:, :, :) = ZERO + allocate(this % fission(groups, n_azi, n_pol)) + this % fission(:, :, :) = ZERO + allocate(this % k_fission(groups, n_azi, n_pol)) + this % k_fission(:, :, :) = ZERO + allocate(this % nu_fission(groups, n_azi, n_pol)) + this % nu_fission(:, :, :) = ZERO + allocate(this % chi(groups, groups, n_azi, n_pol)) + this % chi(:, :, :, :) = ZERO + allocate(temp_mult(groups, groups, n_azi, n_pol)) + temp_mult(:, :, :, :) = ZERO + allocate(mult_num(groups, groups, n_azi, n_pol)) + mult_num(:, :, :, :) = ZERO + allocate(mult_denom(groups, groups, n_azi, n_pol)) + mult_denom(:, :, :, :) = ZERO + allocate(scatt_coeffs(order_dim, groups, groups, n_azi, n_pol)) + scatt_coeffs(:, :, :, :, :) = ZERO + + ! Add contribution from each nuclide in material + do i = 1, mat % n_nuclides + ! Copy atom density of nuclide in material + atom_density = mat % atom_density(i) + + ! Perform our operations which depend upon the type + select type(nuc => nuclides(mat % nuclide(i)) % obj) + type is (MgxsIso) + call fatal_error("Invalid passing of MgxsIso to MgxsAngle object") + type is (MgxsAngle) + ! Add contributions to total, absorption, and fission data (if necessary) + this % total(:, :, :) = this % total(:, :, :) + & + atom_density * nuc % total(:, :, :) + this % absorption(:, :, :) = this % absorption(:, :, :) + & + atom_density * nuc % absorption(:, :, :) + if (nuc % fissionable) then + this % chi = this % chi + atom_density * nuc % chi + this % nu_fission(:, :, :) = this % nu_fission(:, :, :) + & + atom_density * nuc % nu_fission(:, :, :) + if (allocated(nuc % fission)) then + this % fission(:, :, :) = this % fission(:, :, :) + & + atom_density * nuc % fission(:, :, :) + end if + if (allocated(nuc % k_fission)) then + this % k_fission(:, :, :) = this % k_fission(:, :, :) + & + atom_density * nuc % k_fission(:, :, :) + end if + end if + + ! Get the multiplication matrix + ! To combine from nuclidic data we need to use the final relationship + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / + ! sum_i(N_i*(nuscatt_{i,g,g'} / mult_{i,g,g'})) + ! Developed as follows: + ! mult_{gg'} = nuScatt{g,g'} / Scatt{g,g'} + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / sum(N_i*scatt_{i,g,g'}) + ! mult_{gg'} = sum_i(N_i*nuscatt_{i,g,g'}) / + ! sum_i(N_i*(nuscatt_{i,g,g'} / mult_{i,g,g'})) + ! nuscatt_{i,g,g'} can be reconstructed from scatter % energy and + ! scatter % scattxs + do ipol = 1, n_pol + do iazi = 1, n_azi + do gin = 1, groups + do gout = nuc % scatter(iazi, ipol) % obj % gmin(gin), & + nuc % scatter(iazi, ipol) % obj % gmax(gin) + nuscatt = nuc % scatter(iazi, ipol) % obj % scattxs(gin) * & + nuc % scatter(iazi, ipol) % obj % energy(gin) % data(gout) + mult_num(gout, gin, iazi, ipol) = mult_num(gout, gin, iazi, ipol) + & + atom_density * nuscatt + if (nuc % scatter(iazi, ipol) % obj % mult(gin) % data(gout) > ZERO) then + mult_denom(gout, gin, iazi, ipol) = & + mult_denom(gout, gin, iazi, ipol) + & + atom_density * nuscatt / & + nuc % scatter(iazi, ipol) % obj % mult(gin) % data(gout) + else + ! Avoid division by zero + mult_denom(gout, gin, iazi, ipol) = & + mult_denom(gout,gin, iazi, ipol) + atom_density + end if + end do + end do + end do + end do + + ! Get the complete scattering matrix + nuc_order_dim = size(nuc % scatter(1, 1) % obj % dist(1) % data, dim=1) + do ipol = 1, n_pol + do iazi = 1, n_azi + scatt_coeffs(1:min(nuc_order_dim, order_dim), :, :, iazi, ipol) = & + scatt_coeffs(1:min(nuc_order_dim, order_dim), :, :, iazi, ipol) + & + atom_density * nuc % scatter(iazi, ipol) % obj % get_matrix(& + min(nuc_order_dim, order_dim)) + end do + end do + end select + end do + + ! Obtain temp_mult + do ipol = 1, n_pol + do iazi = 1, n_azi + do gin = 1, groups + do gout = 1, groups + if (mult_denom(gout, gin, iazi, ipol) > ZERO) then + temp_mult(gout, gin, iazi, ipol) = & + mult_num(gout, gin, iazi, ipol) / & + mult_denom(gout, gin, iazi, ipol) + else + temp_mult(gout, gin, iazi, ipol) = ONE + end if + end do + end do + end do + end do + + ! Initialize the ScattData Object + do ipol = 1, n_pol + do iazi = 1, n_azi + call this % scatter(iazi, ipol) % obj % init( & + temp_mult(:, :, iazi, ipol), scatt_coeffs(:, :, :, iazi, ipol)) + end do + end do + + ! Now normalize chi + if (mat % fissionable) then + do ipol = 1, n_pol + do iazi = 1, n_azi + do gin = 1, groups + norm = sum(this % chi(:, gin, iazi, ipol)) + if (norm > ZERO) then + this % chi(:, gin, iazi, ipol) = this % chi(:, gin, iazi, ipol) / norm + end if + end do + end do + end do + end if + + ! Deallocate temporaries for the next material + deallocate(scatt_coeffs, temp_mult) + + end subroutine mgxsang_combine + +!=============================================================================== +! MGXS*_SAMPLE_FISSION_ENERGY samples the outgoing energy from a fission event +!=============================================================================== + + function mgxsiso_sample_fission_energy(this, gin, uvw) result(gout) + class(MgxsIso), intent(in) :: this ! Data to work with + integer, intent(in) :: gin ! Incoming energy group + real(8), intent(in) :: uvw(3) ! Particle Direction + integer :: gout ! Sampled outgoing group + real(8) :: xi ! Our random number + real(8) :: prob ! Running probability + + xi = prn() + gout = 1 + prob = this % chi(gout,gin) + + do while (prob < xi) + gout = gout + 1 + prob = prob + this % chi(gout,gin) + end do + + end function mgxsiso_sample_fission_energy + + function mgxsang_sample_fission_energy(this, gin, uvw) result(gout) + class(MgxsAngle), intent(in) :: this ! Data to work with + integer, intent(in) :: gin ! Incoming energy group + real(8), intent(in) :: uvw(3) ! Particle Direction + integer :: gout ! Sampled outgoing group + real(8) :: xi ! Our random number + real(8) :: prob ! Running probability + integer :: iazi, ipol + + call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) + + xi = prn() + gout = 1 + prob = this % chi(gout, gin, iazi, ipol) + + do while (prob < xi) + gout = gout + 1 + prob = prob + this % chi(gout, gin, iazi, ipol) + end do + + end function mgxsang_sample_fission_energy + +!=============================================================================== +! MGXS*_SAMPLE_SCATTER Selects outgoing energy and angle after a scatter event +!=============================================================================== + + subroutine mgxsiso_sample_scatter(this, uvw, gin, gout, mu, wgt) + class(MgxsIso), intent(in) :: this + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + integer, intent(in) :: gin ! Incoming neutron group + integer, intent(out) :: gout ! Sampled outgoin group + real(8), intent(out) :: mu ! Sampled change in angle + real(8), intent(inout) :: wgt ! Particle weight + + call this % scatter % sample(gin, gout, mu, wgt) + + end subroutine mgxsiso_sample_scatter + + subroutine mgxsang_sample_scatter(this, uvw, gin, gout, mu, wgt) + class(MgxsAngle), intent(in) :: this + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + integer, intent(in) :: gin ! Incoming neutron group + integer, intent(out) :: gout ! Sampled outgoin group + real(8), intent(out) :: mu ! Sampled change in angle + real(8), intent(inout) :: wgt ! Particle weight + + integer :: iazi, ipol ! Angular indices + + call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) + call this % scatter(iazi, ipol) % obj % sample(gin, gout, mu, wgt) + + end subroutine mgxsang_sample_scatter + +!=============================================================================== +! MGXS*_CALCULATE_XS determines the multi-group cross sections +! for the material the particle is currently traveling through. +!=============================================================================== + + subroutine mgxsiso_calculate_xs(this, gin, uvw, xs) + class(MgxsIso), intent(in) :: this + integer, intent(in) :: gin ! Incoming neutron group + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + type(MaterialMacroXS), intent(inout) :: xs ! Resultant Mgxs Data + + xs % total = this % total(gin) + xs % elastic = this % scatter % scattxs(gin) + xs % absorption = this % absorption(gin) + xs % fission = this % fission(gin) + xs % nu_fission = this % nu_fission(gin) + + end subroutine mgxsiso_calculate_xs + + subroutine mgxsang_calculate_xs(this, gin, uvw, xs) + class(MgxsAngle), intent(in) :: this + integer, intent(in) :: gin ! Incoming neutron group + real(8), intent(in) :: uvw(3) ! Incoming neutron direction + type(MaterialMacroXS), intent(inout) :: xs ! Resultant Mgxs Data + + integer :: iazi, ipol + + call find_angle(this % polar, this % azimuthal, uvw, iazi, ipol) + xs % total = this % total(gin, iazi, ipol) + xs % elastic = this % scatter(iazi, ipol) % obj % scattxs(gin) + xs % absorption = this % absorption(gin, iazi, ipol) + xs % fission = this % fission(gin, iazi, ipol) + xs % nu_fission = this % nu_fission(gin, iazi, ipol) + + end subroutine mgxsang_calculate_xs + +!=============================================================================== +! find_angle finds the closest angle on the data grid and returns that index +!=============================================================================== + + pure subroutine find_angle(polar, azimuthal, uvw, i_azi, i_pol) + real(8), intent(in) :: polar(:) ! Polar angles [0,pi] + real(8), intent(in) :: azimuthal(:) ! Azi. angles [-pi,pi] + real(8), intent(in) :: uvw(3) ! Direction of motion + integer, intent(inout) :: i_pol ! Closest polar bin + integer, intent(inout) :: i_azi ! Closest azi bin + + real(8) :: my_pol, my_azi, dangle + + ! Convert uvw to polar and azi + + my_pol = acos(uvw(3)) + my_azi = atan2(uvw(2), uvw(1)) + + ! Search for equi-binned angles + dangle = PI / real(size(polar),8) + i_pol = floor(my_pol / dangle + ONE) + dangle = TWO * PI / real(size(azimuthal),8) + i_azi = floor((my_azi + PI) / dangle + ONE) + + end subroutine find_angle + +end module mgxs_header \ No newline at end of file diff --git a/src/nuclide_header.F90 b/src/nuclide_header.F90 index 43fea77b6..92e2d7ba3 100644 --- a/src/nuclide_header.F90 +++ b/src/nuclide_header.F90 @@ -2,49 +2,38 @@ module nuclide_header use, intrinsic :: ISO_FORTRAN_ENV - use ace_header use constants - use endf, only: reaction_name - use error, only: fatal_error + use dict_header, only: DictIntInt + use endf, only: reaction_name, is_fission, is_disappearance + use endf_header, only: Function1D + use error, only: fatal_error, warning use list_header, only: ListInt - use math, only: evaluate_legendre, find_angle + use math, only: evaluate_legendre + use product_header, only: AngleEnergyContainer + use reaction_header, only: Reaction + use stl_vector, only: VectorInt use string + use urr_header, only: UrrData use xml_interface implicit none !=============================================================================== -! Nuclide contains the base nuclidic data for a nuclide, which does not depend -! upon how the nuclear data is represented (i.e., CE, or any variant of MG). -! The extended types, NuclideCE and NuclideMG deal with the rest +! Nuclide contains the base nuclidic data for a nuclide described as needed +! for continuous-energy neutron transport. !=============================================================================== - type, abstract :: Nuclide + type :: Nuclide + ! Nuclide meta-data character(12) :: name ! name of nuclide, e.g. 92235.03c integer :: zaid ! Z and A identifier, e.g. 92235 real(8) :: awr ! Atomic Weight Ratio integer :: listing ! index in xs_listings real(8) :: kT ! temperature in MeV (k*T) - ! Linked list of indices in nuclides array of instances of this same nuclide - type(VectorInt) :: nuc_list - ! Fission information - logical :: fissionable ! nuclide is fissionable? + logical :: fissionable ! nuclide is fissionable? - contains - procedure(nuclide_print_), deferred :: print ! Writes nuclide info - end type Nuclide - - abstract interface - subroutine nuclide_print_(this, unit) - import Nuclide - class(Nuclide),intent(in) :: this - integer, optional, intent(in) :: unit - end subroutine nuclide_print_ - end interface - - type, extends(Nuclide) :: NuclideCE ! Energy grid information integer :: n_grid ! # of nuclide grid points integer, allocatable :: grid_index(:) ! log grid mapping indices @@ -70,24 +59,11 @@ module nuclide_header real(8) :: E_max ! upper cutoff energy for res scattering ! Fission information - logical :: has_partial_fission ! nuclide has partial fission reactions? - integer :: n_fission ! # of fission reactions + logical :: has_partial_fission = .false. ! nuclide has partial fission reactions? + integer :: n_fission ! # of fission reactions + integer :: n_precursor = 0 ! # of delayed neutron precursors integer, allocatable :: index_fission(:) ! indices in reactions - - ! Total fission neutron emission - integer :: nu_t_type - real(8), allocatable :: nu_t_data(:) - - ! Prompt fission neutron emission - integer :: nu_p_type - real(8), allocatable :: nu_p_data(:) - - ! Delayed fission neutron emission - integer :: nu_d_type - integer :: n_precursor ! # of delayed neutron precursors - real(8), allocatable :: nu_d_data(:) - real(8), allocatable :: nu_d_precursor_data(:) - type(AngleEnergyContainer), allocatable :: nu_d_edist(:) + class(Function1D), allocatable :: total_nu ! Unresolved resonance data logical :: urr_present @@ -101,128 +77,14 @@ module nuclide_header ! array; used at tally-time contains - procedure :: clear => nuclidece_clear - procedure :: print => nuclidece_print - end type NuclideCE - - type, abstract, extends(Nuclide) :: NuclideMG - ! Scattering Order Information - integer :: order ! Order of data (Scattering for NuclideIso, - ! Number of angles for all in NuclideAngle) - integer :: scatt_type ! either legendre, histogram, or tabular. - integer :: legendre_mu_points ! Number of tabular points to use to represent - ! Legendre distribs, -1 if sample with the - ! Legendres themselves - contains - procedure(nuclidemg_init_), deferred :: init ! Initialize the data - procedure(nuclidemg_get_xs_), deferred :: get_xs ! Get the requested xs - procedure(nuclidemg_calc_f_), deferred :: calc_f ! Calculates f, given mu - end type NuclideMG - - abstract interface - - subroutine nuclidemg_init_(this, node_xsdata, groups, get_kfiss, get_fiss) - import NuclideMG, Node - class(NuclideMG), intent(inout) :: this ! Working Object - type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml - integer, intent(in) :: groups ! Number of Energy groups - logical, intent(in) :: get_kfiss ! Need Kappa-Fission? - logical, intent(in) :: get_fiss ! Should we get fiss data? - end subroutine nuclidemg_init_ - - function nuclidemg_get_xs_(this, g, xstype, gout, uvw, mu, i_azi, i_pol) & - result(xs) - import NuclideMG - class(NuclideMG), intent(in) :: this - integer, intent(in) :: g ! Incoming Energy group - character(*), intent(in) :: xstype ! Cross Section Type - integer, optional, intent(in) :: gout ! Outgoing Group - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - real(8), optional, intent(in) :: mu ! Change in angle - integer, optional, intent(in) :: i_azi ! Azimuthal Index - integer, optional, intent(in) :: i_pol ! Polar Index - real(8) :: xs ! Resultant xs - end function nuclidemg_get_xs_ - - pure function nuclidemg_calc_f_(this, gin, gout, mu, uvw, i_azi, i_pol) result(f) - import NuclideMG - class(NuclideMG), intent(in) :: this - integer, intent(in) :: gin ! Incoming Energy Group - integer, intent(in) :: gout ! Outgoing Energy Group - real(8), intent(in) :: mu ! Angle of interest - real(8), intent(in), optional :: uvw(3) ! Direction vector - integer, intent(in), optional :: i_azi ! Incoming Energy Group - integer, intent(in), optional :: i_pol ! Outgoing Energy Group - real(8) :: f ! Return value of f(mu) - - end function nuclidemg_calc_f_ - end interface - -!=============================================================================== -! NuclideIso contains the base MGXS data for a nuclide specifically for -! isotropically weighted MGXS -!=============================================================================== - - type, extends(NuclideMG) :: NuclideIso - - ! Microscopic cross sections - real(8), allocatable :: total(:) ! total cross section - real(8), allocatable :: absorption(:) ! absorption cross section - real(8), allocatable :: scatter(:,:,:) ! scattering information - real(8), allocatable :: nu_fission(:,:) ! fission matrix (Gout x Gin) - real(8), allocatable :: k_fission(:) ! kappa-fission - real(8), allocatable :: fission(:) ! neutron production - real(8), allocatable :: chi(:) ! Fission Spectra - real(8), allocatable :: mult(:,:) ! Scatter multiplicity (Gout x Gin) - - contains - procedure :: init => nuclideiso_init ! Initialize Nuclidic MGXS Data - procedure :: print => nuclideiso_print ! Writes nuclide info - procedure :: get_xs => nuclideiso_get_xs ! Gets Size of Data w/in Object - procedure :: calc_f => nuclideiso_calc_f ! Calcs f given mu - end type NuclideIso - -!=============================================================================== -! NuclideAngle contains the base MGXS data for a nuclide specifically for -! explicit angle-dependent weighted MGXS -!=============================================================================== - - type, extends(NuclideMG) :: NuclideAngle - - ! Microscopic cross sections. Dimensions are: (n_pol, n_azi, Nl, Ng, Ng) - real(8), allocatable :: total(:,:,:) ! total cross section - real(8), allocatable :: absorption(:,:,:) ! absorption cross section - real(8), allocatable :: scatter(:,:,:,:,:) ! scattering information - real(8), allocatable :: nu_fission(:,:,:,:) ! fission matrix (Gout x Gin) - real(8), allocatable :: k_fission(:,:,:) ! kappa-fission - real(8), allocatable :: fission(:,:,:) ! neutron production - real(8), allocatable :: chi(:,:,:) ! Fission Spectra - real(8), allocatable :: mult(:,:,:,:) ! Scatter multiplicity (Gout x Gin) - - ! In all cases, right-most indices are theta, phi - integer :: n_pol ! Number of polar angles - integer :: n_azi ! Number of azimuthal angles - real(8), allocatable :: polar(:) ! polar angles - real(8), allocatable :: azimuthal(:) ! azimuthal angles - - contains - procedure :: init => nuclideangle_init ! Initialize Nuclidic MGXS Data - procedure :: print => nuclideangle_print ! Gets Size of Data w/in Object - procedure :: get_xs => nuclideangle_get_xs ! Gets Size of Data w/in Object - procedure :: calc_f => nuclideangle_calc_f ! Calcs f given mu - end type NuclideAngle - -!=============================================================================== -! NUCLIDEMGCONTAINER pointer array for storing Nuclides -!=============================================================================== - - type NuclideMGContainer - class(NuclideMG), pointer :: obj - end type NuclideMGContainer + procedure :: clear => nuclide_clear + procedure :: print => nuclide_print + procedure :: nu => nuclide_nu + end type Nuclide !=============================================================================== ! NUCLIDE0K temporarily contains all 0K cross section data and other parameters -! needed to treat resonance scattering before transferring them to NuclideCE +! needed to treat resonance scattering before transferring them to Nuclide !=============================================================================== type Nuclide0K @@ -257,7 +119,6 @@ module nuclide_header ! Information for URR probability table use logical :: use_ptable ! in URR range with probability tables? - real(8) :: last_prn end type NuclideMicroXS !=============================================================================== @@ -296,469 +157,143 @@ module nuclide_header contains !=============================================================================== -! NUCLIDE_*_INIT reads in the data from the XML file, as already accessed +! NUCLIDE_CLEAR resets and deallocates data in Nuclide !=============================================================================== - subroutine nuclidemg_init(this, node_xsdata) - class(NuclideMG), intent(inout) :: this ! Working Object - type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml + subroutine nuclide_clear(this) - type(Node), pointer :: node_legendre_mu - character(MAX_LINE_LEN) :: temp_str - logical :: enable_leg_mu - - ! Load the data - call get_node_value(node_xsdata, "name", this % name) - this % name = to_lower(this % name) - if (check_for_node(node_xsdata, "kT")) then - call get_node_value(node_xsdata, "kT", this % kT) - else - this % kT = ZERO - end if - if (check_for_node(node_xsdata, "zaid")) then - call get_node_value(node_xsdata, "zaid", this % zaid) - else - this % zaid = -1 - end if - if (check_for_node(node_xsdata, "scatt_type")) then - call get_node_value(node_xsdata, "scatt_type", temp_str) - temp_str = trim(to_lower(temp_str)) - if (temp_str == 'legendre') then - this % scatt_type = ANGLE_LEGENDRE - else if (temp_str == 'histogram') then - this % scatt_type = ANGLE_HISTOGRAM - else if (temp_str == 'tabular') then - this % scatt_type = ANGLE_TABULAR - else - call fatal_error("Invalid Scatt Type Option!") - end if - else - this % scatt_type = ANGLE_LEGENDRE - end if - - if (check_for_node(node_xsdata, "order")) then - call get_node_value(node_xsdata, "order", this % order) - else - call fatal_error("Order Must Be Provided!") - end if - - ! Get scattering treatment - if (check_for_node(node_xsdata, "tabular_legendre")) then - call get_node_ptr(node_xsdata, "tabular_legendre", node_legendre_mu) - if (check_for_node(node_legendre_mu, "enable")) then - call get_node_value(node_legendre_mu, "enable", temp_str) - temp_str = trim(to_lower(temp_str)) - if (temp_str == 'true' .or. temp_str == '1') then - enable_leg_mu = .true. - elseif (temp_str == 'false' .or. temp_str == '0') then - enable_leg_mu = .false. - this % legendre_mu_points = 1 - else - call fatal_error("Unrecognized tabular_legendre/enable: " // temp_str) - end if - else - enable_leg_mu = .true. - this % legendre_mu_points = 33 - end if - if (enable_leg_mu .and. & - check_for_node(node_legendre_mu, "num_points")) then - call get_node_value(node_legendre_mu, "num_points", & - this % legendre_mu_points) - if (this % legendre_mu_points <= 0) then - call fatal_error("num_points element must be positive and non-zero!") - end if - this % legendre_mu_points = -1 * this % legendre_mu_points - end if - else - this % legendre_mu_points = 1 - end if - - if (check_for_node(node_xsdata, "fissionable")) then - call get_node_value(node_xsdata, "fissionable", temp_str) - temp_str = to_lower(temp_str) - if (trim(temp_str) == 'true' .or. trim(temp_str) == '1') then - this % fissionable = .true. - else - this % fissionable = .false. - end if - else - call fatal_error("Fissionable element must be set!") - end if - - end subroutine nuclidemg_init - - subroutine nuclideiso_init(this, node_xsdata, groups, get_kfiss, get_fiss) - class(NuclideIso), intent(inout) :: this ! Working Object - type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml - integer, intent(in) :: groups ! Number of Energy groups - logical, intent(in) :: get_kfiss ! Need Kappa-Fission? - logical, intent(in) :: get_fiss ! Need fiss data? - - real(8), allocatable :: temp_arr(:) - integer :: arr_len - integer :: order_dim - - ! Call generic data gathering routine - call nuclidemg_init(this, node_xsdata) - - ! Load the more specific data - if (this % fissionable) then - - if (check_for_node(node_xsdata, "chi")) then - ! Get chi - allocate(this % chi(groups)) - call get_node_array(node_xsdata, "chi", this % chi) - - ! Get nu_fission (as a vector) - if (check_for_node(node_xsdata, "nu_fission")) then - allocate(temp_arr(groups * 1)) - call get_node_array(node_xsdata, "nu_fission", temp_arr) - allocate(this % nu_fission(groups, 1)) - this % nu_fission = reshape(temp_arr, (/groups, 1/)) - deallocate(temp_arr) - else - call fatal_error("If fissionable, must provide nu_fission!") - end if - - else - ! Get nu_fission (as a matrix) - if (check_for_node(node_xsdata, "nu_fission")) then - - allocate(temp_arr(groups*groups)) - call get_node_array(node_xsdata, "nu_fission", temp_arr) - allocate(this % nu_fission(groups, groups)) - this % nu_fission = reshape(temp_arr, (/groups, groups/)) - deallocate(temp_arr) - else - call fatal_error("If fissionable, must provide nu_fission!") - end if - end if - if (get_fiss) then - allocate(this % fission(groups)) - if (check_for_node(node_xsdata, "fission")) then - call get_node_array(node_xsdata, "fission", this % fission) - else - call fatal_error("Fission data missing, required due to fission& - & tallies in tallies.xml file!") - end if - end if - if (get_kfiss) then - allocate(this % k_fission(groups)) - if (check_for_node(node_xsdata, "kappa_fission")) then - call get_node_array(node_xsdata, "kappa_fission", this % k_fission) - else - call fatal_error("kappa_fission data missing, required due to & - &kappa-fission tallies in tallies.xml file!") - end if - end if - end if - - allocate(this % absorption(groups)) - if (check_for_node(node_xsdata, "absorption")) then - call get_node_array(node_xsdata, "absorption", this % absorption) - else - call fatal_error("Must provide absorption!") - end if - - if (this % scatt_type == ANGLE_LEGENDRE) then - order_dim = this % order + 1 - else if (this % scatt_type == ANGLE_HISTOGRAM) then - order_dim = this % order - else if (this % scatt_type == ANGLE_TABULAR) then - order_dim = this % order - end if - - allocate(this % scatter(groups, groups, order_dim)) - if (check_for_node(node_xsdata, "scatter")) then - allocate(temp_arr(groups * groups * order_dim)) - call get_node_array(node_xsdata, "scatter", temp_arr) - this % scatter = reshape(temp_arr, (/groups, groups, order_dim/)) - deallocate(temp_arr) - else - call fatal_error("Must provide scatter!") - return - end if - - - allocate(this % total(groups)) - if (check_for_node(node_xsdata, "total")) then - call get_node_array(node_xsdata, "total", this % total) - else - this % total = this % absorption + sum(this%scatter(:,:,1),dim=1) - end if - - ! Get Mult Data - allocate(this % mult(groups, groups)) - if (check_for_node(node_xsdata, "multiplicity")) then - arr_len = get_arraysize_double(node_xsdata, "multiplicity") - if (arr_len == groups * groups) then - allocate(temp_arr(arr_len)) - call get_node_array(node_xsdata, "multiplicity", temp_arr) - this % mult = reshape(temp_arr, (/groups, groups/)) - deallocate(temp_arr) - else - call fatal_error("Multiplicity length not same as number of groups& - & squared!") - return - end if - else - this % mult = ONE - end if - - end subroutine nuclideiso_init - - subroutine nuclideangle_init(this, node_xsdata, groups, get_kfiss, get_fiss) - class(NuclideAngle), intent(inout) :: this ! Working Object - type(Node), pointer, intent(in) :: node_xsdata ! Data from MGXS xml - integer, intent(in) :: groups ! Number of Energy groups - logical, intent(in) :: get_kfiss ! Need Kappa-Fission? - logical, intent(in) :: get_fiss ! Should we get fiss data? - - real(8), allocatable :: temp_arr(:) - integer :: arr_len - real(8) :: dangle - integer :: iangle - integer :: order_dim - - ! Call generic data gathering routine - call nuclidemg_init(this, node_xsdata) - - if (this % scatt_type == ANGLE_LEGENDRE) then - order_dim = this % order + 1 - else if (this % scatt_type == ANGLE_HISTOGRAM) then - order_dim = this % order - else if (this % scatt_type == ANGLE_TABULAR) then - order_dim = this % order - end if - - if (check_for_node(node_xsdata, "num_polar")) then - call get_node_value(node_xsdata, "num_polar", this % n_pol) - else - call fatal_error("num_polar Must Be Provided!") - end if - - if (check_for_node(node_xsdata, "num_azimuthal")) then - call get_node_value(node_xsdata, "num_azimuthal", this % n_azi) - else - call fatal_error("num_azimuthal Must Be Provided!") - end if - - ! Load angle data, if present (else equally spaced) - allocate(this % polar(this % n_pol)) - allocate(this % azimuthal(this % n_azi)) - if (check_for_node(node_xsdata, "polar")) then - call fatal_error("User-Specified polar angle bins not yet supported!") - ! When this feature is supported, this line will be activated - call get_node_array(node_xsdata, "polar", this % polar) - else - dangle = PI / real(this % n_pol,8) - do iangle = 1, this % n_pol - this % polar(iangle) = (real(iangle,8) - HALF) * dangle - end do - end if - if (check_for_node(node_xsdata, "azimuthal")) then - call fatal_error("User-Specified azimuthal angle bins not yet supported!") - ! When this feature is supported, this line will be activated - call get_node_array(node_xsdata, "azimuthal", this % azimuthal) - else - dangle = TWO * PI / real(this % n_azi,8) - do iangle = 1, this % n_azi - this % azimuthal(iangle) = -PI + (real(iangle,8) - HALF) * dangle - end do - end if - - ! Load the more specific data - if (this % fissionable) then - - if (check_for_node(node_xsdata, "chi")) then - ! Get chi - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "chi", temp_arr) - allocate(this % chi(groups, this % n_azi, this % n_pol)) - this % chi = reshape(temp_arr, (/groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - - ! Get nu_fission (as a vector) - if (check_for_node(node_xsdata, "nu_fission")) then - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "nu_fission", temp_arr) - allocate(this % nu_fission(groups, 1, this % n_azi, this % n_pol)) - this % nu_fission = reshape(temp_arr, (/groups, 1, this % n_azi, & - this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("If fissionable, must provide nu_fission!") - end if - - else - ! Get nu_fission (as a matrix) - if (check_for_node(node_xsdata, "nu_fission")) then - - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "nu_fission", temp_arr) - allocate(this % nu_fission(groups, groups, this % n_azi, this % n_pol)) - this % nu_fission = reshape(temp_arr, (/groups, groups, & - this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("If fissionable, must provide nu_fission!") - end if - end if - if (get_fiss) then - if (check_for_node(node_xsdata, "fission")) then - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "fission", temp_arr) - allocate(this % fission(groups, this % n_azi, this % n_pol)) - this % fission = reshape(temp_arr, (/groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("Fission data missing, required due to fission& - & tallies in tallies.xml file!") - end if - end if - if (get_kfiss) then - if (check_for_node(node_xsdata, "kappa_fission")) then - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "kappa_fission", temp_arr) - allocate(this % k_fission(groups, this % n_azi, this % n_pol)) - this % k_fission = reshape(temp_arr, (/groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("kappa_fission data missing, required due to & - &kappa-fission tallies in tallies.xml file!") - end if - end if - end if - - if (check_for_node(node_xsdata, "absorption")) then - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "absorption", temp_arr) - allocate(this % absorption(groups, this % n_azi, this % n_pol)) - this % absorption = reshape(temp_arr, (/groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("Must provide absorption!") - end if - - allocate(this % scatter(groups, groups, order_dim, this % n_azi, this % n_pol)) - if (check_for_node(node_xsdata, "scatter")) then - allocate(temp_arr(groups * groups * order_dim * this % n_azi * this%n_pol)) - call get_node_array(node_xsdata, "scatter", temp_arr) - this % scatter = reshape(temp_arr, (/groups, groups, order_dim, & - this%n_azi,this%n_pol/)) - deallocate(temp_arr) - else - call fatal_error("Must provide scatter!") - end if - - if (check_for_node(node_xsdata, "total")) then - allocate(temp_arr(groups * this % n_azi * this % n_pol)) - call get_node_array(node_xsdata, "total", temp_arr) - allocate(this % total(groups, this % n_azi, this % n_pol)) - this % total = reshape(temp_arr, (/groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - this % total = this % absorption + sum(this%scatter(:,:,1,:,:),dim=1) - end if - - ! Get Mult Data - allocate(this % mult(groups, groups, this % n_azi, this % n_pol)) - if (check_for_node(node_xsdata, "multiplicity")) then - arr_len = get_arraysize_double(node_xsdata, "multiplicity") - if (arr_len == groups * groups * this % n_azi * this % n_pol) then - allocate(temp_arr(arr_len)) - call get_node_array(node_xsdata, "multiplicity", temp_arr) - this % mult = reshape(temp_arr, (/groups, groups, this % n_azi, this % n_pol/)) - deallocate(temp_arr) - else - call fatal_error("Multiplicity Length Does Not Match!") - end if - else - this % mult = ONE - end if - - end subroutine nuclideangle_init - -!=============================================================================== -! NUCLIDECE_CLEAR resets and deallocates data in Nuclide, NuclideIso -! or NuclideAngle -!=============================================================================== - - subroutine nuclidece_clear(this) - - class(NuclideCE), intent(inout) :: this ! The Nuclide object to clear + class(Nuclide), intent(inout) :: this ! The Nuclide object to clear integer :: i ! Loop counter if (associated(this % urr_data)) deallocate(this % urr_data) - if (allocated(this % reactions)) then - do i = 1, size(this % reactions) - call this % reactions(i) % clear() - end do - end if - call this % reaction_index % clear() - end subroutine nuclidece_clear + end subroutine nuclide_clear + +!=============================================================================== +! NUCLIDE_NU is an interface to the number of fission neutrons produced +!=============================================================================== + + function nuclide_nu(this, E, emission_mode, group) result(nu) + class(Nuclide), intent(in) :: this + real(8), intent(in) :: E + integer, intent(in) :: emission_mode + integer, optional, intent(in) :: group + real(8) :: nu + + integer :: i + + if (.not. this % fissionable) then + nu = ZERO + return + end if + + select case (emission_mode) + case (EMISSION_PROMPT) + associate (product => this % reactions(this % index_fission(1)) % products(1)) + nu = product % yield % evaluate(E) + end associate + + case (EMISSION_DELAYED) + if (this % n_precursor > 0) then + if (present(group)) then + ! If delayed group specified, determine yield immediately + associate(p => this % reactions(this % index_fission(1)) % products(1 + group)) + nu = p % yield % evaluate(E) + end associate + + else + nu = ZERO + + associate (rx => this % reactions(this % index_fission(1))) + do i = 2, size(rx % products) + associate (product => rx % products(i)) + ! Skip any non-neutron products + if (product % particle /= NEUTRON) exit + + ! Evaluate yield + if (product % emission_mode == EMISSION_DELAYED) then + nu = nu + product % yield % evaluate(E) + end if + end associate + end do + end associate + end if + else + nu = ZERO + end if + + case (EMISSION_TOTAL) + if (allocated(this % total_nu)) then + nu = this % total_nu % evaluate(E) + else + associate (rx => this % reactions(this % index_fission(1))) + nu = rx % products(1) % yield % evaluate(E) + end associate + end if + end select + + end function nuclide_nu + !=============================================================================== ! NUCLIDE*_PRINT displays information about a continuous-energy neutron ! cross_section table and its reactions and secondary angle/energy distributions !=============================================================================== - subroutine nuclidece_print(this, unit) - class(NuclideCE), intent(in) :: this - integer, intent(in), optional :: unit + subroutine nuclide_print(this, unit) + class(Nuclide), intent(in) :: this + integer, intent(in), optional :: unit - integer :: i ! loop index over nuclides - integer :: unit_ ! unit to write to - integer :: size_xs ! memory used for cross-sections (bytes) - integer :: size_urr ! memory used for probability tables (bytes) - type(UrrData), pointer :: urr + integer :: i ! loop index over nuclides + integer :: unit_ ! unit to write to + integer :: size_xs ! memory used for cross-sections (bytes) + integer :: size_urr ! memory used for probability tables (bytes) - ! set default unit for writing information - if (present(unit)) then - unit_ = unit - else - unit_ = OUTPUT_UNIT - end if + ! set default unit for writing information + if (present(unit)) then + unit_ = unit + else + unit_ = OUTPUT_UNIT + end if - ! Initialize totals - size_urr = 0 - size_xs = 0 + ! Initialize totals + size_urr = 0 + size_xs = 0 - ! Basic nuclide information - write(unit_,*) 'Nuclide ' // trim(this % name) - write(unit_,*) ' zaid = ' // trim(to_str(this % zaid)) - write(unit_,*) ' awr = ' // trim(to_str(this % awr)) - write(unit_,*) ' kT = ' // trim(to_str(this % kT)) - write(unit_,*) ' # of grid points = ' // trim(to_str(this % n_grid)) - write(unit_,*) ' Fissionable = ', this % fissionable - write(unit_,*) ' # of fission reactions = ' // trim(to_str(this % n_fission)) - write(unit_,*) ' # of reactions = ' // trim(to_str(this % n_reaction)) + ! Basic nuclide information + write(unit_,*) 'Nuclide ' // trim(this % name) + write(unit_,*) ' zaid = ' // trim(to_str(this % zaid)) + write(unit_,*) ' awr = ' // trim(to_str(this % awr)) + write(unit_,*) ' kT = ' // trim(to_str(this % kT)) + write(unit_,*) ' # of grid points = ' // trim(to_str(this % n_grid)) + write(unit_,*) ' Fissionable = ', this % fissionable + write(unit_,*) ' # of fission reactions = ' // trim(to_str(this % n_fission)) + write(unit_,*) ' # of reactions = ' // trim(to_str(this % n_reaction)) - ! Information on each reaction - write(unit_,*) ' Reaction Q-value COM IE' - do i = 1, this % n_reaction - associate (rxn => this % reactions(i)) - write(unit_,'(3X,A11,1X,F8.3,3X,L1,3X,I6)') & - reaction_name(rxn % MT), rxn % Q_value, rxn % scatter_in_cm, & - rxn % threshold + ! Information on each reaction + write(unit_,*) ' Reaction Q-value COM IE' + do i = 1, this % n_reaction + associate (rxn => this % reactions(i)) + write(unit_,'(3X,A11,1X,F8.3,3X,L1,3X,I6)') & + reaction_name(rxn % MT), rxn % Q_value, rxn % scatter_in_cm, & + rxn % threshold - ! Accumulate data size - size_xs = size_xs + (this % n_grid - rxn%threshold + 1) * 8 - end associate - end do + ! Accumulate data size + size_xs = size_xs + (this % n_grid - rxn%threshold + 1) * 8 + end associate + end do - ! Add memory required for summary reactions (total, absorption, fission, - ! nu-fission) - size_xs = 8 * this % n_grid * 4 + ! Add memory required for summary reactions (total, absorption, fission, + ! nu-fission) + size_xs = 8 * this % n_grid * 4 - ! Write information about URR probability tables - size_urr = 0 - if (this % urr_present) then - urr => this % urr_data + ! Write information about URR probability tables + size_urr = 0 + if (this % urr_present) then + associate(urr => this % urr_data) write(unit_,*) ' Unresolved resonance probability table:' write(unit_,*) ' # of energies = ' // trim(to_str(urr % n_energy)) write(unit_,*) ' # of probabilities = ' // trim(to_str(urr % n_prob)) @@ -771,356 +306,17 @@ module nuclide_header ! Calculate memory used by probability tables and add to total size_urr = urr % n_energy * (urr % n_prob * 6 + 1) * 8 - end if + end associate + end if - ! Write memory used - write(unit_,*) ' Memory Requirements' - write(unit_,*) ' Cross sections = ' // trim(to_str(size_xs)) // ' bytes' - write(unit_,*) ' Probability Tables = ' // & - trim(to_str(size_urr)) // ' bytes' + ! Write memory used + write(unit_,*) ' Memory Requirements' + write(unit_,*) ' Cross sections = ' // trim(to_str(size_xs)) // ' bytes' + write(unit_,*) ' Probability Tables = ' // & + trim(to_str(size_urr)) // ' bytes' - ! Blank line at end of nuclide - write(unit_,*) - end subroutine nuclidece_print - - subroutine nuclidemg_print(this, unit_) - class(NuclideMG), intent(in) :: this - integer, intent(in) :: unit_ - - character(MAX_LINE_LEN) :: temp_str - - ! Basic nuclide information - write(unit_,*) 'Nuclide ' // trim(this % name) - if (this % zaid > 0) then - ! Dont print if data was macroscopic and thus zaid & AWR would be nonsense - write(unit_,*) ' zaid = ' // trim(to_str(this % zaid)) - write(unit_,*) ' awr = ' // trim(to_str(this % awr)) - end if - write(unit_,*) ' kT = ' // trim(to_str(this % kT)) - if (this % scatt_type == ANGLE_LEGENDRE) then - temp_str = "Legendre" - write(unit_,*) ' Scattering Type = ' // trim(temp_str) - write(unit_,*) ' # of Scatter Moments = ' // & - trim(to_str(this % order)) - else if (this % scatt_type == ANGLE_HISTOGRAM) then - temp_str = "Histogram" - write(unit_,*) ' Scattering Type = ' // trim(temp_str) - write(unit_,*) ' # of Scatter Bins = ' // & - trim(to_str(this % order)) - else if (this % scatt_type == ANGLE_TABULAR) then - temp_str = "Tabular" - write(unit_,*) ' Scattering Type = ' // trim(temp_str) - write(unit_,*) ' # of Scatter Points = ' // trim(to_str(this % order)) - end if - write(unit_,*) ' Fissionable = ', this % fissionable - - end subroutine nuclidemg_print - - subroutine nuclideiso_print(this, unit) - - class(NuclideIso), intent(in) :: this - integer, optional, intent(in) :: unit - - integer :: unit_ ! unit to write to - integer :: size_total, size_scattmat, size_mgxs - - ! set default unit for writing information - if (present(unit)) then - unit_ = unit - else - unit_ = OUTPUT_UNIT - end if - - ! Write Basic Nuclide Information - call nuclidemg_print(this, unit_) - - ! Determine size of mgxs and scattering matrices - size_scattmat = (size(this % scatter) + size(this % mult)) * 8 - size_mgxs = size(this % total) + size(this % absorption) + & - size(this % nu_fission) + size(this % k_fission) + & - size(this % fission) + size(this % chi) - size_mgxs = size_mgxs * 8 - - ! Calculate total memory - size_total = size_scattmat + size_mgxs - - ! Write memory used - write(unit_,*) ' Memory Requirements' - write(unit_,*) ' Cross sections = ' // trim(to_str(size_mgxs)) // ' bytes' - write(unit_,*) ' Scattering Matrices = ' // & - trim(to_str(size_scattmat)) // ' bytes' - write(unit_,*) ' Total = ' // trim(to_str(size_total)) // ' bytes' - - ! Blank line at end of nuclide - write(unit_,*) - - end subroutine nuclideiso_print - - subroutine nuclideangle_print(this, unit) - - class(NuclideAngle), intent(in) :: this - integer, optional, intent(in) :: unit - - integer :: unit_ ! unit to write to - integer :: size_total, size_scattmat, size_mgxs - - ! set default unit for writing information - if (present(unit)) then - unit_ = unit - else - unit_ = OUTPUT_UNIT - end if - - ! Write Basic Nuclide Information - call nuclidemg_print(this, unit_) - write(unit_,*) ' # of Polar Angles = ' // trim(to_str(this % n_pol)) - write(unit_,*) ' # of Azimuthal Angles = ' // trim(to_str(this % n_azi)) - - ! Determine size of mgxs and scattering matrices - size_scattmat = (size(this % scatter) + size(this % mult)) * 8 - size_mgxs = size(this % total) + size(this % absorption) + & - size(this % nu_fission) + size(this % k_fission) + & - size(this % fission) + size(this % chi) - size_mgxs = size_mgxs * 8 - - ! Calculate total memory - size_total = size_scattmat + size_mgxs - - ! Write memory used - write(unit_,*) ' Memory Requirements' - write(unit_,*) ' Cross sections = ' // trim(to_str(size_mgxs)) // ' bytes' - write(unit_,*) ' Scattering Matrices = ' // & - trim(to_str(size_scattmat)) // ' bytes' - write(unit_,*) ' Total = ' // trim(to_str(size_total)) // ' bytes' - - ! Blank line at end of nuclide - write(unit_,*) - - - end subroutine nuclideangle_print - -!=============================================================================== -! NUCLIDE*_GET_XS Returns the requested data type -!=============================================================================== - - function nuclideiso_get_xs(this, g, xstype, gout, uvw, mu, i_azi, i_pol) & - result(xs) - class(NuclideIso), intent(in) :: this - integer, intent(in) :: g ! Incoming Energy group - character(*), intent(in) :: xstype ! Cross Section Type - integer, optional, intent(in) :: gout ! Outgoing Group - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - real(8), optional, intent(in) :: mu ! Change in angle - integer, optional, intent(in) :: i_azi ! Azimuthal Index - integer, optional, intent(in) :: i_pol ! Polar Index - real(8) :: xs ! Resultant xs - - xs = ZERO - - if ((xstype == 'nu_fission' .or. xstype == 'fission' .or. xstype =='chi' & - .or. xstype =='k_fission') .and. (.not. this % fissionable)) then - return - end if - - if (present(gout)) then - select case(xstype) - case('mult') - xs = this % mult(gout,g) - case('nu_fission') - xs = this % nu_fission(gout,g) - case('f_mu', 'f_mu/mult') - xs = this % calc_f(g, gout, mu) - if (xstype == 'f_mu/mult') then - xs = xs / this % mult(gout,g) - end if - end select - else - select case(xstype) - case('total') - xs = this % total(g) - case('absorption') - xs = this % absorption(g) - case('fission') - xs = this % fission(g) - case('k_fission') - if (allocated(this % k_fission)) then - xs = this % k_fission(g) - end if - case('chi') - xs = this % chi(g) - case('scatter') - xs = this % total(g) - this % absorption(g) - end select - end if - end function nuclideiso_get_xs - - function nuclideangle_get_xs(this, g, xstype, gout, uvw, mu, i_azi, i_pol) & - result(xs) - class(NuclideAngle), intent(in) :: this - integer, intent(in) :: g ! Incoming Energy group - character(*), intent(in) :: xstype ! Cross Section Type - integer, optional, intent(in) :: gout ! Outgoing Group - real(8), optional, intent(in) :: mu ! Change in angle - real(8), optional, intent(in) :: uvw(3) ! Requested Angle - integer, optional, intent(in) :: i_azi ! Azimuthal Index - integer, optional, intent(in) :: i_pol ! Polar Index - real(8) :: xs ! Resultant xs - - integer :: i_azi_, i_pol_ - - xs = ZERO - - if ((xstype == 'nu_fission' .or. xstype == 'fission' .or. xstype =='chi' & - .or. xstype =='k_fission') .and. (.not. this % fissionable)) then - return - end if - - if (present(i_azi) .and. present(i_pol)) then - i_azi_ = i_azi - i_pol_ = i_pol - else - call find_angle(this % polar, this % azimuthal, uvw, i_azi_, i_pol_) - end if - - if (present(gout)) then - select case(xstype) - case('mult') - xs = this % mult(gout,g,i_azi_,i_pol_) - case('nu_fission') - xs = this % nu_fission(gout,g,i_azi_,i_pol_) - case('chi') - xs = this % chi(gout,i_azi_,i_pol_) - case('f_mu', 'f_mu/mult') - xs = this % calc_f(g, gout, mu, I_AZI=i_azi_, I_POL=i_pol_) - if (xstype == 'f_mu/mult') then - xs = xs / this % mult(gout,g,i_azi_,i_pol_) - end if - end select - else - select case(xstype) - case('total') - xs = this % total(g,i_azi_,i_pol_) - case('absorption') - xs = this % absorption(g,i_azi_,i_pol_) - case('fission') - xs = this % fission(g,i_azi_,i_pol_) - case('k_fission') - if (allocated(this % k_fission)) then - xs = this % k_fission(g,i_azi_,i_pol_) - end if - case('chi') - xs = this % chi(g,i_azi_,i_pol_) - case('scatter') - xs = this % total(g,i_azi_,i_pol_) - this % absorption(g,i_azi_,i_pol_) - end select - end if - - end function nuclideangle_get_xs - -!=============================================================================== -! NUCLIDE*_CALC_F Finds the value of f(mu), the scattering angle probability, -! given mu -!=============================================================================== - - pure function nuclideiso_calc_f(this, gin, gout, mu, uvw, i_azi, i_pol) & - result(f) - class(NuclideIso), intent(in) :: this - integer, intent(in) :: gin ! Incoming Energy Group - integer, intent(in) :: gout ! Outgoing Energy Group - real(8), intent(in) :: mu ! Angle of interest - real(8), intent(in), optional :: uvw(3) ! Direction vector - integer, intent(in), optional :: i_azi ! Incoming Energy Group - integer, intent(in), optional :: i_pol ! Outgoing Energy Group - real(8) :: f ! Return value of f(mu) - - real(8) :: dmu, r - integer :: imu - - if (this % scatt_type == ANGLE_LEGENDRE) then - f = evaluate_legendre(this % scatter(gout,gin,:), mu) - else if (this % scatt_type == ANGLE_TABULAR) then - dmu = TWO / real(this % order - 1,8) - ! Find mu bin algebraically, knowing that the spacing is equal - f = (mu + ONE) / dmu + ONE - imu = floor(f) - ! But save the amount that mu is past the previous index - ! so we can use interpolation later. - f = f - real(imu,8) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % scatter, dim=3)) then - imu = imu - 1 - end if - - ! Now intepolate to find f(mu) - r = f / dmu - f = (ONE - r) * this % scatter(gout,gin,imu) + & - r * this % scatter(gout,gin,imu+1) - else ! (ANGLE_HISTOGRAM) - dmu = TWO / real(this % order,8) - ! Find mu bin algebraically, knowing that the spacing is equal - imu = floor((mu + ONE) / dmu + ONE) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % scatter, dim=3)) then - imu = imu - 1 - end if - f = this % scatter(gout, gin, imu) - - end if - - end function nuclideiso_calc_f - - pure function nuclideangle_calc_f(this, gin, gout, mu, uvw, i_azi, & - i_pol) result(f) - class(NuclideAngle), intent(in) :: this - integer, intent(in) :: gin ! Incoming Energy Group - integer, intent(in) :: gout ! Outgoing Energy Group - real(8), intent(in) :: mu ! Angle of interest - real(8), intent(in), optional :: uvw(3) ! Direction vector - integer, intent(in), optional :: i_azi ! Incoming Energy Group - integer, intent(in), optional :: i_pol ! Outgoing Energy Group - real(8) :: f ! Return value of f(mu) - - real(8) :: dmu, r - integer :: imu - integer :: i_azi_, i_pol_ - if (present(i_azi) .and. present(i_pol)) then - i_azi_ = i_azi - i_pol_ = i_pol - else if (present(uvw)) then - call find_angle(this % polar, this % azimuthal, uvw, i_azi_, i_pol_) - end if - - if (this % scatt_type == ANGLE_LEGENDRE) then - f = evaluate_legendre(this % scatter(gout,gin,:,i_azi_,i_pol_), mu) - else if (this % scatt_type == ANGLE_TABULAR) then - dmu = TWO / real(this % order - 1,8) - ! Find mu bin algebraically, knowing that the spacing is equal - f = (mu + ONE) / dmu + ONE - imu = floor(f) - ! But save the amount that mu is past the previous index - ! so we can use interpolation later. - f = f - real(imu,8) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % scatter, dim=3)) then - imu = imu - 1 - end if - - ! Now intepolate to find f(mu) - r = f / dmu - f = (ONE - r) * this % scatter(gout,gin,imu,i_azi_,i_pol_) + & - r * this % scatter(gout,gin,imu+1,i_azi_,i_pol_) - else ! (ANGLE_HISTOGRAM) - dmu = TWO / real(this % order,8) - ! Find mu bin algebraically, knowing that the spacing is equal - imu = floor((mu + ONE) / dmu + ONE) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % scatter, dim=3)) then - imu = imu - 1 - end if - f = this % scatter(gout, gin, imu,i_azi_,i_pol_) - - end if - - end function nuclideangle_calc_f + ! Blank line at end of nuclide + write(unit_,*) + end subroutine nuclide_print end module nuclide_header diff --git a/src/output.F90 b/src/output.F90 index 125fe010b..768019f8d 100644 --- a/src/output.F90 +++ b/src/output.F90 @@ -2,7 +2,6 @@ module output use, intrinsic :: ISO_FORTRAN_ENV - use ace_header, only: Reaction, UrrData use constants use endf, only: reaction_name use error, only: fatal_error, warning @@ -53,9 +52,9 @@ contains ! Write version information write(UNIT=OUTPUT_UNIT, FMT=*) & - ' Copyright: 2011-2015 Massachusetts Institute of Technology' + ' Copyright: 2011-2016 Massachusetts Institute of Technology' write(UNIT=OUTPUT_UNIT, FMT=*) & - ' License: http://mit-crpg.github.io/openmc/license.html' + ' License: http://openmc.readthedocs.io/en/latest/license.html' write(UNIT=OUTPUT_UNIT, FMT='(6X,"Version:",8X,I1,".",I1,".",I1)') & VERSION_MAJOR, VERSION_MINOR, VERSION_RELEASE #ifdef GIT_SHA1 @@ -336,10 +335,10 @@ contains ! Open log file for writing open(NEWUNIT=unit_xs, FILE=path, STATUS='replace', ACTION='write') - ! Write header - call header("CROSS SECTION TABLES", unit=unit_xs) - if (run_CE) then + ! Write header + call header("CROSS SECTION TABLES", unit=unit_xs) + NUCLIDE_LOOP: do i = 1, n_nuclides_total ! Print information about nuclide call nuclides(i) % print(unit=unit_xs) @@ -350,10 +349,17 @@ contains call sab_tables(i) % print(unit=unit_xs) end do SAB_TABLES_LOOP else + ! Write header + call header("MGXS LIBRARY TABLES", unit=unit_xs) NuclideMG_LOOP: do i = 1, n_nuclides_total ! Print information about nuclide call nuclides_mg(i) % obj % print(unit=unit_xs) end do NuclideMG_LOOP + call header("MATERIAL MGXS TABLES", unit=unit_xs) + MATERIAL_LOOP: do i = 1, n_materials + ! Print information about Materials + call macro_xs(i) % obj % print(unit=unit_xs) + end do MATERIAL_LOOP end if ! Close cross section summary file @@ -771,8 +777,6 @@ contains score_names(abs(SCORE_TOTAL)) = "Total Reaction Rate" score_names(abs(SCORE_SCATTER)) = "Scattering Rate" score_names(abs(SCORE_NU_SCATTER)) = "Scattering Production Rate" - score_names(abs(SCORE_TRANSPORT)) = "Transport Rate" - score_names(abs(SCORE_N_1N)) = "(n,1n) Rate" score_names(abs(SCORE_ABSORPTION)) = "Absorption Rate" score_names(abs(SCORE_FISSION)) = "Fission Rate" score_names(abs(SCORE_NU_FISSION)) = "Nu-Fission Rate" @@ -904,7 +908,11 @@ contains write(UNIT=unit_tally, FMT='(1X,2A,1X,A)') repeat(" ", indent), & "Total Material" else - i_listing = nuclides(i_nuclide) % listing + if (run_CE) then + i_listing = nuclides(i_nuclide) % listing + else + i_listing = nuclides_MG(i_nuclide) % obj % listing + end if write(UNIT=unit_tally, FMT='(1X,2A,1X,A)') repeat(" ", indent), & trim(xs_listings(i_listing) % alias) end if @@ -1159,7 +1167,7 @@ contains function get_label(t, i_filter) result(label) type(TallyObject), intent(in) :: t ! tally object integer, intent(in) :: i_filter ! index in filters array - character(100) :: label ! user-specified identifier + character(MAX_LINE_LEN) :: label ! user-specified identifier integer :: i ! index in cells/surfaces/etc array integer :: bin diff --git a/src/particle_header.F90 b/src/particle_header.F90 index 4ad4119b7..8544cb38b 100644 --- a/src/particle_header.F90 +++ b/src/particle_header.F90 @@ -202,7 +202,7 @@ contains this % last_g = int(src % E) this % E = energy_bin_avg(this % g) end if - this % last_E = src % E + this % last_E = this % E end subroutine initialize_from_source diff --git a/src/particle_restart.F90 b/src/particle_restart.F90 index 9d49a4f97..e5cca17bf 100644 --- a/src/particle_restart.F90 +++ b/src/particle_restart.F90 @@ -34,7 +34,7 @@ contains verbosity = 10 ! Initialize the particle to be tracked - call p%initialize() + call p % initialize() ! Read in the restart information call read_particle_restart(p, previous_run_mode) @@ -46,9 +46,9 @@ contains select case (previous_run_mode) case (MODE_EIGENVALUE) particle_seed = ((current_batch - 1)*gen_per_batch + & - current_gen - 1)*n_particles + p%id + current_gen - 1)*n_particles + p % id case (MODE_FIXEDSOURCE) - particle_seed = p%id + particle_seed = p % id end select call set_particle_seed(particle_seed) @@ -71,7 +71,7 @@ contains integer :: int_scalar integer(HID_T) :: file_id - character(MAX_WORD_LEN) :: mode + character(MAX_WORD_LEN) :: tempstr ! Write meessage call write_message("Loading particle restart file " & @@ -81,32 +81,32 @@ contains file_id = file_open(path_particle_restart, 'r') ! Read data from file - call read_dataset(file_id, 'filetype', int_scalar) - call read_dataset(file_id, 'revision', int_scalar) - call read_dataset(file_id, 'current_batch', current_batch) - call read_dataset(file_id, 'gen_per_batch', gen_per_batch) - call read_dataset(file_id, 'current_gen', current_gen) - call read_dataset(file_id, 'n_particles', n_particles) - call read_dataset(file_id, 'run_mode', mode) - select case (mode) + call read_dataset(tempstr, file_id, 'filetype') + call read_dataset(int_scalar, file_id, 'revision') + call read_dataset(current_batch, file_id, 'current_batch') + call read_dataset(gen_per_batch, file_id, 'gen_per_batch') + call read_dataset(current_gen, file_id, 'current_gen') + call read_dataset(n_particles, file_id, 'n_particles') + call read_dataset(tempstr, file_id, 'run_mode') + select case (tempstr) case ('k-eigenvalue') previous_run_mode = MODE_EIGENVALUE case ('fixed source') previous_run_mode = MODE_FIXEDSOURCE end select - call read_dataset(file_id, 'id', p%id) - call read_dataset(file_id, 'weight', p%wgt) - call read_dataset(file_id, 'energy', p%E) - call read_dataset(file_id, 'energy_group', p%g) - call read_dataset(file_id, 'xyz', p%coord(1)%xyz) - call read_dataset(file_id, 'uvw', p%coord(1)%uvw) + call read_dataset(p % id, file_id, 'id') + call read_dataset(p % wgt, file_id, 'weight') + call read_dataset(p % E, file_id, 'energy') + call read_dataset(p % g, file_id, 'energy_group') + call read_dataset(p % coord(1) % xyz, file_id, 'xyz') + call read_dataset(p % coord(1) % uvw, file_id, 'uvw') ! Set particle last attributes - p%last_wgt = p%wgt - p%last_xyz = p%coord(1)%xyz - p%last_uvw = p%coord(1)%uvw - p%last_E = p%E - p%last_g = p%g + p % last_wgt = p % wgt + p % last_xyz = p % coord(1)%xyz + p % last_uvw = p % coord(1)%uvw + p % last_E = p % E + p % last_g = p % g ! Close hdf5 file call file_close(file_id) diff --git a/src/physics.F90 b/src/physics.F90 index e41b3b4e9..09a43aa99 100644 --- a/src/physics.F90 +++ b/src/physics.F90 @@ -1,13 +1,10 @@ module physics - use ace_header, only: Reaction use constants use cross_section, only: elastic_xs_0K use endf, only: reaction_name use error, only: fatal_error, warning - use fission, only: nu_total, nu_delayed use global - use interpolation, only: interpolate_tab1 use material_header, only: Material use math use mesh, only: get_mesh_indices @@ -16,7 +13,8 @@ module physics use particle_header, only: Particle use particle_restart_write, only: write_particle_restart use physics_common - use random_lcg, only: prn + use random_lcg, only: prn, advance_prn_seed, prn_set_stream + use reaction_header, only: Reaction use search, only: binary_search use secondary_uncorrelated, only: UncorrelatedAngleEnergy use string, only: to_str @@ -58,6 +56,13 @@ contains if (master) call warning("Killing neutron with extremely low energy") end if + ! Advance URR seed stream 'N' times after energy changes + if (p % E /= p % last_E) then + call prn_set_stream(STREAM_URR_PTABLE) + call advance_prn_seed(n_nuc_zaid_total) + call prn_set_stream(STREAM_TRACKING) + endif + end subroutine collision !=============================================================================== @@ -75,7 +80,7 @@ contains integer :: i_nuclide ! index in nuclides array integer :: i_nuc_mat ! index in material's nuclides array integer :: i_reaction ! index in nuc % reactions array - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc call sample_nuclide(p, 'total ', i_nuclide, i_nuc_mat) @@ -198,7 +203,7 @@ contains real(8) :: f real(8) :: prob real(8) :: cutoff - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc ! Get pointer to nuclide nuc => nuclides(i_nuclide) @@ -296,7 +301,7 @@ contains real(8) :: uvw_new(3) ! outgoing uvw for iso-in-lab scattering real(8) :: uvw_old(3) ! incoming uvw for iso-in-lab scattering real(8) :: phi ! azimuthal angle for iso-in-lab scattering - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc ! copy incoming direction uvw_old(:) = p % coord(1) % uvw @@ -411,7 +416,7 @@ contains real(8) :: v_cm(3) ! velocity of center-of-mass real(8) :: v_t(3) ! velocity of target nucleus real(8) :: uvw_cm(3) ! directional cosines in center-of-mass - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc ! get pointer to nuclide nuc => nuclides(i_nuclide) @@ -440,9 +445,9 @@ contains vel = sqrt(dot_product(v_n, v_n)) ! Sample scattering angle - select type (dist => rxn%secondary%distribution(1)%obj) + select type (dist => rxn % products(1) % distribution(1) % obj) type is (UncorrelatedAngleEnergy) - mu_cm = dist%angle%sample(E) + mu_cm = dist % angle % sample(E) end select ! Determine direction cosines in CM @@ -737,7 +742,7 @@ contains !=============================================================================== subroutine sample_target_velocity(nuc, v_target, E, uvw, v_neut, wgt, xs_eff) - type(NuclideCE), intent(in) :: nuc ! target nuclide at temperature T + type(Nuclide), intent(in) :: nuc ! target nuclide at temperature T real(8), intent(out) :: v_target(3) ! target velocity real(8), intent(in) :: v_neut(3) ! neutron velocity real(8), intent(in) :: E ! particle energy @@ -982,7 +987,7 @@ contains !=============================================================================== subroutine sample_cxs_target_velocity(nuc, v_target, E, uvw) - type(NuclideCE), intent(in) :: nuc ! target nuclide at temperature + type(Nuclide), intent(in) :: nuc ! target nuclide at temperature real(8), intent(out) :: v_target(3) real(8), intent(in) :: E real(8), intent(in) :: uvw(3) @@ -1066,11 +1071,9 @@ contains integer :: nu ! actual number of neutrons produced integer :: ijk(3) ! indices in ufs mesh real(8) :: nu_t ! total nu - real(8) :: mu ! fission neutron angular cosine - real(8) :: phi ! fission neutron azimuthal angle real(8) :: weight ! weight adjustment for ufs method logical :: in_mesh ! source site in ufs mesh? - type(NuclideCE), pointer :: nuc + type(Nuclide), pointer :: nuc ! Get pointers nuc => nuclides(i_nuclide) @@ -1138,25 +1141,12 @@ contains ! Set weight of fission bank site bank_array(i) % wgt = ONE/weight - ! Sample cosine of angle -- fission neutrons are always emitted - ! isotropically. Sometimes in ACE data, fission reactions actually have - ! an angular distribution listed, but for those that do, it's simply just - ! a uniform distribution in mu - mu = TWO * prn() - ONE + ! Sample delayed group and angle/energy for fission reaction + call sample_fission_neutron(nuc, nuc % reactions(i_reaction), & + p % E, bank_array(i)) - ! Sample azimuthal angle uniformly in [0,2*pi) - phi = TWO*PI*prn() - bank_array(i) % uvw(1) = mu - bank_array(i) % uvw(2) = sqrt(ONE - mu*mu) * cos(phi) - bank_array(i) % uvw(3) = sqrt(ONE - mu*mu) * sin(phi) - - ! Sample secondary energy distribution for fission reaction and set energy - ! in fission bank - bank_array(i) % E = sample_fission_energy(nuc, & - nuc % reactions(i_reaction), p) - - ! Set the delayed group of the neutron - bank_array(i) % delayed_group = p % delayed_group + ! Set delayed group on particle too + p % delayed_group = bank_array(i) % delayed_group ! Increment the number of neutrons born delayed if (p % delayed_group > 0) then @@ -1175,35 +1165,41 @@ contains end subroutine create_fission_sites !=============================================================================== -! SAMPLE_FISSION_ENERGY +! SAMPLE_FISSION_NEUTRON !=============================================================================== - function sample_fission_energy(nuc, rxn, p) result(E_out) + subroutine sample_fission_neutron(nuc, rxn, E_in, site) + type(Nuclide), intent(in) :: nuc + type(Reaction), intent(in) :: rxn + real(8), intent(in) :: E_in + type(Bank), intent(inout) :: site - type(NuclideCE), intent(in) :: nuc - type(Reaction), intent(in) :: rxn - type(Particle), intent(inout) :: p ! Particle causing fission - real(8) :: E_out ! outgoing energy of fission neutron - - integer :: j ! index on nu energy grid / precursor group - integer :: lc ! index before start of energies/nu values - integer :: NR ! number of interpolation regions - integer :: NE ! number of energies tabulated - integer :: n_sample ! number of times resampling + integer :: group ! index on nu energy grid / precursor group + integer :: n_sample ! number of resamples real(8) :: nu_t ! total nu real(8) :: nu_d ! delayed nu real(8) :: beta ! delayed neutron fraction real(8) :: xi ! random number real(8) :: yield ! delayed neutron precursor yield real(8) :: prob ! cumulative probability + real(8) :: mu ! cosine of scattering angle + real(8) :: phi ! azimuthal angle - ! Determine total nu - nu_t = nu_total(nuc, p % E) + ! Sample cosine of angle -- fission neutrons are always emitted + ! isotropically. Sometimes in ACE data, fission reactions actually have + ! an angular distribution listed, but for those that do, it's simply just + ! a uniform distribution in mu + mu = TWO * prn() - ONE - ! Determine delayed nu - nu_d = nu_delayed(nuc, p % E) + ! Sample azimuthal angle uniformly in [0,2*pi) + phi = TWO*PI*prn() + site % uvw(1) = mu + site % uvw(2) = sqrt(ONE - mu*mu) * cos(phi) + site % uvw(3) = sqrt(ONE - mu*mu) * sin(phi) - ! Determine delayed neutron fraction + ! Determine total nu, delayed nu, and delayed neutron fraction + nu_t = nuc % nu(E_in, EMISSION_TOTAL) + nu_d = nuc % nu(E_in, EMISSION_DELAYED) beta = nu_d / nu_t if (prn() < beta) then @@ -1211,51 +1207,41 @@ contains ! DELAYED NEUTRON SAMPLED ! sampled delayed precursor group - xi = prn() - lc = 1 + xi = prn()*nu_d prob = ZERO - do j = 1, nuc % n_precursor - ! determine number of interpolation regions and energies - NR = int(nuc % nu_d_precursor_data(lc + 1)) - NE = int(nuc % nu_d_precursor_data(lc + 2 + 2*NR)) + do group = 1, nuc % n_precursor ! determine delayed neutron precursor yield for group j - yield = interpolate_tab1(nuc % nu_d_precursor_data( & - lc+1:lc+2+2*NR+2*NE), p % E) + yield = rxn % products(1 + group) % yield % evaluate(E_in) ! Check if this group is sampled prob = prob + yield if (xi < prob) exit - - ! advance pointer - lc = lc + 2 + 2*NR + 2*NE + 1 end do ! if the sum of the probabilities is slightly less than one and the ! random number is greater, j will be greater than nuc % ! n_precursor -- check for this condition - j = min(j, nuc % n_precursor) + group = min(group, nuc % n_precursor) ! set the delayed group for the particle born from fission - p % delayed_group = j + site % delayed_group = group - ! sample from energy distribution n_sample = 0 do - select type (aedist => nuc%nu_d_edist(j)%obj) - type is (UncorrelatedAngleEnergy) - E_out = aedist%energy%sample(p%E) - end select + ! sample from energy/angle distribution -- note that mu has already been + ! sampled above and doesn't need to be resampled + call rxn % products(1 + group) % sample(E_in, site % E, mu) ! resample if energy is greater than maximum neutron energy - if (E_out < energy_max_neutron) exit + if (site % E < energy_max_neutron) exit ! check for large number of resamples n_sample = n_sample + 1 if (n_sample == MAX_SAMPLE) then ! call write_particle_restart(p) call fatal_error("Resampled energy distribution maximum number of " & - &// "times for nuclide " // nuc % name) + // "times for nuclide " // nuc % name) end if end do @@ -1264,28 +1250,27 @@ contains ! PROMPT NEUTRON SAMPLED ! set the delayed group for the particle born from fission to 0 - p % delayed_group = 0 + site % delayed_group = 0 ! sample from prompt neutron energy distribution n_sample = 0 do - call rxn%secondary%sample(p%E, E_out, prob) + call rxn % products(1) % sample(E_in, site % E, mu) ! resample if energy is greater than maximum neutron energy - if (E_out < energy_max_neutron) exit + if (site % E < energy_max_neutron) exit ! check for large number of resamples n_sample = n_sample + 1 if (n_sample == MAX_SAMPLE) then ! call write_particle_restart(p) call fatal_error("Resampled energy distribution maximum number of " & - &// "times for nuclide " // nuc % name) + // "times for nuclide " // nuc % name) end if end do - end if - end function sample_fission_energy + end subroutine sample_fission_neutron !=============================================================================== ! INELASTIC_SCATTER handles all reactions with a single secondary neutron (other @@ -1293,7 +1278,7 @@ contains !=============================================================================== subroutine inelastic_scatter(nuc, rxn, p) - type(NuclideCE), intent(in) :: nuc + type(Nuclide), intent(in) :: nuc type(Reaction), intent(in) :: rxn type(Particle), intent(inout) :: p @@ -1309,7 +1294,7 @@ contains E_in = p % E ! sample outgoing energy and scattering cosine - call rxn%secondary%sample(E_in, E, mu) + call rxn % products(1) % sample(E_in, E, mu) ! if scattering system is in center-of-mass, transfer cosine of scattering ! angle and outgoing energy from CM to LAB @@ -1337,14 +1322,16 @@ contains ! change direction of particle p % coord(1) % uvw = rotate_angle(p % coord(1) % uvw, mu) - ! change weight of particle based on yield - if (rxn % multiplicity_with_E) then - yield = interpolate_tab1(rxn % multiplicity_E, E_in) - p % wgt = yield * p % wgt - else - do i = 1, rxn % multiplicity - 1 - call p % create_secondary(p % coord(1) % uvw, NEUTRON, run_CE=.True.) + ! evaluate yield + yield = rxn % products(1) % yield % evaluate(E_in) + if (mod(yield, ONE) == ZERO) then + ! If yield is integral, create exactly that many secondary particles + do i = 1, nint(yield) - 1 + call p % create_secondary(p % coord(1) % uvw, NEUTRON, run_CE=.true.) end do + else + ! Otherwise, change weight of particle based on yield + p % wgt = yield * p % wgt end if end subroutine inelastic_scatter diff --git a/src/physics_mg.F90 b/src/physics_mg.F90 index 6a58540c1..2e5e467c1 100644 --- a/src/physics_mg.F90 +++ b/src/physics_mg.F90 @@ -5,9 +5,9 @@ module physics_mg use constants use error, only: fatal_error, warning use global - use macroxs_header, only: MacroXS, MacroXSContainer use material_header, only: Material use math, only: rotate_angle + use mgxs_header, only: Mgxs, MgxsContainer use mesh, only: get_mesh_indices use output, only: write_message use particle_header, only: Particle @@ -77,6 +77,7 @@ contains call create_fission_sites(p, p % secondary_bank, p % n_secondary) end if end if + ! If survival biasing is being used, the following subroutine adjusts the ! weight of the particle. Otherwise, it checks to see if absorption occurs @@ -178,7 +179,7 @@ contains real(8) :: phi ! fission neutron azimuthal angle real(8) :: weight ! weight adjustment for ufs method logical :: in_mesh ! source site in ufs mesh? - class(MacroXS), pointer :: xs + class(Mgxs), pointer :: xs ! Get Pointers xs => macro_xs(p % material) % obj @@ -241,14 +242,12 @@ contains ! Set weight of fission bank site bank_array(i) % wgt = ONE/weight - ! Sample cosine of angle -- fission neutrons are always emitted - ! isotropically. Sometimes in ACE data, fission reactions actually have - ! an angular distribution listed, but for those that do, it's simply just - ! a uniform distribution in mu + ! Sample cosine of angle -- fission neutrons are treated as being emitted + ! isotropically. mu = TWO * prn() - ONE ! Sample azimuthal angle uniformly in [0,2*pi) - phi = TWO*PI*prn() + phi = TWO * PI * prn() bank_array(i) % uvw(1) = mu bank_array(i) % uvw(2) = sqrt(ONE - mu*mu) * cos(phi) bank_array(i) % uvw(3) = sqrt(ONE - mu*mu) * sin(phi) @@ -256,7 +255,7 @@ contains ! Sample secondary energy distribution for fission reaction and set energy ! in fission bank bank_array(i) % E = & - real(xs % sample_fission_energy(p % g, fission_bank(i) % uvw), 8) + real(xs % sample_fission_energy(p % g, bank_array(i) % uvw), 8) end do ! increment number of bank sites diff --git a/src/product_header.F90 b/src/product_header.F90 new file mode 100644 index 000000000..e20c173b4 --- /dev/null +++ b/src/product_header.F90 @@ -0,0 +1,62 @@ +module product_header + + use angleenergy_header, only: AngleEnergyContainer + use constants, only: ZERO, MAX_WORD_LEN, EMISSION_PROMPT, EMISSION_DELAYED, & + EMISSION_TOTAL, NEUTRON, PHOTON + use endf_header, only: Tabulated1D, Function1D, Constant1D, Polynomial + use random_lcg, only: prn + +!=============================================================================== +! REACTIONPRODUCT stores a data for a reaction product including its yield and +! angle-energy distributions, each of which has a given probability of occurring +! for a given incoming energy. In general, most products only have one +! angle-energy distribution, but for some cases (e.g., (n,2n) in certain +! nuclides) multiple distinct distributions exist. +!=============================================================================== + + type :: ReactionProduct + integer :: particle + integer :: emission_mode ! prompt, delayed, or total emission + real(8) :: decay_rate ! Decay rate for delayed neutron precursors + class(Function1D), pointer :: yield => null() ! Energy-dependent neutron yield + type(Tabulated1D), allocatable :: applicability(:) + type(AngleEnergyContainer), allocatable :: distribution(:) + contains + procedure :: sample => reactionproduct_sample + end type ReactionProduct + +contains + + subroutine reactionproduct_sample(this, E_in, E_out, mu) + class(ReactionProduct), intent(in) :: this + real(8), intent(in) :: E_in ! incoming energy + real(8), intent(out) :: E_out ! sampled outgoing energy + real(8), intent(out) :: mu ! sampled scattering cosine + + integer :: i ! loop counter + integer :: n ! number of angle-energy distributions + real(8) :: prob ! cumulative probability + real(8) :: c ! sampled cumulative probability + + n = size(this%applicability) + if (n > 1) then + prob = ZERO + c = prn() + do i = 1, n + ! Determine probability that i-th energy distribution is sampled + prob = prob + this % applicability(i) % evaluate(E_in) + + ! If i-th distribution is sampled, sample energy from the distribution + if (c <= prob) then + call this%distribution(i)%obj%sample(E_in, E_out, mu) + exit + end if + end do + else + ! If only one distribution is present, go ahead and sample it + call this%distribution(1)%obj%sample(E_in, E_out, mu) + end if + + end subroutine reactionproduct_sample + +end module product_header diff --git a/src/random_lcg.F90 b/src/random_lcg.F90 index 8f50477c5..08f1034ab 100644 --- a/src/random_lcg.F90 +++ b/src/random_lcg.F90 @@ -24,9 +24,10 @@ module random_lcg !$omp threadprivate(prn_seed, stream) public :: prn + public :: future_prn public :: initialize_prng public :: set_particle_seed - public :: prn_skip + public :: advance_prn_seed public :: prn_set_stream public :: STREAM_TRACKING, STREAM_TALLIES @@ -52,6 +53,21 @@ contains end function prn +!=============================================================================== +! FUTURE_PRN generates a pseudo-random number which is 'n' times ahead from the +! current seed. +!=============================================================================== + + function future_prn(n) result(pseudo_rn) + + integer(8), intent(in) :: n ! number of prns to skip + + real(8) :: pseudo_rn + + pseudo_rn = future_seed(n, prn_seed(stream)) * prn_norm + + end function future_prn + !=============================================================================== ! INITIALIZE_PRNG sets up the random number generator, determining the seed and ! values for g, c, and m. @@ -90,31 +106,32 @@ contains integer :: i do i = 1, N_STREAMS - prn_seed(i) = prn_skip_ahead(id*prn_stride, prn_seed0 + i - 1) + prn_seed(i) = future_seed(id*prn_stride, prn_seed0 + i - 1) end do end subroutine set_particle_seed !=============================================================================== -! PRN_SKIP advances the random number seed 'n' times from the current seed +! ADVANCE_PRN_SEED advances the random number seed 'n' times from the current +! seed. !=============================================================================== - subroutine prn_skip(n) + subroutine advance_prn_seed(n) integer(8), intent(in) :: n ! number of seeds to skip - prn_seed(stream) = prn_skip_ahead(n, prn_seed(stream)) + prn_seed(stream) = future_seed(n, prn_seed(stream)) - end subroutine prn_skip + end subroutine advance_prn_seed !=============================================================================== -! PRN_SKIP_AHEAD advances the random number seed 'skip' times. This is usually +! FUTURE_SEED advances the random number seed 'skip' times. This is usually ! used to skip a fixed number of random numbers (the stride) so that a given ! particle always has the same starting seed regardless of how many processors ! are used !=============================================================================== - function prn_skip_ahead(n, seed) result(new_seed) + function future_seed(n, seed) result(new_seed) integer(8), intent(in) :: n ! number of seeds to skip integer(8), intent(in) :: seed ! original seed @@ -166,7 +183,7 @@ contains ! With G and C, we can now find the new seed new_seed = iand(g_new*seed + c_new, prn_mask) - end function prn_skip_ahead + end function future_seed !=============================================================================== ! PRN_SET_STREAM changes the random number stream. If random numbers are needed diff --git a/src/reaction_header.F90 b/src/reaction_header.F90 new file mode 100644 index 000000000..160ad6323 --- /dev/null +++ b/src/reaction_header.F90 @@ -0,0 +1,21 @@ +module reaction_header + + use product_header, only: ReactionProduct + + implicit none + +!=============================================================================== +! REACTION contains the cross-section and secondary energy and angle +! distributions for a single reaction in a continuous-energy ACE-format table +!=============================================================================== + + type Reaction + integer :: MT ! ENDF MT value + real(8) :: Q_value ! Reaction Q value + integer :: threshold ! Energy grid index of threshold + logical :: scatter_in_cm ! scattering system in center-of-mass? + real(8), allocatable :: sigma(:) ! Cross section values + type(ReactionProduct), allocatable :: products(:) + end type Reaction + +end module reaction_header diff --git a/src/relaxng/geometry.rnc b/src/relaxng/geometry.rnc index 8d25789f5..35d5ef8b2 100644 --- a/src/relaxng/geometry.rnc +++ b/src/relaxng/geometry.rnc @@ -21,8 +21,9 @@ element geometry { (element type { xsd:string { maxLength = "15" } } | attribute type { xsd:string { maxLength = "15" } }) & (element coeffs { list { xsd:double+ } } | attribute coeffs { list { xsd:double+ } }) & - (element boundary { ( "transmit" | "reflective" | "vacuum" ) } | - attribute boundary { ( "transmit" | "reflective" | "vacuum" ) })? + (element boundary { ( "transmit" | "reflective" | "vacuum" | "periodic" ) } | + attribute boundary { ( "transmit" | "reflective" | "vacuum" | "periodic" ) })? & + (element periodic_surface_id { xsd:int } | attribute periodic_surface_id { xsd:int })? }* & element lattice { diff --git a/src/relaxng/geometry.rng b/src/relaxng/geometry.rng index d40401b28..b53d0e8db 100644 --- a/src/relaxng/geometry.rng +++ b/src/relaxng/geometry.rng @@ -173,6 +173,7 @@ transmit reflective vacuum + periodic @@ -180,10 +181,21 @@ transmit reflective vacuum + periodic + + + + + + + + + + diff --git a/src/scattdata_header.F90 b/src/scattdata_header.F90 index f8fddbc6b..12c11e2e4 100644 --- a/src/scattdata_header.F90 +++ b/src/scattdata_header.F90 @@ -8,36 +8,56 @@ module scattdata_header implicit none + +!=============================================================================== +! JAGGED1D and JAGGED2D is a type which allows for jagged 1-D or 2-D array. +!=============================================================================== + + type :: Jagged2D + real(8), allocatable :: data(:, :) + end type Jagged2D + + type :: Jagged1D + real(8), allocatable :: data(:) + end type Jagged1D + !=============================================================================== ! SCATTDATA contains all the data to describe the scattering energy and ! angular distribution !=============================================================================== type, abstract :: ScattData - ! p0 matrix on its own for sampling energy - real(8), allocatable :: energy(:,:) ! (Gout x Gin) - real(8), allocatable :: mult(:,:) ! (Gout x Gin) - real(8), allocatable :: data(:,:,:) ! (Order/Nmu x Gout x Gin) + ! The data attribute of the energy, mult, and dist arrays + ! are not necessarily 1-indexed as they instead will be allocated + ! from a minimum outgoing group to an outgoing minimum group. + ! Normalized p0 matrix on its own for sampling energy + type(Jagged1D), allocatable :: energy(:) ! (Gin % data(Gout)) + ! Nu-scatter multiplication (i.e. nu-scatt/scatt) + type(Jagged1D), allocatable :: mult(:) ! (Gin % data(Gout)) + ! Angular distribution + type(Jagged2D), allocatable :: dist(:) ! (Gin % data(Order/Nmu, Gout) + integer, allocatable :: gmin(:) ! Minimum outgoing group + integer, allocatable :: gmax(:) ! Maximum outgoing group + real(8), allocatable :: scattxs(:) ! Isotropic Sigma_{s,g_{in}} contains procedure(scattdata_init_), deferred :: init ! Initializes ScattData procedure(scattdata_calc_f_), deferred :: calc_f ! Calculates f, given mu procedure(scattdata_sample_), deferred :: sample ! sample the scatter event + procedure :: get_matrix => scattdata_get_matrix ! Rebuild scattering matrix end type ScattData abstract interface - subroutine scattdata_init_(this, order, energy, mult, coeffs) + subroutine scattdata_init_(this, mult, coeffs) import ScattData - class(ScattData), intent(inout) :: this ! Object to work on - integer, intent(in) :: order ! Data Order - real(8), intent(in) :: energy(:,:) ! Energy Transfer Matrix - real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix - real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use + class(ScattData), intent(inout) :: this ! Object to work with + real(8), intent(in) :: mult(:, :) ! Scatter Prod'n Matrix + real(8), intent(in) :: coeffs(:, :, :) ! Coefficients to use end subroutine scattdata_init_ pure function scattdata_calc_f_(this, gin, gout, mu) result(f) import ScattData - class(ScattData), intent(in) :: this ! The ScattData to evaluate + class(ScattData), intent(in) :: this ! Scattering Object to work with integer, intent(in) :: gin ! Incoming Energy Group integer, intent(in) :: gout ! Outgoing Energy Group real(8), intent(in) :: mu ! Angle of interest @@ -47,7 +67,7 @@ module scattdata_header subroutine scattdata_sample_(this, gin, gout, mu, wgt) import ScattData - class(ScattData), intent(in) :: this ! Scattering Object to Use + class(ScattData), intent(in) :: this ! Scattering Object to work with integer, intent(in) :: gin ! Incoming neutron group integer, intent(out) :: gout ! Sampled outgoin group real(8), intent(out) :: mu ! Sampled change in angle @@ -57,30 +77,35 @@ module scattdata_header type, extends(ScattData) :: ScattDataLegendre ! Maximal value for rejection sampling from rectangle - real(8), allocatable :: max_val(:,:) + type(Jagged1D), allocatable :: max_val(:) ! (Gin % data(Gout)) contains - procedure :: init => scattdatalegendre_init - procedure :: calc_f => scattdatalegendre_calc_f - procedure :: sample => scattdatalegendre_sample + procedure :: init => scattdatalegendre_init + procedure :: calc_f => scattdatalegendre_calc_f + procedure :: sample => scattdatalegendre_sample end type ScattDataLegendre - type, extends(ScattData) :: ScattDataHistogram - real(8), allocatable :: mu(:) ! Mu bins - real(8) :: dmu ! Mu spacing + type, extends(ScattData) :: ScattDataHistogram + real(8), allocatable :: mu(:) ! Mu bins + real(8) :: dmu ! Mu spacing + ! Histogram of f(mu) (dist has CDF) + type(Jagged2D), allocatable :: fmu(:) ! (Gin % data(Order/Nmu x Gout) contains - procedure :: init => scattdatahistogram_init - procedure :: calc_f => scattdatahistogram_calc_f - procedure :: sample => scattdatahistogram_sample + procedure :: init => scattdatahistogram_init + procedure :: calc_f => scattdatahistogram_calc_f + procedure :: sample => scattdatahistogram_sample + procedure :: get_matrix => scattdatahistogram_get_matrix end type ScattDataHistogram - type, extends(ScattData) :: ScattDataTabular - real(8), allocatable :: mu(:) ! Mu bins - real(8) :: dmu ! Mu spacing - real(8), allocatable :: fmu(:,:,:) ! PDF of f(mu) + type, extends(ScattData) :: ScattDataTabular + real(8), allocatable :: mu(:) ! Mu bins + real(8) :: dmu ! Mu spacing + ! PDF of f(mu) (dist has CDF) + type(Jagged2D), allocatable :: fmu(:) ! (Gin % data(Order/Nmu x Gout) contains - procedure :: init => scattdatatabular_init - procedure :: calc_f => scattdatatabular_calc_f - procedure :: sample => scattdatatabular_sample + procedure :: init => scattdatatabular_init + procedure :: calc_f => scattdatatabular_calc_f + procedure :: sample => scattdatatabular_sample + procedure :: get_matrix => scattdatatabular_get_matrix end type ScattDataTabular !=============================================================================== @@ -94,189 +119,313 @@ module scattdata_header contains !=============================================================================== -! SCATTDATA_INIT builds the scattdata object +! SCATTDATA*_INIT builds the scattdata object !=============================================================================== subroutine scattdata_init(this, order, energy, mult) - class(ScattData), intent(inout) :: this ! Object to work on - integer, intent(in) :: order ! Data Order - real(8), intent(in) :: energy(:,:) ! Energy Transfer Matrix - real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix + class(ScattData), intent(inout) :: this ! Object to work on + integer, intent(in) :: order ! Data Order + real(8), intent(inout) :: energy(:, :) ! Energy Transfer Matrix + real(8), intent(in) :: mult(:, :) ! Scatter Prod'n Matrix - integer :: groups + integer :: groups, gmin, gmax, gin + real(8) :: norm groups = size(energy, dim=1) - allocate(this % energy(groups, groups)) - this % energy = energy - allocate(this % mult(groups, groups)) - this % mult = mult - allocate(this % data(order, groups, groups)) - this % data = ZERO - + allocate(this % gmin(groups)) + allocate(this % gmax(groups)) + allocate(this % energy(groups)) + allocate(this % mult(groups)) + allocate(this % dist(groups)) + ! Use energy to find the gmin and gmax values + ! Also set energy values when doing it + do gin = 1, groups + ! Make sure energy is normalized (i.e., CDF is 1) + norm = sum(energy(:, gin)) + if (norm /= ZERO) energy(:, gin) = energy(:, gin) / norm + ! Find gmin by checking the P0 moment + do gmin = 1, groups + if (energy(gmin, gin) > ZERO) exit + end do + ! Find gmax by checking the P0 moment + do gmax = groups, 1, -1 + if (energy(gmax, gin) > ZERO) exit + end do + ! Treat the case of all zeros + if (gmin > gmax) then + gmin = gin + gmax = gin + ! By not changing energy(gin) here we are leaving it as zero + end if + allocate(this % energy(gin) % data(gmin:gmax)) + this % energy(gin) % data(gmin:gmax) = energy(gmin:gmax, gin) + allocate(this % mult(gin) % data(gmin:gmax)) + this % mult(gin) % data(gmin:gmax) = mult(gmin:gmax, gin) + allocate(this % dist(gin) % data(order, gmin:gmax)) + this % dist(gin) % data = ZERO + this % gmin(gin) = gmin + this % gmax(gin) = gmax + end do end subroutine scattdata_init - subroutine scattdatalegendre_init(this, order, energy, mult, coeffs) - class(ScattDataLegendre), intent(inout) :: this ! Object to work on - integer, intent(in) :: order ! Data Order - real(8), intent(in) :: energy(:,:) ! Energy Transfer Matrix - real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix - real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use + subroutine scattdatalegendre_init(this, mult, coeffs) + class(ScattDataLegendre), intent(inout) :: this ! Object to work on + real(8), intent(in) :: mult(:, :) ! Scatter Prod'n Matrix + real(8), intent(in) :: coeffs(:, :, :) ! Coefficients to use - real(8) :: dmu, mu, f - integer :: imu, Nmu, gout, gin, groups + real(8) :: dmu, mu, f, norm + integer :: imu, Nmu, gout, gin, groups, order + real(8), allocatable :: energy(:, :) + real(8), allocatable :: matrix(:, :, :) - call scattdata_init(this, order, energy, mult) + groups = size(coeffs, dim=3) + order = size(coeffs, dim=1) - this % data = coeffs + ! make a copy of coeffs that we can use to extract data and normalize + allocate(matrix(order, groups, groups)) + matrix (:, :, :)= coeffs - groups = size(this % energy,dim=1) + ! Get scattxs value + allocate(this % scattxs(groups)) + ! Get this by summing the un-normalized P0 coefficient in matrix + ! over all outgoing groups + this % scattxs(:) = sum(matrix(1, :, :), dim=1) - allocate(this % max_val(groups, groups)) - this % max_val = ZERO - ! Step through the polynomial with fixed number of points to identify - ! the maximal value. - Nmu = 1001 - dmu = TWO / real(Nmu,8) - do imu = 1, Nmu - ! Update mu. Do first and last seperate to avoid float errors - if (imu == 1) then - mu = -ONE - else if (imu == Nmu) then - mu = ONE - end if - mu = -ONE + real(imu - 1,8) * dmu - do gin = 1, groups - do gout = 1, groups - ! Calculate probability - f = this % calc_f(gin,gout,mu) - ! If this is a new max, store it. - if (f > this % max_val(gout,gin)) this % max_val(gout,gin) = f - end do + allocate(energy(groups, groups)) + energy(:, :) = ZERO + ! Build energy transfer probability matrix from data in matrix + ! while also normalizing matrix itself (making CDF of f(mu=1)=1) + do gin = 1, groups + do gout = 1, groups + norm = matrix(1, gout, gin) + energy(gout, gin) = norm + if (norm /= ZERO) then + matrix(:, gout, gin) = matrix(:, gout, gin) / norm + end if end do end do - ! Finally, since we may not have caught the exact max, add 10% margin - this % max_val = this % max_val * 1.1_8 + call scattdata_init(this, order, energy, mult) + allocate(this % max_val(groups)) + ! Set dist values from matrix and initialize max_val + do gin = 1, groups + do gout = this % gmin(gin), this % gmax(gin) + this % dist(gin) % data(:, gout) = matrix(:, gout, gin) + end do + allocate(this % max_val(gin) % data(this % gmin(gin):this % gmax(gin))) + this % max_val(gin) % data(:) = ZERO + end do + + ! Step through the polynomial with fixed number of points to identify + ! the maximal value. + Nmu = 1001 + dmu = TWO / real(Nmu - 1, 8) + do gin = 1, groups + do gout = this % gmin(gin), this % gmax(gin) + do imu = 1, Nmu + ! Update mu. Do first and last seperate to avoid float errors + if (imu == 1) then + mu = -ONE + else if (imu == Nmu) then + mu = ONE + else + mu = -ONE + real(imu - 1, 8) * dmu + end if + ! Calculate probability + f = this % calc_f(gin,gout,mu) + ! If this is a new max, store it. + if (f > this % max_val(gin) % data(gout)) & + this % max_val(gin) % data(gout) = f + end do + ! Finally, since we may not have caught the exact max, add 10% margin + this % max_val(gin) % data(gout) = & + this % max_val(gin) % data(gout) * 1.1_8 + end do + end do end subroutine scattdatalegendre_init - subroutine scattdatahistogram_init(this, order, energy, mult, coeffs) + subroutine scattdatahistogram_init(this, mult, coeffs) class(ScattDataHistogram), intent(inout) :: this ! Object to work on - integer, intent(in) :: order ! Data Order - real(8), intent(in) :: energy(:,:) ! Energy Transfer Matrix - real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix - real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use + real(8), intent(in) :: mult(:, :) ! Scatter Prod'n Matrix + real(8), intent(in) :: coeffs(:, :, :) ! Coefficients to use - integer :: imu, gin, gout, groups + integer :: imu, gin, gout, groups, order real(8) :: norm + real(8), allocatable :: energy(:, :) + real(8), allocatable :: matrix(:, :, :) - groups = size(energy,dim=1) + groups = size(coeffs, dim=3) + order = size(coeffs, dim=1) + + ! make a copy of coeffs that we can use to extract data and normalize + allocate(matrix(order, groups, groups)) + matrix(:, :, :) = coeffs + + ! Get scattxs value + allocate(this % scattxs(groups)) + ! Get this by summing the un-normalized P0 coefficient in matrix + ! over all outgoing groups + this % scattxs(:) = sum(sum(matrix(:, :, :), dim=1), dim=1) + + allocate(energy(groups, groups)) + energy(:, :) = ZERO + ! Build energy transfer probability matrix from data in matrix + ! while also normalizing matrix itself (making CDF of f(mu=1)=1) + do gin = 1, groups + do gout = 1, groups + norm = sum(matrix(:, gout, gin)) + energy(gout, gin) = norm + if (norm /= ZERO) then + matrix(:, gout, gin) = matrix(:, gout, gin) / norm + end if + end do + end do call scattdata_init(this, order, energy, mult) allocate(this % mu(order)) - this % dmu = TWO / real(order,8) + this % dmu = TWO / real(order, 8) this % mu(1) = -ONE do imu = 2, order - this % mu(imu) = -ONE + real(imu - 1,8) * this % dmu + this % mu(imu) = -ONE + real(imu - 1, 8) * this % dmu end do - ! Best to integrate this histogram so we can avoid rejection sampling + ! Integrate this histogram so we can avoid rejection sampling while + ! also saving the original histogram in fmu + allocate(this % fmu(groups)) do gin = 1, groups - do gout = 1, groups - if (energy(gout,gin) > ZERO) then - ! Integrate the histogram - this % data(1,gout,gin) = this % dmu * coeffs(1,gout,gin) - do imu = 2, order - this % data(imu,gout,gin) = this % dmu * coeffs(imu,gout,gin) + & - this % data(imu-1,gout,gin) - end do - ! Now make sure integral norms to zero - norm = this % data(order,gout,gin) - if (norm > ZERO) then - this % data(:,gout,gin) = this % data(:,gout,gin) / norm - end if + allocate(this % fmu(gin) % data(order, & + this % gmin(gin):this % gmax(gin))) + do gout = this % gmin(gin), this % gmax(gin) + ! Store the histogram + this % fmu(gin) % data(:, gout) = matrix(:, gout, gin) + ! Integrate the histogram + this % dist(gin) % data(1, gout) = & + this % dmu * matrix(1, gout, gin) + do imu = 2, order + this % dist(gin) % data(imu, gout) = & + this % dmu * matrix(imu, gout, gin) + & + this % dist(gin) % data(imu - 1, gout) + end do + + ! Now make sure integral norms to zero + norm = this % dist(gin) % data(order, gout) + if (norm > ZERO) then + this % fmu(gin) % data(:, gout) = & + this % fmu(gin) % data(:, gout) / norm + this % dist(gin) % data(:, gout) = & + this % dist(gin) % data(:, gout) / norm end if end do end do end subroutine scattdatahistogram_init - subroutine scattdatatabular_init(this, order, energy, mult, coeffs) + subroutine scattdatatabular_init(this, mult, coeffs) class(ScattDataTabular), intent(inout) :: this ! Object to work on - integer, intent(in) :: order ! Data Order - real(8), intent(in) :: energy(:,:) ! Energy Transfer Matrix - real(8), intent(in) :: mult(:,:) ! Scatter Prod'n Matrix - real(8), intent(in) :: coeffs(:,:,:) ! Coefficients to use + real(8), intent(in) :: mult(:, :) ! Scatter Prod'n Matrix + real(8), intent(in) :: coeffs(:, :, :) ! Coefficients to use - integer :: imu, gin, gout, groups + integer :: imu, gin, gout, groups, order real(8) :: norm - logical :: legendre_flag - integer :: this_order + real(8), allocatable :: energy(:, :) + real(8), allocatable :: matrix(:, :, :) - if (order < 0) then - legendre_flag = .true. - this_order = -1 * order - else - legendre_flag = .false. - this_order = order - end if + groups = size(coeffs, dim=3) + order = size(coeffs, dim=1) - groups = size(energy,dim=1) + ! make a copy of coeffs that we can use to extract data and normalize + allocate(matrix(order, groups, groups)) + matrix(:, :, :) = coeffs - call scattdata_init(this, this_order, energy, mult) - - allocate(this % mu(this_order)) - this % dmu = TWO / real(this_order - 1) - do imu = 1, this_order - 1 - this % mu(imu) = -ONE + real(imu - 1) * this % dmu + ! Build the angular distribution mu values + allocate(this % mu(order)) + this % dmu = TWO / real(order - 1, 8) + this % mu(1) = -ONE + do imu = 2, order - 1 + this % mu(imu) = -ONE + real(imu - 1, 8) * this % dmu end do - this % mu(this_order) = ONE + this % mu(order) = ONE - ! Best to integrate this histogram so we can avoid rejection sampling - allocate(this % fmu(this_order,groups,groups)) + ! Get scattxs + allocate(this % scattxs(groups)) + ! Get this by integrating the scattering distribution over all mu points + ! and then combining over all outgoing groups + ! over all outgoing groups + do gin = 1, groups + norm = ZERO + do gout = 1, groups + do imu = 2, order + norm = norm + HALF * this % dmu * (matrix(imu - 1, gout, gin) + & + matrix(imu, gout, gin)) + end do + end do + this % scattxs(gin) = norm + end do + + allocate(energy(groups, groups)) + energy(:, :) = ZERO + ! Build energy transfer probability matrix from data in matrix do gin = 1, groups do gout = 1, groups - if (energy(gout,gin) > ZERO) then - if (legendre_flag) then - ! Coeffs are legendre coeffs. Need to build f(mu) then integrate - ! and store the integral in this % data - ! Ensure the coeffs are normalized - norm = ONE / coeffs(1,gout,gin) - do imu = 1, this_order - this % fmu(imu,gout,gin) = evaluate_legendre(norm * coeffs(:,gout,gin), this % mu(imu)) - ! Force positivity - if (this % fmu(imu,gout,gin) < ZERO) then - this % fmu(imu,gout,gin) = ZERO - end if - end do - else - ! Coeffs contain f(mu), put in f(mu) to save duplicate. - this % fmu(:,gout,gin) = this % data(:,gout,gin) - end if + norm = ZERO + do imu = 2, order + norm = norm + HALF * this % dmu * & + (matrix(imu - 1, gout, gin) + matrix(imu, gout, gin)) + end do + energy(gout, gin) = norm + end do + end do + call scattdata_init(this, order, energy, mult) - ! Re-normalize fmu for numerical integration issues and in case - ! the negative fix-up introduced un-normalized data - norm = ZERO - do imu = 2, this_order - norm = norm + HALF * this % dmu * (this % fmu(imu-1,gout,gin) + this % fmu(imu,gout,gin)) - end do - if (norm > ZERO) then - this % fmu(:,gout,gin) = this % fmu(:,gout,gin) / norm - end if + ! Calculate f(mu) and integrate it so we can avoid rejection sampling + allocate(this % fmu(groups)) + do gin = 1, groups + allocate(this % fmu(gin) % data(order, & + this % gmin(gin):this % gmax(gin))) + do gout = this % gmin(gin), this % gmax(gin) + ! Coeffs contain f(mu), put in f(mu) as that is where the + ! PDF lives + this % fmu(gin) % data(:, gout) = matrix(:, gout, gin) - ! Now create CDF from fmu with trapezoidal rule - this % data(1,gout,gin) = ZERO - do imu = 2, this_order - 1 - this % data(imu,gout,gin) = this % data(imu-1,gout,gin) + & - HALF * this % dmu * (this % fmu(imu-1,gout,gin) + this % fmu(imu,gout,gin)) - end do - this % data(this_order,gout,gin) = ONE + ! Force positivity + do imu = 1, order + if (this % fmu(gin) % data(imu, gout) < ZERO) then + this % fmu(gin) % data(imu, gout) = ZERO + end if + end do + + ! Re-normalize fmu for numerical integration issues and in case + ! the negative fix-up introduced un-normalized data + norm = ZERO + do imu = 2, order + norm = norm + HALF * this % dmu * & + (this % fmu(gin) % data(imu - 1, gout) + & + this % fmu(gin) % data(imu, gout)) + end do + if (norm > ZERO) then + this % fmu(gin) % data(:, gout) = & + this % fmu(gin) % data(:, gout) / norm + end if + + ! Now create CDF from fmu with trapezoidal rule + this % dist(gin) % data(1, gout) = ZERO + do imu = 2, order + this % dist(gin) % data(imu, gout) = & + this % dist(gin) % data(imu - 1, gout) + & + HALF * this % dmu * (this % fmu(gin) % data(imu - 1, gout) + & + this % fmu(gin) % data(imu, gout)) + end do + ! Ensure we normalize to 1 still + norm = this % dist(gin) % data(order, gout) + if (norm > ZERO) then + this % dist(gin) % data(:, gout) = & + this % dist(gin) % data(:, gout) / norm end if end do end do - end subroutine scattdatatabular_init !=============================================================================== @@ -285,58 +434,69 @@ contains pure function scattdatalegendre_calc_f(this, gin, gout, mu) result(f) class(ScattDataLegendre), intent(in) :: this ! The ScattData to evaluate - integer, intent(in) :: gin ! Incoming Energy Group - integer, intent(in) :: gout ! Outgoing Energy Group - real(8), intent(in) :: mu ! Angle of interest - real(8) :: f ! Return value of f(mu) - - ! Plug mu in to the legendre expansion and go from there - f = evaluate_legendre(this % data(:, gout, gin), mu) - - end function scattdatalegendre_calc_f - - pure function scattdatahistogram_calc_f(this, gin, gout, mu) result(f) - class(ScattDataHistogram), intent(in) :: this ! The ScattData to evaluate - integer, intent(in) :: gin ! Incoming Energy Group - integer, intent(in) :: gout ! Outgoing Energy Group - real(8), intent(in) :: mu ! Angle of interest - real(8) :: f ! Return value of f(mu) - - integer :: imu - - ! Find mu bin - imu = floor((mu + ONE)/ this % dmu + ONE) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % data, dim=1)) then - imu = imu - 1 - end if - - ! Use histogram interpolation to find f(mu) - f = this % data(imu, gout, gin) - - end function scattdatahistogram_calc_f - - pure function scattdatatabular_calc_f(this, gin, gout, mu) result(f) - class(ScattDataTabular), intent(in) :: this ! The ScattData to evaluate integer, intent(in) :: gin ! Incoming Energy Group integer, intent(in) :: gout ! Outgoing Energy Group real(8), intent(in) :: mu ! Angle of interest real(8) :: f ! Return value of f(mu) + ! Plug mu in to the legendre expansion and go from there + if (gout < this % gmin(gin) .or. gout > this % gmax(gin)) then + f = ZERO + else + f = evaluate_legendre(this % dist(gin) % data(:, gout), mu) + end if + + end function scattdatalegendre_calc_f + + pure function scattdatahistogram_calc_f(this, gin, gout, mu) result(f) + class(ScattDataHistogram), intent(in) :: this ! The ScattData to evaluate + integer, intent(in) :: gin ! Incoming Energy Group + integer, intent(in) :: gout ! Outgoing Energy Group + real(8), intent(in) :: mu ! Angle of interest + real(8) :: f ! Return value of f(mu) + + integer :: imu + + if (gout < this % gmin(gin) .or. gout > this % gmax(gin)) then + f = ZERO + else + ! Find mu bin + if (mu == ONE) then + imu = size(this % fmu(gin) % data, dim=1) + else + imu = floor((mu + ONE) / this % dmu + ONE) + end if + + f = this % fmu(gin) % data(imu, gout) + end if + + end function scattdatahistogram_calc_f + + pure function scattdatatabular_calc_f(this, gin, gout, mu) result(f) + class(ScattDataTabular), intent(in) :: this ! The ScattData to evaluate + integer, intent(in) :: gin ! Incoming Energy Group + integer, intent(in) :: gout ! Outgoing Energy Group + real(8), intent(in) :: mu ! Angle of interest + real(8) :: f ! Return value of f(mu) + integer :: imu real(8) :: r - ! Find mu bin - imu = floor((mu + ONE)/ this % dmu + ONE) - ! Adjust so interpolation works on the last bin if necessary - if (imu == size(this % data, dim=1)) then - imu = imu - 1 - end if + if (gout < this % gmin(gin) .or. gout > this % gmax(gin)) then + f = ZERO + else + ! Find mu bin + if (mu == ONE) then + imu = size(this % fmu(gin) % data, dim=1) - 1 + else + imu = floor((mu + ONE) / this % dmu + ONE) + end if - ! ! Now interpolate to find f(mu) - r = (mu - this % mu(imu)) / (this % mu(imu + 1) - this % mu(imu)) - f = (ONE - r) * this % data(imu, gout, gin) + & - r * this % data(imu + 1, gout, gin) + ! Now interpolate to find f(mu) + r = (mu - this % mu(imu)) / (this % mu(imu + 1) - this % mu(imu)) + f = (ONE - r) * this % fmu(gin) % data(imu, gout) + & + r * this % fmu(gin) % data(imu + 1, gout) + end if end function scattdatatabular_calc_f @@ -357,24 +517,24 @@ contains integer :: samples xi = prn() - prob = ZERO - gout = 0 + gout = this % gmin(gin) + prob = this % energy(gin) % data(gout) do while (prob < xi) gout = gout + 1 - prob = prob + this % energy(gout,gin) + prob = prob + this % energy(gin) % data(gout) end do - ! Now we can sample mu using the legendre representation of the thisering + ! Now we can sample mu using the legendre representation of the scattering ! kernel in data(1:this % order) - ! Do with rejection sampling + ! Do with rejection sampling from a rectangular bounding box ! Set maximal value - M = this % max_val(gout,gin) + M = this % max_val(gin) % data(gout) samples = 0 do mu = TWO * prn() - ONE - f = this % calc_f(gin,gout,mu) + f = this % calc_f(gin, gout, mu) if (f > ZERO) then u = prn() * M if (u <= f) then @@ -387,7 +547,7 @@ contains end if end do - wgt = wgt * this % mult(gout,gin) + wgt = wgt * this % mult(gin) % data(gout) end subroutine scattdatalegendre_sample @@ -403,26 +563,26 @@ contains integer :: imu xi = prn() - prob = ZERO - gout = 0 + gout = this % gmin(gin) + prob = this % energy(gin) % data(gout) do while (prob < xi) gout = gout + 1 - prob = prob + this % energy(gout,gin) + prob = prob + this % energy(gin) % data(gout) end do xi = prn() - if (xi < this % data(1,gout,gin)) then + if (xi < this % dist(gin) % data(1, gout)) then imu = 1 else - imu = binary_search(this % data(:,gout,gin), & - size(this % data(:,gout,gin)), xi) + imu = binary_search(this % dist(gin) % data(:, gout), & + size(this % dist(gin) % data(:, gout)), xi) end if ! Randomly select a mu in this bin. mu = prn() * this % dmu + this % mu(imu) - wgt = wgt * this % mult(gout,gin) + wgt = wgt * this % mult(gin) % data(gout) end subroutine scattdatahistogram_sample @@ -440,21 +600,21 @@ contains integer :: k, NP xi = prn() - prob = ZERO - gout = 0 + gout = this % gmin(gin) + prob = this % energy(gin) % data(gout) do while (prob < xi) gout = gout + 1 - prob = prob + this % energy(gout,gin) + prob = prob + this % energy(gin) % data(gout) end do ! determine outgoing cosine bin - NP = size(this % data(:,gout,gin)) + NP = size(this % dist(gin) % data(:, gout)) xi = prn() - c_k = this % data(1,gout,gin) + c_k = this % dist(gin) % data(1, gout) do k = 1, NP - 1 - c_k1 = this % data(k+1,gout,gin) + c_k1 = this % dist(gin) % data(k + 1, gout) if (xi < c_k1) exit c_k = c_k1 end do @@ -462,18 +622,19 @@ contains ! check to make sure k is <= NP - 1 k = min(k, NP - 1) - p0 = this % fmu(k,gout,gin) + p0 = this % fmu(gin) % data(k, gout) mu0 = this % mu(k) ! Linear-linear interpolation to find mu value w/in bin. - p1 = this % fmu(k+1,gout,gin) - mu1 = this % mu(k+1) + p1 = this % fmu(gin) % data(k + 1, gout) + mu1 = this % mu(k + 1) - frac = (p1 - p0)/(mu1 - mu0) + frac = (p1 - p0) / (mu1 - mu0) if (frac == ZERO) then - mu = mu0 + (xi - c_k)/p0 + mu = mu0 + (xi - c_k) / p0 else - mu = mu0 + (sqrt(max(ZERO, p0*p0 + TWO*frac*(xi - c_k))) - p0)/frac + mu = mu0 + & + (sqrt(max(ZERO, p0 * p0 + TWO * frac * (xi - c_k))) - p0) / frac end if if (mu <= -ONE) then @@ -482,8 +643,86 @@ contains mu = ONE end if - wgt = wgt * this % mult(gout,gin) + wgt = wgt * this % mult(gin) % data(gout) end subroutine scattdatatabular_sample +!=============================================================================== +! SCATTDATA*_GET_MATRIX Reproduces the original scattering matrix (densely) +! using ScattData's information of fmu/dist, energy, and scattxs +!=============================================================================== + + pure function scattdata_get_matrix(this, req_order) result(matrix) + class(ScattData), intent(in) :: this ! Scattering Object to work with + integer, intent(in) :: req_order ! Requested order of matrix + real(8), allocatable :: matrix(:, :, :) ! Resultant matrix just built + + integer :: order, groups, gin, gout + + groups = size(this % energy) + ! Set gin and gout for getting the order + order = min(req_order, size(this % dist(1) % data, dim=1)) + + allocate(matrix(order, groups, groups)) + ! Initialize to 0; this way the zero entries in the dense matrix dont + ! need to be explicitly set, requiring a significant increase in the + ! lines of code. + matrix(:, :, :) = ZERO + do gin = 1, groups + do gout = this % gmin(gin), this % gmax(gin) + matrix(:, gout, gin) = this % scattxs(gin) * & + this % energy(gin) % data(gout) * & + this % dist(gin) % data(1:order, gout) + end do + end do + end function scattdata_get_matrix + + pure function scattdatahistogram_get_matrix(this, req_order) result(matrix) + class(ScattDataHistogram), intent(in) :: this ! Scattering Object to work with + integer, intent(in) :: req_order ! Requested order of matrix + real(8), allocatable :: matrix(:, :, :) ! Resultant matrix just built + + integer :: order, groups, gin, gout + + groups = size(this % energy) + order = min(req_order, size(this % dist(1) % data, dim=1)) + + allocate(matrix(order, groups, groups)) + ! Initialize to 0; this way the zero entries in the dense matrix dont + ! need to be explicitly set, requiring a significant increase in the + ! lines of code. + matrix(:, :, :) = ZERO + do gin = 1, groups + do gout = this % gmin(gin), this % gmax(gin) + matrix(:, gout, gin) = this % scattxs(gin) * & + this % energy(gin) % data(gout) * & + this % fmu(gin) % data(1:order, gout) + end do + end do + end function scattdatahistogram_get_matrix + + pure function scattdatatabular_get_matrix(this, req_order) result(matrix) + class(ScattDataTabular), intent(in) :: this ! Scattering Object to work with + integer, intent(in) :: req_order ! Requested order of matrix + real(8), allocatable :: matrix(:, :, :) ! Resultant matrix just built + + integer :: order, groups, gin, gout + + groups = size(this % energy) + order = min(req_order, size(this % dist(1) % data, dim=1)) + + allocate(matrix(order, groups, groups)) + ! Initialize to 0; this way the zero entries in the dense matrix dont + ! need to be explicitly set, requiring a significant increase in the + ! lines of code. + matrix(:, :, :) = ZERO + do gin = 1, groups + do gout = this % gmin(gin), this % gmax(gin) + matrix(:, gout, gin) = this % scattxs(gin) * & + this % energy(gin) % data(gout) * & + this % fmu(gin) % data(1:order, gout) + end do + end do + end function scattdatatabular_get_matrix + end module scattdata_header diff --git a/src/secondary_correlated.F90 b/src/secondary_correlated.F90 index c0289d55e..b556d02dc 100644 --- a/src/secondary_correlated.F90 +++ b/src/secondary_correlated.F90 @@ -1,8 +1,8 @@ module secondary_correlated + use angleenergy_header, only: AngleEnergy use constants, only: ZERO, ONE, TWO, HISTOGRAM, LINEAR_LINEAR use distribution_univariate, only: DistributionContainer - use secondary_header, only: AngleEnergy use random_lcg, only: prn use search, only: binary_search @@ -24,8 +24,8 @@ module secondary_correlated integer :: n_region ! number of interpolation regions integer, allocatable :: breakpoints(:) ! breakpoints of interpolation regions integer, allocatable :: interpolation(:) ! interpolation region codes - real(8), allocatable :: energy_in(:) ! incoming energies - type(AngleEnergyTable), allocatable :: table(:) ! outgoing E/mu distributions + real(8), allocatable :: energy(:) ! incoming energies + type(AngleEnergyTable), allocatable :: distribution(:) ! outgoing E/mu distributions contains procedure :: sample => correlated_sample end type CorrelatedAngleEnergy @@ -61,17 +61,17 @@ contains ! find energy bin and calculate interpolation factor -- if the energy is ! outside the range of the tabulated energies, choose the first or last bins - n_energy_in = size(this%energy_in) - if (E_in < this%energy_in(1)) then + n_energy_in = size(this%energy) + if (E_in < this%energy(1)) then i = 1 r = ZERO - elseif (E_in > this%energy_in(n_energy_in)) then + elseif (E_in > this%energy(n_energy_in)) then i = n_energy_in - 1 r = ONE else - i = binary_search(this%energy_in, n_energy_in, E_in) - r = (E_in - this%energy_in(i)) / & - (this%energy_in(i+1) - this%energy_in(i)) + i = binary_search(this%energy, n_energy_in, E_in) + r = (E_in - this%energy(i)) / & + (this%energy(i+1) - this%energy(i)) end if ! Sample between the ith and (i+1)th bin @@ -82,23 +82,23 @@ contains end if ! interpolation for energy E1 and EK - n_energy_out = size(this%table(i)%e_out) - E_i_1 = this%table(i)%e_out(1) - E_i_K = this%table(i)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i)%e_out) + E_i_1 = this%distribution(i)%e_out(1) + E_i_K = this%distribution(i)%e_out(n_energy_out) - n_energy_out = size(this%table(i+1)%e_out) - E_i1_1 = this%table(i+1)%e_out(1) - E_i1_K = this%table(i+1)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i+1)%e_out) + E_i1_1 = this%distribution(i+1)%e_out(1) + E_i1_K = this%distribution(i+1)%e_out(n_energy_out) E_1 = E_i_1 + r*(E_i1_1 - E_i_1) E_K = E_i_K + r*(E_i1_K - E_i_K) ! determine outgoing energy bin - n_energy_out = size(this%table(l)%e_out) + n_energy_out = size(this%distribution(l)%e_out) r1 = prn() - c_k = this%table(l)%c(1) + c_k = this%distribution(l)%c(1) do k = 1, n_energy_out - 1 - c_k1 = this%table(l)%c(k+1) + c_k1 = this%distribution(l)%c(k+1) if (r1 < c_k1) exit c_k = c_k1 end do @@ -106,9 +106,9 @@ contains ! check to make sure k is <= NP - 1 k = min(k, n_energy_out - 1) - E_l_k = this%table(l)%e_out(k) - p_l_k = this%table(l)%p(k) - if (this%table(l)%interpolation == HISTOGRAM) then + E_l_k = this%distribution(l)%e_out(k) + p_l_k = this%distribution(l)%p(k) + if (this%distribution(l)%interpolation == HISTOGRAM) then ! Histogram interpolation if (p_l_k > ZERO) then E_out = E_l_k + (r1 - c_k)/p_l_k @@ -116,10 +116,10 @@ contains E_out = E_l_k end if - elseif (this%table(l)%interpolation == LINEAR_LINEAR) then + elseif (this%distribution(l)%interpolation == LINEAR_LINEAR) then ! Linear-linear interpolation - E_l_k1 = this%table(l)%e_out(k+1) - p_l_k1 = this%table(l)%p(k+1) + E_l_k1 = this%distribution(l)%e_out(k+1) + p_l_k1 = this%distribution(l)%p(k+1) frac = (p_l_k1 - p_l_k)/(E_l_k1 - E_l_k) if (frac == ZERO) then @@ -139,9 +139,9 @@ contains ! Find correlated angular distribution for closest outgoing energy bin if (r1 - c_k < c_k1 - r1) then - mu = this%table(l)%angle(k)%obj%sample() + mu = this%distribution(l)%angle(k)%obj%sample() else - mu = this%table(l)%angle(k + 1)%obj%sample() + mu = this%distribution(l)%angle(k + 1)%obj%sample() end if end subroutine correlated_sample diff --git a/src/secondary_header.F90 b/src/secondary_header.F90 deleted file mode 100644 index d9a18b6b1..000000000 --- a/src/secondary_header.F90 +++ /dev/null @@ -1,83 +0,0 @@ -module secondary_header - - use constants, only: ZERO - use endf_header, only: Tab1 - use interpolation, only: interpolate_tab1 - use random_lcg, only: prn - -!=============================================================================== -! ANGLEENERGY (abstract) defines a correlated or uncorrelated angle-energy -! distribution that is a function of incoming energy. Each derived type must -! implement a sample() subroutine that returns an outgoing energy and scattering -! cosine given an incoming energy. -!=============================================================================== - - type, abstract :: AngleEnergy - contains - procedure(angleenergy_sample_), deferred :: sample - end type AngleEnergy - - abstract interface - subroutine angleenergy_sample_(this, E_in, E_out, mu) - import AngleEnergy - class(AngleEnergy), intent(in) :: this - real(8), intent(in) :: E_in - real(8), intent(out) :: E_out - real(8), intent(out) :: mu - end subroutine angleenergy_sample_ - end interface - - type :: AngleEnergyContainer - class(AngleEnergy), allocatable :: obj - end type AngleEnergyContainer - -!=============================================================================== -! SECONDARYDISTRIBUTION stores multiple angle-energy distributions, each of -! which has a given probability of occurring for a given incoming energy. In -! general, most secondary distributions only have one angle-energy distribution, -! but for some cases (e.g., (n,2n) in certain nuclides) multiple distinct -! distributions exist. -!=============================================================================== - - type :: SecondaryDistribution - type(Tab1), allocatable :: applicability(:) - type(AngleEnergyContainer), allocatable :: distribution(:) - contains - procedure :: sample => secondary_sample - end type SecondaryDistribution - -contains - - subroutine secondary_sample(this, E_in, E_out, mu) - class(SecondaryDistribution), intent(in) :: this - real(8), intent(in) :: E_in ! incoming energy - real(8), intent(out) :: E_out ! sampled outgoing energy - real(8), intent(out) :: mu ! sampled scattering cosine - - integer :: i ! loop counter - integer :: n ! number of angle-energy distributions - real(8) :: prob ! cumulative probability - real(8) :: c ! sampled cumulative probability - - n = size(this%applicability) - if (n > 1) then - prob = ZERO - c = prn() - do i = 1, n - ! Determine probability that i-th energy distribution is sampled - prob = prob + interpolate_tab1(this%applicability(i), E_in) - - ! If i-th distribution is sampled, sample energy from the distribution - if (c <= prob) then - call this%distribution(i)%obj%sample(E_in, E_out, mu) - exit - end if - end do - else - ! If only one distribution is present, go ahead and sample it - call this%distribution(1)%obj%sample(E_in, E_out, mu) - end if - - end subroutine secondary_sample - -end module secondary_header diff --git a/src/secondary_kalbach.F90 b/src/secondary_kalbach.F90 index 5e6949206..668917d62 100644 --- a/src/secondary_kalbach.F90 +++ b/src/secondary_kalbach.F90 @@ -1,7 +1,7 @@ module secondary_kalbach + use angleenergy_header, only: AngleEnergy use constants, only: ZERO, ONE, TWO, HISTOGRAM, LINEAR_LINEAR - use secondary_header, only: AngleEnergy use random_lcg, only: prn use search, only: binary_search @@ -25,8 +25,8 @@ module secondary_kalbach integer :: n_region ! number of interpolation regions integer, allocatable :: breakpoints(:) ! breakpoints of interpolation regions integer, allocatable :: interpolation(:) ! interpolation region codes - real(8), allocatable :: energy_in(:) ! incoming energies - type(KalbachMannTable), allocatable :: table(:) ! outgoing E/mu parameters + real(8), allocatable :: energy(:) ! incoming energies + type(KalbachMannTable), allocatable :: distribution(:) ! outgoing E/mu parameters contains procedure :: sample => kalbachmann_sample end type KalbachMann @@ -64,17 +64,17 @@ contains ! find energy bin and calculate interpolation factor -- if the energy is ! outside the range of the tabulated energies, choose the first or last bins - n_energy_in = size(this%energy_in) - if (E_in < this%energy_in(1)) then + n_energy_in = size(this%energy) + if (E_in < this%energy(1)) then i = 1 r = ZERO - elseif (E_in > this%energy_in(n_energy_in)) then + elseif (E_in > this%energy(n_energy_in)) then i = n_energy_in - 1 r = ONE else - i = binary_search(this%energy_in, n_energy_in, E_in) - r = (E_in - this%energy_in(i)) / & - (this%energy_in(i+1) - this%energy_in(i)) + i = binary_search(this%energy, n_energy_in, E_in) + r = (E_in - this%energy(i)) / & + (this%energy(i+1) - this%energy(i)) end if ! Sample between the ith and (i+1)th bin @@ -85,23 +85,23 @@ contains end if ! interpolation for energy E1 and EK - n_energy_out = size(this%table(i)%e_out) - E_i_1 = this%table(i)%e_out(1) - E_i_K = this%table(i)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i)%e_out) + E_i_1 = this%distribution(i)%e_out(1) + E_i_K = this%distribution(i)%e_out(n_energy_out) - n_energy_out = size(this%table(i+1)%e_out) - E_i1_1 = this%table(i+1)%e_out(1) - E_i1_K = this%table(i+1)%e_out(n_energy_out) + n_energy_out = size(this%distribution(i+1)%e_out) + E_i1_1 = this%distribution(i+1)%e_out(1) + E_i1_K = this%distribution(i+1)%e_out(n_energy_out) E_1 = E_i_1 + r*(E_i1_1 - E_i_1) E_K = E_i_K + r*(E_i1_K - E_i_K) ! determine outgoing energy bin - n_energy_out = size(this%table(l)%e_out) + n_energy_out = size(this%distribution(l)%e_out) r1 = prn() - c_k = this%table(l)%c(1) + c_k = this%distribution(l)%c(1) do k = 1, n_energy_out - 1 - c_k1 = this%table(l)%c(k+1) + c_k1 = this%distribution(l)%c(k+1) if (r1 < c_k1) exit c_k = c_k1 end do @@ -109,9 +109,9 @@ contains ! check to make sure k is <= NP - 1 k = min(k, n_energy_out - 1) - E_l_k = this%table(l)%e_out(k) - p_l_k = this%table(l)%p(k) - if (this%table(l)%interpolation == HISTOGRAM) then + E_l_k = this%distribution(l)%e_out(k) + p_l_k = this%distribution(l)%p(k) + if (this%distribution(l)%interpolation == HISTOGRAM) then ! Histogram interpolation if (p_l_k > ZERO) then E_out = E_l_k + (r1 - c_k)/p_l_k @@ -120,13 +120,13 @@ contains end if ! Determine Kalbach-Mann parameters - km_r = this%table(l)%r(k) - km_a = this%table(l)%a(k) + km_r = this%distribution(l)%r(k) + km_a = this%distribution(l)%a(k) - elseif (this%table(l)%interpolation == LINEAR_LINEAR) then + elseif (this%distribution(l)%interpolation == LINEAR_LINEAR) then ! Linear-linear interpolation - E_l_k1 = this%table(l)%e_out(k+1) - p_l_k1 = this%table(l)%p(k+1) + E_l_k1 = this%distribution(l)%e_out(k+1) + p_l_k1 = this%distribution(l)%p(k+1) frac = (p_l_k1 - p_l_k)/(E_l_k1 - E_l_k) if (frac == ZERO) then @@ -137,10 +137,10 @@ contains end if ! Determine Kalbach-Mann parameters - km_r = this%table(l)%r(k) + (E_out - E_l_k)/(E_l_k1 - E_l_k) * & - (this%table(l)%r(k+1) - this%table(l)%r(k)) - km_a = this%table(l)%a(k) + (E_out - E_l_k)/(E_l_k1 - E_l_k) * & - (this%table(l)%a(k+1) - this%table(l)%a(k)) + km_r = this%distribution(l)%r(k) + (E_out - E_l_k)/(E_l_k1 - E_l_k) * & + (this%distribution(l)%r(k+1) - this%distribution(l)%r(k)) + km_a = this%distribution(l)%a(k) + (E_out - E_l_k)/(E_l_k1 - E_l_k) * & + (this%distribution(l)%a(k+1) - this%distribution(l)%a(k)) end if ! Now interpolate between incident energy bins i and i + 1 diff --git a/src/secondary_nbody.F90 b/src/secondary_nbody.F90 new file mode 100644 index 000000000..71cae6fa2 --- /dev/null +++ b/src/secondary_nbody.F90 @@ -0,0 +1,70 @@ +module secondary_nbody + + use angleenergy_header, only: AngleEnergy + use constants, only: ONE, TWO, PI + use math, only: maxwell_spectrum + use random_lcg, only: prn + +!=============================================================================== +! NBODYPHASESPACE gives the energy distribution for particles emitted from +! neutron and charged-particle reactions. This corresponds to ACE law 66 and +! ENDF File 6, LAW=6. +!=============================================================================== + + type, extends(AngleEnergy) :: NBodyPhaseSpace + integer :: n_bodies + real(8) :: mass_ratio + real(8) :: A + real(8) :: Q + contains + procedure :: sample => nbody_sample + end type NBodyPhaseSpace + +contains + + subroutine nbody_sample(this, E_in, E_out, mu) + class(NBodyPhaseSpace), intent(in) :: this + real(8), intent(in) :: E_in ! incoming energy + real(8), intent(out) :: E_out ! sampled outgoing energy + real(8), intent(out) :: mu ! sampled outgoing energy + + real(8) :: Ap ! total mass of particles in neutron masses + real(8) :: E_max ! maximum possible COM energy + real(8) :: x, y, v + real(8) :: r1, r2, r3, r4, r5, r6 + + ! By definition, the distribution of the angle is isotropic for an N-body + ! phase space distribution + mu = TWO*prn() - ONE + + ! Determine E_max parameter + Ap = this%mass_ratio + E_max = (Ap - ONE)/Ap * (this%A/(this%A + ONE)*E_in + this%Q) + + ! x is essentially a Maxwellian distribution + x = maxwell_spectrum(ONE) + + select case (this%n_bodies) + case (3) + y = maxwell_spectrum(ONE) + case (4) + r1 = prn() + r2 = prn() + r3 = prn() + y = -log(r1*r2*r3) + case (5) + r1 = prn() + r2 = prn() + r3 = prn() + r4 = prn() + r5 = prn() + r6 = prn() + y = -log(r1*r2*r3*r4) - log(r5) * cos(PI/TWO*r6)**2 + end select + + ! Now determine v and E_out + v = x/(x+y) + E_out = E_max * v + end subroutine nbody_sample + +end module secondary_nbody diff --git a/src/secondary_uncorrelated.F90 b/src/secondary_uncorrelated.F90 index 22a56aa12..7bc8fa13d 100644 --- a/src/secondary_uncorrelated.F90 +++ b/src/secondary_uncorrelated.F90 @@ -1,9 +1,9 @@ module secondary_uncorrelated use angle_distribution, only: AngleDistribution + use angleenergy_header, only: AngleEnergy use constants, only: ONE, TWO use energy_distribution, only: EnergyDistribution - use secondary_header, only: AngleEnergy use random_lcg, only: prn !=============================================================================== diff --git a/src/simulation.F90 b/src/simulation.F90 index 41a28741c..b762979d7 100644 --- a/src/simulation.F90 +++ b/src/simulation.F90 @@ -1,7 +1,7 @@ module simulation #ifdef MPI - use mpi + use message_passing #endif use cmfd_execute, only: cmfd_init_batch, execute_cmfd diff --git a/src/source.F90 b/src/source.F90 index ad565c95c..194c8c6ad 100644 --- a/src/source.F90 +++ b/src/source.F90 @@ -53,7 +53,7 @@ contains file_id = file_open(path_source, 'r', parallel=.true.) ! Read the file type - call read_dataset(file_id, "filetype", filetype) + call read_dataset(filetype, file_id, "filetype") ! Check to make sure this is a source file if (filetype /= 'source') then diff --git a/src/state_point.F90 b/src/state_point.F90 index 6c0e309e2..f37950134 100644 --- a/src/state_point.F90 +++ b/src/state_point.F90 @@ -49,10 +49,8 @@ contains integer, allocatable :: id_array(:) integer, allocatable :: key_array(:) integer(HID_T) :: file_id - integer(HID_T) :: cmfd_group - integer(HID_T) :: tallies_group, tally_group - integer(HID_T) :: meshes_group, mesh_group - integer(HID_T) :: filter_group + integer(HID_T) :: cmfd_group, tallies_group, tally_group, meshes_group, & + mesh_group, filter_group, runtime_group character(20), allocatable :: str_array(:) character(MAX_FILE_LEN) :: filename type(RegularMesh), pointer :: meshp @@ -133,13 +131,13 @@ contains call write_dataset(file_id, "cmfd_on", 1) cmfd_group = create_group(file_id, "cmfd") - call write_dataset(cmfd_group, "indices", cmfd%indices) - call write_dataset(cmfd_group, "k_cmfd", cmfd%k_cmfd) - call write_dataset(cmfd_group, "cmfd_src", cmfd%cmfd_src) - call write_dataset(cmfd_group, "cmfd_entropy", cmfd%entropy) - call write_dataset(cmfd_group, "cmfd_balance", cmfd%balance) - call write_dataset(cmfd_group, "cmfd_dominance", cmfd%dom) - call write_dataset(cmfd_group, "cmfd_srccmp", cmfd%src_cmp) + call write_dataset(cmfd_group, "indices", cmfd % indices) + call write_dataset(cmfd_group, "k_cmfd", cmfd % k_cmfd) + call write_dataset(cmfd_group, "cmfd_src", cmfd % cmfd_src) + call write_dataset(cmfd_group, "cmfd_entropy", cmfd % entropy) + call write_dataset(cmfd_group, "cmfd_balance", cmfd % balance) + call write_dataset(cmfd_group, "cmfd_dominance", cmfd % dom) + call write_dataset(cmfd_group, "cmfd_srccmp", cmfd % src_cmp) call close_group(cmfd_group) else call write_dataset(file_id, "cmfd_on", 0) @@ -155,18 +153,18 @@ contains if (n_meshes > 0) then ! Print list of mesh IDs - current => mesh_dict%keys() + current => mesh_dict % keys() allocate(id_array(n_meshes)) allocate(key_array(n_meshes)) i = 1 do while (associated(current)) - key_array(i) = current%key - id_array(i) = current%value + key_array(i) = current % key + id_array(i) = current % value ! Move to next mesh - next => current%next + next => current % next deallocate(current) current => next i = i + 1 @@ -180,16 +178,17 @@ contains ! Write information for meshes MESH_LOOP: do i = 1, n_meshes meshp => meshes(id_array(i)) - mesh_group = create_group(meshes_group, "mesh " // trim(to_str(meshp%id))) + mesh_group = create_group(meshes_group, "mesh " & + // trim(to_str(meshp % id))) - select case (meshp%type) + select case (meshp % type) case (MESH_REGULAR) call write_dataset(mesh_group, "type", "regular") end select - call write_dataset(mesh_group, "dimension", meshp%dimension) - call write_dataset(mesh_group, "lower_left", meshp%lower_left) - call write_dataset(mesh_group, "upper_right", meshp%upper_right) - call write_dataset(mesh_group, "width", meshp%width) + call write_dataset(mesh_group, "dimension", meshp % dimension) + call write_dataset(mesh_group, "lower_left", meshp % lower_left) + call write_dataset(mesh_group, "upper_right", meshp % upper_right) + call write_dataset(mesh_group, "width", meshp % width) call close_group(mesh_group) end do MESH_LOOP @@ -211,7 +210,7 @@ contains ! Write all tally information except results do i = 1, n_tallies tally => tallies(i) - key_array(i) = tally%id + key_array(i) = tally % id id_array(i) = i end do @@ -226,9 +225,9 @@ contains ! Get pointer to tally tally => tallies(i) tally_group = create_group(tallies_group, "tally " // & - trim(to_str(tally%id))) + trim(to_str(tally % id))) - select case(tally%estimator) + select case(tally % estimator) case (ESTIMATOR_ANALOG) call write_dataset(tally_group, "estimator", "analog") case (ESTIMATOR_TRACKLENGTH) @@ -236,16 +235,17 @@ contains case (ESTIMATOR_COLLISION) call write_dataset(tally_group, "estimator", "collision") end select - call write_dataset(tally_group, "n_realizations", tally%n_realizations) - call write_dataset(tally_group, "n_filters", tally%n_filters) + call write_dataset(tally_group, "n_realizations", & + tally % n_realizations) + call write_dataset(tally_group, "n_filters", tally % n_filters) ! Write filter information - FILTER_LOOP: do j = 1, tally%n_filters + FILTER_LOOP: do j = 1, tally % n_filters filter_group = create_group(tally_group, "filter " // & trim(to_str(j))) ! Write name of type - select case (tally%filters(j)%type) + select case (tally % filters(j) % type) case(FILTER_UNIVERSE) call write_dataset(filter_group, "type", "universe") case(FILTER_MATERIAL) @@ -274,36 +274,41 @@ contains call write_dataset(filter_group, "type", "delayedgroup") end select - call write_dataset(filter_group, "n_bins", tally%filters(j)%n_bins) + call write_dataset(filter_group, "n_bins", & + tally % filters(j) % n_bins) if (tally % filters(j) % type == FILTER_ENERGYIN .or. & tally % filters(j) % type == FILTER_ENERGYOUT .or. & tally % filters(j) % type == FILTER_MU .or. & tally % filters(j) % type == FILTER_POLAR .or. & tally % filters(j) % type == FILTER_AZIMUTHAL) then call write_dataset(filter_group, "bins", & - tally%filters(j)%real_bins) + tally % filters(j) % real_bins) else call write_dataset(filter_group, "bins", & - tally%filters(j)%int_bins) + tally % filters(j) % int_bins) end if call close_group(filter_group) end do FILTER_LOOP ! Set up nuclide bin array and then write - allocate(str_array(tally%n_nuclide_bins)) - NUCLIDE_LOOP: do j = 1, tally%n_nuclide_bins - if (tally%nuclide_bins(j) > 0) then + allocate(str_array(tally % n_nuclide_bins)) + NUCLIDE_LOOP: do j = 1, tally % n_nuclide_bins + if (tally % nuclide_bins(j) > 0) then ! Get index in cross section listings for this nuclide - i_list = nuclides(tally%nuclide_bins(j))%listing + if (run_CE) then + i_list = nuclides(tally % nuclide_bins(j)) % listing + else + i_list = nuclides_MG(tally % nuclide_bins(j)) % obj % listing + end if ! Determine position of . in alias string (e.g. "U-235.71c"). If ! no . is found, just use the entire string. - i_xs = index(xs_listings(i_list)%alias, '.') + i_xs = index(xs_listings(i_list) % alias, '.') if (i_xs > 0) then - str_array(j) = xs_listings(i_list)%alias(1:i_xs - 1) + str_array(j) = xs_listings(i_list) % alias(1:i_xs - 1) else - str_array(j) = xs_listings(i_list)%alias + str_array(j) = xs_listings(i_list) % alias end if else str_array(j) = 'total' @@ -312,32 +317,33 @@ contains call write_dataset(tally_group, "nuclides", str_array) deallocate(str_array) - call write_dataset(tally_group, "n_score_bins", tally%n_score_bins) - allocate(str_array(size(tally%score_bins))) - do j = 1, size(tally%score_bins) - str_array(j) = reaction_name(tally%score_bins(j)) + call write_dataset(tally_group, "n_score_bins", tally % n_score_bins) + allocate(str_array(size(tally % score_bins))) + do j = 1, size(tally % score_bins) + str_array(j) = reaction_name(tally % score_bins(j)) end do call write_dataset(tally_group, "score_bins", str_array) - call write_dataset(tally_group, "n_user_score_bins", tally%n_user_score_bins) + call write_dataset(tally_group, "n_user_score_bins", & + tally % n_user_score_bins) deallocate(str_array) ! Write explicit moment order strings for each score bin k = 1 - allocate(str_array(tally%n_score_bins)) - MOMENT_LOOP: do j = 1, tally%n_user_score_bins - select case(tally%score_bins(k)) + allocate(str_array(tally % n_score_bins)) + MOMENT_LOOP: do j = 1, tally % n_user_score_bins + select case(tally % score_bins(k)) case (SCORE_SCATTER_N, SCORE_NU_SCATTER_N) - str_array(k) = 'P' // trim(to_str(tally%moment_order(k))) + str_array(k) = trim(to_str(tally % moment_order(k))) k = k + 1 case (SCORE_SCATTER_PN, SCORE_NU_SCATTER_PN) - do n_order = 0, tally%moment_order(k) - str_array(k) = 'P' // trim(to_str(n_order)) + do n_order = 0, tally % moment_order(k) + str_array(k) = trim(to_str(n_order)) k = k + 1 end do case (SCORE_SCATTER_YN, SCORE_NU_SCATTER_YN, SCORE_FLUX_YN, & SCORE_TOTAL_YN) - do n_order = 0, tally%moment_order(k) + do n_order = 0, tally % moment_order(k) do nm_order = -n_order, n_order str_array(k) = 'Y' // trim(to_str(n_order)) // ',' // & trim(to_str(nm_order)) @@ -389,8 +395,9 @@ contains tally => tallies(i) ! Write sum and sum_sq for each bin - tally_group = open_group(tallies_group, "tally " // to_str(tally%id)) - call write_dataset(tally_group, "results", tally%results) + tally_group = open_group(tallies_group, "tally " & + // to_str(tally % id)) + call write_dataset(tally_group, "results", tally % results) call close_group(tally_group) end do TALLY_RESULTS @@ -400,13 +407,45 @@ contains end if call close_group(tallies_group) + + ! Write out the runtime metrics. + runtime_group = create_group(file_id, "runtime") + call write_dataset(runtime_group, "total initialization", & + time_initialize % get_value()) + call write_dataset(runtime_group, "reading cross sections", & + time_read_xs % get_value()) + call write_dataset(runtime_group, "simulation", & + time_inactive % get_value() + time_active % get_value()) + call write_dataset(runtime_group, "transport", & + time_transport % get_value()) + if (run_mode == MODE_EIGENVALUE) then + call write_dataset(runtime_group, "inactive batches", & + time_inactive % get_value()) + end if + call write_dataset(runtime_group, "active batches", & + time_active % get_value()) + if (run_mode == MODE_EIGENVALUE) then + call write_dataset(runtime_group, "synchronizing fission bank", & + time_bank % get_value()) + call write_dataset(runtime_group, "sampling source sites", & + time_bank_sample % get_value()) + call write_dataset(runtime_group, "SEND-RECV source sites", & + time_bank_sendrecv % get_value()) + end if + call write_dataset(runtime_group, "accumulating tallies", & + time_tallies % get_value()) + if (cmfd_run) then + call write_dataset(runtime_group, "CMFD", time_cmfd % get_value()) + call write_dataset(runtime_group, "CMFD building matrices", & + time_cmfdbuild % get_value()) + call write_dataset(runtime_group, "CMFD solving matrices", & + time_cmfdsolve % get_value()) + end if + call write_dataset(runtime_group, "total", time_total % get_value()) + call close_group(runtime_group) + call file_close(file_id) end if - - if (master .and. n_tallies > 0) then - deallocate(id_array) - end if - end subroutine write_state_point !=============================================================================== @@ -664,25 +703,25 @@ contains file_id = file_open(path_state_point, 'r', parallel=.true.) ! Read filetype - call read_dataset(file_id, "filetype", word) + call read_dataset(word, file_id, "filetype") if (word /= 'statepoint') then call fatal_error("OpenMC tried to restart from a non-statepoint file.") end if ! Read revision number for state point file and make sure it matches with ! current version - call read_dataset(file_id, "revision", int_array(1)) + call read_dataset(int_array(1), file_id, "revision") if (int_array(1) /= REVISION_STATEPOINT) then call fatal_error("State point version does not match current version & &in OpenMC.") end if ! Read and overwrite random number seed - call read_dataset(file_id, "seed", seed) + call read_dataset(seed, file_id, "seed") ! It is not impossible for a state point to be generated from a CE run but ! to be loaded in to an MG run (or vice versa), check to prevent that. - call read_dataset(file_id, "run_CE", sp_run_CE) + call read_dataset(sp_run_CE, file_id, "run_CE") if (sp_run_CE == 0 .and. run_CE) then call fatal_error("State point file is from multi-group run but & & current run is continous-energy!") @@ -692,24 +731,24 @@ contains end if ! Read and overwrite run information except number of batches - call read_dataset(file_id, "run_mode", word) + call read_dataset(word, file_id, "run_mode") select case(word) case ('fixed source') run_mode = MODE_FIXEDSOURCE case ('k-eigenvalue') run_mode = MODE_EIGENVALUE end select - call read_dataset(file_id, "n_particles", n_particles) - call read_dataset(file_id, "n_batches", int_array(1)) + call read_dataset(n_particles, file_id, "n_particles") + call read_dataset(int_array(1), file_id, "n_batches") ! Take maximum of statepoint n_batches and input n_batches n_batches = max(n_batches, int_array(1)) ! Read batch number to restart at - call read_dataset(file_id, "current_batch", restart_batch) + call read_dataset(restart_batch, file_id, "current_batch") ! Check for source in statepoint if needed - call read_dataset(file_id, "source_present", int_array(1)) + call read_dataset(int_array(1), file_id, "source_present") if (int_array(1) == 1) then source_present = .true. else @@ -723,37 +762,37 @@ contains ! Read information specific to eigenvalue run if (run_mode == MODE_EIGENVALUE) then - call read_dataset(file_id, "n_inactive", int_array(1)) - call read_dataset(file_id, "gen_per_batch", gen_per_batch) - call read_dataset(file_id, "k_generation", & - k_generation(1:restart_batch*gen_per_batch)) - call read_dataset(file_id, "entropy", & - entropy(1:restart_batch*gen_per_batch)) - call read_dataset(file_id, "k_col_abs", k_col_abs) - call read_dataset(file_id, "k_col_tra", k_col_tra) - call read_dataset(file_id, "k_abs_tra", k_abs_tra) - call read_dataset(file_id, "k_combined", real_array(1:2)) + call read_dataset(int_array(1), file_id, "n_inactive") + call read_dataset(gen_per_batch, file_id, "gen_per_batch") + call read_dataset(k_generation(1:restart_batch*gen_per_batch), & + file_id, "k_generation") + call read_dataset(entropy(1:restart_batch*gen_per_batch), & + file_id, "entropy") + call read_dataset(k_col_abs, file_id, "k_col_abs") + call read_dataset(k_col_tra, file_id, "k_col_tra") + call read_dataset(k_abs_tra, file_id, "k_abs_tra") + call read_dataset(real_array(1:2), file_id, "k_combined") ! Take maximum of statepoint n_inactive and input n_inactive n_inactive = max(n_inactive, int_array(1)) ! Read in to see if CMFD was on - call read_dataset(file_id, "cmfd_on", int_array(1)) + call read_dataset(int_array(1), file_id, "cmfd_on") ! Read in CMFD info if (int_array(1) == 1) then cmfd_group = open_group(file_id, "cmfd") - call read_dataset(cmfd_group, "indices", cmfd%indices) - call read_dataset(cmfd_group, "k_cmfd", cmfd%k_cmfd(1:restart_batch)) - call read_dataset(cmfd_group, "cmfd_src", cmfd%cmfd_src) - call read_dataset(cmfd_group, "cmfd_entropy", & - cmfd%entropy(1:restart_batch)) - call read_dataset(cmfd_group, "cmfd_balance", & - cmfd%balance(1:restart_batch)) - call read_dataset(cmfd_group, "cmfd_dominance", & - cmfd%dom(1:restart_batch)) - call read_dataset(cmfd_group, "cmfd_srccmp", & - cmfd%src_cmp(1:restart_batch)) + call read_dataset(cmfd % indices, cmfd_group, "indices") + call read_dataset(cmfd % k_cmfd(1:restart_batch), cmfd_group, "k_cmfd") + call read_dataset(cmfd % cmfd_src, cmfd_group, "cmfd_src") + call read_dataset(cmfd % entropy(1:restart_batch), cmfd_group, & + "cmfd_entropy") + call read_dataset(cmfd % balance(1:restart_batch), cmfd_group, & + "cmfd_balance") + call read_dataset(cmfd % dom(1:restart_batch), cmfd_group, & + "cmfd_dominance") + call read_dataset(cmfd % src_cmp(1:restart_batch), cmfd_group, & + "cmfd_srccmp") call close_group(cmfd_group) end if end if @@ -773,14 +812,14 @@ contains #endif ! Read number of realizations for global tallies - call read_dataset(file_id, "n_realizations", n_realizations, indep=.true.) + call read_dataset(n_realizations, file_id, "n_realizations", indep=.true.) ! Read global tally data call read_dataset(file_id, "global_tallies", global_tallies) ! Check if tally results are present tallies_group = open_group(file_id, "tallies") - call read_dataset(tallies_group, "tallies_present", int_array(1), & + call read_dataset(int_array(1), tallies_group, "tallies_present", & indep=.true.) ! Read in sum and sum squared @@ -793,8 +832,8 @@ contains tally_group = open_group(tallies_group, "tally " // & trim(to_str(tally % id))) call read_dataset(tally_group, "results", tally % results) - call read_dataset(tally_group, "n_realizations", & - tally % n_realizations) + call read_dataset(tally % n_realizations, tally_group, & + "n_realizations") call close_group(tally_group) end do TALLY_RESULTS end if @@ -820,7 +859,7 @@ contains file_id = file_open(path_source_point, 'r', parallel=.true.) ! Read file type - call read_dataset(file_id, "filetype", int_array(1)) + call read_dataset(int_array(1), file_id, "filetype") end if diff --git a/src/summary.F90 b/src/summary.F90 index e662aa473..aabf6c22b 100644 --- a/src/summary.F90 +++ b/src/summary.F90 @@ -1,10 +1,9 @@ module summary - use ace_header, only: Reaction, UrrData use constants use endf, only: reaction_name use geometry_header, only: Cell, Universe, Lattice, RectLattice, & - &HexLattice + &HexLattice, BASE_UNIVERSE use global use hdf5_interface use material_header, only: Material @@ -14,6 +13,7 @@ module summary use surface_header use string, only: to_str use tally_header, only: TallyObject + use output, only: find_offset use hdf5 @@ -68,6 +68,7 @@ contains "description", "Number of generations per batch") end if + call write_nuclides(file_id) call write_geometry(file_id) call write_materials(file_id) if (n_tallies > 0) then @@ -105,6 +106,49 @@ contains end subroutine write_header +!=============================================================================== +! WRITE_NUCLIDES +!=============================================================================== + + subroutine write_nuclides(file_id) + integer(HID_T), intent(in) :: file_id + integer(HID_T) :: nuclide_group + integer :: i + character(12), allocatable :: nucnames(:) + real(8), allocatable :: awrs(:) + integer, allocatable :: zaids(:) + + ! Write useful data from nuclide objects + nuclide_group = create_group(file_id, "nuclides") + call write_dataset(nuclide_group, "n_nuclides_total", n_nuclides_total) + + ! Build array of nuclide names, awrs, and zaids + allocate(nucnames(n_nuclides_total)) + allocate(awrs(n_nuclides_total)) + allocate(zaids(n_nuclides_total)) + do i = 1, n_nuclides_total + if (run_CE) then + nucnames(i) = xs_listings(nuclides(i) % listing) % alias + awrs(i) = nuclides(i) % awr + zaids(i) = nuclides(i) % zaid + else + nucnames(i) = xs_listings(nuclides_MG(i) % obj % listing) % alias + awrs(i) = nuclides_MG(i) % obj % awr + zaids(i) = nuclides_MG(i) % obj % zaid + end if + end do + + ! Write nuclide names, awrs and zaids + call write_dataset(nuclide_group, "names", nucnames) + call write_dataset(nuclide_group, "awrs", awrs) + call write_dataset(nuclide_group, "zaids", zaids) + + call close_group(nuclide_group) + + deallocate(nucnames, awrs, zaids) + + end subroutine write_nuclides + !=============================================================================== ! WRITE_GEOMETRY !=============================================================================== @@ -534,6 +578,10 @@ contains type(RegularMesh), pointer :: m type(TallyObject), pointer :: t + integer :: offset ! distibcell offset + character(MAX_LINE_LEN), allocatable :: paths(:) ! distribcell paths array + character(MAX_LINE_LEN) :: path ! distribcell path + tallies_group = create_group(file_id, "tallies") ! Write total number of meshes @@ -576,21 +624,40 @@ contains ! Write number of filters call write_dataset(tally_group, "n_filters", t%n_filters) - FILTER_LOOP: do j = 1, t%n_filters + FILTER_LOOP: do j = 1, t % n_filters filter_group = create_group(tally_group, "filter " // trim(to_str(j))) ! Write number of bins for this filter - call write_dataset(filter_group, "n_bins", t%filters(j)%n_bins) + call write_dataset(filter_group, "n_bins", t % filters(j) % n_bins) ! Write filter bins - if (t%filters(j)%type == FILTER_ENERGYIN .or. & - t%filters(j)%type == FILTER_ENERGYOUT .or. & - t%filters(j)%type == FILTER_MU .or. & - t%filters(j)%type == FILTER_POLAR .or. & - t%filters(j)%type == FILTER_AZIMUTHAL) then - call write_dataset(filter_group, "bins", t%filters(j)%real_bins) + if (t % filters(j) % type == FILTER_ENERGYIN .or. & + t % filters(j)% type == FILTER_ENERGYOUT .or. & + t % filters(j) % type == FILTER_MU .or. & + t % filters(j) % type == FILTER_POLAR .or. & + t % filters(j) % type == FILTER_AZIMUTHAL) then + call write_dataset(filter_group, "bins", t % filters(j) % real_bins) else - call write_dataset(filter_group, "bins", t%filters(j)%int_bins) + call write_dataset(filter_group, "bins", t % filters(j) % int_bins) + end if + + ! Write paths to reach each distribcell instance + if (t % filters(j) % type == FILTER_DISTRIBCELL) then + ! Allocate array of strings for each distribcell path + allocate(paths(t % filters(j) % n_bins)) + + ! Store path for each distribcell instance + do k = 1, t % filters(j) % n_bins + path = '' + offset = 1 + call find_offset(t % filters(j) % int_bins(1), & + universes(BASE_UNIVERSE), k, offset, path) + paths(k) = path + end do + + ! Write array of distribcell paths to summary file + call write_dataset(filter_group, "paths", paths) + deallocate(paths) end if ! Write name of type @@ -630,7 +697,11 @@ contains allocate(str_array(t%n_nuclide_bins)) NUCLIDE_LOOP: do j = 1, t%n_nuclide_bins if (t%nuclide_bins(j) > 0) then - i_list = nuclides(t%nuclide_bins(j))%listing + if (run_CE) then + i_list = nuclides(t % nuclide_bins(j)) % listing + else + i_list = nuclides_MG(t % nuclide_bins(j)) % obj % listing + end if i_xs = index(xs_listings(i_list)%alias, '.') if (i_xs > 0) then str_array(j) = xs_listings(i_list)%alias(1:i_xs - 1) @@ -694,63 +765,4 @@ contains end subroutine write_tallies -!=============================================================================== -! WRITE_TIMING -!=============================================================================== - - subroutine write_timing(file_id) - integer(HID_T), intent(in) :: file_id - - integer(8) :: total_particles - integer(HID_T) :: time_group - real(8) :: speed - - time_group = create_group(file_id, "timing") - - ! Write timing data - call write_dataset(time_group, "time_initialize", time_initialize%elapsed) - call write_dataset(time_group, "time_read_xs", time_read_xs%elapsed) - call write_dataset(time_group, "time_transport", time_transport%elapsed) - call write_dataset(time_group, "time_bank", time_bank%elapsed) - call write_dataset(time_group, "time_bank_sample", time_bank_sample%elapsed) - call write_dataset(time_group, "time_bank_sendrecv", time_bank_sendrecv%elapsed) - call write_dataset(time_group, "time_tallies", time_tallies%elapsed) - call write_dataset(time_group, "time_inactive", time_inactive%elapsed) - call write_dataset(time_group, "time_active", time_active%elapsed) - call write_dataset(time_group, "time_finalize", time_finalize%elapsed) - call write_dataset(time_group, "time_total", time_total%elapsed) - - ! Add descriptions to timing data - call write_attribute_string(time_group, "time_initialize", "description", & - "Total time elapsed for initialization (s)") - call write_attribute_string(time_group, "time_read_xs", "description", & - "Time reading cross-section libraries (s)") - call write_attribute_string(time_group, "time_transport", "description", & - "Time in transport only (s)") - call write_attribute_string(time_group, "time_bank", "description", & - "Total time synchronizing fission bank (s)") - call write_attribute_string(time_group, "time_bank_sample", "description", & - "Time between generations sampling source sites (s)") - call write_attribute_string(time_group, "time_bank_sendrecv", "description", & - "Time between generations SEND/RECVing source sites (s)") - call write_attribute_string(time_group, "time_tallies", "description", & - "Time between batches accumulating tallies (s)") - call write_attribute_string(time_group, "time_inactive", "description", & - "Total time in inactive batches (s)") - call write_attribute_string(time_group, "time_active", "description", & - "Total time in active batches (s)") - call write_attribute_string(time_group, "time_finalize", "description", & - "Total time for finalization (s)") - call write_attribute_string(time_group, "time_total", "description", & - "Total time elapsed (s)") - - ! Write calculation rate - total_particles = n_particles * n_batches * gen_per_batch - speed = real(total_particles) / (time_inactive%elapsed + & - time_active%elapsed) - call write_dataset(time_group, "neutrons_per_second", speed) - - call close_group(time_group) - end subroutine write_timing - end module summary diff --git a/src/surface_header.F90 b/src/surface_header.F90 index 468655217..68e5144b7 100644 --- a/src/surface_header.F90 +++ b/src/surface_header.F90 @@ -1,6 +1,6 @@ module surface_header - use constants, only: ONE, TWO, ZERO, HALF, INFINITY, FP_COINCIDENT + use constants, only: NONE, ONE, TWO, ZERO, HALF, INFINITY, FP_COINCIDENT implicit none @@ -15,7 +15,8 @@ module surface_header neighbor_pos(:), & ! List of cells on positive side neighbor_neg(:) ! List of cells on negative side integer :: bc ! Boundary condition - character(len=104) :: name = "" ! User-defined name + integer :: i_periodic = NONE ! Index of corresponding periodic surface + character(len=104) :: name = "" ! User-defined name contains procedure :: sense procedure :: reflect diff --git a/src/tally.F90 b/src/tally.F90 index 5a54d9846..0c41b6f98 100644 --- a/src/tally.F90 +++ b/src/tally.F90 @@ -1,7 +1,7 @@ module tally - use ace_header, only: Reaction use constants + use endf_header, only: Constant1D use error, only: fatal_error use geometry_header use global @@ -15,8 +15,6 @@ module tally use search, only: binary_search use string, only: to_str use tally_header, only: TallyResult, TallyMapItem, TallyMapElement - use fission, only: nu_total, nu_delayed, yield_delayed - use interpolation, only: interpolate_tab1 #ifdef MPI use message_passing @@ -28,8 +26,9 @@ module tally !$omp threadprivate(position) - procedure(score_general_), pointer :: score_general => null() - procedure(get_scoring_bins_), pointer :: get_scoring_bins => null() + procedure(score_general_), pointer :: score_general => null() + procedure(score_analog_tally_), pointer :: score_analog_tally => null() + procedure(get_scoring_bins_), pointer :: get_scoring_bins => null() abstract interface subroutine score_general_(p, t, start_index, filter_index, i_nuclide, & @@ -45,6 +44,11 @@ module tally real(8), intent(in) :: atom_density ! atom/b-cm end subroutine score_general_ + subroutine score_analog_tally_(p) + import Particle + type(Particle), intent(in) :: p + end subroutine score_analog_tally_ + subroutine get_scoring_bins_(p, i_tally, found_bin) import Particle type(Particle), intent(in) :: p @@ -62,11 +66,13 @@ contains subroutine init_tally_routines() if (run_CE) then - score_general => score_general_ce - get_scoring_bins => get_scoring_bins_ce + score_general => score_general_ce + score_analog_tally => score_analog_tally_ce + get_scoring_bins => get_scoring_bins_ce else - score_general => score_general_mg - get_scoring_bins => get_scoring_bins_mg + score_general => score_general_mg + score_analog_tally => score_analog_tally_mg + get_scoring_bins => get_scoring_bins_mg end if end subroutine init_tally_routines @@ -245,9 +251,9 @@ contains ! Only analog estimators are available. ! Skip any event where the particle didn't scatter if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of - ! neutrons exiting a reaction with neutrons in the exit channel + ! For scattering production, we need to use the pre-collision weight + ! times the yield as the estimate for the number of neutrons exiting a + ! reaction with neutrons in the exit channel if (p % event_MT == ELASTIC .or. p % event_MT == N_LEVEL .or. & (p % event_MT >= N_N1 .and. p % event_MT <= N_NC)) then ! Don't waste time on very common reactions we know have multiplicities @@ -257,16 +263,17 @@ contains m = nuclides(p%event_nuclide)%reaction_index% & get_key(p % event_MT) - ! Get multiplicity and apply to score + ! Get yield and apply to score associate (rxn => nuclides(p%event_nuclide)%reactions(m)) - if (rxn % multiplicity_with_E) then - ! Then the multiplicity was already incorporated in to p % wgt - ! per the scattering routine, + select type (yield => rxn % products(1) % yield) + type is (Constant1D) + ! Grab the yield from the reaction + score = p % last_wgt * yield % y + class default + ! the yield was already incorporated in to p % wgt per the + ! scattering routine score = p % wgt - else - ! Grab the multiplicity from the rxn - score = p % last_wgt * rxn % multiplicity - end if + end select end associate end if @@ -279,7 +286,7 @@ contains cycle SCORE_LOOP end if ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of + ! weight times the yield as the estimate for the number of ! neutrons exiting a reaction with neutrons in the exit channel if (p % event_MT == ELASTIC .or. p % event_MT == N_LEVEL .or. & (p % event_MT >= N_N1 .and. p % event_MT <= N_NC)) then @@ -290,16 +297,17 @@ contains m = nuclides(p%event_nuclide)%reaction_index% & get_key(p % event_MT) - ! Get multiplicity and apply to score + ! Get yield and apply to score associate (rxn => nuclides(p%event_nuclide)%reactions(m)) - if (rxn % multiplicity_with_E) then - ! Then the multiplicity was already incorporated in to p % wgt - ! per the scattering routine, + select type (yield => rxn % products(1) % yield) + type is (Constant1D) + ! Grab the yield from the reaction + score = p % last_wgt * yield % y + class default + ! the yield was already incorporated in to p % wgt per the + ! scattering routine score = p % wgt - else - ! Grab the multiplicity from the rxn - score = p % last_wgt * rxn % multiplicity - end if + end select end associate end if @@ -312,7 +320,7 @@ contains cycle SCORE_LOOP end if ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of + ! weight times the yield as the estimate for the number of ! neutrons exiting a reaction with neutrons in the exit channel if (p % event_MT == ELASTIC .or. p % event_MT == N_LEVEL .or. & (p % event_MT >= N_N1 .and. p % event_MT <= N_NC)) then @@ -323,44 +331,21 @@ contains m = nuclides(p%event_nuclide)%reaction_index% & get_key(p % event_MT) - ! Get multiplicity and apply to score + ! Get yield and apply to score associate (rxn => nuclides(p%event_nuclide)%reactions(m)) - if (rxn % multiplicity_with_E) then - ! Then the multiplicity was already incorporated in to p % wgt - ! per the scattering routine, + select type (yield => rxn % products(1) % yield) + type is (Constant1D) + ! Grab the yield from the reaction + score = p % last_wgt * yield % y + class default + ! the yield was already incorporated in to p % wgt per the + ! scattering routine score = p % wgt - else - ! Grab the multiplicity from the rxn - score = p % last_wgt * rxn % multiplicity - end if + end select end associate end if - case (SCORE_TRANSPORT) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! get material macros - macro_total = material_xs % total - macro_scatt = material_xs % total - material_xs % absorption - ! Score total rate - p1 scatter rate Note estimator needs to be - ! adjusted since tallying is only occuring when a scatter has - ! happened. Effectively this means multiplying the estimator by - ! total/scatter macro - score = (macro_total - p % mu * macro_scatt) * (ONE / macro_scatt) - - - case (SCORE_N_1N) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! Skip any events where weight of particle changed - if (p % wgt /= p % last_wgt) cycle SCORE_LOOP - ! All events that reach this point are (n,1n) reactions - score = p % last_wgt - - case (SCORE_ABSORPTION) if (t % estimator == ESTIMATOR_ANALOG) then if (survival_biasing) then @@ -499,12 +484,11 @@ contains d = t % filters(dg_filter) % int_bins(d_bin) ! Compute the yield for this delayed group - yield = yield_delayed(nuclides(p % event_nuclide), E, d) + yield = nuclides(p % event_nuclide) % nu(E, EMISSION_DELAYED, d) ! Compute the score and tally to bin score = p % absorb_wgt * yield * micro_xs(p % event_nuclide) & - % fission * nu_delayed(nuclides(p % event_nuclide), E) / & - micro_xs(p % event_nuclide) % absorption + % fission / micro_xs(p % event_nuclide) % absorption call score_fission_delayed_dg(t, d_bin, score, score_index) end do cycle SCORE_LOOP @@ -512,9 +496,9 @@ contains ! If the delayed group filter is not present, compute the score ! by multiplying the absorbed weight by the fraction of the ! delayed-nu-fission xs to the absorption xs - score = p % absorb_wgt * micro_xs(p % event_nuclide) & - % fission * nu_delayed(nuclides(p % event_nuclide), E) / & - micro_xs(p % event_nuclide) % absorption + score = p % absorb_wgt * micro_xs(p % event_nuclide) % fission & + * nuclides(p % event_nuclide) % nu(E, EMISSION_DELAYED) & + / micro_xs(p % event_nuclide) % absorption end if end if else @@ -564,11 +548,11 @@ contains d = t % filters(dg_filter) % int_bins(d_bin) ! Compute the yield for this delayed group - yield = yield_delayed(nuclides(i_nuclide), E, d) + yield = nuclides(i_nuclide) % nu(E, EMISSION_DELAYED, d) ! Compute the score and tally to bin - score = micro_xs(i_nuclide) % fission * yield & - * nu_delayed(nuclides(i_nuclide), E) * atom_density * flux + score = micro_xs(i_nuclide) % fission * yield * & + atom_density * flux call score_fission_delayed_dg(t, d_bin, score, score_index) end do cycle SCORE_LOOP @@ -576,8 +560,8 @@ contains ! If the delayed group filter is not present, compute the score ! by multiplying the delayed-nu-fission macro xs by the flux - score = micro_xs(i_nuclide) % fission * & - nu_delayed(nuclides(i_nuclide), E) * atom_density * flux + score = micro_xs(i_nuclide) % fission * nuclides(i_nuclide) % & + nu(E, EMISSION_DELAYED) * atom_density * flux end if ! Tally is on total nuclides @@ -602,11 +586,10 @@ contains d = t % filters(dg_filter) % int_bins(d_bin) ! Get the yield for the desired nuclide and delayed group - yield = yield_delayed(nuclides(i_nuc), E, d) + yield = nuclides(i_nuc) % nu(E, EMISSION_DELAYED, d) ! Compute the score and tally to bin - score = micro_xs(i_nuc) % fission * yield & - * nu_delayed(nuclides(i_nuc), E) * atom_density_ * flux + score = micro_xs(i_nuc) % fission * yield * atom_density_ * flux call score_fission_delayed_dg(t, d_bin, score, score_index) end do end do @@ -625,8 +608,8 @@ contains i_nuc = materials(p % material) % nuclide(l) ! Accumulate the contribution from each nuclide - score = score + micro_xs(i_nuc) % fission & - * nu_delayed(nuclides(i_nuc), E) * atom_density_ * flux + score = score + micro_xs(i_nuc) % fission * nuclides(i_nuc) % & + nu(E, EMISSION_DELAYED) * atom_density_ * flux end do end if end if @@ -802,16 +785,48 @@ contains integer :: score_bin ! scoring bin, e.g. SCORE_FLUX integer :: score_index ! scoring bin index real(8) :: score ! analog tally score - real(8) :: macro_total ! material macro total xs - real(8) :: macro_scatt ! material macro scatt xs - real(8) :: micro_abs ! nuclidic microscopic abs real(8) :: p_uvw(3) ! Particle's current uvw + integer :: p_g ! Particle group to use for getting info + ! to tally with. + class(Mgxs), pointer :: matxs + class(Mgxs), pointer :: nucxs - ! Set the direction, if needed for nuclidic data, so that nuc % get_xs - ! knows wihch direction it should be using for direction-dependent - ! mgxs - if (i_nuclide > 0) then + ! Set the direction and group to use with get_xs + ! this only depends on if we + if (t % estimator == ESTIMATOR_ANALOG .or. & + t % estimator == ESTIMATOR_COLLISION) then + if (survival_biasing) then + ! Then we either are alive and had a scatter (and so g changed), + ! or are dead and g did not change + if (p % alive) then + p_uvw = p % last_uvw + p_g = p % last_g + else + p_uvw = p % coord(p % n_coord) % uvw + p_g = p % g + end if + else if (p % event == EVENT_SCATTER) then + ! Then the energy group has been changed by the scattering routine + ! meaning gin is now in p % last_g + p_uvw = p % last_uvw + p_g = p % last_g + else + ! No scatter, no change in g. + p_uvw = p % coord(p % n_coord) % uvw + p_g = p % g + end if + else + ! No actual collision so g has not changed. p_uvw = p % coord(p % n_coord) % uvw + p_g = p % g + end if + + ! To significantly reduce de-referencing, point matxs to the + ! macroscopic Mgxs for the material of interest + matxs => macro_xs(p % material) % obj + ! Do same for nucxs, point it to the microscopic nuclide data of interest + if (i_nuclide > 0) then + nucxs => nuclides_MG(i_nuclide) % obj end if i = 0 @@ -862,13 +877,16 @@ contains else score = p % last_wgt end if + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('total', p_g, UVW=p_uvw) / & + matxs % get_xs('total', p_g, UVW=p_uvw) + end if else if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'total', UVW=p_uvw) * & - atom_density * flux - end associate + score = nucxs % get_xs('total', p_g, UVW=p_uvw) * & + atom_density * flux else score = material_xs % total * flux end if @@ -876,7 +894,8 @@ contains case (SCORE_INVERSE_VELOCITY) - if (t % estimator == ESTIMATOR_ANALOG) then + if (t % estimator == ESTIMATOR_ANALOG .or. & + t % estimator == ESTIMATOR_COLLISION) then ! All events score to an inverse velocity bin. We actually use a ! collision estimator in place of an analog one since there is no way ! to count 'events' exactly for the inverse velocity @@ -887,177 +906,97 @@ contains else score = p % last_wgt end if - score = score * inverse_velocities(p % last_g) + score = score * inverse_velocities(p_g) / material_xs % total else ! For inverse velocity, we need no cross section - score = score * inverse_velocities(p % g) + score = flux * inverse_velocities(p_g) end if - case (SCORE_SCATTER, SCORE_SCATTER_N) + case (SCORE_SCATTER, SCORE_SCATTER_N, SCORE_SCATTER_PN, SCORE_SCATTER_YN) if (t % estimator == ESTIMATOR_ANALOG) then ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP + if (p % event /= EVENT_SCATTER) then + if (score_bin == SCORE_SCATTER_PN) then + i = i + t % moment_order(i) + else if (score_bin == SCORE_SCATTER_YN) then + i = i + (t % moment_order(i) + 1)**2 - 1 + end if + cycle SCORE_LOOP + end if + ! Since only scattering events make it here, again we can use ! the weight entering the collision as the estimator for the ! reaction rate score = p % last_wgt - else - ! Note SCORE_SCATTER_N not available for tracklength/collision. + ! Since we transport based on material data, the angle selected + ! was not selected from the f(mu) for the nuclide. Therefore + ! adjust the score by the actual probability for that nuclide. if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'scatter', UVW=p_uvw) * & - atom_density * flux - end associate + score = score * atom_density * & + nucxs % get_xs('scatter*f_mu/mult', p % last_g, p % g, & + UVW=p_uvw, MU=p % mu) / & + matxs % get_xs('scatter*f_mu/mult', p % last_g, p % g, & + UVW=p_uvw, MU=p % mu) + end if + + else + ! Note SCORE_SCATTER_*N not available for tracklength/collision. + if (i_nuclide > 0) then + score = atom_density * flux * & + nucxs % get_xs('scatter/mult', p_g, UVW=p_uvw) else - ! Get the scattering x/s (stored in % elastic) - score = material_xs % elastic * flux + ! Get the scattering x/s and take away + ! the multiplication baked in to sigS + score = flux * & + matxs % get_xs('scatter/mult', p_g, UVW=p_uvw) end if end if - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu/mult', p % last_g, & - p % last_uvw, p % mu) - end associate + + case (SCORE_NU_SCATTER, SCORE_NU_SCATTER_N, SCORE_NU_SCATTER_PN, & + SCORE_NU_SCATTER_YN) + if (t % estimator == ESTIMATOR_ANALOG) then + ! Skip any event where the particle didn't scatter + if (p % event /= EVENT_SCATTER) then + if (score_bin == SCORE_NU_SCATTER_PN) then + i = i + t % moment_order(i) + else if (score_bin == SCORE_NU_SCATTER_YN) then + i = i + (t % moment_order(i) + 1)**2 - 1 + end if + cycle SCORE_LOOP + end if + + ! For scattering production, we need to use the pre-collision + ! weight times the multiplicity as the estimate for the number of + ! neutrons exiting a reaction with neutrons in the exit channel + score = p % wgt + + ! Since we transport based on material data, the angle selected + ! was not selected from the f(mu) for the nuclide. Therefore + ! adjust the score by the actual probability for that nuclide. + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('scatter*f_mu', p % last_g, p % g, & + UVW=p_uvw, MU=p % mu) / & + matxs % get_xs('scatter*f_mu', p % last_g, p % g, & + UVW=p_uvw, MU=p % mu) + end if + else - score = score / & - macro_xs(p % material) % obj % get_xs(p % g, 'mult', & - p % last_g, & - p % last_uvw) + ! Note SCORE_NU_SCATTER_*N not available for tracklength/collision. + if (i_nuclide > 0) then + score = nucxs % get_xs('scatter', p_g, UVW=p_uvw) * & + atom_density * flux + else + ! Get the scattering x/s, which includes multiplication + score = matxs % get_xs('scatter', p_g, UVW=p_uvw) * flux + end if end if - case (SCORE_SCATTER_PN) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) then - i = i + t % moment_order(i) - cycle SCORE_LOOP - end if - ! Since only scattering events make it here, again we can use - ! the weight entering the collision as the estimator for the - ! reaction rate - score = p % last_wgt - - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu/mult', p % last_g, & - p % last_uvw, p % mu) - end associate - else - score = score / & - macro_xs(p % material) % obj % get_xs(p % g, 'mult', & - p % last_g, & - p % last_uvw) - end if - - - case (SCORE_SCATTER_YN) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) then - i = i + (t % moment_order(i) + 1)**2 - 1 - cycle SCORE_LOOP - end if - ! Since only scattering events make it here, again we can use - ! the weight entering the collision as the estimator for the - ! reaction rate - score = p % last_wgt - - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu/mult', p % last_g, & - p % last_uvw, p % mu) - end associate - else - score = score / & - macro_xs(p % material) % obj % get_xs(p % g, 'mult', & - p % last_g, & - p % last_uvw) - end if - - - case (SCORE_NU_SCATTER, SCORE_NU_SCATTER_N) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of - ! neutrons exiting a reaction with neutrons in the exit channel - score = p % wgt - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu', p % last_g, & - p % last_uvw, p % mu) - end associate - end if - - - case (SCORE_NU_SCATTER_PN) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) then - i = i + t % moment_order(i) - cycle SCORE_LOOP - end if - ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of - ! neutrons exiting a reaction with neutrons in the exit channel - score = p % wgt - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu', p % last_g, & - p % last_uvw, p % mu) - end associate - end if - - - case (SCORE_NU_SCATTER_YN) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) then - i = i + (t % moment_order(i) + 1)**2 - 1 - cycle SCORE_LOOP - end if - ! For scattering production, we need to use the pre-collision - ! weight times the multiplicity as the estimate for the number of - ! neutrons exiting a reaction with neutrons in the exit channel - score = p % wgt - if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = score * nuc % get_xs(p % g, 'f_mu', p % last_g, & - p % last_uvw, p % mu) - end associate - end if - - - case (SCORE_TRANSPORT) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! get material macros - macro_total = material_xs % total - macro_scatt = material_xs % elastic - ! Score total rate - p1 scatter rate Note estimator needs to be - ! adjusted since tallying is only occuring when a scatter has - ! happened. Effectively this means multiplying the estimator by - ! total/scatter macro - score = (macro_total - p % mu * macro_scatt) * (ONE / macro_scatt) - - - case (SCORE_N_1N) - ! Only analog estimators are available. - ! Skip any event where the particle didn't scatter - if (p % event /= EVENT_SCATTER) cycle SCORE_LOOP - ! Skip any events where weight of particle changed - if (p % wgt /= p % last_wgt) cycle SCORE_LOOP - ! All events that reach this point are (n,1n) reactions - score = p % last_wgt - - case (SCORE_ABSORPTION) if (t % estimator == ESTIMATOR_ANALOG) then if (survival_biasing) then @@ -1071,13 +1010,15 @@ contains ! can just use the particle's weight entering the collision score = p % last_wgt end if - + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('absorption', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + end if else if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'absorption', UVW=p_uvw) & - * atom_density * flux - end associate + score = nucxs % get_xs('absorption', p_g, UVW=p_uvw) * & + atom_density * flux else score = material_xs % absorption * flux end if @@ -1090,38 +1031,30 @@ contains ! No fission events occur if survival biasing is on -- need to ! calculate fraction of absorptions that would have resulted in ! fission - associate (nuc => nuclides_MG(i_nuclide) % obj) - micro_abs = nuc % get_xs(p % g, 'absorption', UVW=p_uvw) - if (micro_abs > ZERO) then - score = p % absorb_wgt * & - nuc % get_xs(p % g, 'fission', UVW=p_uvw) & - / micro_abs - else - score = ZERO - end if - end associate + score = p % absorb_wgt else ! Skip any non-absorption events if (p % event == EVENT_SCATTER) cycle SCORE_LOOP ! All fission events will contribute, so again we can use ! particle's weight entering the collision as the estimate for the ! fission reaction rate - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = p % last_wgt & - * nuc % get_xs(p % g, 'fission', UVW=p_uvw) & - / nuc % get_xs(p % g, 'absorption', UVW=p_uvw) - end associate + score = p % last_wgt end if - + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + else + score = score * & + matxs % get_xs('fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + end if else if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'fission', UVW=p_uvw) * & - atom_density * flux - end associate + score = nucxs % get_xs('fission', p_g, UVW=p_uvw) * & + atom_density * flux else - score = flux * macro_xs(p % material) % obj % get_xs(p % g, & - 'fission', UVW=p_uvw) + score = flux * material_xs % fission end if end if @@ -1136,7 +1069,8 @@ contains ! neutrons were emitted with different energies, multiple ! outgoing energy bins may have been scored to. The following ! logic treats this special case and results to multiple bins - call score_fission_eout_mg(p, t, score_index) + call score_fission_eout_mg(p, t, score_index, i_nuclide, & + atom_density) cycle SCORE_LOOP end if end if @@ -1144,16 +1078,16 @@ contains ! No fission events occur if survival biasing is on -- need to ! calculate fraction of absorptions that would have resulted in ! nu-fission - associate (nuc => nuclides_MG(i_nuclide) % obj) - micro_abs = nuc % get_xs(p % g, 'absorption', UVW=p_uvw) - if (micro_abs > ZERO) then - score = p % absorb_wgt * & - nuc % get_xs(p % g, 'fission', UVW=p_uvw) / & - micro_abs - else - score = ZERO - end if - end associate + score = p % absorb_wgt + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('nu_fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + else + score = score * & + matxs % get_xs('nu_fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + end if else ! Skip any non-fission events if (.not. p % fission) cycle SCORE_LOOP @@ -1163,14 +1097,17 @@ contains ! bank. Since this was weighted by 1/keff, we multiply by keff ! to get the proper score. score = keff * p % wgt_bank + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('fission', p_g, UVW=p_uvw) / & + matxs % get_xs('fission', p_g, UVW=p_uvw) + end if end if else if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'nu_fission', UVW=p_uvw) & - * atom_density * flux - end associate + score = nucxs % get_xs('nu_fission', p_g, UVW=p_uvw) * & + atom_density * flux else score = material_xs % nu_fission * flux end if @@ -1178,43 +1115,36 @@ contains case (SCORE_KAPPA_FISSION) - ! Determine kappa-fission cross section - score = ZERO if (t % estimator == ESTIMATOR_ANALOG) then if (survival_biasing) then ! No fission events occur if survival biasing is on -- need to ! calculate fraction of absorptions that would have resulted in - ! fission scale by kappa-fission - associate (nuc => nuclides_MG(i_nuclide) % obj) - micro_abs = nuc % get_xs(p % g, 'absorption', UVW=p_uvw) - if (micro_abs > ZERO) then - score = p % absorb_wgt * & - nuc % get_xs(p % g, 'k_fission', UVW=p_uvw) / & - micro_abs - end if - end associate + ! fission + score = p % absorb_wgt else ! Skip any non-absorption events if (p % event == EVENT_SCATTER) cycle SCORE_LOOP ! All fission events will contribute, so again we can use - ! particle's weight entering the collision as the estimate for - ! the fission energy production rate - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = p % last_wgt * & - nuc % get_xs(p % g, 'k_fission', UVW=p_uvw) / & - nuc % get_xs(p % g, 'absorption', UVW=p_uvw) - end associate + ! particle's weight entering the collision as the estimate for the + ! fission reaction rate + score = p % last_wgt + end if + if (i_nuclide > 0) then + score = score * atom_density * & + nucxs % get_xs('kappa_fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) + else + score = score * & + matxs % get_xs('kappa_fission', p_g, UVW=p_uvw) / & + matxs % get_xs('absorption', p_g, UVW=p_uvw) end if - else if (i_nuclide > 0) then - associate (nuc => nuclides_MG(i_nuclide) % obj) - score = nuc % get_xs(p % g, 'k_fission', UVW=p_uvw) & - * atom_density * flux - end associate + score = flux * atom_density * & + nucxs % get_xs('kappa_fission', p_g, UVW=p_uvw) else - score = flux * macro_xs(p % material) % obj % get_xs(p % g, & - 'k_fission', UVW=p_uvw) + score = flux * matxs % get_xs('kappa_fission', p_g, UVW=p_uvw) + end if end if @@ -1231,6 +1161,8 @@ contains score, i) end do SCORE_LOOP + + nullify(matxs,nucxs) end subroutine score_general_mg !=============================================================================== @@ -1405,7 +1337,7 @@ contains ! triggered at every collision, not every event !=============================================================================== - subroutine score_analog_tally(p) + subroutine score_analog_tally_ce(p) type(Particle), intent(in) :: p @@ -1415,17 +1347,9 @@ contains ! position during the loop integer :: filter_index ! single index for single bin integer :: i_nuclide ! index in nuclides array - real(8) :: last_wgt ! pre-collision particle weight - real(8) :: wgt ! post-collision particle weight - real(8) :: mu ! cosine of angle of collision logical :: found_bin ! scoring bin found? type(TallyObject), pointer :: t - ! Copy particle's pre- and post-collision weight and angle - last_wgt = p % last_wgt - wgt = p % wgt - mu = p % mu - ! A loop over all tallies is necessary because we need to simultaneously ! determine different filter bins for the same tally in order to score to it @@ -1504,7 +1428,87 @@ contains ! Reset tally map positioning position = 0 - end subroutine score_analog_tally + end subroutine score_analog_tally_ce + + subroutine score_analog_tally_mg(p) + + type(Particle), intent(in) :: p + + integer :: i, m + integer :: i_tally + integer :: k ! loop index for nuclide bins + ! position during the loop + integer :: filter_index ! single index for single bin + integer :: i_nuclide ! index in nuclides array + logical :: found_bin ! scoring bin found? + type(TallyObject), pointer :: t + type(Material), pointer :: mat + real(8) :: atom_density + + ! A loop over all tallies is necessary because we need to simultaneously + ! determine different filter bins for the same tally in order to score to it + + TALLY_LOOP: do i = 1, active_analog_tallies % size() + ! Get index of tally and pointer to tally + i_tally = active_analog_tallies % get_item(i) + t => tallies(i_tally) + + ! Get pointer to current material. We need this in order to determine what + ! nuclides are in the material + mat => materials(p % material) + + ! ======================================================================= + ! DETERMINE SCORING BIN COMBINATION + + call get_scoring_bins(p, i_tally, found_bin) + if (.not. found_bin) cycle + + ! ======================================================================= + ! CALCULATE RESULTS AND ACCUMULATE TALLY + + ! If we have made it here, we have a scoring combination of bins for this + ! tally -- now we need to determine where in the results array we should + ! be accumulating the tally values + + ! Determine scoring index for this filter combination + filter_index = sum((matching_bins(1:t%n_filters) - 1) * t % stride) + 1 + + ! Check for nuclide bins + k = 0 + NUCLIDE_LOOP: do while (k < t % n_nuclide_bins) + + ! Increment the index in the list of nuclide bins + k = k + 1 + + i_nuclide = t % nuclide_bins(k) + + ! Check to see if this nuclide was in the material of our collision. + do m = 1, mat % n_nuclides + if (mat % nuclide(m) == i_nuclide) then + atom_density = mat % atom_density(m) + exit + end if + end do + + ! Determine score for each bin + call score_general(p, t, (k-1)*t % n_score_bins, filter_index, & + i_nuclide, atom_density, ZERO) + + end do NUCLIDE_LOOP + + ! If the user has specified that we can assume all tallies are spatially + ! separate, this implies that once a tally has been scored to, we needn't + ! check the others. This cuts down on overhead when there are many + ! tallies specified + + if (assume_separate) exit TALLY_LOOP + + end do TALLY_LOOP + + ! Reset tally map positioning + position = 0 + + end subroutine score_analog_tally_mg !=============================================================================== ! SCORE_FISSION_EOUT handles a special case where we need to store neutron @@ -1567,10 +1571,12 @@ contains end subroutine score_fission_eout_ce - subroutine score_fission_eout_mg(p, t, i_score) + subroutine score_fission_eout_mg(p, t, i_score, i_nuclide, atom_density) type(Particle), intent(in) :: p type(TallyObject), intent(inout) :: t - integer, intent(in) :: i_score ! index for score + integer, intent(in) :: i_score ! index for score + integer, intent(in) :: i_nuclide ! index for nuclide + real(8), intent(in) :: atom_density integer :: i ! index of outgoing energy filter integer :: n ! number of energies on filter @@ -1579,6 +1585,7 @@ contains integer :: i_filter ! index for matching filter bin combination real(8) :: score ! actual score integer :: gout ! energy group of fission bank site + integer :: gin ! energy group of incident particle real(8) :: E_out ! save original outgoing energy bin and score index @@ -1597,6 +1604,18 @@ contains do k = 1, p % n_bank ! determine score based on bank site weight and keff score = keff * fission_bank(n_bank - p % n_bank + k) % wgt + if (i_nuclide > 0) then + if (survival_biasing) then + gin = p % g + else + gin = p % last_g + end if + score = score * atom_density * & + nuclides_MG(i_nuclide) % obj % get_xs('fission', gin, & + UVW=p % last_uvw) / & + macro_xs(p % material) % obj % get_xs('fission', gin, & + UVW=p % last_uvw) + end if if (t % energyout_matches_groups) then ! determine outgoing energy from fission bank @@ -1606,7 +1625,7 @@ contains matching_bins(i) = gout else ! determine outgoing energy from fission bank - E_out = fission_bank(n_bank - p % n_bank + k) % E + E_out = energy_bin_avg(int(fission_bank(n_bank - p % n_bank + k) % E)) ! check if outgoing energy is within specified range on filter if (E_out < t % filters(i) % real_bins(1) .or. & @@ -2602,7 +2621,6 @@ contains end if end if - case (FILTER_ENERGYOUT) if (t % energyout_matches_groups) then ! Since all groups are filters, the filter bin is the group @@ -2626,7 +2644,6 @@ contains end if end if - case (FILTER_MU) ! determine mu bin n = t % filters(i) % n_bins diff --git a/src/tracking.F90 b/src/tracking.F90 index e634112bc..d52b09a75 100644 --- a/src/tracking.F90 +++ b/src/tracking.F90 @@ -7,7 +7,6 @@ module tracking cross_lattice, check_cell_overlap use geometry_header, only: Universe, BASE_UNIVERSE use global - use macroxs_header, only: MacroXS use output, only: write_message use particle_header, only: LocalCoord, Particle use physics, only: collision @@ -98,6 +97,7 @@ contains material_xs % total = ZERO material_xs % elastic = ZERO material_xs % absorption = ZERO + material_xs % fission = ZERO material_xs % nu_fission = ZERO end if end if diff --git a/src/urr_header.F90 b/src/urr_header.F90 new file mode 100644 index 000000000..96e182d2e --- /dev/null +++ b/src/urr_header.F90 @@ -0,0 +1,20 @@ +module urr_header + + implicit none + +!=============================================================================== +! URRDATA contains probability tables for the unresolved resonance range. +!=============================================================================== + + type UrrData + integer :: n_energy ! # of incident neutron energies + integer :: n_prob ! # of probabilities + integer :: interp ! inteprolation (2=lin-lin, 5=log-log) + integer :: inelastic_flag ! inelastic competition flag + integer :: absorption_flag ! other absorption flag + logical :: multiply_smooth ! multiply by smooth cross section? + real(8), allocatable :: energy(:) ! incident energies + real(8), allocatable :: prob(:,:,:) ! actual probabibility tables + end type UrrData + +end module urr_header diff --git a/tests/input_set.py b/tests/input_set.py index daff38ba1..13c0e99a7 100644 --- a/tests/input_set.py +++ b/tests/input_set.py @@ -5,9 +5,9 @@ from openmc.stats import Box class InputSet(object): def __init__(self): - self.settings = openmc.SettingsFile() - self.materials = openmc.MaterialsFile() - self.geometry = openmc.GeometryFile() + self.settings = openmc.Settings() + self.materials = openmc.Materials() + self.geometry = openmc.Geometry() self.tallies = None self.plots = None @@ -15,8 +15,10 @@ class InputSet(object): self.settings.export_to_xml() self.materials.export_to_xml() self.geometry.export_to_xml() - if self.tallies is not None: self.tallies.export_to_xml() - if self.plots is not None: self.plots.export_to_xml() + if self.tallies is not None: + self.tallies.export_to_xml() + if self.plots is not None: + self.plots.export_to_xml() def build_default_materials_and_geometry(self): # Define materials. @@ -82,7 +84,7 @@ class InputSet(object): hot_water.add_s_alpha_beta('HH2O', '71t') rpv_steel = openmc.Material(name='Reactor pressure vessel steel', - material_id=5) + material_id=5) rpv_steel.set_density('g/cm3', 7.9) rpv_steel.add_nuclide("Fe-54", 0.05437098, 'wo') rpv_steel.add_nuclide("Fe-56", 0.88500663, 'wo') @@ -113,7 +115,7 @@ class InputSet(object): rpv_steel.add_nuclide("Cu-65", 0.0006304, 'wo') lower_rad_ref = openmc.Material(name='Lower radial reflector', - material_id=6) + material_id=6) lower_rad_ref.set_density('g/cm3', 4.32) lower_rad_ref.add_nuclide("H-1", 0.0095661, 'wo') lower_rad_ref.add_nuclide("O-16", 0.0759107, 'wo') @@ -189,7 +191,8 @@ class InputSet(object): bot_plate.add_nuclide("Cr-54", 0.004612692337, 'wo') bot_plate.add_s_alpha_beta('HH2O', '71t') - bot_nozzle = openmc.Material(name='Bottom nozzle region', material_id=9) + bot_nozzle = openmc.Material(name='Bottom nozzle region', + material_id=9) bot_nozzle.set_density('g/cm3', 2.53) bot_nozzle.add_nuclide("H-1", 0.0245014, 'wo') bot_nozzle.add_nuclide("O-16", 0.1944274, 'wo') @@ -252,7 +255,8 @@ class InputSet(object): top_fa.add_nuclide("Zr-96", 0.02511169542, 'wo') top_fa.add_s_alpha_beta('HH2O', '71t') - bot_fa = openmc.Material(name='Bottom of fuel assemblies', material_id=12) + bot_fa = openmc.Material(name='Bottom of fuel assemblies', + material_id=12) bot_fa.set_density('g/cm3', 1.762) bot_fa.add_nuclide("H-1", 0.0292856, 'wo') bot_fa.add_nuclide("O-16", 0.2323919, 'wo') @@ -267,9 +271,9 @@ class InputSet(object): # Define the materials file. self.materials.default_xs = '71c' - self.materials.add_materials((fuel, clad, cold_water, hot_water, - rpv_steel, lower_rad_ref, upper_rad_ref, bot_plate, bot_nozzle, - top_nozzle, top_fa, bot_fa)) + self.materials += (fuel, clad, cold_water, hot_water, rpv_steel, + lower_rad_ref, upper_rad_ref, bot_plate, + bot_nozzle, top_nozzle, top_fa, bot_fa) # Define surfaces. s1 = openmc.ZCylinder(R=0.41, surface_id=1) @@ -350,7 +354,6 @@ class InputSet(object): # Define fuel lattices. l100 = openmc.RectLattice(name='Fuel assembly (lower half)', lattice_id=100) - l100.dimension = (17, 17) l100.lower_left = (-10.71, -10.71) l100.pitch = (1.26, 1.26) l100.universes = [ @@ -384,7 +387,6 @@ class InputSet(object): l101 = openmc.RectLattice(name='Fuel assembly (upper half)', lattice_id=101) - l101.dimension = (17, 17) l101.lower_left = (-10.71, -10.71) l101.pitch = (1.26, 1.26) l101.universes = [ @@ -444,7 +446,6 @@ class InputSet(object): # Define core lattices l200 = openmc.RectLattice(name='Core lattice (lower half)', lattice_id=200) - l200.dimension = (21, 21) l200.lower_left = (-224.91, -224.91) l200.pitch = (21.42, 21.42) l200.universes = [ @@ -472,7 +473,6 @@ class InputSet(object): l201 = openmc.RectLattice(name='Core lattice (lower half)', lattice_id=201) - l201.dimension = (21, 21) l201.lower_left = (-224.91, -224.91) l201.pitch = (21.42, 21.42) l201.universes = [ @@ -550,11 +550,8 @@ class InputSet(object): root.add_cells((c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11, c12)) - # Define the geometry file. - geometry = openmc.Geometry() - geometry.root_universe = root - - self.geometry.geometry = geometry + # Assign root universe to geometry + self.geometry.root_universe = root def build_default_settings(self): self.settings.batches = 10 @@ -573,6 +570,109 @@ class InputSet(object): self.plots.add_plot(plot) + +class PinCellInputSet(object): + def __init__(self): + self.settings = openmc.Settings() + self.materials = openmc.Materials() + self.geometry = openmc.Geometry() + self.tallies = None + self.plots = None + + def export(self): + self.settings.export_to_xml() + self.materials.export_to_xml() + self.geometry.export_to_xml() + if self.tallies is not None: + self.tallies.export_to_xml() + if self.plots is not None: + self.plots.export_to_xml() + + def build_default_materials_and_geometry(self): + # Define materials. + fuel = openmc.Material(name='Fuel') + fuel.set_density('g/cm3', 10.29769) + fuel.add_nuclide("U-234", 4.4843e-6) + fuel.add_nuclide("U-235", 5.5815e-4) + fuel.add_nuclide("U-238", 2.2408e-2) + fuel.add_nuclide("O-16", 4.5829e-2) + + clad = openmc.Material(name='Cladding') + clad.set_density('g/cm3', 6.55) + clad.add_nuclide("Zr-90", 2.1827e-2) + clad.add_nuclide("Zr-91", 4.7600e-3) + clad.add_nuclide("Zr-92", 7.2758e-3) + clad.add_nuclide("Zr-94", 7.3734e-3) + clad.add_nuclide("Zr-96", 1.1879e-3) + + hot_water = openmc.Material(name='Hot borated water') + hot_water.set_density('g/cm3', 0.740582) + hot_water.add_nuclide("H-1", 4.9457e-2) + hot_water.add_nuclide("O-16", 2.4672e-2) + hot_water.add_nuclide("B-10", 8.0042e-6) + hot_water.add_nuclide("B-11", 3.2218e-5) + hot_water.add_s_alpha_beta('HH2O', '71t') + + # Define the materials file. + self.materials.default_xs = '71c' + self.materials += (fuel, clad, hot_water) + + # Instantiate ZCylinder surfaces + fuel_or = openmc.ZCylinder(x0=0, y0=0, R=0.39218, name='Fuel OR') + clad_or = openmc.ZCylinder(x0=0, y0=0, R=0.45720, name='Clad OR') + left = openmc.XPlane(x0=-0.63, name='left') + right = openmc.XPlane(x0=0.63, name='right') + bottom = openmc.YPlane(y0=-0.63, name='bottom') + top = openmc.YPlane(y0=0.63, name='top') + + left.boundary_type = 'reflective' + right.boundary_type = 'reflective' + top.boundary_type = 'reflective' + bottom.boundary_type = 'reflective' + + # Instantiate Cells + fuel_pin = openmc.Cell(name='cell 1') + cladding = openmc.Cell(name='cell 3') + water = openmc.Cell(name='cell 2') + + # Use surface half-spaces to define regions + fuel_pin.region = -fuel_or + cladding.region = +fuel_or & -clad_or + water.region = +clad_or & +left & -right & +bottom & -top + + # Register Materials with Cells + fuel_pin.fill = fuel + cladding.fill = clad + water.fill = hot_water + + # Instantiate Universe + root = openmc.Universe(universe_id=0, name='root universe') + + # Register Cells with Universe + root.add_cells([fuel_pin, cladding, water]) + + # Instantiate a Geometry, register the root Universe, and export to XML + self.geometry.root_universe = root + + def build_default_settings(self): + self.settings.batches = 10 + self.settings.inactive = 5 + self.settings.particles = 100 + self.settings.source = Source(space=Box([-0.63, -0.63, -1], + [0.63, 0.63, 1], + only_fissionable=True)) + + def build_defualt_plots(self): + plot = openmc.Plot() + plot.filename = 'mat' + plot.origin = (0.0, 0.0, 0) + plot.width = (1.26, 1.26) + plot.pixels = (300, 300) + plot.color = 'mat' + + self.plots.add_plot(plot) + + class MGInputSet(InputSet): def build_default_materials_and_geometry(self): # Define materials needed for 1D/1G slab problem @@ -593,26 +693,26 @@ class MGInputSet(InputSet): # Define the materials file. self.materials.default_xs = '71c' - self.materials.add_materials((uo2, clad, water)) + self.materials += (uo2, clad, water) # Define surfaces. # Assembly/Problem Boundary - left = openmc.XPlane(x0=0.0, surface_id=200, - boundary_type='reflective') - right = openmc.XPlane(x0=10.0, surface_id=201, - boundary_type='reflective') + left = openmc.XPlane(x0=0.0, surface_id=200, + boundary_type='reflective') + right = openmc.XPlane(x0=10.0, surface_id=201, + boundary_type='reflective') bottom = openmc.YPlane(y0=0.0, surface_id=300, boundary_type='reflective') - top = openmc.YPlane(y0=10.0, surface_id=301, - boundary_type='reflective') + top = openmc.YPlane(y0=10.0, surface_id=301, + boundary_type='reflective') - down = openmc.ZPlane(z0=0.0, surface_id=0, - boundary_type='reflective') + down = openmc.ZPlane(z0=0.0, surface_id=0, + boundary_type='reflective') fuel_clad_intfc = openmc.ZPlane(z0=2.0, surface_id=1) clad_lwtr_intfc = openmc.ZPlane(z0=2.4, surface_id=2) - up = openmc.ZPlane(z0=5.0, surface_id=3, - boundary_type='reflective') + up = openmc.ZPlane(z0=5.0, surface_id=3, + boundary_type='reflective') # Define cells c1 = openmc.Cell(cell_id=1) @@ -628,14 +728,10 @@ class MGInputSet(InputSet): # Define root universe. root = openmc.Universe(universe_id=0, name='root universe') - root.add_cells((c1,c2,c3)) - - # Define the geometry file. - geometry = openmc.Geometry() - geometry.root_universe = root - - self.geometry.geometry = geometry + root.add_cells((c1, c2, c3)) + # Assign root universe to geometry + self.geometry.root_universe = root def build_default_settings(self): self.settings.batches = 10 @@ -656,8 +752,3 @@ class MGInputSet(InputSet): plot.color = 'mat' self.plots.add_plot(plot) - - - - - diff --git a/tests/run_tests.py b/tests/run_tests.py index 48fc23d4a..5a04f340a 100755 --- a/tests/run_tests.py +++ b/tests/run_tests.py @@ -300,9 +300,12 @@ if options.list_build_configs: # Delete items of dictionary that don't match regular expression if options.build_config is not None: + to_delete = [] for key in tests: if not re.search(options.build_config, key): - del tests[key] + to_delete.append(key) + for key in to_delete: + del tests[key] # Check for dashboard and determine whether to push results to server # Note that there are only 3 basic dashboards: @@ -363,10 +366,14 @@ sourcepoint_batch|statepoint_interval|survival_biasing|\ tally_assumesep|translation|uniform_fs|universe|void" # Delete items of dictionary if valgrind or coverage and not in script mode +to_delete = [] if not script_mode: for key in tests: if re.search('valgrind|coverage', key): - del tests[key] + to_delete.append(key) + +for key in to_delete: + del tests[key] # Check if tests empty if len(list(tests.keys())) == 0: diff --git a/tests/test_asymmetric_lattice/inputs_true.dat b/tests/test_asymmetric_lattice/inputs_true.dat index e3b00b185..f40e661b3 100644 --- a/tests/test_asymmetric_lattice/inputs_true.dat +++ b/tests/test_asymmetric_lattice/inputs_true.dat @@ -1 +1 @@ -b9b4222c4beea80fe6083590f6b785303d174972d80671fb661bac8e030db6f4a61648240cfad6162799361fc0e08a23c61d31aff844d978528d6dad5b5fbc63 \ No newline at end of file +9b859eb5501c05b6a652d299bd0cadc0a924ffae31117babbdc9f7f8ca87689322c275818eb0dde0ff5fa78317d8d8f1585b18dcc772e3ff4ed499de8a491dc3 \ No newline at end of file diff --git a/tests/test_asymmetric_lattice/results_true.dat b/tests/test_asymmetric_lattice/results_true.dat index ec4b88388..a33b9c9e5 100644 --- a/tests/test_asymmetric_lattice/results_true.dat +++ b/tests/test_asymmetric_lattice/results_true.dat @@ -1 +1 @@ -b5f96919ca474cd1c9c9d0acde3b8aac4a1cf636443c72a38b6c5a4221a8ce3e90182aaef2f664e44b9175ca257a89db2328b63e19388ee0e5006de4b3d92ce6 \ No newline at end of file +bc8bef8121f9b6470e4fea817a4e48eabb1ecba1f42761a4cbd77d71181bf9e1612df4a3d6ddfbcd08a3086ac873e5f3c3e560bf96b2b7c959a2f7aad7e4e08d \ No newline at end of file diff --git a/tests/test_asymmetric_lattice/test_asymmetric_lattice.py b/tests/test_asymmetric_lattice/test_asymmetric_lattice.py index fdb21db33..40def1f62 100644 --- a/tests/test_asymmetric_lattice/test_asymmetric_lattice.py +++ b/tests/test_asymmetric_lattice/test_asymmetric_lattice.py @@ -7,8 +7,6 @@ import hashlib sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness import openmc -from openmc.source import Source -from openmc.stats import Box class AsymmetricLatticeTestHarness(PyAPITestHarness): @@ -20,13 +18,12 @@ class AsymmetricLatticeTestHarness(PyAPITestHarness): self._input_set.build_default_materials_and_geometry() # Extract universes encapsulating fuel and water assemblies - geometry = self._input_set.geometry.geometry + geometry = self._input_set.geometry water = geometry.get_universes_by_name('water assembly (hot)')[0] fuel = geometry.get_universes_by_name('fuel assembly (hot)')[0] # Construct a 3x3 lattice of fuel assemblies core_lat = openmc.RectLattice(name='3x3 Core Lattice', lattice_id=202) - core_lat.dimension = (3, 3) core_lat.lower_left = (-32.13, -32.13) core_lat.pitch = (21.42, 21.42) core_lat.universes = [[fuel, water, water], @@ -49,19 +46,18 @@ class AsymmetricLatticeTestHarness(PyAPITestHarness): root_univ.add_cell(root_cell) # Over-ride geometry in the input set with this 3x3 lattice - self._input_set.geometry.geometry.root_universe = root_univ + self._input_set.geometry.root_universe = root_univ # Initialize a "distribcell" filter for the fuel pin cell distrib_filter = openmc.Filter(type='distribcell', bins=[27]) # Initialize the tallies tally = openmc.Tally(name='distribcell tally', tally_id=27) - tally.add_filter(distrib_filter) - tally.add_score('nu-fission') + tally.filters.append(distrib_filter) + tally.scores.append('nu-fission') # Initialize the tallies file - tallies_file = openmc.TalliesFile() - tallies_file.add_tally(tally) + tallies_file = openmc.Tallies([tally]) # Assign the tallies file to the input set self._input_set.tallies = tallies_file @@ -70,7 +66,7 @@ class AsymmetricLatticeTestHarness(PyAPITestHarness): self._input_set.build_default_settings() # Specify summary output and correct source sampling box - source = Source(space=Box([-32, -32, 0], [32, 32, 32])) + source = openmc.Source(space=openmc.stats.Box([-32, -32, 0], [32, 32, 32])) source.space.only_fissionable = True self._input_set.settings.source = source self._input_set.settings.output = {'summary': True} @@ -85,11 +81,6 @@ class AsymmetricLatticeTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Extract the tally of interest tally = sp.get_tally(name='distribcell tally') @@ -99,8 +90,8 @@ class AsymmetricLatticeTestHarness(PyAPITestHarness): outstr += ', '.join(map(str, tally.std_dev.flatten())) + '\n' # Extract fuel assembly lattices from the summary - core = su.get_cell_by_id(1) - fuel = su.get_cell_by_id(80) + core = sp.summary.get_cell_by_id(1) + fuel = sp.summary.get_cell_by_id(80) fuel = fuel.fill core = core.fill diff --git a/tests/test_cmfd_feed/results_true.dat b/tests/test_cmfd_feed/results_true.dat index 9c109db6a..4579fa545 100644 --- a/tests/test_cmfd_feed/results_true.dat +++ b/tests/test_cmfd_feed/results_true.dat @@ -1,128 +1,128 @@ k-combined: -1.168349E+00 1.145333E-02 +1.169891E+00 6.289481E-03 tally 1: -1.167844E+01 -1.366808E+01 -2.141846E+01 -4.598143E+01 -2.928738E+01 -8.615095E+01 -3.513015E+01 -1.241914E+02 -3.715164E+01 -1.384553E+02 -3.639309E+01 -1.327919E+02 -3.370872E+01 -1.138391E+02 -2.875251E+01 -8.292323E+01 -2.117740E+01 -4.512961E+01 -1.130554E+01 -1.289872E+01 +1.173921E+01 +1.385460E+01 +2.164076E+01 +4.699369E+01 +2.906462E+01 +8.464935E+01 +3.382312E+01 +1.147095E+02 +3.632006E+01 +1.323878E+02 +3.655412E+01 +1.341064E+02 +3.347756E+01 +1.124264E+02 +2.931337E+01 +8.607243E+01 +2.182947E+01 +4.789563E+01 +1.147668E+01 +1.325716E+01 tally 2: -2.339531E+01 -2.755922E+01 -1.646762E+01 -1.365289E+01 -2.146174E+00 -2.369613E-01 -4.309769E+01 -9.312913E+01 -3.054873E+01 -4.681242E+01 -4.076365E+00 -8.462370E-01 -5.840647E+01 -1.715260E+02 -4.161366E+01 -8.713062E+01 -5.382541E+00 -1.473814E+00 -6.927641E+01 -2.411359E+02 -4.943841E+01 -1.228850E+02 -6.282202E+00 -1.990021E+00 -7.308593E+01 -2.678848E+02 -5.202069E+01 -1.357621E+02 -6.826145E+00 -2.353974E+00 -7.117026E+01 -2.543546E+02 -5.068896E+01 -1.290261E+02 -6.342979E+00 -2.033850E+00 -6.615720E+01 -2.193712E+02 -4.725156E+01 -1.119514E+02 -6.024815E+00 -1.833752E+00 -5.738164E+01 -1.651944E+02 -4.081217E+01 -8.360122E+01 -5.326191E+00 -1.435896E+00 -4.208669E+01 -8.911740E+01 -2.994944E+01 -4.517409E+01 -3.905846E+00 -7.855247E-01 -2.273578E+01 -2.615080E+01 -1.603853E+01 -1.303560E+01 -2.160924E+00 -2.473278E-01 +2.298190E+01 +2.667071E+01 +1.600292E+01 +1.293670E+01 +2.252427E+00 +2.605738E-01 +4.268506E+01 +9.161215E+01 +3.022909E+01 +4.598915E+01 +3.873926E+00 +7.615035E-01 +5.680399E+01 +1.623878E+02 +4.033805E+01 +8.196263E+01 +5.280610E+00 +1.414008E+00 +6.814741E+01 +2.331778E+02 +4.851618E+01 +1.182330E+02 +6.261805E+00 +1.983205E+00 +7.392922E+01 +2.740255E+02 +5.253586E+01 +1.384152E+02 +6.733810E+00 +2.278242E+00 +7.332860E+01 +2.698608E+02 +5.227405E+01 +1.371810E+02 +6.714658E+00 +2.273652E+00 +6.830172E+01 +2.340687E+02 +4.867159E+01 +1.188724E+02 +6.215002E+00 +1.956978E+00 +5.885634E+01 +1.736180E+02 +4.170434E+01 +8.719622E+01 +5.253064E+00 +1.396224E+00 +4.372001E+01 +9.593570E+01 +3.106511E+01 +4.844647E+01 +3.817991E+00 +7.509063E-01 +2.338260E+01 +2.752103E+01 +1.636606E+01 +1.347591E+01 +2.220013E+00 +2.515671E-01 tally 3: -1.584939E+01 -1.265206E+01 -1.096930E+00 -6.173135E-02 -2.940258E+01 -4.337818E+01 -1.932931E+00 -1.884749E-01 -4.008186E+01 -8.086427E+01 -2.512704E+00 -3.189987E-01 -4.759648E+01 -1.139252E+02 -3.041630E+00 -4.683237E-01 -5.006181E+01 -1.257467E+02 -3.137042E+00 -4.981005E-01 -4.883211E+01 -1.197646E+02 -3.130686E+00 -4.987337E-01 -4.550029E+01 -1.038199E+02 -2.853740E+00 -4.127265E-01 -3.937822E+01 -7.785807E+01 -2.488983E+00 -3.156421E-01 -2.884912E+01 -4.192640E+01 -1.855316E+00 -1.745109E-01 -1.543635E+01 -1.208459E+01 -1.025635E+00 -5.351565E-02 +1.538752E+01 +1.196478E+01 +1.079685E+00 +6.010786E-02 +2.911906E+01 +4.269070E+01 +1.822657E+00 +1.671851E-01 +3.885421E+01 +7.608218E+01 +2.541517E+00 +3.262452E-01 +4.673300E+01 +1.097036E+02 +2.885308E+00 +4.214444E-01 +5.059247E+01 +1.283984E+02 +3.222797E+00 +5.237329E-01 +5.034856E+01 +1.272538E+02 +3.230225E+00 +5.273425E-01 +4.688476E+01 +1.103152E+02 +2.941287E+00 +4.363750E-01 +4.013746E+01 +8.077506E+01 +2.634234E+00 +3.520271E-01 +2.996995E+01 +4.510282E+01 +1.946504E+00 +1.919104E-01 +1.575153E+01 +1.248536E+01 +1.020705E+00 +5.413570E-02 tally 4: 0.000000E+00 0.000000E+00 @@ -160,8 +160,8 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.119914E+00 -4.908283E-01 +3.049469E+00 +4.677325E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -208,10 +208,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.567786E+00 -1.556825E+00 -2.766088E+00 -3.864023E-01 +5.514939E+00 +1.528899E+00 +2.770358E+00 +3.879191E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -256,10 +256,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.491891E+00 -2.819491E+00 -5.235154E+00 -1.377898E+00 +7.294002E+00 +2.675589E+00 +5.032131E+00 +1.275040E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -304,10 +304,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.810357E+00 -3.898704E+00 -7.233068E+00 -2.630659E+00 +8.668860E+00 +3.776102E+00 +7.036008E+00 +2.490719E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -352,10 +352,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.374583E+00 -4.414420E+00 -8.565683E+00 -3.687428E+00 +9.345868E+00 +4.380719E+00 +8.352414E+00 +3.501945E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -400,10 +400,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.001252E+00 -4.073267E+00 -8.974821E+00 -4.050120E+00 +9.223771E+00 +4.270119E+00 +9.093766E+00 +4.158282E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -448,10 +448,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.236452E+00 -3.401934E+00 -9.042286E+00 -4.102906E+00 +8.530966E+00 +3.651778E+00 +9.219150E+00 +4.264346E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -496,10 +496,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.028546E+00 -2.482380E+00 -8.577643E+00 -3.691947E+00 +7.204424E+00 +2.604203E+00 +8.690373E+00 +3.785262E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -544,10 +544,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.159585E+00 -1.342512E+00 -7.389236E+00 -2.745028E+00 +5.326721E+00 +1.426975E+00 +7.513640E+00 +2.833028E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -592,10 +592,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.762685E+00 -3.914181E-01 -5.471849E+00 -1.509910E+00 +2.847310E+00 +4.090440E-01 +5.661144E+00 +1.607138E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -642,8 +642,8 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.038522E+00 -4.643520E-01 +3.025812E+00 +4.597241E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -662,114 +662,114 @@ k cmfd 0.000000E+00 0.000000E+00 0.000000E+00 -1.180802E+00 -1.162698E+00 -1.162794E+00 -1.159752E+00 -1.152596E+00 -1.151652E+00 -1.148131E+00 -1.151875E+00 -1.151434E+00 -1.158833E+00 -1.160751E+00 -1.155305E+00 -1.155356E+00 -1.158866E+00 -1.161574E+00 -1.154691E+00 +1.170416E+00 +1.172966E+00 +1.165537E+00 +1.170979E+00 +1.161922E+00 +1.157523E+00 +1.158873E+00 +1.162877E+00 +1.167102E+00 +1.168130E+00 +1.170570E+00 +1.168115E+00 +1.174081E+00 +1.169458E+00 +1.167848E+00 +1.165116E+00 cmfd entropy 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.214195E+00 -3.225164E+00 -3.227316E+00 -3.225663E+00 -3.226390E+00 -3.225832E+00 -3.226707E+00 -3.227866E+00 -3.229948E+00 -3.229269E+00 -3.230044E+00 -3.231568E+00 -3.234694E+00 -3.234771E+00 -3.234915E+00 -3.235876E+00 +3.203643E+00 +3.207943E+00 +3.213367E+00 +3.214360E+00 +3.219634E+00 +3.222232E+00 +3.221744E+00 +3.224544E+00 +3.225990E+00 +3.227769E+00 +3.227417E+00 +3.230728E+00 +3.231662E+00 +3.233316E+00 +3.233193E+00 +3.232564E+00 cmfd balance 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -4.742525E-03 -2.646417E-03 -1.981783E-03 -1.856593E-03 -1.797685E-03 -2.122587E-03 -1.200823E-03 -2.177249E-03 -1.442840E-03 -1.477754E-03 -1.236325E-03 -1.048988E-03 -8.395164E-04 -7.380254E-04 -7.742837E-04 -8.235911E-04 +4.009063E-03 +4.431773E-03 +3.152698E-03 +3.510424E-03 +2.052087E-03 +2.068633E-03 +1.502416E-03 +1.589822E-03 +1.566016E-03 +1.219159E-03 +1.017888E-03 +9.771569E-04 +1.010126E-03 +1.073397E-03 +1.172784E-03 +9.827488E-04 cmfd dominance ratio 0.000E+00 0.000E+00 0.000E+00 0.000E+00 - 5.467E-01 - 5.518E-01 - 5.535E-01 - 5.500E-01 + 5.397E-01 + 5.425E-01 5.481E-01 - 5.478E-01 - 5.467E-01 - 5.465E-01 - 5.493E-01 - 5.488E-01 - 5.491E-01 + 5.473E-01 5.503E-01 - 5.529E-01 - 5.531E-01 - 5.534E-01 - 5.552E-01 + 5.502E-01 + 5.483E-01 + 5.520E-01 + 5.505E-01 + 3.216E-01 + 5.373E-01 + 5.517E-01 + 5.508E-01 + 5.524E-01 + 5.524E-01 + 5.523E-01 cmfd openmc source comparison 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.168094E-03 -5.978693E-03 -4.369223E-03 -4.546309E-03 -4.222522E-03 -4.221686E-03 -4.604208E-03 -3.950286E-03 -2.939283E-03 -3.667020E-03 -2.592899E-03 -2.272158E-03 -1.229170E-03 -1.114150E-03 -1.060490E-03 -1.714222E-03 +6.959835E-03 +5.655657E-03 +3.886178E-03 +4.035110E-03 +3.043277E-03 +5.455479E-03 +4.515313E-03 +2.439842E-03 +2.114036E-03 +2.673135E-03 +2.431753E-03 +4.330931E-03 +3.404650E-03 +3.680302E-03 +3.309625E-03 +3.705544E-03 cmfd source -4.724285E-02 -8.305825E-02 -1.081058E-01 -1.314542E-01 -1.357299E-01 -1.359417E-01 -1.240918E-01 -1.087580E-01 -8.111239E-02 -4.450518E-02 +4.697085E-02 +7.920706E-02 +1.107968E-01 +1.250932E-01 +1.383930E-01 +1.380648E-01 +1.246874E-01 +1.113705E-01 +8.203754E-02 +4.337882E-02 diff --git a/tests/test_cmfd_nofeed/results_true.dat b/tests/test_cmfd_nofeed/results_true.dat index 308dd7d82..d8a17d676 100644 --- a/tests/test_cmfd_nofeed/results_true.dat +++ b/tests/test_cmfd_nofeed/results_true.dat @@ -1,128 +1,128 @@ k-combined: -1.171115E+00 6.173328E-03 +1.167381E+00 9.433736E-03 tally 1: -1.151618E+01 -1.331859E+01 -2.120660E+01 -4.514836E+01 -2.759616E+01 -7.639131E+01 -3.216668E+01 -1.036501E+02 -3.664720E+01 -1.345450E+02 -3.771246E+01 -1.424209E+02 -3.523750E+01 -1.245225E+02 -2.973298E+01 -8.860064E+01 -2.152108E+01 -4.647187E+01 -1.169538E+01 -1.375047E+01 +1.196136E+01 +1.442468E+01 +2.133857E+01 +4.600706E+01 +2.874353E+01 +8.287538E+01 +3.400779E+01 +1.158949E+02 +3.736443E+01 +1.398466E+02 +3.705095E+01 +1.376767E+02 +3.486173E+01 +1.220362E+02 +2.910935E+01 +8.507181E+01 +2.034762E+01 +4.156717E+01 +1.074970E+01 +1.160733E+01 tally 2: -2.274639E+01 -2.606952E+01 -1.588200E+01 -1.270445E+01 -2.140989E+00 -2.357207E-01 -4.205792E+01 -8.880940E+01 -2.970000E+01 -4.427086E+01 -3.919645E+00 -7.773724E-01 -5.560960E+01 -1.559764E+02 -3.947900E+01 -7.872700E+01 -5.238942E+00 -1.400918E+00 -6.492259E+01 -2.117369E+02 -4.612200E+01 -1.069035E+02 -5.989449E+00 -1.813201E+00 -7.217377E+01 -2.608499E+02 -5.148500E+01 -1.327923E+02 -6.607336E+00 -2.205529E+00 -7.305896E+01 -2.681514E+02 -5.187500E+01 -1.352457E+02 -6.722921E+00 -2.290262E+00 -6.884269E+01 -2.380550E+02 -4.904800E+01 -1.208314E+02 -6.177320E+00 -1.927173E+00 -5.902100E+01 -1.748370E+02 -4.201000E+01 -8.858460E+01 -5.542381E+00 -1.549108E+00 -4.268091E+01 -9.151405E+01 -3.029500E+01 -4.614050E+01 -3.822093E+00 -7.420139E-01 -2.362279E+01 -2.812041E+01 -1.653100E+01 -1.377737E+01 -2.336090E+00 -2.851840E-01 +2.321994E+01 +2.726751E+01 +1.624000E+01 +1.334217E+01 +2.239367E+00 +2.607315E-01 +4.184801E+01 +8.813953E+01 +2.955600E+01 +4.401685E+01 +3.937924E+00 +7.877545E-01 +5.620223E+01 +1.589242E+02 +3.981400E+01 +7.983679E+01 +5.183337E+00 +1.367303E+00 +6.834724E+01 +2.342244E+02 +4.869600E+01 +1.189597E+02 +6.288549E+00 +1.997858E+00 +7.481522E+01 +2.802998E+02 +5.346500E+01 +1.431835E+02 +6.691123E+00 +2.252645E+00 +7.381412E+01 +2.733775E+02 +5.269700E+01 +1.393729E+02 +6.846095E+00 +2.360683E+00 +6.907775E+01 +2.396751E+02 +4.918500E+01 +1.215909E+02 +6.400076E+00 +2.073871E+00 +5.783260E+01 +1.680814E+02 +4.107800E+01 +8.480751E+01 +5.269220E+00 +1.404986E+00 +4.120212E+01 +8.516646E+01 +2.930300E+01 +4.310295E+01 +3.730803E+00 +7.015777E-01 +2.228419E+01 +2.504033E+01 +1.554100E+01 +1.217931E+01 +2.126451E+00 +2.315275E-01 tally 3: -1.524100E+01 -1.171023E+01 -1.071050E+00 -5.839198E-02 -2.862800E+01 -4.113148E+01 -1.892774E+00 -1.812712E-01 -3.804600E+01 -7.316097E+01 -2.423654E+00 -2.968521E-01 -4.434600E+01 -9.882906E+01 -2.823929E+00 -4.033633E-01 -4.955300E+01 -1.230293E+02 -3.226029E+00 -5.265680E-01 -4.999400E+01 -1.256474E+02 -3.232464E+00 -5.286388E-01 -4.724300E+01 -1.121029E+02 -3.015553E+00 -4.606928E-01 -4.051300E+01 -8.239672E+01 -2.592073E+00 -3.412174E-01 -2.912700E+01 -4.265700E+01 -1.875109E+00 -1.785438E-01 -1.593500E+01 -1.280638E+01 -1.038638E+00 -5.538157E-02 +1.561100E+01 +1.233967E+01 +1.095984E+00 +6.181387E-02 +2.847800E+01 +4.088161E+01 +1.815210E+00 +1.669969E-01 +3.834200E+01 +7.408022E+01 +2.446117E+00 +3.017834E-01 +4.687600E+01 +1.102381E+02 +2.954924E+00 +4.412809E-01 +5.155100E+01 +1.331461E+02 +3.204714E+00 +5.178544E-01 +5.067700E+01 +1.289238E+02 +3.246710E+00 +5.326374E-01 +4.738600E+01 +1.128834E+02 +3.035962E+00 +4.640211E-01 +3.953600E+01 +7.858196E+01 +2.507574E+00 +3.186456E-01 +2.819300E+01 +3.991455E+01 +1.846612E+00 +1.725570E-01 +1.497500E+01 +1.131312E+01 +9.213728E-01 +4.422001E-02 tally 4: 0.000000E+00 0.000000E+00 @@ -160,8 +160,8 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.065000E+00 -4.742170E-01 +3.090000E+00 +4.810640E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -208,10 +208,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.420000E+00 -1.474674E+00 -2.693000E+00 -3.667090E-01 +5.555000E+00 +1.551579E+00 +2.833000E+00 +4.078910E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -256,10 +256,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.243000E+00 -2.637431E+00 -5.092000E+00 -1.305200E+00 +7.271000E+00 +2.659755E+00 +5.095000E+00 +1.310819E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -304,10 +304,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.280000E+00 -3.445670E+00 -6.765000E+00 -2.307253E+00 +8.577000E+00 +3.703215E+00 +7.026000E+00 +2.486552E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -352,10 +352,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.980000E+00 -4.046484E+00 -8.108000E+00 -3.299338E+00 +9.393000E+00 +4.422429E+00 +8.572000E+00 +3.680852E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -400,10 +400,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.016000E+00 -4.079320E+00 -8.962000E+00 -4.034032E+00 +9.265000E+00 +4.305625E+00 +9.261000E+00 +4.304411E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -448,10 +448,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.465000E+00 -3.595665E+00 -9.296000E+00 -4.340524E+00 +8.535000E+00 +3.659395E+00 +9.303000E+00 +4.350791E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -496,10 +496,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.247000E+00 -2.638527E+00 -8.865000E+00 -3.946315E+00 +7.104000E+00 +2.544182E+00 +8.693000E+00 +3.799545E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -544,10 +544,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.179000E+00 -1.353661E+00 -7.492000E+00 -2.817588E+00 +5.168000E+00 +1.344390E+00 +7.334000E+00 +2.700052E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -592,10 +592,10 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.821000E+00 -4.067990E-01 -5.617000E+00 -1.587757E+00 +2.724000E+00 +3.745680E-01 +5.416000E+00 +1.471086E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -642,8 +642,8 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.134000E+00 -4.937920E-01 +2.960000E+00 +4.397840E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -662,114 +662,114 @@ k cmfd 0.000000E+00 0.000000E+00 0.000000E+00 -1.180802E+00 -1.163440E+00 -1.148572E+00 -1.151423E+00 -1.143374E+00 -1.144091E+00 -1.146212E+00 -1.144900E+00 -1.153511E+00 -1.158766E+00 -1.159179E+00 -1.156627E+00 -1.160647E+00 -1.162860E+00 -1.164312E+00 -1.164928E+00 +1.170416E+00 +1.172572E+00 +1.171159E+00 +1.170281E+00 +1.159698E+00 +1.151967E+00 +1.146706E+00 +1.147137E+00 +1.152154E+00 +1.156980E+00 +1.156370E+00 +1.155975E+00 +1.155295E+00 +1.154881E+00 +1.153714E+00 +1.159485E+00 cmfd entropy 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.214195E+00 -3.222259E+00 -3.225989E+00 -3.230436E+00 -3.228875E+00 -3.229003E+00 -3.228502E+00 -3.230397E+00 -3.231417E+00 -3.231192E+00 -3.229995E+00 -3.229396E+00 -3.228730E+00 -3.228091E+00 -3.227600E+00 -3.229723E+00 +3.203643E+00 +3.204555E+00 +3.210935E+00 +3.213980E+00 +3.219204E+00 +3.222234E+00 +3.226210E+00 +3.226808E+00 +3.224445E+00 +3.222460E+00 +3.222458E+00 +3.222447E+00 +3.220832E+00 +3.220841E+00 +3.221580E+00 +3.220523E+00 cmfd balance 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -4.742525E-03 -3.110598E-03 -2.490108E-03 -2.114137E-03 -2.190200E-03 -3.281877E-03 -2.219193E-03 -2.458372E-03 -2.200863E-03 -2.181858E-03 -2.064212E-03 -1.961178E-03 -1.713250E-03 -1.665361E-03 -1.436016E-03 -1.193462E-03 +4.009063E-03 +4.869662E-03 +2.997290E-03 +2.711191E-03 +1.688329E-03 +1.855396E-03 +1.403977E-03 +1.398430E-03 +1.818402E-03 +1.761252E-03 +1.646650E-03 +1.480120E-03 +1.399560E-03 +1.400162E-03 +1.178362E-03 +1.292279E-03 cmfd dominance ratio 0.000E+00 0.000E+00 0.000E+00 0.000E+00 - 5.467E-01 - 5.505E-01 - 5.514E-01 + 5.397E-01 + 5.405E-01 + 5.412E-01 + 5.428E-01 + 5.460E-01 + 4.531E-01 + 5.528E-01 5.531E-01 - 5.529E-01 - 5.501E-01 - 5.484E-01 - 5.500E-01 - 5.506E-01 - 5.508E-01 - 5.504E-01 - 5.500E-01 - 5.480E-01 - 5.482E-01 - 5.475E-01 5.493E-01 + 5.468E-01 + 5.482E-01 + 5.487E-01 + 5.471E-01 + 5.465E-01 + 5.461E-01 + 5.443E-01 cmfd openmc source comparison 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.168094E-03 -5.976241E-03 -4.426550E-03 -4.107499E-03 -4.957716E-03 -4.026213E-03 -3.986000E-03 -2.702714E-03 -3.619345E-03 -4.909616E-03 -3.355042E-03 -2.945724E-03 -3.010811E-03 -2.965662E-03 -2.673073E-03 -1.669634E-03 +6.959835E-03 +5.494668E-03 +4.076255E-03 +4.451120E-03 +3.035589E-03 +3.391773E-03 +1.907995E-03 +2.482495E-03 +2.994917E-03 +3.104683E-03 +2.309343E-03 +2.151358E-03 +2.348850E-03 +1.976731E-03 +2.080638E-03 +2.301327E-03 cmfd source -4.539734E-02 -8.104913E-02 -1.045143E-01 -1.221516E-01 -1.398002E-01 -1.400323E-01 -1.304628E-01 -1.120006E-01 -8.038230E-02 -4.420934E-02 +4.638920E-02 +7.751172E-02 +1.056089E-01 +1.282509E-01 +1.396713E-01 +1.415740E-01 +1.323405E-01 +1.092839E-01 +7.981779E-02 +3.955174E-02 diff --git a/tests/test_complex_cell/results_true.dat b/tests/test_complex_cell/results_true.dat index 97f228e3e..da3acd2aa 100644 --- a/tests/test_complex_cell/results_true.dat +++ b/tests/test_complex_cell/results_true.dat @@ -1,11 +1,11 @@ k-combined: -2.565769E-01 8.980879E-04 +2.531110E-01 3.041974E-03 tally 1: -2.584080E+00 -1.335682E+00 -2.763580E+00 -1.528633E+00 -1.007148E+00 -2.031543E-01 -1.113696E-01 -2.485351E-03 +2.594626E+00 +1.346701E+00 +2.683653E+00 +1.440725E+00 +9.933862E-01 +1.977011E-01 +1.112289E-01 +2.476655E-03 diff --git a/tests/test_confidence_intervals/results_true.dat b/tests/test_confidence_intervals/results_true.dat index fb13bdad2..e519180c8 100644 --- a/tests/test_confidence_intervals/results_true.dat +++ b/tests/test_confidence_intervals/results_true.dat @@ -1,5 +1,5 @@ k-combined: -2.913599E-01 6.738749E-03 +2.955487E-01 7.001017E-03 tally 1: -6.420923E+01 -5.190738E+02 +6.492201E+01 +5.290724E+02 diff --git a/tests/test_density/results_true.dat b/tests/test_density/results_true.dat index 1dbadc039..65135bbc9 100644 --- a/tests/test_density/results_true.dat +++ b/tests/test_density/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.088237E+00 1.999252E-02 +1.102244E+00 1.114944E-02 diff --git a/tests/test_distribmat/inputs_true.dat b/tests/test_distribmat/inputs_true.dat index fddab0a60..9c8a86bfa 100644 --- a/tests/test_distribmat/inputs_true.dat +++ b/tests/test_distribmat/inputs_true.dat @@ -1 +1 @@ -401b8be1b296db7f21ccae089c7ac480044d953b7264ca0ae8e34bb79e24cbb57195bcb568deda6f2f7e07366bbfac408a92306351b9169edd04499723707e1b \ No newline at end of file +96c54eb4f1da175445bf2187449ee32c9ff435d8c60e9421a4a16497aae9f233e3e494f531892dd55f6ac1a06e0240799503ff19e14e2436a0b0f0d83ba56cb8 \ No newline at end of file diff --git a/tests/test_distribmat/results_true.dat b/tests/test_distribmat/results_true.dat index 70464fbc6..bf96784d7 100644 --- a/tests/test_distribmat/results_true.dat +++ b/tests/test_distribmat/results_true.dat @@ -1,9 +1,9 @@ k-combined: -1.309285E+00 1.263629E-02 +1.291341E+00 1.269369E-02 Cell ID = 11 Name = - Material = [2, 3, void, 2] + Fill = [2, 3, None, 2] Region = -10000 Rotation = None Translation = None diff --git a/tests/test_distribmat/test_distribmat.py b/tests/test_distribmat/test_distribmat.py index a0608c108..96d41c3fb 100644 --- a/tests/test_distribmat/test_distribmat.py +++ b/tests/test_distribmat/test_distribmat.py @@ -28,9 +28,8 @@ class DistribmatTestHarness(PyAPITestHarness): light_fuel.set_density('g/cc', 2.0) light_fuel.add_nuclide('U-235', 1.0) - mats_file = openmc.MaterialsFile() + mats_file = openmc.Materials([moderator, dense_fuel, light_fuel]) mats_file.default_xs = '71c' - mats_file.add_materials([moderator, dense_fuel, light_fuel]) mats_file.export_to_xml() @@ -46,7 +45,7 @@ class DistribmatTestHarness(PyAPITestHarness): r0 = openmc.ZCylinder(R=0.3) c11 = openmc.Cell(cell_id=11) c11.region = -r0 - c11.fill = [dense_fuel, light_fuel, 'void', dense_fuel] + c11.fill = [dense_fuel, light_fuel, None, dense_fuel] c12 = openmc.Cell(cell_id=12) c12.region = +r0 c12.fill = moderator @@ -54,7 +53,6 @@ class DistribmatTestHarness(PyAPITestHarness): fuel_univ.add_cells((c11, c12)) lat = openmc.RectLattice(lattice_id=101) - lat.dimension = [2, 2] lat.lower_left = [-2.0, -2.0] lat.pitch = [2.0, 2.0] lat.universes = [[fuel_univ]*2]*2 @@ -74,16 +72,14 @@ class DistribmatTestHarness(PyAPITestHarness): geometry = openmc.Geometry() geometry.root_universe = root_univ - geo_file = openmc.GeometryFile() - geo_file.geometry = geometry - geo_file.export_to_xml() + geometry.export_to_xml() #################### # Settings #################### - sets_file = openmc.SettingsFile() + sets_file = openmc.Settings() sets_file.batches = 5 sets_file.inactive = 0 sets_file.particles = 1000 @@ -96,7 +92,7 @@ class DistribmatTestHarness(PyAPITestHarness): # Plots #################### - plots_file = openmc.PlotsFile() + plots_file = openmc.Plots() plot = openmc.Plot(plot_id=1) plot.basis = 'xy' diff --git a/tests/test_eigenvalue_genperbatch/results_true.dat b/tests/test_eigenvalue_genperbatch/results_true.dat index 9e87c901d..846a17e08 100644 --- a/tests/test_eigenvalue_genperbatch/results_true.dat +++ b/tests/test_eigenvalue_genperbatch/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.015627E-01 5.978844E-03 +3.001412E-01 2.669737E-03 diff --git a/tests/test_eigenvalue_no_inactive/results_true.dat b/tests/test_eigenvalue_no_inactive/results_true.dat index fbbe84cc3..2b4373e7e 100644 --- a/tests/test_eigenvalue_no_inactive/results_true.dat +++ b/tests/test_eigenvalue_no_inactive/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.130246E-01 6.960311E-03 +3.080574E-01 6.889659E-03 diff --git a/tests/test_energy_grid/results_true.dat b/tests/test_energy_grid/results_true.dat index 9556a981b..0a607592c 100644 --- a/tests/test_energy_grid/results_true.dat +++ b/tests/test_energy_grid/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.155788E-01 7.559348E-03 +3.330789E-01 2.216495E-03 diff --git a/tests/test_energy_laws/results_true.dat b/tests/test_energy_laws/results_true.dat index 48eb6bc81..02465fa79 100644 --- a/tests/test_energy_laws/results_true.dat +++ b/tests/test_energy_laws/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.130076E+00 1.938907E-03 +2.122164E+00 1.946222E-02 diff --git a/tests/test_entropy/results_true.dat b/tests/test_entropy/results_true.dat index 8b37789c3..e3e0daea0 100644 --- a/tests/test_entropy/results_true.dat +++ b/tests/test_entropy/results_true.dat @@ -1,13 +1,13 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 entropy: -7.608094E+00 -8.167702E+00 -8.273634E+00 -8.239452E+00 -8.234598E+00 -8.278421E+00 -8.260773E+00 -8.351860E+00 -8.303719E+00 -8.271058E+00 +7.601626E+00 +8.085658E+00 +8.263983E+00 +8.284792E+00 +8.420379E+00 +8.302840E+00 +8.316079E+00 +8.299781E+00 +8.329297E+00 +8.361325E+00 diff --git a/tests/test_filter_distribcell/case-1/results_true.dat b/tests/test_filter_distribcell/case-1/results_true.dat index 49bf3ed4e..a1f062e1b 100644 --- a/tests/test_filter_distribcell/case-1/results_true.dat +++ b/tests/test_filter_distribcell/case-1/results_true.dat @@ -1,14 +1,14 @@ k-combined: 0.000000E+00 0.000000E+00 tally 1: -1.440759E-02 -2.075788E-04 -1.222930E-02 -1.495558E-04 -1.407292E-02 -1.980471E-04 -1.034365E-02 -1.069911E-04 +1.548980E-02 +2.399339E-04 +1.278780E-02 +1.635279E-04 +1.426319E-02 +2.034385E-04 +1.018927E-02 +1.038213E-04 tally 2: -5.105347E-02 -2.606457E-03 +5.273007E-02 +2.780460E-03 diff --git a/tests/test_filter_distribcell/case-2/results_true.dat b/tests/test_filter_distribcell/case-2/results_true.dat index bb2f498cb..4e2583f3e 100644 --- a/tests/test_filter_distribcell/case-2/results_true.dat +++ b/tests/test_filter_distribcell/case-2/results_true.dat @@ -1,11 +1,11 @@ k-combined: 0.000000E+00 0.000000E+00 tally 1: -7.326285E-03 -5.367445E-05 -8.565980E-03 -7.337601E-05 -9.027116E-03 -8.148882E-05 -8.045879E-03 -6.473617E-05 +7.588170E-03 +5.758032E-05 +8.402486E-03 +7.060177E-05 +8.682518E-03 +7.538613E-05 +8.119997E-03 +6.593435E-05 diff --git a/tests/test_filter_distribcell/case-3/results_true.dat b/tests/test_filter_distribcell/case-3/results_true.dat index f5f85d29f..32c1fced1 100644 --- a/tests/test_filter_distribcell/case-3/results_true.dat +++ b/tests/test_filter_distribcell/case-3/results_true.dat @@ -1 +1 @@ -6008cf2ba8eecaaa5a600fa337cf54cef018e98bdba8e3bd26c6f44587376a838d5bc5e86301b2e308f9eb248e3efafd45a5336f4023d962d7921d158a621e0c \ No newline at end of file +7bef4810e3bba5df56fef96d9a946dc8dc8ac136ba5282d2975456f3de8fc47ea4ba557d6c83d0938579e11e2a0da5e8e4d03b3cd1f0c0d969d25c218b2ec0bc \ No newline at end of file diff --git a/tests/test_filter_distribcell/case-4/results_true.dat b/tests/test_filter_distribcell/case-4/results_true.dat index b8bd2b339..88e78d757 100644 --- a/tests/test_filter_distribcell/case-4/results_true.dat +++ b/tests/test_filter_distribcell/case-4/results_true.dat @@ -1,17 +1,17 @@ k-combined: 0.000000E+00 0.000000E+00 tally 1: -2.166056E-02 -4.691799E-04 -2.281665E-02 -5.205994E-04 -1.938848E-02 -3.759132E-04 -3.055366E-02 -9.335264E-04 -2.338209E-02 -5.467222E-04 -2.719869E-02 -7.397689E-04 -1.895698E-02 -3.593670E-04 +2.265319E-02 +5.131669E-04 +2.026852E-02 +4.108129E-04 +2.051718E-02 +4.209546E-04 +3.015130E-02 +9.091009E-04 +2.356397E-02 +5.552606E-04 +2.558974E-02 +6.548348E-04 +2.012046E-02 +4.048330E-04 diff --git a/tests/test_filter_mesh_2d/results_true.dat b/tests/test_filter_mesh_2d/results_true.dat index 21946086b..f4c597952 100644 --- a/tests/test_filter_mesh_2d/results_true.dat +++ b/tests/test_filter_mesh_2d/results_true.dat @@ -1,5 +1,5 @@ k-combined: -1.005983E+00 2.248579E-02 +9.581522E-01 4.261830E-02 tally 1: 0.000000E+00 0.000000E+00 @@ -45,10 +45,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.228098E-02 -1.042062E-03 -3.222708E-01 -1.038585E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -57,8 +53,16 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.474078E-01 +2.172907E-02 +6.386562E-02 +4.078817E-03 0.000000E+00 0.000000E+00 +2.905797E-02 +8.443654E-04 +7.532560E-03 +5.673946E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -67,6 +71,10 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.149324E-01 +1.320945E-02 +2.465048E-02 +3.049063E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -75,14 +83,20 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -8.182335E-01 -3.748630E-01 -2.711997E-01 -5.338821E-02 -3.359680E-01 -5.168399E-02 0.000000E+00 0.000000E+00 +7.002118E-02 +4.902965E-03 +5.128548E-01 +1.258296E-01 +1.379070E+00 +4.300261E-01 +1.040956E+00 +3.089102E-01 +1.237157E+00 +6.284409E-01 +9.539296E-01 +5.206980E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -91,12 +105,30 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.001407E+00 +1.600000E+00 +7.159080E-01 +2.988090E-01 0.000000E+00 0.000000E+00 -3.706070E-01 -1.373496E-01 0.000000E+00 0.000000E+00 +3.473499E-01 +1.206520E-01 +1.597805E-01 +1.297695E-02 +1.438568E-01 +1.597365E-02 +8.612279E-02 +5.910825E-03 +9.004671E-01 +2.791173E-01 +6.485841E+00 +1.046238E+01 +6.743595E+00 +1.135216E+01 +7.681046E-01 +1.896252E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -107,143 +139,40 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +9.572791E-01 +8.942065E-01 0.000000E+00 0.000000E+00 -3.931419E-01 -9.002841E-02 -1.092722E+00 -3.733055E-01 -2.384227E+00 -1.926937E+00 -9.101131E-01 -3.634496E-01 -3.284661E-01 -1.078900E-01 0.000000E+00 0.000000E+00 -6.885295E-02 -4.740728E-03 0.000000E+00 0.000000E+00 -2.419633E-02 -5.854622E-04 -9.286912E-02 -7.247209E-03 -5.629729E-01 -9.281109E-02 -7.345786E-01 -1.755550E-01 -1.219449E-01 -1.487057E-02 +5.299733E-01 +2.205463E-01 +1.349846E+00 +6.808561E-01 +6.874433E-01 +2.287801E-01 +5.651386E-01 +1.286874E-01 +5.729905E-01 +2.680764E-01 +5.509254E-01 +1.200498E-01 +1.494910E+00 +6.327940E-01 +2.444256E-01 +2.804968E-02 +6.927475E-01 +2.317744E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.983303E-01 -3.797884E-02 -4.840974E-02 -1.266547E-03 -1.183485E+00 -4.184814E-01 -3.027254E-01 -8.598449E-02 -9.889868E-01 -4.608531E-01 -8.698103E-01 -4.598559E-01 -1.332831E+00 -4.809984E-01 -1.564949E+00 -5.782651E-01 -1.143572E+00 -4.399439E-01 -1.326651E+00 -6.376565E-01 -1.716813E+00 -1.314280E+00 -7.673229E-01 -2.364966E-01 -2.539284E+00 -1.945563E+00 -1.263219E+00 -4.919339E-01 -5.430042E-01 -1.300266E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -7.553587E-01 -1.738170E-01 -2.048487E+00 -1.239856E+00 -3.761862E-01 -8.452912E-02 -0.000000E+00 -0.000000E+00 -9.675232E-02 -9.361012E-03 -2.319594E-01 -2.331698E-02 -1.573495E+00 -6.394722E-01 -4.432570E-01 -1.005943E-01 -9.353148E-01 -3.125416E-01 -8.359366E-01 -2.985072E-01 -1.657665E+00 -9.207020E-01 -3.737550E+00 -3.558505E+00 -1.742376E+00 -8.732217E-01 -5.153816E+00 -6.543973E+00 -1.653035E+00 -1.061068E+00 -9.963191E-01 -3.716347E-01 -2.282805E-01 -2.383414E-02 -8.749983E-01 -2.714666E-01 -1.728411E-01 -1.190218E-02 -9.250054E-02 -4.341922E-03 -6.353807E-02 -4.037086E-03 -1.811729E-01 -1.711154E-02 -3.218800E-01 -7.906855E-02 -1.057036E+00 -3.778638E-01 -9.231639E-01 -2.991795E-01 -3.375678E-01 -1.041383E-01 -1.181686E-01 -8.023920E-03 -4.912969E-01 -2.073894E-01 -9.395786E-01 -4.653730E-01 -6.998437E-01 -2.917085E-01 -3.074214E+00 -2.819088E+00 -2.570673E+00 -1.358321E+00 -1.108912E+00 -3.843307E-01 -4.950896E-02 -2.451137E-03 -0.000000E+00 -0.000000E+00 -0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -251,28 +180,26 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -8.757958E-02 -7.670183E-03 0.000000E+00 +4.425042E-01 +5.854257E-02 +2.237774E+00 +1.109643E+00 +7.495196E-01 +1.939234E-01 +3.804197E-01 +1.225870E-01 +1.009880E-01 +9.392497E-03 +2.424177E+00 +1.613025E+00 +2.226123E+00 +1.203763E+00 +1.939766E+00 +1.132042E+00 +3.953753E-01 +1.420303E-01 0.000000E+00 -6.469411E-01 -1.789549E-01 -7.829878E-01 -2.033989E-01 -8.994770E-01 -2.351438E-01 -4.712797E-01 -7.213659E-02 -2.133532E+00 -9.765422E-01 -4.533607E-01 -1.511497E-01 -1.878729E+00 -2.099266E+00 -4.287190E+00 -4.748691E+00 -1.961229E+00 -1.085868E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -280,185 +207,235 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.501129E-02 +6.255649E-04 +3.984785E-01 +1.486414E-01 +1.251028E-01 +1.306358E-02 0.000000E+00 0.000000E+00 +9.831996E-01 +4.846833E-01 +4.237107E-01 +6.002592E-02 +8.922533E-01 +2.835397E-01 0.000000E+00 0.000000E+00 +3.174349E-01 +1.007649E-01 +1.260449E+00 +5.881747E-01 +3.147407E+00 +3.333589E+00 +2.021896E+00 +1.425606E+00 +1.377786E-01 +1.716503E-02 +3.011069E-02 +9.066538E-04 0.000000E+00 -1.061692E-01 -1.127190E-02 -1.912282E-01 -3.656822E-02 -3.289827E-01 -1.075283E-01 -1.750908E+00 -8.092384E-01 -2.156426E+00 -9.498067E-01 -1.480596E+00 -6.002164E-01 -3.249216E-01 -1.005106E-01 -8.875810E-02 -7.878000E-03 -2.458176E-01 -4.377921E-02 -2.766784E+00 -2.677426E+00 -2.703501E+00 -2.548083E+00 0.000000E+00 +5.118696E-02 +2.620104E-03 +0.000000E+00 +0.000000E+00 +1.484996E-01 +2.205214E-02 +9.889831E-01 +3.657975E-01 +2.850134E+00 +2.250972E+00 +4.131352E-01 +6.756111E-02 +8.393183E-03 +7.044551E-05 +0.000000E+00 +0.000000E+00 +7.462571E-02 +5.568996E-03 +0.000000E+00 +0.000000E+00 +2.560771E-01 +6.557550E-02 +9.262861E-03 +8.580060E-05 +2.505905E-01 +6.279558E-02 +5.136552E-01 +2.638417E-01 +1.441275E+00 +5.086865E-01 +2.913901E+00 +1.841912E+00 +6.978650E-01 +2.584000E-01 +1.451562E-02 +2.107031E-04 +0.000000E+00 +0.000000E+00 +3.079994E-03 +9.486363E-06 +1.492571E+00 +6.318792E-01 +2.083542E+00 +1.599782E+00 +2.677440E+00 +2.382024E+00 +4.457483E-01 +5.194318E-02 +5.424180E-02 +2.942173E-03 +0.000000E+00 +0.000000E+00 +2.355899E-02 +5.550260E-04 +3.571813E-02 +1.275785E-03 +6.588191E-01 +2.543824E-01 +4.171440E-01 +8.701395E-02 +7.735493E-01 +1.575534E-01 +4.033076E-01 +5.492660E-02 +4.513270E+00 +5.611449E+00 +1.653243E+00 +8.369762E-01 +1.045336E-01 +1.092727E-02 +2.486634E-01 +2.561523E-02 +1.090478E+00 +5.381842E-01 +6.314497E-01 +1.552199E-01 +3.417016E+00 +2.972256E+00 +5.709899E+00 +7.095076E+00 +1.194169E+00 +4.790398E-01 +1.420269E-01 +2.017163E-02 +0.000000E+00 +0.000000E+00 +3.214464E-01 +1.033278E-01 +2.222160E-02 +4.937996E-04 +2.028040E-01 +4.112944E-02 +1.417427E+00 +9.671327E-01 +1.453489E+00 +6.697189E-01 +8.534416E-01 +2.290345E-01 +5.367404E+00 +6.853344E+00 +1.237276E+00 +4.961691E-01 +5.835684E-02 +3.405521E-03 +5.574899E-01 +1.049542E-01 +4.235354E+00 +5.638989E+00 +2.034493E+00 +1.162774E+00 +1.533605E+00 +8.644495E-01 +4.663027E+00 +5.641430E+00 +1.261505E+00 +7.705206E-01 +1.954689E+00 +9.874394E-01 +1.449729E-01 +2.101714E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +1.398153E-01 +1.954832E-02 +5.089636E-01 +8.836228E-02 +1.422521E+00 +6.953668E-01 +1.137705E+00 +5.670907E-01 +3.521780E-01 +6.575561E-02 0.000000E+00 0.000000E+00 +7.713789E-01 +2.948263E-01 +3.267703E-01 +4.763836E-02 +1.252153E+00 +4.563949E-01 +1.962807E-01 +2.410165E-02 +1.357567E+00 +4.362757E-01 +2.356462E-01 +3.082678E-02 +1.380025E+00 +4.289689E-01 +1.876891E-01 +1.675278E-02 0.000000E+00 0.000000E+00 0.000000E+00 -1.981880E-01 -3.927848E-02 -2.789456E-01 -5.304261E-02 -3.897689E-01 -9.413685E-02 -9.140885E-01 -2.822974E-01 -1.887726E+00 -7.592780E-01 -1.841624E+00 -1.680236E+00 -4.059938E-01 -1.562853E-01 -2.897077E-01 -8.393057E-02 0.000000E+00 0.000000E+00 -2.445051E-01 -5.978276E-02 -2.234657E-01 -2.716625E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +1.940736E-01 +2.763730E-02 +6.059470E-02 +3.671718E-03 +3.479381E-01 +1.210609E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -4.783335E-02 -2.288029E-03 -5.606011E-01 -1.607491E-01 -1.908325E+00 -1.505641E+00 -1.255795E-01 -1.541635E-02 -7.395548E-01 -2.274416E-01 -5.986733E-01 -9.576988E-02 -1.095026E+00 -4.872910E-01 -1.043470E+00 -3.153965E-01 -1.004973E+00 -6.046910E-01 -1.724071E-01 -2.775427E-02 0.000000E+00 +3.452042E-02 +1.191659E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +3.679762E-01 +1.354065E-01 +5.043842E-02 +2.544034E-03 0.000000E+00 -1.244277E-01 -1.548225E-02 -1.222119E-01 -1.493575E-02 0.000000E+00 0.000000E+00 -5.470039E-01 -2.992133E-01 -4.313918E-01 -1.128703E-01 -1.088037E+00 -6.007745E-01 -1.013469E+00 -5.646900E-01 -4.738741E-01 -2.245567E-01 -6.086518E-02 -3.704570E-03 -1.126662E+00 -4.675322E-01 -1.008459E+00 -4.616352E-01 -1.309592E+00 -5.665211E-01 -1.334050E+00 -5.264819E-01 -7.324996E-01 -2.577124E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.227736E-01 -1.041828E-01 -9.218244E-01 -2.000301E-01 -2.119900E+00 -1.123846E+00 -4.366404E-02 -1.015133E-03 0.000000E+00 0.000000E+00 -2.309730E-01 -2.570742E-02 -1.270911E+00 -4.617932E-01 -1.107069E+00 -4.574496E-01 -1.269137E-01 -1.610709E-02 -2.207099E-01 -4.871286E-02 -9.075694E-02 -8.236821E-03 -1.046380E-01 -7.875036E-03 -2.836364E-01 -3.508209E-02 -4.509177E-01 -7.393615E-02 -1.077505E+00 -3.209541E-01 -1.204982E-02 -1.451982E-04 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -2.502937E-01 -5.035125E-02 -1.367234E+00 -5.128884E-01 -5.563575E-01 -2.510519E-01 -3.174809E-01 -1.007941E-01 -9.152129E-01 -2.609325E-01 -9.040668E-01 -2.263595E-01 -7.868812E-01 -2.436310E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -467,60 +444,22 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.390904E-01 -4.907887E-02 -6.577001E-01 -2.346964E-01 -1.023735E-01 -8.287220E-03 -1.499600E-02 -2.248801E-04 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.395650E-01 -1.947839E-02 -1.040555E+00 -3.043523E-01 -1.426976E+00 -6.218295E-01 -8.342758E-01 -2.539692E-01 -3.101170E-01 -9.617255E-02 -6.319919E-02 -3.629541E-03 -1.292774E-01 -8.674372E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.056616E-01 -4.198926E-01 -7.349640E-02 -5.401721E-03 -5.146331E-01 -1.555789E-01 -2.464783E-01 -5.430051E-02 -7.263842E-02 -5.276340E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.587357E-01 -4.992769E-01 -1.756477E+00 -7.884472E-01 -2.541705E-01 -4.325743E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -528,19 +467,17 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.678278E-01 +2.097037E-02 +5.312751E-02 +1.423243E-03 +3.374418E-01 +1.138670E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.496519E-02 -4.948061E-03 -1.596404E-01 -2.548506E-02 -2.454011E-02 -6.022168E-04 -1.235276E-01 -1.525907E-02 0.000000E+00 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+0.000000E+00 +0.000000E+00 +0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/tests/test_filter_mesh_3d/results_true.dat b/tests/test_filter_mesh_3d/results_true.dat index 239a9f01a..88a522827 100644 --- a/tests/test_filter_mesh_3d/results_true.dat +++ b/tests/test_filter_mesh_3d/results_true.dat @@ -1,5 +1,5 @@ k-combined: -1.005983E+00 2.248579E-02 +9.581522E-01 4.261830E-02 tally 1: 0.000000E+00 0.000000E+00 @@ -753,8 +753,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.228098E-02 -1.042062E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -787,8 +785,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.222708E-01 -1.038585E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -901,6 +897,10 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.083669E-01 +1.174340E-02 +3.904088E-02 +1.524190E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -931,6 +931,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +6.386562E-02 +4.078817E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -997,6 +999,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.905797E-02 +8.443654E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1029,6 +1033,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +7.532560E-03 +5.673946E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1251,6 +1257,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.306116E-02 +1.705939E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1261,12 +1269,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -2.009463E-01 -4.037943E-02 -1.741795E-01 -3.033850E-02 -4.431077E-01 -1.023945E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1299,10 +1301,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.699856E-01 -1.749182E-02 -1.012141E-01 -1.024430E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1329,12 +1327,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -2.427282E-01 -4.346756E-02 -8.576175E-02 -6.594648E-03 -7.478060E-03 -5.592138E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1451,6 +1443,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +7.002118E-02 +4.902965E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1475,10 +1469,16 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.465169E-02 +6.077057E-04 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +2.623543E-01 +4.112454E-02 +2.258489E-01 +5.100771E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1501,6 +1501,18 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.729718E-01 +2.991925E-02 +2.994456E-02 +8.966764E-04 +9.977770E-03 +9.955590E-05 +4.396029E-01 +6.352573E-02 +5.669837E-01 +1.209384E-01 +1.423672E-01 +1.771243E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1515,6 +1527,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.722215E-02 +2.966024E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1525,6 +1539,12 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +1.565669E-02 +2.451318E-04 +8.200689E-01 +2.392978E-01 +1.748649E-01 +1.584562E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1541,6 +1561,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +3.036511E-02 +9.220402E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1553,6 +1575,12 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +9.998387E-02 +7.936690E-03 +1.089115E+00 +5.614559E-01 +4.805840E-02 +2.309610E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1579,12 +1607,12 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -6.645869E-02 -4.416757E-03 -3.041483E-01 -9.250621E-02 0.000000E+00 0.000000E+00 +2.742414E-01 +7.520835E-02 +6.796882E-01 +2.348838E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1773,6 +1801,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +3.448095E-01 +5.774877E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1805,6 +1835,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +6.033873E-01 +2.672168E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1843,8 +1875,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.931419E-01 -9.002841E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1875,12 +1905,6 @@ tally 1: 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-3.300694E-04 -3.102983E-01 -9.628505E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +2.396759E-03 +5.744454E-06 +8.372603E-02 +5.869219E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2019,8 +2045,18 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +4.409446E-02 +1.944321E-03 +2.812104E-01 +7.907926E-02 0.000000E+00 0.000000E+00 +1.125733E-01 +1.267274E-02 +3.364085E-01 +6.085429E-02 +8.236284E-02 +4.869311E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2037,28 +2073,56 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +4.381770E-02 +1.919990E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 +8.563908E-02 +4.712912E-03 +9.597166E-01 +3.206571E-01 +3.164476E-01 +5.280988E-02 +2.073790E+00 +1.188596E+00 +9.609431E-01 +2.621642E-01 +4.350509E-01 +1.399885E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -6.885295E-02 -4.740728E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 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@@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.098236E-02 -1.206123E-04 -5.047052E-02 -2.547273E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.065577E-02 -7.244766E-05 -2.076046E-02 -4.309969E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2191,18 +2259,10 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.209931E-01 -7.784762E-03 -1.059137E-01 -1.121770E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.883880E-01 -1.626283E-02 -1.476781E-01 -2.180883E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2225,16 +2285,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -5.464783E-03 -2.986386E-05 -4.827060E-01 -1.236578E-01 -2.938269E-02 -8.633425E-04 -1.103939E-01 -1.218681E-02 -1.066312E-01 -7.137023E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2265,10 +2315,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -6.448951E-03 -4.158897E-05 -1.154960E-01 -1.333932E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2333,6 +2379,8 @@ tally 1: 0.000000E+00 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+0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +5.214580E-02 +2.719184E-03 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -9359,10 +9363,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.668786E-02 -2.784846E-04 -2.256035E-01 -5.089693E-02 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/tests/test_fixed_source/results_true.dat b/tests/test_fixed_source/results_true.dat index b3def050e..c7ddf3c0b 100644 --- a/tests/test_fixed_source/results_true.dat +++ b/tests/test_fixed_source/results_true.dat @@ -1,6 +1,6 @@ tally 1: -4.563929E+02 -2.091711E+04 +4.518784E+02 +2.056386E+04 leakage: -9.780000E+00 -9.566400E+00 +9.750000E+00 +9.508100E+00 diff --git a/tests/test_infinite_cell/results_true.dat b/tests/test_infinite_cell/results_true.dat index 0b8d92951..b909c92bb 100644 --- a/tests/test_infinite_cell/results_true.dat +++ b/tests/test_infinite_cell/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.788797E-02 1.378250E-03 +9.893460E-02 1.178316E-03 diff --git a/tests/test_iso_in_lab/inputs_true.dat b/tests/test_iso_in_lab/inputs_true.dat new file mode 100644 index 000000000..bd722c9f6 --- /dev/null +++ b/tests/test_iso_in_lab/inputs_true.dat @@ -0,0 +1 @@ +85faac9b8c725ec9242ebc3793b70dcd1c8e58aeb4296345aefd8031304263bd66eaad0c6f1c61a1c644b73f397699856ab3d76d2b397295176650b4069acc9e \ No newline at end of file diff --git a/tests/test_iso_in_lab/results_true.dat b/tests/test_iso_in_lab/results_true.dat new file mode 100644 index 000000000..354ccb0f8 --- /dev/null +++ b/tests/test_iso_in_lab/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +9.638450E-01 1.237705E-02 diff --git a/tests/test_iso_in_lab/test_iso_in_lab.py b/tests/test_iso_in_lab/test_iso_in_lab.py new file mode 100644 index 000000000..b60daea11 --- /dev/null +++ b/tests/test_iso_in_lab/test_iso_in_lab.py @@ -0,0 +1,26 @@ +#!/usr/bin/env python + +import os +import sys +import glob +import hashlib +sys.path.insert(0, os.pardir) +from testing_harness import PyAPITestHarness +import openmc +import openmc.mgxs + + +class IsoInLabTestHarness(PyAPITestHarness): + + def _build_inputs(self): + """Write input XML files with iso-in-lab scattering.""" + + self._input_set.build_default_materials_and_geometry() + self._input_set.build_default_settings() + self._input_set.materials.make_isotropic_in_lab() + self._input_set.export() + + +if __name__ == '__main__': + harness = IsoInLabTestHarness('statepoint.10.*') + harness.main() diff --git a/tests/test_lattice/results_true.dat b/tests/test_lattice/results_true.dat index cf51dd5d7..1d3d47fc4 100644 --- a/tests/test_lattice/results_true.dat +++ b/tests/test_lattice/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.042388E+00 1.575316E-01 +9.413559E-01 6.157522E-02 diff --git a/tests/test_lattice_hex/results_true.dat b/tests/test_lattice_hex/results_true.dat index b88285ff2..4ba727dbf 100644 --- a/tests/test_lattice_hex/results_true.dat +++ b/tests/test_lattice_hex/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.831014E-01 2.269849E-02 +2.496460E-01 1.257055E-02 diff --git a/tests/test_lattice_mixed/results_true.dat b/tests/test_lattice_mixed/results_true.dat index 7cea76ba0..d3c19b11a 100644 --- a/tests/test_lattice_mixed/results_true.dat +++ b/tests/test_lattice_mixed/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.922449E-01 1.281824E-02 +9.790311E-01 9.660522E-03 diff --git a/tests/test_lattice_multiple/results_true.dat b/tests/test_lattice_multiple/results_true.dat index 6caffdd95..5c00c4486 100644 --- a/tests/test_lattice_multiple/results_true.dat +++ b/tests/test_lattice_multiple/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.005983E+00 2.248579E-02 +9.581522E-01 4.261830E-02 diff --git a/tests/test_mg_basic/inputs_true.dat b/tests/test_mg_basic/inputs_true.dat index fdbdb1c96..3f83de760 100644 --- a/tests/test_mg_basic/inputs_true.dat +++ b/tests/test_mg_basic/inputs_true.dat @@ -1 +1 @@ -04b4a5099f0097bbe02983c67dea691d0d0d4ece7fb7c264b9b2c29955baa9e870b6fa999480da08ead1e5a0c078ae33ce1b0a5c8594ad465aedf9bf3933e104 \ No newline at end of file +2fdba76bad058eec6e43657692ef759de79c934076067d4ec5c9f2bdb131877e001f67e16b16bb14889e5e0a1ba84c780979b9d6772573aa6f82d979774c2af8 \ No newline at end of file diff --git a/tests/test_mg_basic/results_true.dat b/tests/test_mg_basic/results_true.dat index 35f3e73d4..55c2af813 100644 --- a/tests/test_mg_basic/results_true.dat +++ b/tests/test_mg_basic/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.045320E+00 5.851680E-02 +1.033731E+00 4.974463E-02 diff --git a/tests/test_mg_max_order/inputs_true.dat b/tests/test_mg_max_order/inputs_true.dat index 1ad336e19..63bdaab03 100644 --- a/tests/test_mg_max_order/inputs_true.dat +++ b/tests/test_mg_max_order/inputs_true.dat @@ -1 +1 @@ -abe20c626d613e73ccb1a3f8468ad1b9aecca528afa9e8131a411d754eb86b8ab64a6fb1fdc9c0b8b8158ff7c82f548de5912041bf035aa5a2d4532cfe0c9510 \ No newline at end of file +60a35864ad71646309d7f1687ba0826d4d53a5b2e8babf73614362645205484bad3c0e7bf605ec0b11cadf58474b2e3d0a97bf2d9297f9118682c37ff0269afd \ No newline at end of file diff --git a/tests/test_mg_max_order/results_true.dat b/tests/test_mg_max_order/results_true.dat index 1b2300560..f75c1300a 100644 --- a/tests/test_mg_max_order/results_true.dat +++ b/tests/test_mg_max_order/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.083030E+00 1.855038E-02 +1.055274E+00 1.715904E-02 diff --git a/tests/test_mg_max_order/test_mg_max_order.py b/tests/test_mg_max_order/test_mg_max_order.py index 2f5ee4e4e..088f6914b 100644 --- a/tests/test_mg_max_order/test_mg_max_order.py +++ b/tests/test_mg_max_order/test_mg_max_order.py @@ -27,7 +27,7 @@ class MGNuclideInputSet(MGInputSet): # Define the materials file. self.materials.default_xs = '71c' - self.materials.add_materials((uo2, clad, water)) + self.materials += (uo2, clad, water) # Define surfaces. @@ -68,7 +68,7 @@ class MGNuclideInputSet(MGInputSet): geometry = openmc.Geometry() geometry.root_universe = root - self.geometry.geometry = geometry + self.geometry = geometry class MGMaxOrderTestHarness(PyAPITestHarness): def __init__(self, statepoint_name, tallies_present, mg=False): @@ -76,9 +76,10 @@ class MGMaxOrderTestHarness(PyAPITestHarness): self._input_set = MGNuclideInputSet() def _build_inputs(self): - super(MGMaxOrderTestHarness, self)._build_inputs() # Set P1 scattering self._input_set.settings.max_order = 1 + # Call standard input build + super(MGMaxOrderTestHarness, self)._build_inputs() if __name__ == '__main__': harness = MGMaxOrderTestHarness('statepoint.10.*', False, mg=True) diff --git a/tests/test_mg_nuclide/inputs_true.dat b/tests/test_mg_nuclide/inputs_true.dat index eb643bbaf..e0af3352b 100644 --- a/tests/test_mg_nuclide/inputs_true.dat +++ b/tests/test_mg_nuclide/inputs_true.dat @@ -1 +1 @@ -c9f9e7211bfb2af58130bedfd64592d093b7bfa424953eba433ecf08940595a96b8de7a892f12d1ab465cebd8e5dd784114c1b1299b534ed329df92752c9ed1f \ No newline at end of file +0efba3dd7882fdd38756d0a8f01ff00d7a1abdaab6430b3f090f3339e552448453bbb733852b6bd6ff09608d923c282f168320f942fc2eb3a45610873c588734 \ No newline at end of file diff --git a/tests/test_mg_nuclide/results_true.dat b/tests/test_mg_nuclide/results_true.dat index 5b60cef22..55c2af813 100644 --- a/tests/test_mg_nuclide/results_true.dat +++ b/tests/test_mg_nuclide/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.380785E-01 5.556526E-03 +1.033731E+00 4.974463E-02 diff --git a/tests/test_mg_nuclide/test_mg_nuclide.py b/tests/test_mg_nuclide/test_mg_nuclide.py index deb784bad..89694eea2 100644 --- a/tests/test_mg_nuclide/test_mg_nuclide.py +++ b/tests/test_mg_nuclide/test_mg_nuclide.py @@ -12,21 +12,21 @@ class MGNuclideInputSet(MGInputSet): # Define materials needed for 1D/1G slab problem # This time do using nuclide, not macroscopic uo2 = openmc.Material(name='UO2', material_id=1) - uo2.set_density('g/cm3', 1.0) + uo2.set_density('sum', 1.0) uo2.add_nuclide("uo2_iso", 1.0) clad = openmc.Material(name='Clad', material_id=2) - clad.set_density('g/cm3', 1.0) + clad.set_density('sum', 1.0) clad.add_nuclide("clad_ang_mu", 1.0) - water_data = openmc.Nuclide('lwtr_iso_mu', '71c') + # water_data = openmc.Nuclide('lwtr_iso_mu', '71c') water = openmc.Material(name='LWTR', material_id=3) - water.set_density('g/cm3', 1.0) + water.set_density('sum', 1.0) water.add_nuclide("lwtr_iso_mu", 1.0) # Define the materials file. self.materials.default_xs = '71c' - self.materials.add_materials((uo2, clad, water)) + self.materials += (uo2, clad, water) # Define surfaces. @@ -67,7 +67,7 @@ class MGNuclideInputSet(MGInputSet): geometry = openmc.Geometry() geometry.root_universe = root - self.geometry.geometry = geometry + self.geometry = geometry class MGNuclideTestHarness(PyAPITestHarness): def __init__(self, statepoint_name, tallies_present, mg=False): diff --git a/tests/test_mg_tallies/inputs_true.dat b/tests/test_mg_tallies/inputs_true.dat index 304d2e888..41bbd2136 100644 --- a/tests/test_mg_tallies/inputs_true.dat +++ b/tests/test_mg_tallies/inputs_true.dat @@ -1 +1 @@ -ca8490e0e4549fed727ddc75b6d92cfe5162e11b905218a0afaa3ce2ee0763e2ff38074de27aaa678818624f49c5823650475dfa8f66f502a98fc03145399c0d \ No newline at end of file +6c437c3f9281c52a80a9b166971aa0f5db7ff8b6cf65c79b6d7bf294fad30cc7044f6a665cd9059f8580441bcbb581f7152ff5bccbc21fbcc407847ea6fe3306 \ No newline at end of file diff --git a/tests/test_mg_tallies/results_true.dat b/tests/test_mg_tallies/results_true.dat index 0cb47a712..debbfa537 100644 --- a/tests/test_mg_tallies/results_true.dat +++ b/tests/test_mg_tallies/results_true.dat @@ -1,86 +1,86 @@ k-combined: -1.045320E+00 5.851680E-02 +1.033731E+00 4.974463E-02 tally 1: -2.286064E+00 -1.057353E+00 -6.503987E-02 -8.851627E-04 -3.376363E+00 -2.323627E+00 -2.733240E-02 -1.607534E-04 -6.776283E-02 -9.880704E-04 -2.391658E+00 -1.201477E+00 -7.241106E-02 -1.103780E-03 -3.614949E+00 -2.730438E+00 -3.146867E-02 -2.110753E-04 -7.801752E-02 -1.297373E-03 -2.762725E+00 -1.705088E+00 -8.684520E-02 -1.654173E-03 -4.172232E+00 -3.847245E+00 -3.834947E-02 -3.212662E-04 -9.507651E-02 -1.974662E-03 -2.802290E+00 -1.773339E+00 -8.347451E-02 -1.574952E-03 -4.206829E+00 -3.971225E+00 -3.593646E-02 -2.967708E-04 -8.909414E-02 -1.824101E-03 -2.383708E+00 -1.176784E+00 -7.337273E-02 -1.097240E-03 -3.624903E+00 -2.690697E+00 -3.213890E-02 -2.139948E-04 -7.967917E-02 -1.315319E-03 -2.398216E+00 -1.234567E+00 -6.905889E-02 -9.879327E-04 -3.479138E+00 -2.538252E+00 -2.911091E-02 -1.750648E-04 -7.217215E-02 -1.076035E-03 -2.563998E+00 -1.354089E+00 -7.357381E-02 -1.097086E-03 -3.753156E+00 -2.867475E+00 -3.097034E-02 -1.948794E-04 -7.678206E-02 -1.197826E-03 -2.293243E+00 -1.172767E+00 -6.702582E-02 -9.267762E-04 -3.407144E+00 -2.469472E+00 -2.857514E-02 -1.688581E-04 -7.084385E-02 -1.037886E-03 +3.163666E+00 +2.165097E+00 +9.964133E-02 +2.052446E-03 +4.861844E+00 +4.978206E+00 +4.417216E-02 +4.040216E-04 +1.095122E-01 +2.483317E-03 +3.324437E+00 +2.299850E+00 +9.574329E-02 +1.968438E-03 +4.881821E+00 +4.943976E+00 +4.041706E-02 +3.650255E-04 +1.002025E-01 +2.243628E-03 +3.199995E+00 +2.091126E+00 +8.859707E-02 +1.592091E-03 +4.671522E+00 +4.439001E+00 +3.660515E-02 +2.728602E-04 +9.075197E-02 +1.677135E-03 +2.910284E+00 +1.723356E+00 +9.207508E-02 +1.744614E-03 +4.421737E+00 +3.979362E+00 +4.080063E-02 +3.481887E-04 +1.011535E-01 +2.140141E-03 +2.506574E+00 +1.326705E+00 +8.637880E-02 +1.598941E-03 +3.920683E+00 +3.263607E+00 +3.978214E-02 +3.424111E-04 +9.862841E-02 +2.104629E-03 +2.951103E+00 +1.826551E+00 +8.748324E-02 +1.648479E-03 +4.309848E+00 +3.903067E+00 +3.741466E-02 +3.141687E-04 +9.275891E-02 +1.931037E-03 +3.048521E+00 +2.007251E+00 +9.483162E-02 +1.935789E-03 +4.599534E+00 +4.527383E+00 +4.168244E-02 +3.813062E-04 +1.033396E-01 +2.343697E-03 +2.982958E+00 +1.966657E+00 +9.896454E-02 +2.016812E-03 +4.645921E+00 +4.599347E+00 +4.489740E-02 +4.108900E-04 +1.113102E-01 +2.525534E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -171,86 +171,86 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -2.604127E+00 -1.442914E+00 -7.142299E-02 -1.083324E-03 -3.786547E+00 -2.990260E+00 -2.935394E-02 -1.905369E-04 -7.277467E-02 -1.171135E-03 -2.457755E+00 -1.228862E+00 -6.655630E-02 -9.411086E-04 -3.528688E+00 -2.561047E+00 -2.709124E-02 -1.640319E-04 -6.716494E-02 -1.008221E-03 -2.450846E+00 -1.295337E+00 -6.779278E-02 -9.992248E-04 -3.519409E+00 -2.693620E+00 -2.793186E-02 -1.714064E-04 -6.924902E-02 -1.053549E-03 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-9.657439E-02 -1.966961E-03 -2.644733E+00 -1.407404E+00 -8.635553E-02 -1.527997E-03 -4.094426E+00 -3.382785E+00 -3.888081E-02 -3.161126E-04 -9.639381E-02 -1.942985E-03 +2.603449E+00 +1.382310E+00 +7.044110E-02 +1.048854E-03 +3.683939E+00 +2.770822E+00 +2.858207E-02 +1.846566E-04 +7.086104E-02 +1.134991E-03 +2.458052E+00 +1.211571E+00 +7.271340E-02 +1.061659E-03 +3.628656E+00 +2.636961E+00 +3.113049E-02 +1.956492E-04 +7.717911E-02 +1.202557E-03 +2.200265E+00 +9.745445E-01 +7.058665E-02 +1.016272E-03 +3.372745E+00 +2.298238E+00 +3.151097E-02 +2.069373E-04 +7.812240E-02 +1.271940E-03 +2.154223E+00 +9.469347E-01 +6.893166E-02 +1.008453E-03 +3.298063E+00 +2.220933E+00 +3.075978E-02 +2.125545E-04 +7.626005E-02 +1.306466E-03 +2.057172E+00 +8.672290E-01 +6.372568E-02 +8.190278E-04 +3.108552E+00 +1.951197E+00 +2.795535E-02 +1.595890E-04 +6.930727E-02 +9.809131E-04 +2.295642E+00 +1.124640E+00 +6.209725E-02 +8.275041E-04 +3.320499E+00 +2.339919E+00 +2.530846E-02 +1.388437E-04 +6.274506E-02 +8.534023E-04 +2.411516E+00 +1.208668E+00 +7.127755E-02 +1.051206E-03 +3.599456E+00 +2.675604E+00 +3.057946E-02 +1.929511E-04 +7.581300E-02 +1.185973E-03 +2.170599E+00 +9.911770E-01 +6.225331E-02 +8.096954E-04 +3.174400E+00 +2.102442E+00 +2.621745E-02 +1.490631E-04 +6.499865E-02 +9.162161E-04 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1021,86 +1021,86 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.316522E+00 -2.302876E+00 -8.987919E-02 -1.676655E-03 -4.716109E+00 -4.596488E+00 -3.654407E-02 -2.855910E-04 -9.060053E-02 -1.755384E-03 -3.091331E+00 -2.117646E+00 -8.528196E-02 -1.564336E-03 -4.492326E+00 -4.405850E+00 -3.513814E-02 -2.665883E-04 -8.711494E-02 -1.638584E-03 -2.649730E+00 -1.444519E+00 -8.510948E-02 -1.506094E-03 -4.117595E+00 -3.501517E+00 -3.810553E-02 -3.052819E-04 -9.447172E-02 -1.876414E-03 -2.875773E+00 -1.758531E+00 -9.127582E-02 -1.780419E-03 -4.328266E+00 -3.989840E+00 -4.045386E-02 -3.513542E-04 -1.002937E-01 -2.159598E-03 -3.102792E+00 -1.949906E+00 -9.153879E-02 -1.691646E-03 -4.578530E+00 -4.235906E+00 -3.913672E-02 -3.094156E-04 -9.702826E-02 -1.901822E-03 -3.238743E+00 -2.146355E+00 -8.902551E-02 -1.593536E-03 -4.683916E+00 -4.438028E+00 -3.660342E-02 -2.683183E-04 -9.074766E-02 -1.649218E-03 -3.006635E+00 -1.887385E+00 -8.716712E-02 -1.586834E-03 -4.383965E+00 -4.008888E+00 -3.688262E-02 -2.862513E-04 -9.143987E-02 -1.759443E-03 -2.749904E+00 -1.550561E+00 -9.244273E-02 -1.748082E-03 -4.241273E+00 -3.669144E+00 -4.208622E-02 -3.633241E-04 -1.043407E-01 -2.233170E-03 +2.374348E+00 +1.146696E+00 +6.443426E-02 +8.746572E-04 +3.428224E+00 +2.405912E+00 +2.629872E-02 +1.523681E-04 +6.520012E-02 +9.365302E-04 +2.464893E+00 +1.229701E+00 +7.050588E-02 +1.022217E-03 +3.660115E+00 +2.719644E+00 +2.971255E-02 +1.859463E-04 +7.366374E-02 +1.142918E-03 +2.086598E+00 +8.776819E-01 +6.304625E-02 +8.239181E-04 +3.124875E+00 +1.968039E+00 +2.731211E-02 +1.609716E-04 +6.771252E-02 +9.894116E-04 +2.314873E+00 +1.083111E+00 +5.761556E-02 +6.762901E-04 +3.205662E+00 +2.074555E+00 +2.215216E-02 +1.044406E-04 +5.491992E-02 +6.419437E-04 +2.313273E+00 +1.119912E+00 +6.126598E-02 +7.845228E-04 +3.266340E+00 +2.226545E+00 +2.455456E-02 +1.271226E-04 +6.087598E-02 +7.813588E-04 +2.283282E+00 +1.100474E+00 +6.665553E-02 +9.193170E-04 +3.364565E+00 +2.364829E+00 +2.834631E-02 +1.672037E-04 +7.027653E-02 +1.027717E-03 +2.186072E+00 +9.712029E-01 +7.000241E-02 +1.019717E-03 +3.374290E+00 +2.313941E+00 +3.125803E-02 +2.124583E-04 +7.749531E-02 +1.305874E-03 +2.250156E+00 +1.052173E+00 +6.400255E-02 +8.818690E-04 +3.268015E+00 +2.245559E+00 +2.679559E-02 +1.634377E-04 +6.643197E-02 +1.004569E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1191,86 +1191,86 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -2.556952E+00 -1.416458E+00 -8.087467E-02 -1.431667E-03 -3.806748E+00 -3.158182E+00 -3.571995E-02 -2.831832E-04 -8.855737E-02 -1.740585E-03 -2.546384E+00 -1.446967E+00 -8.000281E-02 -1.363415E-03 -3.844739E+00 -3.222133E+00 -3.533522E-02 -2.621956E-04 -8.760354E-02 -1.611584E-03 -2.474418E+00 -1.302438E+00 -7.728372E-02 -1.265047E-03 -3.818517E+00 -3.076074E+00 -3.414744E-02 -2.483215E-04 -8.465877E-02 -1.526307E-03 -2.478272E+00 -1.299434E+00 -7.866430E-02 -1.293627E-03 -3.758685E+00 -2.973817E+00 -3.491240E-02 -2.542033E-04 -8.655529E-02 -1.562460E-03 -2.941937E+00 -1.842278E+00 -9.491310E-02 -1.902183E-03 -4.564730E+00 -4.427111E+00 -4.252722E-02 -3.828960E-04 -1.054340E-01 -2.353469E-03 -2.850564E+00 -1.719152E+00 -8.118192E-02 -1.404765E-03 -4.190858E+00 -3.722715E+00 -3.411695E-02 -2.522778E-04 -8.458318E-02 -1.550625E-03 -2.726097E+00 -1.648250E+00 -7.879124E-02 -1.424955E-03 -3.940978E+00 -3.461222E+00 -3.322044E-02 -2.688615E-04 -8.236053E-02 -1.652557E-03 -2.304822E+00 -1.153775E+00 -7.500010E-02 -1.314077E-03 -3.542935E+00 -2.786864E+00 -3.369367E-02 -2.798215E-04 -8.353377E-02 -1.719922E-03 +2.149693E+00 +9.566763E-01 +6.325375E-02 +8.781459E-04 +3.163781E+00 +2.089993E+00 +2.699802E-02 +1.754950E-04 +6.693384E-02 +1.078679E-03 +2.368262E+00 +1.206255E+00 +6.517665E-02 +9.363557E-04 +3.403305E+00 +2.501730E+00 +2.677251E-02 +1.620249E-04 +6.637476E-02 +9.958857E-04 +2.280249E+00 +1.070455E+00 +7.456831E-02 +1.147671E-03 +3.475673E+00 +2.476848E+00 +3.352210E-02 +2.345869E-04 +8.310842E-02 +1.441888E-03 +2.226928E+00 +1.011037E+00 +7.770236E-02 +1.243393E-03 +3.524398E+00 +2.538453E+00 +3.601410E-02 +2.702997E-04 +8.928663E-02 +1.661396E-03 +2.407411E+00 +1.170093E+00 +7.171133E-02 +1.029235E-03 +3.502484E+00 +2.461827E+00 +3.070568E-02 +1.889715E-04 +7.612591E-02 +1.161513E-03 +2.331359E+00 +1.134448E+00 +6.734317E-02 +9.407363E-04 +3.333577E+00 +2.267345E+00 +2.832929E-02 +1.772720E-04 +7.023433E-02 +1.089602E-03 +2.008838E+00 +8.722179E-01 +5.586199E-02 +7.051708E-04 +2.903675E+00 +1.807255E+00 +2.309145E-02 +1.322637E-04 +5.724863E-02 +8.129585E-04 +2.226061E+00 +1.048269E+00 +6.536859E-02 +9.623671E-04 +3.297988E+00 +2.324450E+00 +2.791406E-02 +1.866630E-04 +6.920490E-02 +1.147324E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2892,15 +2892,15 @@ tally 1: 0.000000E+00 0.000000E+00 tally 2: -4.283244E+01 -3.698890E+02 -4.285612E+01 -3.702981E+02 -6.926001E+00 -9.669342E+00 -6.926497E+00 -9.670727E+00 -1.223563E+02 -3.025594E+03 -1.223563E+02 -3.025594E+03 +4.076711E+01 +3.341374E+02 +4.077838E+01 +3.343221E+02 +6.274781E+00 +7.937573E+00 +6.275007E+00 +7.938146E+00 +1.122968E+02 +2.557771E+03 +1.122968E+02 +2.557771E+03 diff --git a/tests/test_mg_tallies/test_mg_tallies.py b/tests/test_mg_tallies/test_mg_tallies.py index c54fb4d32..3048f4a39 100644 --- a/tests/test_mg_tallies/test_mg_tallies.py +++ b/tests/test_mg_tallies/test_mg_tallies.py @@ -27,24 +27,15 @@ class MGTalliesTestHarness(PyAPITestHarness): mat_filter = openmc.Filter(type='material', bins=[1,2,3]) tally1 = openmc.Tally(tally_id=1) - tally1.add_filter(mesh_filter) - tally1.add_score('total') - tally1.add_score('absorption') - tally1.add_score('flux') - tally1.add_score('fission') - tally1.add_score('nu-fission') + tally1.filters = [mesh_filter] + tally1.scores = ['total', 'absorption', 'flux', + 'fission', 'nu-fission'] tally2 = openmc.Tally(tally_id=2) - tally2.add_filter(mat_filter) - tally2.add_filter(energy_filter) - tally2.add_filter(energyout_filter) - tally2.add_score('scatter') - tally2.add_score('nu-scatter') + tally2.filters = [mat_filter, energy_filter, energyout_filter] + tally2.scores = ['scatter', 'nu-scatter'] - self._input_set.tallies = openmc.TalliesFile() - self._input_set.tallies.add_mesh(mesh) - self._input_set.tallies.add_tally(tally1) - self._input_set.tallies.add_tally(tally2) + self._input_set.tallies = openmc.Tallies([tally1, tally2]) super(MGTalliesTestHarness, self)._build_inputs() diff --git a/tests/test_mgxs_library_ce_to_mg/inputs_true.dat b/tests/test_mgxs_library_ce_to_mg/inputs_true.dat new file mode 100644 index 000000000..9633a46a8 --- /dev/null +++ b/tests/test_mgxs_library_ce_to_mg/inputs_true.dat @@ -0,0 +1 @@ +34d5891f6f17c2d4b686b814ba61ba0045bc4289e278b1c3c47dbba59b83837fcfe15f2b8d58e7a2b07627b73d51e40348d70e9ed36dbb7cc94468d61c068c4c \ No newline at end of file diff --git a/tests/test_mgxs_library_ce_to_mg/results_true.dat b/tests/test_mgxs_library_ce_to_mg/results_true.dat new file mode 100644 index 000000000..16441af8c --- /dev/null +++ b/tests/test_mgxs_library_ce_to_mg/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +1.094839E+00 1.203524E-02 diff --git a/tests/test_mgxs_library_ce_to_mg/test_mgxs_library_ce_to_mg.py b/tests/test_mgxs_library_ce_to_mg/test_mgxs_library_ce_to_mg.py new file mode 100644 index 000000000..0f7cba4a8 --- /dev/null +++ b/tests/test_mgxs_library_ce_to_mg/test_mgxs_library_ce_to_mg.py @@ -0,0 +1,94 @@ +#!/usr/bin/env python + +import os +import sys +import glob +import hashlib +sys.path.insert(0, os.pardir) +from testing_harness import PyAPITestHarness +from input_set import PinCellInputSet +import openmc +import openmc.mgxs + + +class MGXSTestHarness(PyAPITestHarness): + def _build_inputs(self): + # Set the input set to use the pincell model + self._input_set = PinCellInputSet() + + # Generate inputs using parent class routine + super(MGXSTestHarness, self)._build_inputs() + + # Initialize a two-group structure + energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, + 20.]) + + # Initialize MGXS Library for a few cross section types + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) + self.mgxs_lib.by_nuclide = False + self.mgxs_lib.mgxs_types = ['total', 'absorption', 'nu-fission matrix', + 'nu-scatter matrix', 'multiplicity matrix'] + self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.correction = None + self.mgxs_lib.legendre_order = 3 + self.mgxs_lib.domain_type = 'material' + self.mgxs_lib.build_library() + + # Initialize a tallies file + self._input_set.tallies = openmc.Tallies() + self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) + self._input_set.tallies.export_to_xml() + + def _run_openmc(self): + # Initial run + if self._opts.mpi_exec is not None: + returncode = openmc.run(mpi_procs=self._opts.mpi_np, + openmc_exec=self._opts.exe, + mpi_exec=self._opts.mpi_exec) + + else: + returncode = openmc.run(openmc_exec=self._opts.exe) + + assert returncode == 0, 'CE OpenMC calculation did not exit' \ + 'successfully.' + + # Build MG Inputs + # Get data needed to execute Library calculations. + statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] + sp = openmc.StatePoint(statepoint) + self.mgxs_lib.load_from_statepoint(sp) + self._input_set.mgxs_file, self._input_set.materials, \ + self._input_set.geometry = self.mgxs_lib.create_mg_mode() + + # Modify settings so we can run in MG mode + self._input_set.settings.cross_sections = './mgxs.xml' + self._input_set.settings.energy_mode = 'multi-group' + + # Write modified input files + self._input_set.settings.export_to_xml() + self._input_set.geometry.export_to_xml() + self._input_set.materials.export_to_xml() + self._input_set.mgxs_file.export_to_xml() + # Dont need tallies.xml, so remove the file + if os.path.exists('./tallies.xml'): + os.remove('./tallies.xml') + + # Re-run MG mode. + if self._opts.mpi_exec is not None: + returncode = openmc.run(mpi_procs=self._opts.mpi_np, + openmc_exec=self._opts.exe, + mpi_exec=self._opts.mpi_exec) + + else: + returncode = openmc.run(openmc_exec=self._opts.exe) + + def _cleanup(self): + super(MGXSTestHarness, self)._cleanup() + f = os.path.join(os.getcwd(), 'mgxs.xml') + if os.path.exists(f): + os.remove(f) + + +if __name__ == '__main__': + harness = MGXSTestHarness('statepoint.10.*', False) + harness.main() diff --git a/tests/test_mgxs_library_condense/inputs_true.dat b/tests/test_mgxs_library_condense/inputs_true.dat index b94f64122..79ca0ec66 100644 --- a/tests/test_mgxs_library_condense/inputs_true.dat +++ b/tests/test_mgxs_library_condense/inputs_true.dat @@ -1 +1 @@ -53b1740921b71e4ead909ab9e4c25f7d43990fe7d7051fde6f66c39c0a6082177385640244010e1b9dbeaf5f34adf1627e9603088af729fadd6b589c19102edc \ No newline at end of file +317a63a9dd3bfd84e969667b00f46018e56c04c356461a75103f63569e6b70c84d0da7f5e611faaf1b2631330b05ab4346223d3d843018ce0ce8876671a450c0 \ No newline at end of file diff --git a/tests/test_mgxs_library_condense/results_true.dat b/tests/test_mgxs_library_condense/results_true.dat index 45891fc30..13c277b15 100644 --- a/tests/test_mgxs_library_condense/results_true.dat +++ b/tests/test_mgxs_library_condense/results_true.dat @@ -1,49 +1,108 @@ material group in nuclide mean std. dev. -0 1 1 total 0.419289 0.01638 material group in nuclide mean std. dev. -0 1 1 total 0.07774 0.003273 material group in group out nuclide mean std. dev. -0 1 1 1 total 0.352665 0.015654 material group out nuclide mean std. dev. -0 1 1 total 1 0.119622 material group in nuclide mean std. dev. -0 2 1 total 0.247316 0.009562 material group in nuclide mean std. dev. -0 2 1 total 0 0 material group in group out nuclide mean std. dev. -0 2 1 1 total 0.244838 0.009996 material group out nuclide mean std. dev. -0 2 1 total 0 0 material group in nuclide mean std. dev. -0 3 1 total 0.409938 0.042262 material group in nuclide mean std. dev. -0 3 1 total 0 0 material group in group out nuclide mean std. dev. -0 3 1 1 total 0.403354 0.041386 material group out nuclide mean std. dev. -0 3 1 total 0 0 material group in nuclide mean std. dev. -0 4 1 total 0.344007 0.05352 material group in nuclide mean std. dev. -0 4 1 total 0 0 material group in group out nuclide mean std. dev. -0 4 1 1 total 0.340438 0.052067 material group out nuclide mean std. dev. -0 4 1 total 0 0 material group in nuclide mean std. dev. -0 5 1 total 0 0 material group in nuclide mean std. dev. -0 5 1 total 0 0 material group in group out nuclide mean std. dev. -0 5 1 1 total 0 0 material group out nuclide mean std. dev. -0 5 1 total 0 0 material group in nuclide mean std. dev. -0 6 1 total 0 0 material group in nuclide mean std. dev. -0 6 1 total 0 0 material group in group out nuclide mean std. dev. -0 6 1 1 total 0 0 material group out nuclide mean std. dev. -0 6 1 total 0 0 material group in nuclide mean std. dev. -0 7 1 total 0 0 material group in nuclide mean std. dev. -0 7 1 total 0 0 material group in group out nuclide mean std. dev. -0 7 1 1 total 0 0 material group out nuclide mean std. dev. -0 7 1 total 0 0 material group in nuclide mean std. dev. -0 8 1 total 0 0 material group in nuclide mean std. dev. -0 8 1 total 0 0 material group in group out nuclide mean std. dev. -0 8 1 1 total 0 0 material group out nuclide mean std. dev. -0 8 1 total 0 0 material group in nuclide mean std. dev. -0 9 1 total 0.751873 0.559701 material group in nuclide mean std. dev. -0 9 1 total 0 0 material group in group out nuclide mean std. dev. -0 9 1 1 total 0.695491 0.50757 material group out nuclide mean std. dev. -0 9 1 total 0 0 material group in nuclide mean std. dev. -0 10 1 total 0 0 material group in nuclide mean std. dev. -0 10 1 total 0 0 material group in group out nuclide mean std. dev. -0 10 1 1 total 0 0 material group out nuclide mean std. dev. -0 10 1 total 0 0 material group in nuclide mean std. dev. -0 11 1 total 0.457329 0.403578 material group in nuclide mean std. dev. -0 11 1 total 0 0 material group in group out nuclide mean std. dev. -0 11 1 1 total 0.446737 0.392775 material group out nuclide mean std. dev. -0 11 1 total 0 0 material group in nuclide mean std. dev. -0 12 1 total 0.574978 0.38864 material group in nuclide mean std. dev. -0 12 1 total 0 0 material group in group out nuclide mean std. dev. -0 12 1 1 total 0.559478 0.377512 material group out nuclide mean std. dev. -0 12 1 total 0 0 \ No newline at end of file +0 10000 1 total 0.453624 0.021053 + material group in nuclide mean std. dev. +0 10000 1 total 0.400852 0.022858 + material group in nuclide mean std. dev. +0 10000 1 total 0.400852 0.022858 + material group in nuclide mean std. dev. +0 10000 1 total 0.064903 0.004313 + material group in nuclide mean std. dev. +0 10000 1 total 0.028048 0.00458 + material group in nuclide mean std. dev. +0 10000 1 total 0.036855 0.002622 + material group in nuclide mean std. dev. +0 10000 1 total 0.090649 0.00641 + material group in nuclide mean std. dev. +0 10000 1 total 7.137955 0.507364 + material group in nuclide mean std. dev. +0 10000 1 total 0.388721 0.01783 + material group in nuclide mean std. dev. +0 10000 1 total 0.389304 0.023076 + material group in group out nuclide moment mean std. dev. +0 10000 1 1 total P0 0.389304 0.023146 +1 10000 1 1 total P1 0.046224 0.005907 +2 10000 1 1 total P2 0.017984 0.002883 +3 10000 1 1 total P3 0.006628 0.002457 + material group in group out nuclide moment mean std. dev. +0 10000 1 1 total P0 0.389304 0.023146 +1 10000 1 1 total P1 0.046224 0.005907 +2 10000 1 1 total P2 0.017984 0.002883 +3 10000 1 1 total P3 0.006628 0.002457 + material group in group out nuclide mean std. dev. +0 10000 1 1 total 1.0 0.066111 + material group in group out nuclide mean std. dev. +0 10000 1 1 total 0.085835 0.005592 + material group out nuclide mean std. dev. +0 10000 1 total 1.0 0.046071 + material group in nuclide mean std. dev. +0 10001 1 total 0.311594 0.013793 + material group in nuclide mean std. dev. +0 10001 1 total 0.279255 0.02919 + material group in nuclide mean std. dev. +0 10001 1 total 0.279255 0.02919 + material group in nuclide mean std. dev. +0 10001 1 total 0.00221 0.000286 + material group in nuclide mean std. dev. +0 10001 1 total 0.00221 0.000286 + material group in nuclide mean std. dev. +0 10001 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10001 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10001 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10001 1 total 0.309384 0.013551 + material group in nuclide mean std. dev. +0 10001 1 total 0.307987 0.029308 + material group in group out nuclide moment mean std. dev. +0 10001 1 1 total P0 0.307987 0.029308 +1 10001 1 1 total P1 0.030617 0.007464 +2 10001 1 1 total P2 0.018911 0.004323 +3 10001 1 1 total P3 0.006235 0.003338 + material group in group out nuclide moment mean std. dev. +0 10001 1 1 total P0 0.307987 0.029308 +1 10001 1 1 total P1 0.030617 0.007464 +2 10001 1 1 total P2 0.018911 0.004323 +3 10001 1 1 total P3 0.006235 0.003338 + material group in group out nuclide mean std. dev. +0 10001 1 1 total 1.0 0.095039 + material group in group out nuclide mean std. dev. +0 10001 1 1 total 0.0 0.0 + material group out nuclide mean std. dev. +0 10001 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10002 1 total 0.904999 0.043964 + material group in nuclide mean std. dev. +0 10002 1 total 0.499184 0.040914 + material group in nuclide mean std. dev. +0 10002 1 total 0.499184 0.040914 + material group in nuclide mean std. dev. +0 10002 1 total 0.00606 0.000555 + material group in nuclide mean std. dev. +0 10002 1 total 0.00606 0.000555 + material group in nuclide mean std. dev. +0 10002 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10002 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10002 1 total 0.0 0.0 + material group in nuclide mean std. dev. +0 10002 1 total 0.898938 0.043493 + material group in nuclide mean std. dev. +0 10002 1 total 0.903415 0.043959 + material group in group out nuclide moment mean std. dev. +0 10002 1 1 total P0 0.903415 0.043586 +1 10002 1 1 total P1 0.410417 0.015877 +2 10002 1 1 total P2 0.143301 0.007187 +3 10002 1 1 total P3 0.008739 0.003571 + material group in group out nuclide moment mean std. dev. +0 10002 1 1 total P0 0.903415 0.043586 +1 10002 1 1 total P1 0.410417 0.015877 +2 10002 1 1 total P2 0.143301 0.007187 +3 10002 1 1 total P3 0.008739 0.003571 + material group in group out nuclide mean std. dev. +0 10002 1 1 total 1.0 0.056867 + material group in group out nuclide mean std. dev. +0 10002 1 1 total 0.0 0.0 + material group out nuclide mean std. dev. +0 10002 1 total 0.0 0.0 diff --git a/tests/test_mgxs_library_condense/test_mgxs_library_condense.py b/tests/test_mgxs_library_condense/test_mgxs_library_condense.py index 82ce3acab..5571b59f2 100644 --- a/tests/test_mgxs_library_condense/test_mgxs_library_condense.py +++ b/tests/test_mgxs_library_condense/test_mgxs_library_condense.py @@ -6,33 +6,35 @@ import glob import hashlib sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness +from input_set import PinCellInputSet import openmc import openmc.mgxs class MGXSTestHarness(PyAPITestHarness): def _build_inputs(self): - - # The openmc.mgxs module needs a summary.h5 file - self._input_set.settings.output = {'summary': True} + # Set the input set to use the pincell model + self._input_set = PinCellInputSet() # Generate inputs using parent class routine super(MGXSTestHarness, self)._build_inputs() # Initialize a two-group structure - energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, 20.]) + energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, + 20.]) # Initialize MGXS Library for a few cross section types - self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry) + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) self.mgxs_lib.by_nuclide = False - self.mgxs_lib.mgxs_types = ['transport', 'nu-fission', - 'nu-scatter matrix', 'chi'] + # Test all MGXS types + self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.legendre_order = 3 self.mgxs_lib.domain_type = 'material' self.mgxs_lib.build_library() # Initialize a tallies file - self._input_set.tallies = openmc.TalliesFile() + self._input_set.tallies = openmc.Tallies() self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) self._input_set.tallies.export_to_xml() @@ -43,11 +45,6 @@ class MGXSTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the MGXS library from the statepoint self.mgxs_lib.load_from_statepoint(sp) @@ -61,7 +58,7 @@ class MGXSTestHarness(PyAPITestHarness): for mgxs_type in condense_lib.mgxs_types: mgxs = condense_lib.get_mgxs(domain, mgxs_type) df = mgxs.get_pandas_dataframe() - outstr += df.to_string() + outstr += df.to_string() + '\n' # Hash the results if necessary if hash_output: diff --git a/tests/test_mgxs_library_distribcell/inputs_true.dat b/tests/test_mgxs_library_distribcell/inputs_true.dat index 04e56658f..dc67b7c56 100644 --- a/tests/test_mgxs_library_distribcell/inputs_true.dat +++ b/tests/test_mgxs_library_distribcell/inputs_true.dat @@ -1 +1 @@ -224a9e84e87c8a21385326d34ef27c046107d4a2ace6ee85d7a36142a3726e12532e2fc1a318ab707437e0b306a81c6d2b80c531d4c3210d4162242e6265ba70 \ No newline at end of file +88849ac150f9c389e67de96356dfceb0bde08643f68ca25699e67d263995b95893d7340a2b08b2f0f5075fc5020f73553c5287ec6c56ace2f35ce0214961e123 \ No newline at end of file diff --git a/tests/test_mgxs_library_distribcell/results_true.dat b/tests/test_mgxs_library_distribcell/results_true.dat index ad9b949de..5000d60c3 100644 --- a/tests/test_mgxs_library_distribcell/results_true.dat +++ b/tests/test_mgxs_library_distribcell/results_true.dat @@ -1,5 +1,36 @@ avg(distribcell) group in nuclide mean std. dev. -0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.720213 1.424323 avg(distribcell) group in nuclide mean std. dev. -0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0 0 avg(distribcell) group in group out nuclide mean std. dev. -0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total 0.70466 1.403916 avg(distribcell) group out nuclide mean std. dev. -0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0 0 \ No newline at end of file +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 1.145934 0.553822 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.718919 0.520644 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.718919 0.520644 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.019762 0.010629 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.019762 0.010629 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.0 0.0 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.0 0.0 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.0 0.0 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 1.126172 0.54344 + avg(distribcell) group in nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 1.142547 0.570131 + avg(distribcell) group in group out nuclide moment mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P0 1.142547 0.570131 +1 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P1 0.447381 0.216322 +2 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P2 0.141202 0.066504 +3 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P3 0.039228 0.024621 + avg(distribcell) group in group out nuclide moment mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P0 1.142547 0.570131 +1 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P1 0.447381 0.216322 +2 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P2 0.141202 0.066504 +3 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total P3 0.039228 0.024621 + avg(distribcell) group in group out nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total 1.0 0.529717 + avg(distribcell) group in group out nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 1 total 0.0 0.0 + avg(distribcell) group out nuclide mean std. dev. +0 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 1 total 0.0 0.0 diff --git a/tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py b/tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py index 1de21a603..30593e54b 100644 --- a/tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py +++ b/tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py @@ -12,10 +12,6 @@ import openmc.mgxs class MGXSTestHarness(PyAPITestHarness): def _build_inputs(self): - - # The openmc.mgxs module needs a summary.h5 file - self._input_set.settings.output = {'summary': True} - # Generate inputs using parent class routine super(MGXSTestHarness, self)._build_inputs() @@ -24,18 +20,19 @@ class MGXSTestHarness(PyAPITestHarness): # Initialize MGXS Library for a few cross section types # for one material-filled cell in the geometry - self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry) + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) self.mgxs_lib.by_nuclide = False - self.mgxs_lib.mgxs_types = ['transport', 'nu-fission', - 'nu-scatter matrix', 'chi'] + # Test all MGXS types + self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.legendre_order = 3 self.mgxs_lib.domain_type = 'distribcell' material_cells = self.mgxs_lib.openmc_geometry.get_all_material_cells() self.mgxs_lib.domains = [material_cells[-1]] self.mgxs_lib.build_library() # Initialize a tallies file - self._input_set.tallies = openmc.TalliesFile() + self._input_set.tallies = openmc.Tallies() self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) self._input_set.tallies.export_to_xml() @@ -46,11 +43,6 @@ class MGXSTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the MGXS library from the statepoint self.mgxs_lib.load_from_statepoint(sp) @@ -63,7 +55,7 @@ class MGXSTestHarness(PyAPITestHarness): for mgxs_type in avg_lib.mgxs_types: mgxs = avg_lib.get_mgxs(domain, mgxs_type) df = mgxs.get_pandas_dataframe() - outstr += df.to_string() + outstr += df.to_string() + '\n' # Hash the results if necessary if hash_output: diff --git a/tests/test_mgxs_library_hdf5/inputs_true.dat b/tests/test_mgxs_library_hdf5/inputs_true.dat index b94f64122..79ca0ec66 100644 --- a/tests/test_mgxs_library_hdf5/inputs_true.dat +++ b/tests/test_mgxs_library_hdf5/inputs_true.dat @@ -1 +1 @@ -53b1740921b71e4ead909ab9e4c25f7d43990fe7d7051fde6f66c39c0a6082177385640244010e1b9dbeaf5f34adf1627e9603088af729fadd6b589c19102edc \ No newline at end of file +317a63a9dd3bfd84e969667b00f46018e56c04c356461a75103f63569e6b70c84d0da7f5e611faaf1b2631330b05ab4346223d3d843018ce0ce8876671a450c0 \ No newline at end of file diff --git a/tests/test_mgxs_library_hdf5/results_true.dat b/tests/test_mgxs_library_hdf5/results_true.dat index eec581046..7391b2e42 100644 --- a/tests/test_mgxs_library_hdf5/results_true.dat +++ b/tests/test_mgxs_library_hdf5/results_true.dat @@ -1,168 +1,195 @@ -domain=1 type=transport -[ 0.38437891 0.81208747] -[ 0.01648997 0.07418959] -domain=1 type=nu-fission -[ 0.02127008 0.69604034] -[ 0.0008939 0.05345764] -domain=1 type=nu-scatter matrix -[[ 3.49923892e-01 1.73140769e-04] - [ 1.94810926e-03 3.79607212e-01]] -[[ 0.01664928 0.0001732 ] - [ 0.00195193 0.04007819]] -domain=1 type=chi +domain=10000 type=total +[ 0.41482549 0.66016992] +[ 0.02279291 0.04751893] +domain=10000 type=transport +[ 0.35685964 0.64764766] +[ 0.0254936 0.02370374] +domain=10000 type=nu-transport +[ 0.35685964 0.64764766] +[ 0.0254936 0.02370374] +domain=10000 type=absorption +[ 0.02740784 0.26451074] +[ 0.0026925 0.02336708] +domain=10000 type=capture +[ 0.01984455 0.07171935] +[ 0.0026433 0.02520786] +domain=10000 type=fission +[ 0.00756329 0.19279139] +[ 0.00050848 0.01710592] +domain=10000 type=nu-fission +[ 0.01943174 0.46977478] +[ 0.00132298 0.041682 ] +domain=10000 type=kappa-fission +[ 1.47456982 37.28689641] +[ 0.09923532 3.30837772] +domain=10000 type=scatter +[ 0.38741765 0.39565918] +[ 0.02062573 0.02512506] +domain=10000 type=nu-scatter +[ 0.38518839 0.4123894 ] +[ 0.02694562 0.01542528] +domain=10000 type=scatter matrix +[[[ 3.84199458e-01 5.18702843e-02 2.00688453e-02 9.47771571e-03] + [ 9.88930393e-04 -2.07234596e-04 -1.03366181e-04 2.34290623e-04]] + + [[ 9.24639909e-04 -7.67704968e-04 4.93788872e-04 -1.71497229e-04] + [ 4.11464759e-01 1.64817280e-02 6.37149049e-03 -1.04991221e-02]]] +[[[ 0.02700101 0.00698255 0.0028465 0.00223352] + [ 0.00048242 0.00014901 0.00018432 0.00012817]] + + [[ 0.00092488 0.00076791 0.00049392 0.00017154] + [ 0.01524494 0.00450173 0.01055075 0.01043819]]] +domain=10000 type=nu-scatter matrix +[[[ 3.84199458e-01 5.18702843e-02 2.00688453e-02 9.47771571e-03] + [ 9.88930393e-04 -2.07234596e-04 -1.03366181e-04 2.34290623e-04]] + + [[ 9.24639909e-04 -7.67704968e-04 4.93788872e-04 -1.71497229e-04] + [ 4.11464759e-01 1.64817280e-02 6.37149049e-03 -1.04991221e-02]]] +[[[ 0.02700101 0.00698255 0.0028465 0.00223352] + [ 0.00048242 0.00014901 0.00018432 0.00012817]] + + [[ 0.00092488 0.00076791 0.00049392 0.00017154] + [ 0.01524494 0.00450173 0.01055075 0.01043819]]] +domain=10000 type=multiplicity matrix +[[ 1. 1.] + [ 1. 1.]] +[[ 0.07851646 0.68718427] + [ 1.41421356 0.04113035]] +domain=10000 type=nu-fission matrix +[[ 0.02014243 0. ] + [ 0.45436647 0. ]] +[[ 0.00314909 0. ] + [ 0.02742551 0. ]] +domain=10000 type=chi [ 1. 0.] -[ 0.11962178 0. ] -domain=2 type=transport -[ 0.24504295 0.26645769] -[ 0.00882749 0.05220872] -domain=2 type=nu-fission +[ 0.04607052 0. ] +domain=10001 type=total +[ 0.31373767 0.3008214 ] +[ 0.0155819 0.02805245] +domain=10001 type=transport +[ 0.27322787 0.31237484] +[ 0.03311537 0.04960583] +domain=10001 type=nu-transport +[ 0.27322787 0.31237484] +[ 0.03311537 0.04960583] +domain=10001 type=absorption +[ 0.00157499 0.00540038] +[ 0.00032255 0.00061814] +domain=10001 type=capture +[ 0.00157499 0.00540038] +[ 0.00032255 0.00061814] +domain=10001 type=fission [ 0. 0.] [ 0. 0.] -domain=2 type=nu-scatter matrix -[[ 0.24365718 0. ] - [ 0. 0.25478661]] -[[ 0.00908307 0. ] - [ 0. 0.05556256]] -domain=2 type=chi +domain=10001 type=nu-fission [ 0. 0.] [ 0. 0.] -domain=3 type=transport -[ 0.28227749 1.42731974] -[ 0.03724175 0.24712746] -domain=3 type=nu-fission +domain=10001 type=kappa-fission [ 0. 0.] [ 0. 0.] -domain=3 type=nu-scatter matrix -[[ 0.25396726 0.02727268] - [ 0. 1.37652669]] -[[ 0.03617307 0.00180698] - [ 0. 0.2402569 ]] -domain=3 type=chi -[ 0. 0.] -[ 0. 0.] -domain=4 type=transport -[ 0.25572316 1.17976682] -[ 0.05191655 0.22938034] -domain=4 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=4 type=nu-scatter matrix -[[ 0.23297756 0.02228141] - [ 0. 1.14680862]] -[[ 0.04977114 0.00262525] - [ 0. 0.22219839]] -domain=4 type=chi -[ 0. 0.] -[ 0. 0.] -domain=5 type=transport -[ 0. 0.] -[ 0. 0.] -domain=5 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=5 type=nu-scatter matrix +domain=10001 type=scatter +[ 0.31216268 0.29542102] +[ 0.01532192 0.02744549] +domain=10001 type=nu-scatter +[ 0.31012074 0.29626427] +[ 0.03378811 0.04379223] +domain=10001 type=scatter matrix +[[[ 0.31012074 0.03822959 0.02074494 0.0079643 ] + [ 0. 0. 0. 0. ]] + + [[ 0. 0. 0. 0. ] + [ 0.29626427 -0.01121364 0.00883657 -0.00327007]]] +[[[ 0.03378811 0.008484 0.00469561 0.00373162] + [ 0. 0. 0. 0. ]] + + [[ 0. 0. 0. 0. ] + [ 0.04379223 0.01618037 0.01150396 0.00732885]]] +domain=10001 type=nu-scatter matrix +[[[ 0.31012074 0.03822959 0.02074494 0.0079643 ] + [ 0. 0. 0. 0. ]] + + [[ 0. 0. 0. 0. ] + [ 0.29626427 -0.01121364 0.00883657 -0.00327007]]] +[[[ 0.03378811 0.008484 0.00469561 0.00373162] + [ 0. 0. 0. 0. ]] + + [[ 0. 0. 0. 0. ] + [ 0.04379223 0.01618037 0.01150396 0.00732885]]] +domain=10001 type=multiplicity matrix +[[ 1. 0.] + [ 0. 1.]] +[[ 0.1087787 0. ] + [ 0. 0.14242717]] +domain=10001 type=nu-fission matrix [[ 0. 0.] [ 0. 0.]] [[ 0. 0.] [ 0. 0.]] -domain=5 type=chi +domain=10001 type=chi [ 0. 0.] [ 0. 0.] -domain=6 type=transport +domain=10002 type=total +[ 0.66457226 2.05238401] +[ 0.03121475 0.22434291] +domain=10002 type=transport +[ 0.29056526 1.51643801] +[ 0.02385185 0.23519727] +domain=10002 type=nu-transport +[ 0.29056526 1.51643801] +[ 0.02385185 0.23519727] +domain=10002 type=absorption +[ 0.0006904 0.03168726] +[ 4.41475687e-05 3.74655858e-03] +domain=10002 type=capture +[ 0.0006904 0.03168726] +[ 4.41475687e-05 3.74655858e-03] +domain=10002 type=fission [ 0. 0.] [ 0. 0.] -domain=6 type=nu-fission +domain=10002 type=nu-fission [ 0. 0.] [ 0. 0.] -domain=6 type=nu-scatter matrix +domain=10002 type=kappa-fission +[ 0. 0.] +[ 0. 0.] +domain=10002 type=scatter +[ 0.66388186 2.02069676] +[ 0.03117268 0.22060445] +domain=10002 type=nu-scatter +[ 0.6712692 2.03538833] +[ 0.02618637 0.25806033] +domain=10002 type=scatter matrix +[[[ 6.39901485e-01 3.81167449e-01 1.52391898e-01 9.14802229e-03] + [ 3.13677198e-02 8.75772321e-03 -2.56790106e-03 -3.78480288e-03]] + + [[ 4.43343134e-04 3.99960414e-04 3.19562707e-04 2.13846969e-04] + [ 2.03494499e+00 5.09940513e-01 1.11174609e-01 2.49884357e-02]]] +[[[ 2.47091228e-02 1.62432649e-02 8.15627770e-03 3.88856214e-03] + [ 1.72811290e-03 9.25670501e-04 1.01398475e-03 8.17075571e-04]] + + [[ 4.44850393e-04 4.01320183e-04 3.20649143e-04 2.14573997e-04] + [ 2.57799889e-01 5.12359063e-02 1.30198170e-02 8.31235256e-03]]] +domain=10002 type=nu-scatter matrix +[[[ 6.39901485e-01 3.81167449e-01 1.52391898e-01 9.14802229e-03] + [ 3.13677198e-02 8.75772321e-03 -2.56790106e-03 -3.78480288e-03]] + + [[ 4.43343134e-04 3.99960414e-04 3.19562707e-04 2.13846969e-04] + [ 2.03494499e+00 5.09940513e-01 1.11174609e-01 2.49884357e-02]]] +[[[ 2.47091228e-02 1.62432649e-02 8.15627770e-03 3.88856214e-03] + [ 1.72811290e-03 9.25670501e-04 1.01398475e-03 8.17075571e-04]] + + [[ 4.44850393e-04 4.01320183e-04 3.20649143e-04 2.14573997e-04] + [ 2.57799889e-01 5.12359063e-02 1.30198170e-02 8.31235256e-03]]] +domain=10002 type=multiplicity matrix +[[ 1. 1.] + [ 1. 1.]] +[[ 0.03860919 0.06766735] + [ 1.41421356 0.13592921]] +domain=10002 type=nu-fission matrix [[ 0. 0.] [ 0. 0.]] [[ 0. 0.] [ 0. 0.]] -domain=6 type=chi -[ 0. 0.] -[ 0. 0.] -domain=7 type=transport -[ 0. 0.] -[ 0. 0.] -domain=7 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=7 type=nu-scatter matrix -[[ 0. 0.] - [ 0. 0.]] -[[ 0. 0.] - [ 0. 0.]] -domain=7 type=chi -[ 0. 0.] -[ 0. 0.] -domain=8 type=transport -[ 0. 0.] -[ 0. 0.] -domain=8 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=8 type=nu-scatter matrix -[[ 0. 0.] - [ 0. 0.]] -[[ 0. 0.] - [ 0. 0.]] -domain=8 type=chi -[ 0. 0.] -[ 0. 0.] -domain=9 type=transport -[ 0.50403601 1.68709544] -[ 0.37962374 2.53662237] -domain=9 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=9 type=nu-scatter matrix -[[ 0.50403601 0. ] - [ 0. 1.41795483]] -[[ 0.37962374 0. ] - [ 0. 2.15802716]] -domain=9 type=chi -[ 0. 0.] -[ 0. 0.] -domain=10 type=transport -[ 0. 0.] -[ 0. 0.] -domain=10 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=10 type=nu-scatter matrix -[[ 0. 0.] - [ 0. 0.]] -[[ 0. 0.] - [ 0. 0.]] -domain=10 type=chi -[ 0. 0.] -[ 0. 0.] -domain=11 type=transport -[ 0.30282618 1.00614519] -[ 0.40131081 1.09163785] -domain=11 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=11 type=nu-scatter matrix -[[ 0.27567871 0.02714747] - [ 0. 0.95792921]] -[[ 0.38567601 0.02000859] - [ 0. 1.05195936]] -domain=11 type=chi -[ 0. 0.] -[ 0. 0.] -domain=12 type=transport -[ 0.25593293 1.11334475] -[ 0.26842571 0.98867569] -domain=12 type=nu-fission -[ 0. 0.] -[ 0. 0.] -domain=12 type=nu-scatter matrix -[[ 0.22631045 0.02962248] - [ 0. 1.07168976]] -[[ 0.25487194 0.0177599 ] - [ 0. 0.95829029]] -domain=12 type=chi +domain=10002 type=chi [ 0. 0.] [ 0. 0.] diff --git a/tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py b/tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py index 642073104..000a1f8cb 100644 --- a/tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py +++ b/tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py @@ -7,33 +7,35 @@ import hashlib import h5py sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness +from input_set import PinCellInputSet import openmc import openmc.mgxs class MGXSTestHarness(PyAPITestHarness): def _build_inputs(self): - - # The openmc.mgxs module needs a summary.h5 file - self._input_set.settings.output = {'summary': True} + # Set the input set to use the pincell model + self._input_set = PinCellInputSet() # Generate inputs using parent class routine super(MGXSTestHarness, self)._build_inputs() # Initialize a two-group structure - energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, 20.]) + energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, + 20.]) # Initialize MGXS Library for a few cross section types - self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry) + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) self.mgxs_lib.by_nuclide = False - self.mgxs_lib.mgxs_types = ['transport', 'nu-fission', - 'nu-scatter matrix', 'chi'] + # Test all MGXS types + self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.legendre_order = 3 self.mgxs_lib.domain_type = 'material' self.mgxs_lib.build_library() # Initialize a tallies file - self._input_set.tallies = openmc.TalliesFile() + self._input_set.tallies = openmc.Tallies() self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) self._input_set.tallies.export_to_xml() @@ -44,14 +46,9 @@ class MGXSTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the MGXS library from the statepoint self.mgxs_lib.load_from_statepoint(sp) - + # Export the MGXS Library to an HDF5 file self.mgxs_lib.build_hdf5_store(directory='.') @@ -67,7 +64,7 @@ class MGXSTestHarness(PyAPITestHarness): outstr += str(f[key][...]) + '\n' key = 'material/{0}/{1}/std. dev.'.format(domain.id, mgxs_type) outstr += str(f[key][...]) + '\n' - + # Close the MGXS HDF5 file f.close() @@ -79,7 +76,6 @@ class MGXSTestHarness(PyAPITestHarness): return outstr - def _cleanup(self): super(MGXSTestHarness, self)._cleanup() f = os.path.join(os.getcwd(), 'tallies.xml') diff --git a/tests/test_mgxs_library_no_nuclides/inputs_true.dat b/tests/test_mgxs_library_no_nuclides/inputs_true.dat index b94f64122..79ca0ec66 100644 --- a/tests/test_mgxs_library_no_nuclides/inputs_true.dat +++ b/tests/test_mgxs_library_no_nuclides/inputs_true.dat @@ -1 +1 @@ -53b1740921b71e4ead909ab9e4c25f7d43990fe7d7051fde6f66c39c0a6082177385640244010e1b9dbeaf5f34adf1627e9603088af729fadd6b589c19102edc \ No newline at end of file +317a63a9dd3bfd84e969667b00f46018e56c04c356461a75103f63569e6b70c84d0da7f5e611faaf1b2631330b05ab4346223d3d843018ce0ce8876671a450c0 \ No newline at end of file diff --git a/tests/test_mgxs_library_no_nuclides/results_true.dat b/tests/test_mgxs_library_no_nuclides/results_true.dat index 761851268..599cee6c4 100644 --- a/tests/test_mgxs_library_no_nuclides/results_true.dat +++ b/tests/test_mgxs_library_no_nuclides/results_true.dat @@ -1,121 +1,231 @@ material group in nuclide mean std. dev. -1 1 1 total 0.384379 0.01649 -0 1 2 total 0.812087 0.07419 material group in nuclide mean std. dev. -1 1 1 total 0.02127 0.000894 -0 1 2 total 0.69604 0.053458 material group in group out nuclide mean std. dev. -3 1 1 1 total 0.349924 0.016649 -2 1 1 2 total 0.000173 0.000173 -1 1 2 1 total 0.001948 0.001952 -0 1 2 2 total 0.379607 0.040078 material group out nuclide mean std. dev. -1 1 1 total 1 0.119622 -0 1 2 total 0 0.000000 material group in nuclide mean std. dev. -1 2 1 total 0.245043 0.008827 -0 2 2 total 0.266458 0.052209 material group in nuclide mean std. dev. -1 2 1 total 0 0 -0 2 2 total 0 0 material group in group out nuclide mean std. dev. -3 2 1 1 total 0.243657 0.009083 -2 2 1 2 total 0.000000 0.000000 -1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.254787 0.055563 material group out nuclide mean std. dev. -1 2 1 total 0 0 -0 2 2 total 0 0 material group in nuclide mean std. dev. -1 3 1 total 0.282277 0.037242 -0 3 2 total 1.427320 0.247127 material group in nuclide mean std. dev. -1 3 1 total 0 0 -0 3 2 total 0 0 material group in group out nuclide mean std. dev. -3 3 1 1 total 0.253967 0.036173 -2 3 1 2 total 0.027273 0.001807 -1 3 2 1 total 0.000000 0.000000 -0 3 2 2 total 1.376527 0.240257 material group out nuclide mean std. dev. -1 3 1 total 0 0 -0 3 2 total 0 0 material group in nuclide mean std. dev. -1 4 1 total 0.255723 0.051917 -0 4 2 total 1.179767 0.229380 material group in nuclide mean std. dev. -1 4 1 total 0 0 -0 4 2 total 0 0 material group in group out nuclide mean std. dev. -3 4 1 1 total 0.232978 0.049771 -2 4 1 2 total 0.022281 0.002625 -1 4 2 1 total 0.000000 0.000000 -0 4 2 2 total 1.146809 0.222198 material group out nuclide mean std. dev. -1 4 1 total 0 0 -0 4 2 total 0 0 material group in nuclide mean std. dev. -1 5 1 total 0 0 -0 5 2 total 0 0 material group in nuclide mean std. dev. -1 5 1 total 0 0 -0 5 2 total 0 0 material group in group out nuclide mean std. dev. -3 5 1 1 total 0 0 -2 5 1 2 total 0 0 -1 5 2 1 total 0 0 -0 5 2 2 total 0 0 material group out nuclide mean std. dev. -1 5 1 total 0 0 -0 5 2 total 0 0 material group in nuclide mean std. dev. -1 6 1 total 0 0 -0 6 2 total 0 0 material group in nuclide mean std. dev. -1 6 1 total 0 0 -0 6 2 total 0 0 material group in group out nuclide mean std. dev. -3 6 1 1 total 0 0 -2 6 1 2 total 0 0 -1 6 2 1 total 0 0 -0 6 2 2 total 0 0 material group out nuclide mean std. dev. -1 6 1 total 0 0 -0 6 2 total 0 0 material group in nuclide mean std. dev. -1 7 1 total 0 0 -0 7 2 total 0 0 material group in nuclide mean std. dev. -1 7 1 total 0 0 -0 7 2 total 0 0 material group in group out nuclide mean std. dev. -3 7 1 1 total 0 0 -2 7 1 2 total 0 0 -1 7 2 1 total 0 0 -0 7 2 2 total 0 0 material group out nuclide mean std. dev. -1 7 1 total 0 0 -0 7 2 total 0 0 material group in nuclide mean std. dev. -1 8 1 total 0 0 -0 8 2 total 0 0 material group in nuclide mean std. dev. -1 8 1 total 0 0 -0 8 2 total 0 0 material group in group out nuclide mean std. dev. -3 8 1 1 total 0 0 -2 8 1 2 total 0 0 -1 8 2 1 total 0 0 -0 8 2 2 total 0 0 material group out nuclide mean std. dev. -1 8 1 total 0 0 -0 8 2 total 0 0 material group in nuclide mean std. dev. -1 9 1 total 0.504036 0.379624 -0 9 2 total 1.687095 2.536622 material group in nuclide mean std. dev. -1 9 1 total 0 0 -0 9 2 total 0 0 material group in group out nuclide mean std. dev. -3 9 1 1 total 0.504036 0.379624 -2 9 1 2 total 0.000000 0.000000 -1 9 2 1 total 0.000000 0.000000 -0 9 2 2 total 1.417955 2.158027 material group out nuclide mean std. dev. -1 9 1 total 0 0 -0 9 2 total 0 0 material group in nuclide mean std. dev. -1 10 1 total 0 0 -0 10 2 total 0 0 material group in nuclide mean std. dev. -1 10 1 total 0 0 -0 10 2 total 0 0 material group in group out nuclide mean std. dev. -3 10 1 1 total 0 0 -2 10 1 2 total 0 0 -1 10 2 1 total 0 0 -0 10 2 2 total 0 0 material group out nuclide mean std. dev. -1 10 1 total 0 0 -0 10 2 total 0 0 material group in nuclide mean std. dev. -1 11 1 total 0.302826 0.401311 -0 11 2 total 1.006145 1.091638 material group in nuclide mean std. dev. -1 11 1 total 0 0 -0 11 2 total 0 0 material group in group out nuclide mean std. dev. -3 11 1 1 total 0.275679 0.385676 -2 11 1 2 total 0.027147 0.020009 -1 11 2 1 total 0.000000 0.000000 -0 11 2 2 total 0.957929 1.051959 material group out nuclide mean std. dev. -1 11 1 total 0 0 -0 11 2 total 0 0 material group in nuclide mean std. dev. -1 12 1 total 0.255933 0.268426 -0 12 2 total 1.113345 0.988676 material group in nuclide mean std. dev. -1 12 1 total 0 0 -0 12 2 total 0 0 material group in group out nuclide mean std. dev. -3 12 1 1 total 0.226310 0.254872 -2 12 1 2 total 0.029622 0.017760 -1 12 2 1 total 0.000000 0.000000 -0 12 2 2 total 1.071690 0.958290 material group out nuclide mean std. dev. -1 12 1 total 0 0 -0 12 2 total 0 0 \ No newline at end of file +1 10000 1 total 0.414825 0.022793 +0 10000 2 total 0.660170 0.047519 + 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+ material group in group out nuclide moment mean std. dev. +12 10001 1 1 total P0 0.310121 0.033788 +13 10001 1 1 total P1 0.038230 0.008484 +14 10001 1 1 total P2 0.020745 0.004696 +15 10001 1 1 total P3 0.007964 0.003732 +8 10001 1 2 total P0 0.000000 0.000000 +9 10001 1 2 total P1 0.000000 0.000000 +10 10001 1 2 total P2 0.000000 0.000000 +11 10001 1 2 total P3 0.000000 0.000000 +4 10001 2 1 total P0 0.000000 0.000000 +5 10001 2 1 total P1 0.000000 0.000000 +6 10001 2 1 total P2 0.000000 0.000000 +7 10001 2 1 total P3 0.000000 0.000000 +0 10001 2 2 total P0 0.296264 0.043792 +1 10001 2 2 total P1 -0.011214 0.016180 +2 10001 2 2 total P2 0.008837 0.011504 +3 10001 2 2 total P3 -0.003270 0.007329 + material group in group out nuclide moment mean std. dev. +12 10001 1 1 total P0 0.310121 0.033788 +13 10001 1 1 total P1 0.038230 0.008484 +14 10001 1 1 total P2 0.020745 0.004696 +15 10001 1 1 total P3 0.007964 0.003732 +8 10001 1 2 total P0 0.000000 0.000000 +9 10001 1 2 total P1 0.000000 0.000000 +10 10001 1 2 total P2 0.000000 0.000000 +11 10001 1 2 total P3 0.000000 0.000000 +4 10001 2 1 total P0 0.000000 0.000000 +5 10001 2 1 total P1 0.000000 0.000000 +6 10001 2 1 total P2 0.000000 0.000000 +7 10001 2 1 total P3 0.000000 0.000000 +0 10001 2 2 total P0 0.296264 0.043792 +1 10001 2 2 total P1 -0.011214 0.016180 +2 10001 2 2 total P2 0.008837 0.011504 +3 10001 2 2 total P3 -0.003270 0.007329 + material group in group out nuclide mean std. dev. +3 10001 1 1 total 1.0 0.108779 +2 10001 1 2 total 0.0 0.000000 +1 10001 2 1 total 0.0 0.000000 +0 10001 2 2 total 1.0 0.142427 + material group in group out nuclide mean std. dev. +3 10001 1 1 total 0.0 0.0 +2 10001 1 2 total 0.0 0.0 +1 10001 2 1 total 0.0 0.0 +0 10001 2 2 total 0.0 0.0 + material group out nuclide mean std. dev. +1 10001 1 total 0.0 0.0 +0 10001 2 total 0.0 0.0 + material group in nuclide mean std. dev. +1 10002 1 total 0.664572 0.031215 +0 10002 2 total 2.052384 0.224343 + material group in nuclide mean std. dev. +1 10002 1 total 0.290565 0.023852 +0 10002 2 total 1.516438 0.235197 + material group in nuclide mean std. dev. +1 10002 1 total 0.290565 0.023852 +0 10002 2 total 1.516438 0.235197 + material group in nuclide mean std. dev. +1 10002 1 total 0.000690 0.000044 +0 10002 2 total 0.031687 0.003747 + material group in nuclide mean std. dev. +1 10002 1 total 0.000690 0.000044 +0 10002 2 total 0.031687 0.003747 + material group in nuclide mean std. dev. +1 10002 1 total 0.0 0.0 +0 10002 2 total 0.0 0.0 + material group in nuclide mean std. dev. +1 10002 1 total 0.0 0.0 +0 10002 2 total 0.0 0.0 + material group in nuclide mean std. dev. +1 10002 1 total 0.0 0.0 +0 10002 2 total 0.0 0.0 + material group in nuclide mean std. dev. +1 10002 1 total 0.663882 0.031173 +0 10002 2 total 2.020697 0.220604 + material group in nuclide mean std. dev. +1 10002 1 total 0.671269 0.026186 +0 10002 2 total 2.035388 0.258060 + material group in group out nuclide moment mean std. dev. +12 10002 1 1 total P0 0.639901 0.024709 +13 10002 1 1 total P1 0.381167 0.016243 +14 10002 1 1 total P2 0.152392 0.008156 +15 10002 1 1 total P3 0.009148 0.003889 +8 10002 1 2 total P0 0.031368 0.001728 +9 10002 1 2 total P1 0.008758 0.000926 +10 10002 1 2 total P2 -0.002568 0.001014 +11 10002 1 2 total P3 -0.003785 0.000817 +4 10002 2 1 total P0 0.000443 0.000445 +5 10002 2 1 total P1 0.000400 0.000401 +6 10002 2 1 total P2 0.000320 0.000321 +7 10002 2 1 total P3 0.000214 0.000215 +0 10002 2 2 total P0 2.034945 0.257800 +1 10002 2 2 total P1 0.509941 0.051236 +2 10002 2 2 total P2 0.111175 0.013020 +3 10002 2 2 total P3 0.024988 0.008312 + material group in group out nuclide moment mean std. dev. +12 10002 1 1 total P0 0.639901 0.024709 +13 10002 1 1 total P1 0.381167 0.016243 +14 10002 1 1 total P2 0.152392 0.008156 +15 10002 1 1 total P3 0.009148 0.003889 +8 10002 1 2 total P0 0.031368 0.001728 +9 10002 1 2 total P1 0.008758 0.000926 +10 10002 1 2 total P2 -0.002568 0.001014 +11 10002 1 2 total P3 -0.003785 0.000817 +4 10002 2 1 total P0 0.000443 0.000445 +5 10002 2 1 total P1 0.000400 0.000401 +6 10002 2 1 total P2 0.000320 0.000321 +7 10002 2 1 total P3 0.000214 0.000215 +0 10002 2 2 total P0 2.034945 0.257800 +1 10002 2 2 total P1 0.509941 0.051236 +2 10002 2 2 total P2 0.111175 0.013020 +3 10002 2 2 total P3 0.024988 0.008312 + material group in group out nuclide mean std. dev. +3 10002 1 1 total 1.0 0.038609 +2 10002 1 2 total 1.0 0.067667 +1 10002 2 1 total 1.0 1.414214 +0 10002 2 2 total 1.0 0.135929 + material group in group out nuclide mean std. dev. +3 10002 1 1 total 0.0 0.0 +2 10002 1 2 total 0.0 0.0 +1 10002 2 1 total 0.0 0.0 +0 10002 2 2 total 0.0 0.0 + material group out nuclide mean std. dev. +1 10002 1 total 0.0 0.0 +0 10002 2 total 0.0 0.0 diff --git a/tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py b/tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py index 2afa9039e..2c0a2e278 100644 --- a/tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py +++ b/tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py @@ -6,33 +6,35 @@ import glob import hashlib sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness +from input_set import PinCellInputSet import openmc import openmc.mgxs class MGXSTestHarness(PyAPITestHarness): def _build_inputs(self): - - # The openmc.mgxs module needs a summary.h5 file - self._input_set.settings.output = {'summary': True} + # Set the input set to use the pincell model + self._input_set = PinCellInputSet() # Generate inputs using parent class routine super(MGXSTestHarness, self)._build_inputs() # Initialize a two-group structure - energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, 20.]) + energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, + 20.]) # Initialize MGXS Library for a few cross section types - self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry) + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) self.mgxs_lib.by_nuclide = False - self.mgxs_lib.mgxs_types = ['transport', 'nu-fission', - 'nu-scatter matrix', 'chi'] + # Test all MGXS types + self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.legendre_order = 3 self.mgxs_lib.domain_type = 'material' self.mgxs_lib.build_library() # Initialize a tallies file - self._input_set.tallies = openmc.TalliesFile() + self._input_set.tallies = openmc.Tallies() self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) self._input_set.tallies.export_to_xml() @@ -43,11 +45,6 @@ class MGXSTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the MGXS library from the statepoint self.mgxs_lib.load_from_statepoint(sp) @@ -57,7 +54,7 @@ class MGXSTestHarness(PyAPITestHarness): for mgxs_type in self.mgxs_lib.mgxs_types: mgxs = self.mgxs_lib.get_mgxs(domain, mgxs_type) df = mgxs.get_pandas_dataframe() - outstr += df.to_string() + outstr += df.to_string() + '\n' # Hash the results if necessary if hash_output: diff --git a/tests/test_mgxs_library_nuclides/inputs_true.dat b/tests/test_mgxs_library_nuclides/inputs_true.dat index f87bc242d..8dbb564c6 100644 --- a/tests/test_mgxs_library_nuclides/inputs_true.dat +++ b/tests/test_mgxs_library_nuclides/inputs_true.dat @@ -1 +1 @@ -c6a2a1c707bc723fd38bafd18efcfb22beaac0bd5953d7524ced1d47866cc1e1ee4152e39234d32a06fe43aff446fb12f8c5b62a44075607f274778b49110762 \ No newline at end of file +eebb1469278f470b5859ed83e9b6526e7c4e3fed503bd22e414c6dc13b19b8e4cb6a44e3c14269e6e173f43056eda78268f455662ae119280bc18ea6a071dac7 \ No newline at end of file diff --git a/tests/test_mgxs_library_nuclides/results_true.dat b/tests/test_mgxs_library_nuclides/results_true.dat index 23ac0e423..4f47bd417 100644 --- a/tests/test_mgxs_library_nuclides/results_true.dat +++ b/tests/test_mgxs_library_nuclides/results_true.dat @@ -1,1971 +1 @@ - material group in nuclide mean std. dev. -34 1 1 U-234 0.000000 0.000000 -35 1 1 U-235 0.008559 0.001742 -36 1 1 U-236 0.002643 0.000794 -37 1 1 U-238 0.213622 0.010911 -38 1 1 Np-237 0.000000 0.000000 -39 1 1 Pu-238 0.000000 0.000000 -40 1 1 Pu-239 0.005787 0.001050 -41 1 1 Pu-240 0.005702 0.000850 -42 1 1 Pu-241 0.000869 0.000366 -43 1 1 Pu-242 0.000655 0.000537 -44 1 1 Am-241 0.000000 0.000000 -45 1 1 Am-242m 0.000000 0.000000 -46 1 1 Am-243 0.000000 0.000000 -47 1 1 Cm-242 0.000000 0.000000 -48 1 1 Cm-243 0.000000 0.000000 -49 1 1 Cm-244 0.000000 0.000000 -50 1 1 Cm-245 0.000000 0.000000 -51 1 1 Mo-95 0.000302 0.000216 -52 1 1 Tc-99 0.000782 0.000434 -53 1 1 Ru-101 0.000346 0.000212 -54 1 1 Ru-103 0.000000 0.000000 -55 1 1 Ag-109 0.000000 0.000000 -56 1 1 Xe-135 0.000000 0.000000 -57 1 1 Cs-133 0.000189 0.000264 -58 1 1 Nd-143 0.000721 0.000364 -59 1 1 Nd-145 0.000637 0.000253 -60 1 1 Sm-147 0.000009 0.000238 -61 1 1 Sm-149 0.000000 0.000000 -62 1 1 Sm-150 0.000003 0.000243 -63 1 1 Sm-151 0.000000 0.000000 -64 1 1 Sm-152 0.000874 0.000388 -65 1 1 Eu-153 0.000173 0.000173 -66 1 1 Gd-155 0.000000 0.000000 -67 1 1 O-16 0.142506 0.008222 -0 1 2 U-234 0.001948 0.001952 -1 1 2 U-235 0.179956 0.028209 -2 1 2 U-236 0.000000 0.000000 -3 1 2 U-238 0.239279 0.039048 -4 1 2 Np-237 0.000000 0.000000 -5 1 2 Pu-238 0.000000 0.000000 -6 1 2 Pu-239 0.159745 0.015751 -7 1 2 Pu-240 0.007792 0.003677 -8 1 2 Pu-241 0.017533 0.003806 -9 1 2 Pu-242 0.000000 0.000000 -10 1 2 Am-241 0.000000 0.000000 -11 1 2 Am-242m 0.000000 0.000000 -12 1 2 Am-243 0.000000 0.000000 -13 1 2 Cm-242 0.000000 0.000000 -14 1 2 Cm-243 0.000000 0.000000 -15 1 2 Cm-244 0.000000 0.000000 -16 1 2 Cm-245 0.000000 0.000000 -17 1 2 Mo-95 0.002250 0.004232 -18 1 2 Tc-99 0.003544 0.002528 -19 1 2 Ru-101 0.000000 0.000000 -20 1 2 Ru-103 0.000000 0.000000 -21 1 2 Ag-109 0.000000 0.000000 -22 1 2 Xe-135 0.027274 0.004025 -23 1 2 Cs-133 0.000000 0.000000 -24 1 2 Nd-143 0.006532 0.002517 -25 1 2 Nd-145 0.001948 0.001952 -26 1 2 Sm-147 0.000000 0.000000 -27 1 2 Sm-149 0.007792 0.005701 -28 1 2 Sm-150 0.000000 0.000000 -29 1 2 Sm-151 0.000000 0.000000 -30 1 2 Sm-152 0.000000 0.000000 -31 1 2 Eu-153 0.001686 0.001968 -32 1 2 Gd-155 0.000000 0.000000 -33 1 2 O-16 0.154807 0.023798 material group in nuclide mean std. dev. -34 1 1 U-234 6.771527e-06 2.982583e-07 -35 1 1 U-235 9.687933e-03 4.305720e-04 -36 1 1 U-236 6.279974e-05 3.653120e-06 -37 1 1 U-238 6.335930e-03 4.715525e-04 -38 1 1 Np-237 1.237030e-05 6.333955e-07 -39 1 1 Pu-238 7.369063e-06 5.017525e-07 -40 1 1 Pu-239 4.007893e-03 2.607619e-04 -41 1 1 Pu-240 6.479096e-05 3.728060e-06 -42 1 1 Pu-241 1.074454e-03 4.688479e-05 -43 1 1 Pu-242 5.512610e-06 2.976651e-07 -44 1 1 Am-241 1.088373e-06 8.489934e-08 -45 1 1 Am-242m 1.143307e-06 9.912400e-08 -46 1 1 Am-243 7.745526e-07 5.413923e-08 -47 1 1 Cm-242 4.311566e-07 1.922427e-08 -48 1 1 Cm-243 2.363328e-07 2.235666e-08 -49 1 1 Cm-244 2.840125e-07 2.412051e-08 -50 1 1 Cm-245 3.017505e-07 1.594090e-08 -51 1 1 Mo-95 0.000000e+00 0.000000e+00 -52 1 1 Tc-99 0.000000e+00 0.000000e+00 -53 1 1 Ru-101 0.000000e+00 0.000000e+00 -54 1 1 Ru-103 0.000000e+00 0.000000e+00 -55 1 1 Ag-109 0.000000e+00 0.000000e+00 -56 1 1 Xe-135 0.000000e+00 0.000000e+00 -57 1 1 Cs-133 0.000000e+00 0.000000e+00 -58 1 1 Nd-143 0.000000e+00 0.000000e+00 -59 1 1 Nd-145 0.000000e+00 0.000000e+00 -60 1 1 Sm-147 0.000000e+00 0.000000e+00 -61 1 1 Sm-149 0.000000e+00 0.000000e+00 -62 1 1 Sm-150 0.000000e+00 0.000000e+00 -63 1 1 Sm-151 0.000000e+00 0.000000e+00 -64 1 1 Sm-152 0.000000e+00 0.000000e+00 -65 1 1 Eu-153 0.000000e+00 0.000000e+00 -66 1 1 Gd-155 0.000000e+00 0.000000e+00 -67 1 1 O-16 0.000000e+00 0.000000e+00 -0 1 2 U-234 4.267300e-07 3.529845e-08 -1 1 2 U-235 3.629246e-01 2.964548e-02 -2 1 2 U-236 5.921657e-06 4.881464e-07 -3 1 2 U-238 5.196256e-07 4.286610e-08 -4 1 2 Np-237 2.424211e-07 1.741823e-08 -5 1 2 Pu-238 3.255627e-05 2.692686e-06 -6 1 2 Pu-239 2.868384e-01 2.056896e-02 -7 1 2 Pu-240 4.398266e-06 3.658267e-07 -8 1 2 Pu-241 4.607239e-02 3.797176e-03 -9 1 2 Pu-242 8.451967e-08 6.979002e-09 -10 1 2 Am-241 4.678607e-06 3.253889e-07 -11 1 2 Am-242m 1.417675e-04 1.218350e-05 -12 1 2 Am-243 7.648834e-08 6.303843e-09 -13 1 2 Cm-242 9.433314e-07 7.794362e-08 -14 1 2 Cm-243 1.767995e-06 1.454123e-07 -15 1 2 Cm-244 1.533962e-07 1.266951e-08 -16 1 2 Cm-245 1.145063e-05 9.419051e-07 -17 1 2 Mo-95 0.000000e+00 0.000000e+00 -18 1 2 Tc-99 0.000000e+00 0.000000e+00 -19 1 2 Ru-101 0.000000e+00 0.000000e+00 -20 1 2 Ru-103 0.000000e+00 0.000000e+00 -21 1 2 Ag-109 0.000000e+00 0.000000e+00 -22 1 2 Xe-135 0.000000e+00 0.000000e+00 -23 1 2 Cs-133 0.000000e+00 0.000000e+00 -24 1 2 Nd-143 0.000000e+00 0.000000e+00 -25 1 2 Nd-145 0.000000e+00 0.000000e+00 -26 1 2 Sm-147 0.000000e+00 0.000000e+00 -27 1 2 Sm-149 0.000000e+00 0.000000e+00 -28 1 2 Sm-150 0.000000e+00 0.000000e+00 -29 1 2 Sm-151 0.000000e+00 0.000000e+00 -30 1 2 Sm-152 0.000000e+00 0.000000e+00 -31 1 2 Eu-153 0.000000e+00 0.000000e+00 -32 1 2 Gd-155 0.000000e+00 0.000000e+00 -33 1 2 O-16 0.000000e+00 0.000000e+00 material group in group out nuclide mean std. dev. -102 1 1 1 U-234 0.000000 0.000000 -103 1 1 1 U-235 0.002846 0.001185 -104 1 1 1 U-236 0.001951 0.000829 -105 1 1 1 U-238 0.197520 0.011618 -106 1 1 1 Np-237 0.000000 0.000000 -107 1 1 1 Pu-238 0.000000 0.000000 -108 1 1 1 Pu-239 0.001285 0.000461 -109 1 1 1 Pu-240 0.001027 0.000635 -110 1 1 1 Pu-241 0.000004 0.000242 -111 1 1 1 Pu-242 0.000481 0.000372 -112 1 1 1 Am-241 0.000000 0.000000 -113 1 1 1 Am-242m 0.000000 0.000000 -114 1 1 1 Am-243 0.000000 0.000000 -115 1 1 1 Cm-242 0.000000 0.000000 -116 1 1 1 Cm-243 0.000000 0.000000 -117 1 1 1 Cm-244 0.000000 0.000000 -118 1 1 1 Cm-245 0.000000 0.000000 -119 1 1 1 Mo-95 0.000302 0.000216 -120 1 1 1 Tc-99 0.000262 0.000195 -121 1 1 1 Ru-101 0.000000 0.000000 -122 1 1 1 Ru-103 0.000000 0.000000 -123 1 1 1 Ag-109 0.000000 0.000000 -124 1 1 1 Xe-135 0.000000 0.000000 -125 1 1 1 Cs-133 0.000016 0.000234 -126 1 1 1 Nd-143 0.000721 0.000364 -127 1 1 1 Nd-145 0.000463 0.000281 -128 1 1 1 Sm-147 0.000009 0.000238 -129 1 1 1 Sm-149 0.000000 0.000000 -130 1 1 1 Sm-150 0.000003 0.000243 -131 1 1 1 Sm-151 0.000000 0.000000 -132 1 1 1 Sm-152 0.000700 0.000424 -133 1 1 1 Eu-153 0.000000 0.000000 -134 1 1 1 Gd-155 0.000000 0.000000 -135 1 1 1 O-16 0.142333 0.008156 -68 1 1 2 U-234 0.000000 0.000000 -69 1 1 2 U-235 0.000000 0.000000 -70 1 1 2 U-236 0.000000 0.000000 -71 1 1 2 U-238 0.000000 0.000000 -72 1 1 2 Np-237 0.000000 0.000000 -73 1 1 2 Pu-238 0.000000 0.000000 -74 1 1 2 Pu-239 0.000000 0.000000 -75 1 1 2 Pu-240 0.000000 0.000000 -76 1 1 2 Pu-241 0.000000 0.000000 -77 1 1 2 Pu-242 0.000000 0.000000 -78 1 1 2 Am-241 0.000000 0.000000 -79 1 1 2 Am-242m 0.000000 0.000000 -80 1 1 2 Am-243 0.000000 0.000000 -81 1 1 2 Cm-242 0.000000 0.000000 -82 1 1 2 Cm-243 0.000000 0.000000 -83 1 1 2 Cm-244 0.000000 0.000000 -84 1 1 2 Cm-245 0.000000 0.000000 -85 1 1 2 Mo-95 0.000000 0.000000 -86 1 1 2 Tc-99 0.000000 0.000000 -87 1 1 2 Ru-101 0.000000 0.000000 -88 1 1 2 Ru-103 0.000000 0.000000 -89 1 1 2 Ag-109 0.000000 0.000000 -90 1 1 2 Xe-135 0.000000 0.000000 -91 1 1 2 Cs-133 0.000000 0.000000 -92 1 1 2 Nd-143 0.000000 0.000000 -93 1 1 2 Nd-145 0.000000 0.000000 -94 1 1 2 Sm-147 0.000000 0.000000 -95 1 1 2 Sm-149 0.000000 0.000000 -96 1 1 2 Sm-150 0.000000 0.000000 -97 1 1 2 Sm-151 0.000000 0.000000 -98 1 1 2 Sm-152 0.000000 0.000000 -99 1 1 2 Eu-153 0.000000 0.000000 -100 1 1 2 Gd-155 0.000000 0.000000 -101 1 1 2 O-16 0.000173 0.000173 -34 1 2 1 U-234 0.000000 0.000000 -35 1 2 1 U-235 0.000000 0.000000 -36 1 2 1 U-236 0.000000 0.000000 -37 1 2 1 U-238 0.000000 0.000000 -38 1 2 1 Np-237 0.000000 0.000000 -39 1 2 1 Pu-238 0.000000 0.000000 -40 1 2 1 Pu-239 0.000000 0.000000 -41 1 2 1 Pu-240 0.000000 0.000000 -42 1 2 1 Pu-241 0.000000 0.000000 -43 1 2 1 Pu-242 0.000000 0.000000 -44 1 2 1 Am-241 0.000000 0.000000 -45 1 2 1 Am-242m 0.000000 0.000000 -46 1 2 1 Am-243 0.000000 0.000000 -47 1 2 1 Cm-242 0.000000 0.000000 -48 1 2 1 Cm-243 0.000000 0.000000 -49 1 2 1 Cm-244 0.000000 0.000000 -50 1 2 1 Cm-245 0.000000 0.000000 -51 1 2 1 Mo-95 0.000000 0.000000 -52 1 2 1 Tc-99 0.000000 0.000000 -53 1 2 1 Ru-101 0.000000 0.000000 -54 1 2 1 Ru-103 0.000000 0.000000 -55 1 2 1 Ag-109 0.000000 0.000000 -56 1 2 1 Xe-135 0.000000 0.000000 -57 1 2 1 Cs-133 0.000000 0.000000 -58 1 2 1 Nd-143 0.000000 0.000000 -59 1 2 1 Nd-145 0.000000 0.000000 -60 1 2 1 Sm-147 0.000000 0.000000 -61 1 2 1 Sm-149 0.000000 0.000000 -62 1 2 1 Sm-150 0.000000 0.000000 -63 1 2 1 Sm-151 0.000000 0.000000 -64 1 2 1 Sm-152 0.000000 0.000000 -65 1 2 1 Eu-153 0.000000 0.000000 -66 1 2 1 Gd-155 0.000000 0.000000 -67 1 2 1 O-16 0.001948 0.001952 -0 1 2 2 U-234 0.000000 0.000000 -1 1 2 2 U-235 0.010470 0.006106 -2 1 2 2 U-236 0.000000 0.000000 -3 1 2 2 U-238 0.208109 0.039197 -4 1 2 2 Np-237 0.000000 0.000000 -5 1 2 2 Pu-238 0.000000 0.000000 -6 1 2 2 Pu-239 0.000000 0.000000 -7 1 2 2 Pu-240 0.000000 0.000000 -8 1 2 2 Pu-241 0.000000 0.000000 -9 1 2 2 Pu-242 0.000000 0.000000 -10 1 2 2 Am-241 0.000000 0.000000 -11 1 2 2 Am-242m 0.000000 0.000000 -12 1 2 2 Am-243 0.000000 0.000000 -13 1 2 2 Cm-242 0.000000 0.000000 -14 1 2 2 Cm-243 0.000000 0.000000 -15 1 2 2 Cm-244 0.000000 0.000000 -16 1 2 2 Cm-245 0.000000 0.000000 -17 1 2 2 Mo-95 0.000302 0.002551 -18 1 2 2 Tc-99 0.003544 0.002528 -19 1 2 2 Ru-101 0.000000 0.000000 -20 1 2 2 Ru-103 0.000000 0.000000 -21 1 2 2 Ag-109 0.000000 0.000000 -22 1 2 2 Xe-135 0.000000 0.000000 -23 1 2 2 Cs-133 0.000000 0.000000 -24 1 2 2 Nd-143 0.002636 0.002073 -25 1 2 2 Nd-145 0.000000 0.000000 -26 1 2 2 Sm-147 0.000000 0.000000 -27 1 2 2 Sm-149 0.000000 0.000000 -28 1 2 2 Sm-150 0.000000 0.000000 -29 1 2 2 Sm-151 0.000000 0.000000 -30 1 2 2 Sm-152 0.000000 0.000000 -31 1 2 2 Eu-153 0.001686 0.001968 -32 1 2 2 Gd-155 0.000000 0.000000 -33 1 2 2 O-16 0.152859 0.022894 material group out nuclide mean std. dev. -34 1 1 U-234 0 0.000000 -35 1 1 U-235 1 0.127079 -36 1 1 U-236 0 0.000000 -37 1 1 U-238 1 0.153215 -38 1 1 Np-237 0 0.000000 -39 1 1 Pu-238 0 0.000000 -40 1 1 Pu-239 1 0.150979 -41 1 1 Pu-240 0 0.000000 -42 1 1 Pu-241 1 0.203534 -43 1 1 Pu-242 0 0.000000 -44 1 1 Am-241 0 0.000000 -45 1 1 Am-242m 0 0.000000 -46 1 1 Am-243 0 0.000000 -47 1 1 Cm-242 0 0.000000 -48 1 1 Cm-243 0 0.000000 -49 1 1 Cm-244 0 0.000000 -50 1 1 Cm-245 0 0.000000 -51 1 1 Mo-95 0 0.000000 -52 1 1 Tc-99 0 0.000000 -53 1 1 Ru-101 0 0.000000 -54 1 1 Ru-103 0 0.000000 -55 1 1 Ag-109 0 0.000000 -56 1 1 Xe-135 0 0.000000 -57 1 1 Cs-133 0 0.000000 -58 1 1 Nd-143 0 0.000000 -59 1 1 Nd-145 0 0.000000 -60 1 1 Sm-147 0 0.000000 -61 1 1 Sm-149 0 0.000000 -62 1 1 Sm-150 0 0.000000 -63 1 1 Sm-151 0 0.000000 -64 1 1 Sm-152 0 0.000000 -65 1 1 Eu-153 0 0.000000 -66 1 1 Gd-155 0 0.000000 -67 1 1 O-16 0 0.000000 -0 1 2 U-234 0 0.000000 -1 1 2 U-235 0 0.000000 -2 1 2 U-236 0 0.000000 -3 1 2 U-238 0 0.000000 -4 1 2 Np-237 0 0.000000 -5 1 2 Pu-238 0 0.000000 -6 1 2 Pu-239 0 0.000000 -7 1 2 Pu-240 0 0.000000 -8 1 2 Pu-241 0 0.000000 -9 1 2 Pu-242 0 0.000000 -10 1 2 Am-241 0 0.000000 -11 1 2 Am-242m 0 0.000000 -12 1 2 Am-243 0 0.000000 -13 1 2 Cm-242 0 0.000000 -14 1 2 Cm-243 0 0.000000 -15 1 2 Cm-244 0 0.000000 -16 1 2 Cm-245 0 0.000000 -17 1 2 Mo-95 0 0.000000 -18 1 2 Tc-99 0 0.000000 -19 1 2 Ru-101 0 0.000000 -20 1 2 Ru-103 0 0.000000 -21 1 2 Ag-109 0 0.000000 -22 1 2 Xe-135 0 0.000000 -23 1 2 Cs-133 0 0.000000 -24 1 2 Nd-143 0 0.000000 -25 1 2 Nd-145 0 0.000000 -26 1 2 Sm-147 0 0.000000 -27 1 2 Sm-149 0 0.000000 -28 1 2 Sm-150 0 0.000000 -29 1 2 Sm-151 0 0.000000 -30 1 2 Sm-152 0 0.000000 -31 1 2 Eu-153 0 0.000000 -32 1 2 Gd-155 0 0.000000 -33 1 2 O-16 0 0.000000 material group in nuclide mean std. dev. -5 2 1 Zr-90 0.118578 0.008347 -6 2 1 Zr-91 0.040887 0.002988 -7 2 1 Zr-92 0.033882 0.004365 -8 2 1 Zr-94 0.046281 0.005422 -9 2 1 Zr-96 0.005415 0.002113 -0 2 2 Zr-90 0.122479 0.032627 -1 2 2 Zr-91 0.035669 0.009683 -2 2 2 Zr-92 0.049331 0.021936 -3 2 2 Zr-94 0.058978 0.020081 -4 2 2 Zr-96 0.000000 0.000000 material group in nuclide mean std. dev. -5 2 1 Zr-90 0 0 -6 2 1 Zr-91 0 0 -7 2 1 Zr-92 0 0 -8 2 1 Zr-94 0 0 -9 2 1 Zr-96 0 0 -0 2 2 Zr-90 0 0 -1 2 2 Zr-91 0 0 -2 2 2 Zr-92 0 0 -3 2 2 Zr-94 0 0 -4 2 2 Zr-96 0 0 material group in group out nuclide mean std. dev. -15 2 1 1 Zr-90 0.118578 0.008347 -16 2 1 1 Zr-91 0.039963 0.003053 -17 2 1 1 Zr-92 0.033882 0.004365 -18 2 1 1 Zr-94 0.046281 0.005422 -19 2 1 1 Zr-96 0.004953 0.002087 -10 2 1 2 Zr-90 0.000000 0.000000 -11 2 1 2 Zr-91 0.000000 0.000000 -12 2 1 2 Zr-92 0.000000 0.000000 -13 2 1 2 Zr-94 0.000000 0.000000 -14 2 1 2 Zr-96 0.000000 0.000000 -5 2 2 1 Zr-90 0.000000 0.000000 -6 2 2 1 Zr-91 0.000000 0.000000 -7 2 2 1 Zr-92 0.000000 0.000000 -8 2 2 1 Zr-94 0.000000 0.000000 -9 2 2 1 Zr-96 0.000000 0.000000 -0 2 2 2 Zr-90 0.122479 0.032627 -1 2 2 2 Zr-91 0.023998 0.011915 -2 2 2 2 Zr-92 0.049331 0.021936 -3 2 2 2 Zr-94 0.058978 0.020081 -4 2 2 2 Zr-96 0.000000 0.000000 material group out nuclide mean std. dev. -5 2 1 Zr-90 0 0 -6 2 1 Zr-91 0 0 -7 2 1 Zr-92 0 0 -8 2 1 Zr-94 0 0 -9 2 1 Zr-96 0 0 -0 2 2 Zr-90 0 0 -1 2 2 Zr-91 0 0 -2 2 2 Zr-92 0 0 -3 2 2 Zr-94 0 0 -4 2 2 Zr-96 0 0 material group in nuclide mean std. dev. -4 3 1 H-1 0.206179 0.034791 -5 3 1 O-16 0.075190 0.004750 -6 3 1 B-10 0.000741 0.000470 -7 3 1 B-11 0.000167 0.000208 -0 3 2 H-1 1.323003 0.239067 -1 3 2 O-16 0.071243 0.013291 -2 3 2 B-10 0.033075 0.004283 -3 3 2 B-11 0.000000 0.000000 material group in nuclide mean std. dev. -4 3 1 H-1 0 0 -5 3 1 O-16 0 0 -6 3 1 B-10 0 0 -7 3 1 B-11 0 0 -0 3 2 H-1 0 0 -1 3 2 O-16 0 0 -2 3 2 B-10 0 0 -3 3 2 B-11 0 0 material group in group out nuclide mean std. dev. -12 3 1 1 H-1 0.178758 0.033618 -13 3 1 1 O-16 0.075042 0.004782 -14 3 1 1 B-10 0.000000 0.000000 -15 3 1 1 B-11 0.000167 0.000208 -8 3 1 2 H-1 0.027124 0.001806 -9 3 1 2 O-16 0.000148 0.000148 -10 3 1 2 B-10 0.000000 0.000000 -11 3 1 2 B-11 0.000000 0.000000 -4 3 2 1 H-1 0.000000 0.000000 -5 3 2 1 O-16 0.000000 0.000000 -6 3 2 1 B-10 0.000000 0.000000 -7 3 2 1 B-11 0.000000 0.000000 -0 3 2 2 H-1 1.305284 0.235145 -1 3 2 2 O-16 0.071243 0.013291 -2 3 2 2 B-10 0.000000 0.000000 -3 3 2 2 B-11 0.000000 0.000000 material group out nuclide mean std. dev. -4 3 1 H-1 0 0 -5 3 1 O-16 0 0 -6 3 1 B-10 0 0 -7 3 1 B-11 0 0 -0 3 2 H-1 0 0 -1 3 2 O-16 0 0 -2 3 2 B-10 0 0 -3 3 2 B-11 0 0 material group in nuclide mean std. dev. -4 4 1 H-1 0.188813 0.045599 -5 4 1 O-16 0.066636 0.008217 -6 4 1 B-10 0.000232 0.000233 -7 4 1 B-11 0.000042 0.000300 -0 4 2 H-1 1.088920 0.221595 -1 4 2 O-16 0.064481 0.014318 -2 4 2 B-10 0.026367 0.010478 -3 4 2 B-11 0.000000 0.000000 material group in nuclide mean std. dev. -4 4 1 H-1 0 0 -5 4 1 O-16 0 0 -6 4 1 B-10 0 0 -7 4 1 B-11 0 0 -0 4 2 H-1 0 0 -1 4 2 O-16 0 0 -2 4 2 B-10 0 0 -3 4 2 B-11 0 0 material group in group out nuclide mean std. dev. -12 4 1 1 H-1 0.166764 0.043861 -13 4 1 1 O-16 0.066172 0.007943 -14 4 1 1 B-10 0.000000 0.000000 -15 4 1 1 B-11 0.000042 0.000300 -8 4 1 2 H-1 0.021817 0.002327 -9 4 1 2 O-16 0.000464 0.000466 -10 4 1 2 B-10 0.000000 0.000000 -11 4 1 2 B-11 0.000000 0.000000 -4 4 2 1 H-1 0.000000 0.000000 -5 4 2 1 O-16 0.000000 0.000000 -6 4 2 1 B-10 0.000000 0.000000 -7 4 2 1 B-11 0.000000 0.000000 -0 4 2 2 H-1 1.082328 0.222438 -1 4 2 2 O-16 0.064481 0.014318 -2 4 2 2 B-10 0.000000 0.000000 -3 4 2 2 B-11 0.000000 0.000000 material group out nuclide mean std. dev. -4 4 1 H-1 0 0 -5 4 1 O-16 0 0 -6 4 1 B-10 0 0 -7 4 1 B-11 0 0 -0 4 2 H-1 0 0 -1 4 2 O-16 0 0 -2 4 2 B-10 0 0 -3 4 2 B-11 0 0 material group in nuclide mean std. dev. -27 5 1 Fe-54 0 0 -28 5 1 Fe-56 0 0 -29 5 1 Fe-57 0 0 -30 5 1 Fe-58 0 0 -31 5 1 Ni-58 0 0 -32 5 1 Ni-60 0 0 -33 5 1 Ni-61 0 0 -34 5 1 Ni-62 0 0 -35 5 1 Ni-64 0 0 -36 5 1 Mn-55 0 0 -37 5 1 Mo-92 0 0 -38 5 1 Mo-94 0 0 -39 5 1 Mo-95 0 0 -40 5 1 Mo-96 0 0 -41 5 1 Mo-97 0 0 -42 5 1 Mo-98 0 0 -43 5 1 Mo-100 0 0 -44 5 1 Si-28 0 0 -45 5 1 Si-29 0 0 -46 5 1 Si-30 0 0 -47 5 1 Cr-50 0 0 -48 5 1 Cr-52 0 0 -49 5 1 Cr-53 0 0 -50 5 1 Cr-54 0 0 -51 5 1 C-Nat 0 0 -52 5 1 Cu-63 0 0 -53 5 1 Cu-65 0 0 -0 5 2 Fe-54 0 0 -1 5 2 Fe-56 0 0 -2 5 2 Fe-57 0 0 -3 5 2 Fe-58 0 0 -4 5 2 Ni-58 0 0 -5 5 2 Ni-60 0 0 -6 5 2 Ni-61 0 0 -7 5 2 Ni-62 0 0 -8 5 2 Ni-64 0 0 -9 5 2 Mn-55 0 0 -10 5 2 Mo-92 0 0 -11 5 2 Mo-94 0 0 -12 5 2 Mo-95 0 0 -13 5 2 Mo-96 0 0 -14 5 2 Mo-97 0 0 -15 5 2 Mo-98 0 0 -16 5 2 Mo-100 0 0 -17 5 2 Si-28 0 0 -18 5 2 Si-29 0 0 -19 5 2 Si-30 0 0 -20 5 2 Cr-50 0 0 -21 5 2 Cr-52 0 0 -22 5 2 Cr-53 0 0 -23 5 2 Cr-54 0 0 -24 5 2 C-Nat 0 0 -25 5 2 Cu-63 0 0 -26 5 2 Cu-65 0 0 material group in nuclide mean std. dev. -27 5 1 Fe-54 0 0 -28 5 1 Fe-56 0 0 -29 5 1 Fe-57 0 0 -30 5 1 Fe-58 0 0 -31 5 1 Ni-58 0 0 -32 5 1 Ni-60 0 0 -33 5 1 Ni-61 0 0 -34 5 1 Ni-62 0 0 -35 5 1 Ni-64 0 0 -36 5 1 Mn-55 0 0 -37 5 1 Mo-92 0 0 -38 5 1 Mo-94 0 0 -39 5 1 Mo-95 0 0 -40 5 1 Mo-96 0 0 -41 5 1 Mo-97 0 0 -42 5 1 Mo-98 0 0 -43 5 1 Mo-100 0 0 -44 5 1 Si-28 0 0 -45 5 1 Si-29 0 0 -46 5 1 Si-30 0 0 -47 5 1 Cr-50 0 0 -48 5 1 Cr-52 0 0 -49 5 1 Cr-53 0 0 -50 5 1 Cr-54 0 0 -51 5 1 C-Nat 0 0 -52 5 1 Cu-63 0 0 -53 5 1 Cu-65 0 0 -0 5 2 Fe-54 0 0 -1 5 2 Fe-56 0 0 -2 5 2 Fe-57 0 0 -3 5 2 Fe-58 0 0 -4 5 2 Ni-58 0 0 -5 5 2 Ni-60 0 0 -6 5 2 Ni-61 0 0 -7 5 2 Ni-62 0 0 -8 5 2 Ni-64 0 0 -9 5 2 Mn-55 0 0 -10 5 2 Mo-92 0 0 -11 5 2 Mo-94 0 0 -12 5 2 Mo-95 0 0 -13 5 2 Mo-96 0 0 -14 5 2 Mo-97 0 0 -15 5 2 Mo-98 0 0 -16 5 2 Mo-100 0 0 -17 5 2 Si-28 0 0 -18 5 2 Si-29 0 0 -19 5 2 Si-30 0 0 -20 5 2 Cr-50 0 0 -21 5 2 Cr-52 0 0 -22 5 2 Cr-53 0 0 -23 5 2 Cr-54 0 0 -24 5 2 C-Nat 0 0 -25 5 2 Cu-63 0 0 -26 5 2 Cu-65 0 0 material group in group out nuclide mean std. dev. -81 5 1 1 Fe-54 0 0 -82 5 1 1 Fe-56 0 0 -83 5 1 1 Fe-57 0 0 -84 5 1 1 Fe-58 0 0 -85 5 1 1 Ni-58 0 0 -86 5 1 1 Ni-60 0 0 -87 5 1 1 Ni-61 0 0 -88 5 1 1 Ni-62 0 0 -89 5 1 1 Ni-64 0 0 -90 5 1 1 Mn-55 0 0 -91 5 1 1 Mo-92 0 0 -92 5 1 1 Mo-94 0 0 -93 5 1 1 Mo-95 0 0 -94 5 1 1 Mo-96 0 0 -95 5 1 1 Mo-97 0 0 -96 5 1 1 Mo-98 0 0 -97 5 1 1 Mo-100 0 0 -98 5 1 1 Si-28 0 0 -99 5 1 1 Si-29 0 0 -100 5 1 1 Si-30 0 0 -101 5 1 1 Cr-50 0 0 -102 5 1 1 Cr-52 0 0 -103 5 1 1 Cr-53 0 0 -104 5 1 1 Cr-54 0 0 -105 5 1 1 C-Nat 0 0 -106 5 1 1 Cu-63 0 0 -107 5 1 1 Cu-65 0 0 -54 5 1 2 Fe-54 0 0 -55 5 1 2 Fe-56 0 0 -56 5 1 2 Fe-57 0 0 -57 5 1 2 Fe-58 0 0 -58 5 1 2 Ni-58 0 0 -59 5 1 2 Ni-60 0 0 -60 5 1 2 Ni-61 0 0 -61 5 1 2 Ni-62 0 0 -62 5 1 2 Ni-64 0 0 -63 5 1 2 Mn-55 0 0 -64 5 1 2 Mo-92 0 0 -65 5 1 2 Mo-94 0 0 -66 5 1 2 Mo-95 0 0 -67 5 1 2 Mo-96 0 0 -68 5 1 2 Mo-97 0 0 -69 5 1 2 Mo-98 0 0 -70 5 1 2 Mo-100 0 0 -71 5 1 2 Si-28 0 0 -72 5 1 2 Si-29 0 0 -73 5 1 2 Si-30 0 0 -74 5 1 2 Cr-50 0 0 -75 5 1 2 Cr-52 0 0 -76 5 1 2 Cr-53 0 0 -77 5 1 2 Cr-54 0 0 -78 5 1 2 C-Nat 0 0 -79 5 1 2 Cu-63 0 0 -80 5 1 2 Cu-65 0 0 -27 5 2 1 Fe-54 0 0 -28 5 2 1 Fe-56 0 0 -29 5 2 1 Fe-57 0 0 -30 5 2 1 Fe-58 0 0 -31 5 2 1 Ni-58 0 0 -32 5 2 1 Ni-60 0 0 -33 5 2 1 Ni-61 0 0 -34 5 2 1 Ni-62 0 0 -35 5 2 1 Ni-64 0 0 -36 5 2 1 Mn-55 0 0 -37 5 2 1 Mo-92 0 0 -38 5 2 1 Mo-94 0 0 -39 5 2 1 Mo-95 0 0 -40 5 2 1 Mo-96 0 0 -41 5 2 1 Mo-97 0 0 -42 5 2 1 Mo-98 0 0 -43 5 2 1 Mo-100 0 0 -44 5 2 1 Si-28 0 0 -45 5 2 1 Si-29 0 0 -46 5 2 1 Si-30 0 0 -47 5 2 1 Cr-50 0 0 -48 5 2 1 Cr-52 0 0 -49 5 2 1 Cr-53 0 0 -50 5 2 1 Cr-54 0 0 -51 5 2 1 C-Nat 0 0 -52 5 2 1 Cu-63 0 0 -53 5 2 1 Cu-65 0 0 -0 5 2 2 Fe-54 0 0 -1 5 2 2 Fe-56 0 0 -2 5 2 2 Fe-57 0 0 -3 5 2 2 Fe-58 0 0 -4 5 2 2 Ni-58 0 0 -5 5 2 2 Ni-60 0 0 -6 5 2 2 Ni-61 0 0 -7 5 2 2 Ni-62 0 0 -8 5 2 2 Ni-64 0 0 -9 5 2 2 Mn-55 0 0 -10 5 2 2 Mo-92 0 0 -11 5 2 2 Mo-94 0 0 -12 5 2 2 Mo-95 0 0 -13 5 2 2 Mo-96 0 0 -14 5 2 2 Mo-97 0 0 -15 5 2 2 Mo-98 0 0 -16 5 2 2 Mo-100 0 0 -17 5 2 2 Si-28 0 0 -18 5 2 2 Si-29 0 0 -19 5 2 2 Si-30 0 0 -20 5 2 2 Cr-50 0 0 -21 5 2 2 Cr-52 0 0 -22 5 2 2 Cr-53 0 0 -23 5 2 2 Cr-54 0 0 -24 5 2 2 C-Nat 0 0 -25 5 2 2 Cu-63 0 0 -26 5 2 2 Cu-65 0 0 material group out nuclide mean std. dev. -27 5 1 Fe-54 0 0 -28 5 1 Fe-56 0 0 -29 5 1 Fe-57 0 0 -30 5 1 Fe-58 0 0 -31 5 1 Ni-58 0 0 -32 5 1 Ni-60 0 0 -33 5 1 Ni-61 0 0 -34 5 1 Ni-62 0 0 -35 5 1 Ni-64 0 0 -36 5 1 Mn-55 0 0 -37 5 1 Mo-92 0 0 -38 5 1 Mo-94 0 0 -39 5 1 Mo-95 0 0 -40 5 1 Mo-96 0 0 -41 5 1 Mo-97 0 0 -42 5 1 Mo-98 0 0 -43 5 1 Mo-100 0 0 -44 5 1 Si-28 0 0 -45 5 1 Si-29 0 0 -46 5 1 Si-30 0 0 -47 5 1 Cr-50 0 0 -48 5 1 Cr-52 0 0 -49 5 1 Cr-53 0 0 -50 5 1 Cr-54 0 0 -51 5 1 C-Nat 0 0 -52 5 1 Cu-63 0 0 -53 5 1 Cu-65 0 0 -0 5 2 Fe-54 0 0 -1 5 2 Fe-56 0 0 -2 5 2 Fe-57 0 0 -3 5 2 Fe-58 0 0 -4 5 2 Ni-58 0 0 -5 5 2 Ni-60 0 0 -6 5 2 Ni-61 0 0 -7 5 2 Ni-62 0 0 -8 5 2 Ni-64 0 0 -9 5 2 Mn-55 0 0 -10 5 2 Mo-92 0 0 -11 5 2 Mo-94 0 0 -12 5 2 Mo-95 0 0 -13 5 2 Mo-96 0 0 -14 5 2 Mo-97 0 0 -15 5 2 Mo-98 0 0 -16 5 2 Mo-100 0 0 -17 5 2 Si-28 0 0 -18 5 2 Si-29 0 0 -19 5 2 Si-30 0 0 -20 5 2 Cr-50 0 0 -21 5 2 Cr-52 0 0 -22 5 2 Cr-53 0 0 -23 5 2 Cr-54 0 0 -24 5 2 C-Nat 0 0 -25 5 2 Cu-63 0 0 -26 5 2 Cu-65 0 0 material group in nuclide mean std. dev. -21 6 1 H-1 0 0 -22 6 1 O-16 0 0 -23 6 1 B-10 0 0 -24 6 1 B-11 0 0 -25 6 1 Fe-54 0 0 -26 6 1 Fe-56 0 0 -27 6 1 Fe-57 0 0 -28 6 1 Fe-58 0 0 -29 6 1 Ni-58 0 0 -30 6 1 Ni-60 0 0 -31 6 1 Ni-61 0 0 -32 6 1 Ni-62 0 0 -33 6 1 Ni-64 0 0 -34 6 1 Mn-55 0 0 -35 6 1 Si-28 0 0 -36 6 1 Si-29 0 0 -37 6 1 Si-30 0 0 -38 6 1 Cr-50 0 0 -39 6 1 Cr-52 0 0 -40 6 1 Cr-53 0 0 -41 6 1 Cr-54 0 0 -0 6 2 H-1 0 0 -1 6 2 O-16 0 0 -2 6 2 B-10 0 0 -3 6 2 B-11 0 0 -4 6 2 Fe-54 0 0 -5 6 2 Fe-56 0 0 -6 6 2 Fe-57 0 0 -7 6 2 Fe-58 0 0 -8 6 2 Ni-58 0 0 -9 6 2 Ni-60 0 0 -10 6 2 Ni-61 0 0 -11 6 2 Ni-62 0 0 -12 6 2 Ni-64 0 0 -13 6 2 Mn-55 0 0 -14 6 2 Si-28 0 0 -15 6 2 Si-29 0 0 -16 6 2 Si-30 0 0 -17 6 2 Cr-50 0 0 -18 6 2 Cr-52 0 0 -19 6 2 Cr-53 0 0 -20 6 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 6 1 H-1 0 0 -22 6 1 O-16 0 0 -23 6 1 B-10 0 0 -24 6 1 B-11 0 0 -25 6 1 Fe-54 0 0 -26 6 1 Fe-56 0 0 -27 6 1 Fe-57 0 0 -28 6 1 Fe-58 0 0 -29 6 1 Ni-58 0 0 -30 6 1 Ni-60 0 0 -31 6 1 Ni-61 0 0 -32 6 1 Ni-62 0 0 -33 6 1 Ni-64 0 0 -34 6 1 Mn-55 0 0 -35 6 1 Si-28 0 0 -36 6 1 Si-29 0 0 -37 6 1 Si-30 0 0 -38 6 1 Cr-50 0 0 -39 6 1 Cr-52 0 0 -40 6 1 Cr-53 0 0 -41 6 1 Cr-54 0 0 -0 6 2 H-1 0 0 -1 6 2 O-16 0 0 -2 6 2 B-10 0 0 -3 6 2 B-11 0 0 -4 6 2 Fe-54 0 0 -5 6 2 Fe-56 0 0 -6 6 2 Fe-57 0 0 -7 6 2 Fe-58 0 0 -8 6 2 Ni-58 0 0 -9 6 2 Ni-60 0 0 -10 6 2 Ni-61 0 0 -11 6 2 Ni-62 0 0 -12 6 2 Ni-64 0 0 -13 6 2 Mn-55 0 0 -14 6 2 Si-28 0 0 -15 6 2 Si-29 0 0 -16 6 2 Si-30 0 0 -17 6 2 Cr-50 0 0 -18 6 2 Cr-52 0 0 -19 6 2 Cr-53 0 0 -20 6 2 Cr-54 0 0 material group in group out nuclide mean std. dev. -63 6 1 1 H-1 0 0 -64 6 1 1 O-16 0 0 -65 6 1 1 B-10 0 0 -66 6 1 1 B-11 0 0 -67 6 1 1 Fe-54 0 0 -68 6 1 1 Fe-56 0 0 -69 6 1 1 Fe-57 0 0 -70 6 1 1 Fe-58 0 0 -71 6 1 1 Ni-58 0 0 -72 6 1 1 Ni-60 0 0 -73 6 1 1 Ni-61 0 0 -74 6 1 1 Ni-62 0 0 -75 6 1 1 Ni-64 0 0 -76 6 1 1 Mn-55 0 0 -77 6 1 1 Si-28 0 0 -78 6 1 1 Si-29 0 0 -79 6 1 1 Si-30 0 0 -80 6 1 1 Cr-50 0 0 -81 6 1 1 Cr-52 0 0 -82 6 1 1 Cr-53 0 0 -83 6 1 1 Cr-54 0 0 -42 6 1 2 H-1 0 0 -43 6 1 2 O-16 0 0 -44 6 1 2 B-10 0 0 -45 6 1 2 B-11 0 0 -46 6 1 2 Fe-54 0 0 -47 6 1 2 Fe-56 0 0 -48 6 1 2 Fe-57 0 0 -49 6 1 2 Fe-58 0 0 -50 6 1 2 Ni-58 0 0 -51 6 1 2 Ni-60 0 0 -52 6 1 2 Ni-61 0 0 -53 6 1 2 Ni-62 0 0 -54 6 1 2 Ni-64 0 0 -55 6 1 2 Mn-55 0 0 -56 6 1 2 Si-28 0 0 -57 6 1 2 Si-29 0 0 -58 6 1 2 Si-30 0 0 -59 6 1 2 Cr-50 0 0 -60 6 1 2 Cr-52 0 0 -61 6 1 2 Cr-53 0 0 -62 6 1 2 Cr-54 0 0 -21 6 2 1 H-1 0 0 -22 6 2 1 O-16 0 0 -23 6 2 1 B-10 0 0 -24 6 2 1 B-11 0 0 -25 6 2 1 Fe-54 0 0 -26 6 2 1 Fe-56 0 0 -27 6 2 1 Fe-57 0 0 -28 6 2 1 Fe-58 0 0 -29 6 2 1 Ni-58 0 0 -30 6 2 1 Ni-60 0 0 -31 6 2 1 Ni-61 0 0 -32 6 2 1 Ni-62 0 0 -33 6 2 1 Ni-64 0 0 -34 6 2 1 Mn-55 0 0 -35 6 2 1 Si-28 0 0 -36 6 2 1 Si-29 0 0 -37 6 2 1 Si-30 0 0 -38 6 2 1 Cr-50 0 0 -39 6 2 1 Cr-52 0 0 -40 6 2 1 Cr-53 0 0 -41 6 2 1 Cr-54 0 0 -0 6 2 2 H-1 0 0 -1 6 2 2 O-16 0 0 -2 6 2 2 B-10 0 0 -3 6 2 2 B-11 0 0 -4 6 2 2 Fe-54 0 0 -5 6 2 2 Fe-56 0 0 -6 6 2 2 Fe-57 0 0 -7 6 2 2 Fe-58 0 0 -8 6 2 2 Ni-58 0 0 -9 6 2 2 Ni-60 0 0 -10 6 2 2 Ni-61 0 0 -11 6 2 2 Ni-62 0 0 -12 6 2 2 Ni-64 0 0 -13 6 2 2 Mn-55 0 0 -14 6 2 2 Si-28 0 0 -15 6 2 2 Si-29 0 0 -16 6 2 2 Si-30 0 0 -17 6 2 2 Cr-50 0 0 -18 6 2 2 Cr-52 0 0 -19 6 2 2 Cr-53 0 0 -20 6 2 2 Cr-54 0 0 material group out nuclide mean std. dev. -21 6 1 H-1 0 0 -22 6 1 O-16 0 0 -23 6 1 B-10 0 0 -24 6 1 B-11 0 0 -25 6 1 Fe-54 0 0 -26 6 1 Fe-56 0 0 -27 6 1 Fe-57 0 0 -28 6 1 Fe-58 0 0 -29 6 1 Ni-58 0 0 -30 6 1 Ni-60 0 0 -31 6 1 Ni-61 0 0 -32 6 1 Ni-62 0 0 -33 6 1 Ni-64 0 0 -34 6 1 Mn-55 0 0 -35 6 1 Si-28 0 0 -36 6 1 Si-29 0 0 -37 6 1 Si-30 0 0 -38 6 1 Cr-50 0 0 -39 6 1 Cr-52 0 0 -40 6 1 Cr-53 0 0 -41 6 1 Cr-54 0 0 -0 6 2 H-1 0 0 -1 6 2 O-16 0 0 -2 6 2 B-10 0 0 -3 6 2 B-11 0 0 -4 6 2 Fe-54 0 0 -5 6 2 Fe-56 0 0 -6 6 2 Fe-57 0 0 -7 6 2 Fe-58 0 0 -8 6 2 Ni-58 0 0 -9 6 2 Ni-60 0 0 -10 6 2 Ni-61 0 0 -11 6 2 Ni-62 0 0 -12 6 2 Ni-64 0 0 -13 6 2 Mn-55 0 0 -14 6 2 Si-28 0 0 -15 6 2 Si-29 0 0 -16 6 2 Si-30 0 0 -17 6 2 Cr-50 0 0 -18 6 2 Cr-52 0 0 -19 6 2 Cr-53 0 0 -20 6 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 7 1 H-1 0 0 -22 7 1 O-16 0 0 -23 7 1 B-10 0 0 -24 7 1 B-11 0 0 -25 7 1 Fe-54 0 0 -26 7 1 Fe-56 0 0 -27 7 1 Fe-57 0 0 -28 7 1 Fe-58 0 0 -29 7 1 Ni-58 0 0 -30 7 1 Ni-60 0 0 -31 7 1 Ni-61 0 0 -32 7 1 Ni-62 0 0 -33 7 1 Ni-64 0 0 -34 7 1 Mn-55 0 0 -35 7 1 Si-28 0 0 -36 7 1 Si-29 0 0 -37 7 1 Si-30 0 0 -38 7 1 Cr-50 0 0 -39 7 1 Cr-52 0 0 -40 7 1 Cr-53 0 0 -41 7 1 Cr-54 0 0 -0 7 2 H-1 0 0 -1 7 2 O-16 0 0 -2 7 2 B-10 0 0 -3 7 2 B-11 0 0 -4 7 2 Fe-54 0 0 -5 7 2 Fe-56 0 0 -6 7 2 Fe-57 0 0 -7 7 2 Fe-58 0 0 -8 7 2 Ni-58 0 0 -9 7 2 Ni-60 0 0 -10 7 2 Ni-61 0 0 -11 7 2 Ni-62 0 0 -12 7 2 Ni-64 0 0 -13 7 2 Mn-55 0 0 -14 7 2 Si-28 0 0 -15 7 2 Si-29 0 0 -16 7 2 Si-30 0 0 -17 7 2 Cr-50 0 0 -18 7 2 Cr-52 0 0 -19 7 2 Cr-53 0 0 -20 7 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 7 1 H-1 0 0 -22 7 1 O-16 0 0 -23 7 1 B-10 0 0 -24 7 1 B-11 0 0 -25 7 1 Fe-54 0 0 -26 7 1 Fe-56 0 0 -27 7 1 Fe-57 0 0 -28 7 1 Fe-58 0 0 -29 7 1 Ni-58 0 0 -30 7 1 Ni-60 0 0 -31 7 1 Ni-61 0 0 -32 7 1 Ni-62 0 0 -33 7 1 Ni-64 0 0 -34 7 1 Mn-55 0 0 -35 7 1 Si-28 0 0 -36 7 1 Si-29 0 0 -37 7 1 Si-30 0 0 -38 7 1 Cr-50 0 0 -39 7 1 Cr-52 0 0 -40 7 1 Cr-53 0 0 -41 7 1 Cr-54 0 0 -0 7 2 H-1 0 0 -1 7 2 O-16 0 0 -2 7 2 B-10 0 0 -3 7 2 B-11 0 0 -4 7 2 Fe-54 0 0 -5 7 2 Fe-56 0 0 -6 7 2 Fe-57 0 0 -7 7 2 Fe-58 0 0 -8 7 2 Ni-58 0 0 -9 7 2 Ni-60 0 0 -10 7 2 Ni-61 0 0 -11 7 2 Ni-62 0 0 -12 7 2 Ni-64 0 0 -13 7 2 Mn-55 0 0 -14 7 2 Si-28 0 0 -15 7 2 Si-29 0 0 -16 7 2 Si-30 0 0 -17 7 2 Cr-50 0 0 -18 7 2 Cr-52 0 0 -19 7 2 Cr-53 0 0 -20 7 2 Cr-54 0 0 material group in group out nuclide mean std. dev. -63 7 1 1 H-1 0 0 -64 7 1 1 O-16 0 0 -65 7 1 1 B-10 0 0 -66 7 1 1 B-11 0 0 -67 7 1 1 Fe-54 0 0 -68 7 1 1 Fe-56 0 0 -69 7 1 1 Fe-57 0 0 -70 7 1 1 Fe-58 0 0 -71 7 1 1 Ni-58 0 0 -72 7 1 1 Ni-60 0 0 -73 7 1 1 Ni-61 0 0 -74 7 1 1 Ni-62 0 0 -75 7 1 1 Ni-64 0 0 -76 7 1 1 Mn-55 0 0 -77 7 1 1 Si-28 0 0 -78 7 1 1 Si-29 0 0 -79 7 1 1 Si-30 0 0 -80 7 1 1 Cr-50 0 0 -81 7 1 1 Cr-52 0 0 -82 7 1 1 Cr-53 0 0 -83 7 1 1 Cr-54 0 0 -42 7 1 2 H-1 0 0 -43 7 1 2 O-16 0 0 -44 7 1 2 B-10 0 0 -45 7 1 2 B-11 0 0 -46 7 1 2 Fe-54 0 0 -47 7 1 2 Fe-56 0 0 -48 7 1 2 Fe-57 0 0 -49 7 1 2 Fe-58 0 0 -50 7 1 2 Ni-58 0 0 -51 7 1 2 Ni-60 0 0 -52 7 1 2 Ni-61 0 0 -53 7 1 2 Ni-62 0 0 -54 7 1 2 Ni-64 0 0 -55 7 1 2 Mn-55 0 0 -56 7 1 2 Si-28 0 0 -57 7 1 2 Si-29 0 0 -58 7 1 2 Si-30 0 0 -59 7 1 2 Cr-50 0 0 -60 7 1 2 Cr-52 0 0 -61 7 1 2 Cr-53 0 0 -62 7 1 2 Cr-54 0 0 -21 7 2 1 H-1 0 0 -22 7 2 1 O-16 0 0 -23 7 2 1 B-10 0 0 -24 7 2 1 B-11 0 0 -25 7 2 1 Fe-54 0 0 -26 7 2 1 Fe-56 0 0 -27 7 2 1 Fe-57 0 0 -28 7 2 1 Fe-58 0 0 -29 7 2 1 Ni-58 0 0 -30 7 2 1 Ni-60 0 0 -31 7 2 1 Ni-61 0 0 -32 7 2 1 Ni-62 0 0 -33 7 2 1 Ni-64 0 0 -34 7 2 1 Mn-55 0 0 -35 7 2 1 Si-28 0 0 -36 7 2 1 Si-29 0 0 -37 7 2 1 Si-30 0 0 -38 7 2 1 Cr-50 0 0 -39 7 2 1 Cr-52 0 0 -40 7 2 1 Cr-53 0 0 -41 7 2 1 Cr-54 0 0 -0 7 2 2 H-1 0 0 -1 7 2 2 O-16 0 0 -2 7 2 2 B-10 0 0 -3 7 2 2 B-11 0 0 -4 7 2 2 Fe-54 0 0 -5 7 2 2 Fe-56 0 0 -6 7 2 2 Fe-57 0 0 -7 7 2 2 Fe-58 0 0 -8 7 2 2 Ni-58 0 0 -9 7 2 2 Ni-60 0 0 -10 7 2 2 Ni-61 0 0 -11 7 2 2 Ni-62 0 0 -12 7 2 2 Ni-64 0 0 -13 7 2 2 Mn-55 0 0 -14 7 2 2 Si-28 0 0 -15 7 2 2 Si-29 0 0 -16 7 2 2 Si-30 0 0 -17 7 2 2 Cr-50 0 0 -18 7 2 2 Cr-52 0 0 -19 7 2 2 Cr-53 0 0 -20 7 2 2 Cr-54 0 0 material group out nuclide mean std. dev. -21 7 1 H-1 0 0 -22 7 1 O-16 0 0 -23 7 1 B-10 0 0 -24 7 1 B-11 0 0 -25 7 1 Fe-54 0 0 -26 7 1 Fe-56 0 0 -27 7 1 Fe-57 0 0 -28 7 1 Fe-58 0 0 -29 7 1 Ni-58 0 0 -30 7 1 Ni-60 0 0 -31 7 1 Ni-61 0 0 -32 7 1 Ni-62 0 0 -33 7 1 Ni-64 0 0 -34 7 1 Mn-55 0 0 -35 7 1 Si-28 0 0 -36 7 1 Si-29 0 0 -37 7 1 Si-30 0 0 -38 7 1 Cr-50 0 0 -39 7 1 Cr-52 0 0 -40 7 1 Cr-53 0 0 -41 7 1 Cr-54 0 0 -0 7 2 H-1 0 0 -1 7 2 O-16 0 0 -2 7 2 B-10 0 0 -3 7 2 B-11 0 0 -4 7 2 Fe-54 0 0 -5 7 2 Fe-56 0 0 -6 7 2 Fe-57 0 0 -7 7 2 Fe-58 0 0 -8 7 2 Ni-58 0 0 -9 7 2 Ni-60 0 0 -10 7 2 Ni-61 0 0 -11 7 2 Ni-62 0 0 -12 7 2 Ni-64 0 0 -13 7 2 Mn-55 0 0 -14 7 2 Si-28 0 0 -15 7 2 Si-29 0 0 -16 7 2 Si-30 0 0 -17 7 2 Cr-50 0 0 -18 7 2 Cr-52 0 0 -19 7 2 Cr-53 0 0 -20 7 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 8 1 H-1 0 0 -22 8 1 O-16 0 0 -23 8 1 B-10 0 0 -24 8 1 B-11 0 0 -25 8 1 Fe-54 0 0 -26 8 1 Fe-56 0 0 -27 8 1 Fe-57 0 0 -28 8 1 Fe-58 0 0 -29 8 1 Ni-58 0 0 -30 8 1 Ni-60 0 0 -31 8 1 Ni-61 0 0 -32 8 1 Ni-62 0 0 -33 8 1 Ni-64 0 0 -34 8 1 Mn-55 0 0 -35 8 1 Si-28 0 0 -36 8 1 Si-29 0 0 -37 8 1 Si-30 0 0 -38 8 1 Cr-50 0 0 -39 8 1 Cr-52 0 0 -40 8 1 Cr-53 0 0 -41 8 1 Cr-54 0 0 -0 8 2 H-1 0 0 -1 8 2 O-16 0 0 -2 8 2 B-10 0 0 -3 8 2 B-11 0 0 -4 8 2 Fe-54 0 0 -5 8 2 Fe-56 0 0 -6 8 2 Fe-57 0 0 -7 8 2 Fe-58 0 0 -8 8 2 Ni-58 0 0 -9 8 2 Ni-60 0 0 -10 8 2 Ni-61 0 0 -11 8 2 Ni-62 0 0 -12 8 2 Ni-64 0 0 -13 8 2 Mn-55 0 0 -14 8 2 Si-28 0 0 -15 8 2 Si-29 0 0 -16 8 2 Si-30 0 0 -17 8 2 Cr-50 0 0 -18 8 2 Cr-52 0 0 -19 8 2 Cr-53 0 0 -20 8 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 8 1 H-1 0 0 -22 8 1 O-16 0 0 -23 8 1 B-10 0 0 -24 8 1 B-11 0 0 -25 8 1 Fe-54 0 0 -26 8 1 Fe-56 0 0 -27 8 1 Fe-57 0 0 -28 8 1 Fe-58 0 0 -29 8 1 Ni-58 0 0 -30 8 1 Ni-60 0 0 -31 8 1 Ni-61 0 0 -32 8 1 Ni-62 0 0 -33 8 1 Ni-64 0 0 -34 8 1 Mn-55 0 0 -35 8 1 Si-28 0 0 -36 8 1 Si-29 0 0 -37 8 1 Si-30 0 0 -38 8 1 Cr-50 0 0 -39 8 1 Cr-52 0 0 -40 8 1 Cr-53 0 0 -41 8 1 Cr-54 0 0 -0 8 2 H-1 0 0 -1 8 2 O-16 0 0 -2 8 2 B-10 0 0 -3 8 2 B-11 0 0 -4 8 2 Fe-54 0 0 -5 8 2 Fe-56 0 0 -6 8 2 Fe-57 0 0 -7 8 2 Fe-58 0 0 -8 8 2 Ni-58 0 0 -9 8 2 Ni-60 0 0 -10 8 2 Ni-61 0 0 -11 8 2 Ni-62 0 0 -12 8 2 Ni-64 0 0 -13 8 2 Mn-55 0 0 -14 8 2 Si-28 0 0 -15 8 2 Si-29 0 0 -16 8 2 Si-30 0 0 -17 8 2 Cr-50 0 0 -18 8 2 Cr-52 0 0 -19 8 2 Cr-53 0 0 -20 8 2 Cr-54 0 0 material group in group out nuclide mean std. dev. -63 8 1 1 H-1 0 0 -64 8 1 1 O-16 0 0 -65 8 1 1 B-10 0 0 -66 8 1 1 B-11 0 0 -67 8 1 1 Fe-54 0 0 -68 8 1 1 Fe-56 0 0 -69 8 1 1 Fe-57 0 0 -70 8 1 1 Fe-58 0 0 -71 8 1 1 Ni-58 0 0 -72 8 1 1 Ni-60 0 0 -73 8 1 1 Ni-61 0 0 -74 8 1 1 Ni-62 0 0 -75 8 1 1 Ni-64 0 0 -76 8 1 1 Mn-55 0 0 -77 8 1 1 Si-28 0 0 -78 8 1 1 Si-29 0 0 -79 8 1 1 Si-30 0 0 -80 8 1 1 Cr-50 0 0 -81 8 1 1 Cr-52 0 0 -82 8 1 1 Cr-53 0 0 -83 8 1 1 Cr-54 0 0 -42 8 1 2 H-1 0 0 -43 8 1 2 O-16 0 0 -44 8 1 2 B-10 0 0 -45 8 1 2 B-11 0 0 -46 8 1 2 Fe-54 0 0 -47 8 1 2 Fe-56 0 0 -48 8 1 2 Fe-57 0 0 -49 8 1 2 Fe-58 0 0 -50 8 1 2 Ni-58 0 0 -51 8 1 2 Ni-60 0 0 -52 8 1 2 Ni-61 0 0 -53 8 1 2 Ni-62 0 0 -54 8 1 2 Ni-64 0 0 -55 8 1 2 Mn-55 0 0 -56 8 1 2 Si-28 0 0 -57 8 1 2 Si-29 0 0 -58 8 1 2 Si-30 0 0 -59 8 1 2 Cr-50 0 0 -60 8 1 2 Cr-52 0 0 -61 8 1 2 Cr-53 0 0 -62 8 1 2 Cr-54 0 0 -21 8 2 1 H-1 0 0 -22 8 2 1 O-16 0 0 -23 8 2 1 B-10 0 0 -24 8 2 1 B-11 0 0 -25 8 2 1 Fe-54 0 0 -26 8 2 1 Fe-56 0 0 -27 8 2 1 Fe-57 0 0 -28 8 2 1 Fe-58 0 0 -29 8 2 1 Ni-58 0 0 -30 8 2 1 Ni-60 0 0 -31 8 2 1 Ni-61 0 0 -32 8 2 1 Ni-62 0 0 -33 8 2 1 Ni-64 0 0 -34 8 2 1 Mn-55 0 0 -35 8 2 1 Si-28 0 0 -36 8 2 1 Si-29 0 0 -37 8 2 1 Si-30 0 0 -38 8 2 1 Cr-50 0 0 -39 8 2 1 Cr-52 0 0 -40 8 2 1 Cr-53 0 0 -41 8 2 1 Cr-54 0 0 -0 8 2 2 H-1 0 0 -1 8 2 2 O-16 0 0 -2 8 2 2 B-10 0 0 -3 8 2 2 B-11 0 0 -4 8 2 2 Fe-54 0 0 -5 8 2 2 Fe-56 0 0 -6 8 2 2 Fe-57 0 0 -7 8 2 2 Fe-58 0 0 -8 8 2 2 Ni-58 0 0 -9 8 2 2 Ni-60 0 0 -10 8 2 2 Ni-61 0 0 -11 8 2 2 Ni-62 0 0 -12 8 2 2 Ni-64 0 0 -13 8 2 2 Mn-55 0 0 -14 8 2 2 Si-28 0 0 -15 8 2 2 Si-29 0 0 -16 8 2 2 Si-30 0 0 -17 8 2 2 Cr-50 0 0 -18 8 2 2 Cr-52 0 0 -19 8 2 2 Cr-53 0 0 -20 8 2 2 Cr-54 0 0 material group out nuclide mean std. dev. -21 8 1 H-1 0 0 -22 8 1 O-16 0 0 -23 8 1 B-10 0 0 -24 8 1 B-11 0 0 -25 8 1 Fe-54 0 0 -26 8 1 Fe-56 0 0 -27 8 1 Fe-57 0 0 -28 8 1 Fe-58 0 0 -29 8 1 Ni-58 0 0 -30 8 1 Ni-60 0 0 -31 8 1 Ni-61 0 0 -32 8 1 Ni-62 0 0 -33 8 1 Ni-64 0 0 -34 8 1 Mn-55 0 0 -35 8 1 Si-28 0 0 -36 8 1 Si-29 0 0 -37 8 1 Si-30 0 0 -38 8 1 Cr-50 0 0 -39 8 1 Cr-52 0 0 -40 8 1 Cr-53 0 0 -41 8 1 Cr-54 0 0 -0 8 2 H-1 0 0 -1 8 2 O-16 0 0 -2 8 2 B-10 0 0 -3 8 2 B-11 0 0 -4 8 2 Fe-54 0 0 -5 8 2 Fe-56 0 0 -6 8 2 Fe-57 0 0 -7 8 2 Fe-58 0 0 -8 8 2 Ni-58 0 0 -9 8 2 Ni-60 0 0 -10 8 2 Ni-61 0 0 -11 8 2 Ni-62 0 0 -12 8 2 Ni-64 0 0 -13 8 2 Mn-55 0 0 -14 8 2 Si-28 0 0 -15 8 2 Si-29 0 0 -16 8 2 Si-30 0 0 -17 8 2 Cr-50 0 0 -18 8 2 Cr-52 0 0 -19 8 2 Cr-53 0 0 -20 8 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 9 1 H-1 0.106160 0.179178 -22 9 1 O-16 0.272020 0.171699 -23 9 1 B-10 0.000000 0.000000 -24 9 1 B-11 0.000000 0.000000 -25 9 1 Fe-54 0.000000 0.000000 -26 9 1 Fe-56 0.000000 0.000000 -27 9 1 Fe-57 0.000000 0.000000 -28 9 1 Fe-58 0.000000 0.000000 -29 9 1 Ni-58 0.000000 0.000000 -30 9 1 Ni-60 0.000000 0.000000 -31 9 1 Ni-61 0.000000 0.000000 -32 9 1 Ni-62 0.000000 0.000000 -33 9 1 Ni-64 0.000000 0.000000 -34 9 1 Mn-55 0.085133 0.082479 -35 9 1 Si-28 0.000000 0.000000 -36 9 1 Si-29 0.000000 0.000000 -37 9 1 Si-30 0.000000 0.000000 -38 9 1 Cr-50 0.000000 0.000000 -39 9 1 Cr-52 0.000000 0.000000 -40 9 1 Cr-53 0.040723 0.079827 -41 9 1 Cr-54 0.000000 0.000000 -0 9 2 H-1 1.417955 2.158027 -1 9 2 O-16 0.000000 0.000000 -2 9 2 B-10 0.269141 0.380622 -3 9 2 B-11 0.000000 0.000000 -4 9 2 Fe-54 0.000000 0.000000 -5 9 2 Fe-56 0.000000 0.000000 -6 9 2 Fe-57 0.000000 0.000000 -7 9 2 Fe-58 0.000000 0.000000 -8 9 2 Ni-58 0.000000 0.000000 -9 9 2 Ni-60 0.000000 0.000000 -10 9 2 Ni-61 0.000000 0.000000 -11 9 2 Ni-62 0.000000 0.000000 -12 9 2 Ni-64 0.000000 0.000000 -13 9 2 Mn-55 0.000000 0.000000 -14 9 2 Si-28 0.000000 0.000000 -15 9 2 Si-29 0.000000 0.000000 -16 9 2 Si-30 0.000000 0.000000 -17 9 2 Cr-50 0.000000 0.000000 -18 9 2 Cr-52 0.000000 0.000000 -19 9 2 Cr-53 0.000000 0.000000 -20 9 2 Cr-54 0.000000 0.000000 material group in nuclide mean std. dev. -21 9 1 H-1 0 0 -22 9 1 O-16 0 0 -23 9 1 B-10 0 0 -24 9 1 B-11 0 0 -25 9 1 Fe-54 0 0 -26 9 1 Fe-56 0 0 -27 9 1 Fe-57 0 0 -28 9 1 Fe-58 0 0 -29 9 1 Ni-58 0 0 -30 9 1 Ni-60 0 0 -31 9 1 Ni-61 0 0 -32 9 1 Ni-62 0 0 -33 9 1 Ni-64 0 0 -34 9 1 Mn-55 0 0 -35 9 1 Si-28 0 0 -36 9 1 Si-29 0 0 -37 9 1 Si-30 0 0 -38 9 1 Cr-50 0 0 -39 9 1 Cr-52 0 0 -40 9 1 Cr-53 0 0 -41 9 1 Cr-54 0 0 -0 9 2 H-1 0 0 -1 9 2 O-16 0 0 -2 9 2 B-10 0 0 -3 9 2 B-11 0 0 -4 9 2 Fe-54 0 0 -5 9 2 Fe-56 0 0 -6 9 2 Fe-57 0 0 -7 9 2 Fe-58 0 0 -8 9 2 Ni-58 0 0 -9 9 2 Ni-60 0 0 -10 9 2 Ni-61 0 0 -11 9 2 Ni-62 0 0 -12 9 2 Ni-64 0 0 -13 9 2 Mn-55 0 0 -14 9 2 Si-28 0 0 -15 9 2 Si-29 0 0 -16 9 2 Si-30 0 0 -17 9 2 Cr-50 0 0 -18 9 2 Cr-52 0 0 -19 9 2 Cr-53 0 0 -20 9 2 Cr-54 0 0 material group in group out nuclide mean std. dev. -63 9 1 1 H-1 0.106160 0.179178 -64 9 1 1 O-16 0.272020 0.171699 -65 9 1 1 B-10 0.000000 0.000000 -66 9 1 1 B-11 0.000000 0.000000 -67 9 1 1 Fe-54 0.000000 0.000000 -68 9 1 1 Fe-56 0.000000 0.000000 -69 9 1 1 Fe-57 0.000000 0.000000 -70 9 1 1 Fe-58 0.000000 0.000000 -71 9 1 1 Ni-58 0.000000 0.000000 -72 9 1 1 Ni-60 0.000000 0.000000 -73 9 1 1 Ni-61 0.000000 0.000000 -74 9 1 1 Ni-62 0.000000 0.000000 -75 9 1 1 Ni-64 0.000000 0.000000 -76 9 1 1 Mn-55 0.085133 0.082479 -77 9 1 1 Si-28 0.000000 0.000000 -78 9 1 1 Si-29 0.000000 0.000000 -79 9 1 1 Si-30 0.000000 0.000000 -80 9 1 1 Cr-50 0.000000 0.000000 -81 9 1 1 Cr-52 0.000000 0.000000 -82 9 1 1 Cr-53 0.040723 0.079827 -83 9 1 1 Cr-54 0.000000 0.000000 -42 9 1 2 H-1 0.000000 0.000000 -43 9 1 2 O-16 0.000000 0.000000 -44 9 1 2 B-10 0.000000 0.000000 -45 9 1 2 B-11 0.000000 0.000000 -46 9 1 2 Fe-54 0.000000 0.000000 -47 9 1 2 Fe-56 0.000000 0.000000 -48 9 1 2 Fe-57 0.000000 0.000000 -49 9 1 2 Fe-58 0.000000 0.000000 -50 9 1 2 Ni-58 0.000000 0.000000 -51 9 1 2 Ni-60 0.000000 0.000000 -52 9 1 2 Ni-61 0.000000 0.000000 -53 9 1 2 Ni-62 0.000000 0.000000 -54 9 1 2 Ni-64 0.000000 0.000000 -55 9 1 2 Mn-55 0.000000 0.000000 -56 9 1 2 Si-28 0.000000 0.000000 -57 9 1 2 Si-29 0.000000 0.000000 -58 9 1 2 Si-30 0.000000 0.000000 -59 9 1 2 Cr-50 0.000000 0.000000 -60 9 1 2 Cr-52 0.000000 0.000000 -61 9 1 2 Cr-53 0.000000 0.000000 -62 9 1 2 Cr-54 0.000000 0.000000 -21 9 2 1 H-1 0.000000 0.000000 -22 9 2 1 O-16 0.000000 0.000000 -23 9 2 1 B-10 0.000000 0.000000 -24 9 2 1 B-11 0.000000 0.000000 -25 9 2 1 Fe-54 0.000000 0.000000 -26 9 2 1 Fe-56 0.000000 0.000000 -27 9 2 1 Fe-57 0.000000 0.000000 -28 9 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-16 9 2 2 Si-30 0.000000 0.000000 -17 9 2 2 Cr-50 0.000000 0.000000 -18 9 2 2 Cr-52 0.000000 0.000000 -19 9 2 2 Cr-53 0.000000 0.000000 -20 9 2 2 Cr-54 0.000000 0.000000 material group out nuclide mean std. dev. -21 9 1 H-1 0 0 -22 9 1 O-16 0 0 -23 9 1 B-10 0 0 -24 9 1 B-11 0 0 -25 9 1 Fe-54 0 0 -26 9 1 Fe-56 0 0 -27 9 1 Fe-57 0 0 -28 9 1 Fe-58 0 0 -29 9 1 Ni-58 0 0 -30 9 1 Ni-60 0 0 -31 9 1 Ni-61 0 0 -32 9 1 Ni-62 0 0 -33 9 1 Ni-64 0 0 -34 9 1 Mn-55 0 0 -35 9 1 Si-28 0 0 -36 9 1 Si-29 0 0 -37 9 1 Si-30 0 0 -38 9 1 Cr-50 0 0 -39 9 1 Cr-52 0 0 -40 9 1 Cr-53 0 0 -41 9 1 Cr-54 0 0 -0 9 2 H-1 0 0 -1 9 2 O-16 0 0 -2 9 2 B-10 0 0 -3 9 2 B-11 0 0 -4 9 2 Fe-54 0 0 -5 9 2 Fe-56 0 0 -6 9 2 Fe-57 0 0 -7 9 2 Fe-58 0 0 -8 9 2 Ni-58 0 0 -9 9 2 Ni-60 0 0 -10 9 2 Ni-61 0 0 -11 9 2 Ni-62 0 0 -12 9 2 Ni-64 0 0 -13 9 2 Mn-55 0 0 -14 9 2 Si-28 0 0 -15 9 2 Si-29 0 0 -16 9 2 Si-30 0 0 -17 9 2 Cr-50 0 0 -18 9 2 Cr-52 0 0 -19 9 2 Cr-53 0 0 -20 9 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 10 1 H-1 0 0 -22 10 1 O-16 0 0 -23 10 1 B-10 0 0 -24 10 1 B-11 0 0 -25 10 1 Fe-54 0 0 -26 10 1 Fe-56 0 0 -27 10 1 Fe-57 0 0 -28 10 1 Fe-58 0 0 -29 10 1 Ni-58 0 0 -30 10 1 Ni-60 0 0 -31 10 1 Ni-61 0 0 -32 10 1 Ni-62 0 0 -33 10 1 Ni-64 0 0 -34 10 1 Mn-55 0 0 -35 10 1 Si-28 0 0 -36 10 1 Si-29 0 0 -37 10 1 Si-30 0 0 -38 10 1 Cr-50 0 0 -39 10 1 Cr-52 0 0 -40 10 1 Cr-53 0 0 -41 10 1 Cr-54 0 0 -0 10 2 H-1 0 0 -1 10 2 O-16 0 0 -2 10 2 B-10 0 0 -3 10 2 B-11 0 0 -4 10 2 Fe-54 0 0 -5 10 2 Fe-56 0 0 -6 10 2 Fe-57 0 0 -7 10 2 Fe-58 0 0 -8 10 2 Ni-58 0 0 -9 10 2 Ni-60 0 0 -10 10 2 Ni-61 0 0 -11 10 2 Ni-62 0 0 -12 10 2 Ni-64 0 0 -13 10 2 Mn-55 0 0 -14 10 2 Si-28 0 0 -15 10 2 Si-29 0 0 -16 10 2 Si-30 0 0 -17 10 2 Cr-50 0 0 -18 10 2 Cr-52 0 0 -19 10 2 Cr-53 0 0 -20 10 2 Cr-54 0 0 material group in nuclide mean std. dev. -21 10 1 H-1 0 0 -22 10 1 O-16 0 0 -23 10 1 B-10 0 0 -24 10 1 B-11 0 0 -25 10 1 Fe-54 0 0 -26 10 1 Fe-56 0 0 -27 10 1 Fe-57 0 0 -28 10 1 Fe-58 0 0 -29 10 1 Ni-58 0 0 -30 10 1 Ni-60 0 0 -31 10 1 Ni-61 0 0 -32 10 1 Ni-62 0 0 -33 10 1 Ni-64 0 0 -34 10 1 Mn-55 0 0 -35 10 1 Si-28 0 0 -36 10 1 Si-29 0 0 -37 10 1 Si-30 0 0 -38 10 1 Cr-50 0 0 -39 10 1 Cr-52 0 0 -40 10 1 Cr-53 0 0 -41 10 1 Cr-54 0 0 -0 10 2 H-1 0 0 -1 10 2 O-16 0 0 -2 10 2 B-10 0 0 -3 10 2 B-11 0 0 -4 10 2 Fe-54 0 0 -5 10 2 Fe-56 0 0 -6 10 2 Fe-57 0 0 -7 10 2 Fe-58 0 0 -8 10 2 Ni-58 0 0 -9 10 2 Ni-60 0 0 -10 10 2 Ni-61 0 0 -11 10 2 Ni-62 0 0 -12 10 2 Ni-64 0 0 -13 10 2 Mn-55 0 0 -14 10 2 Si-28 0 0 -15 10 2 Si-29 0 0 -16 10 2 Si-30 0 0 -17 10 2 Cr-50 0 0 -18 10 2 Cr-52 0 0 -19 10 2 Cr-53 0 0 -20 10 2 Cr-54 0 0 material group in group out nuclide mean std. dev. -63 10 1 1 H-1 0 0 -64 10 1 1 O-16 0 0 -65 10 1 1 B-10 0 0 -66 10 1 1 B-11 0 0 -67 10 1 1 Fe-54 0 0 -68 10 1 1 Fe-56 0 0 -69 10 1 1 Fe-57 0 0 -70 10 1 1 Fe-58 0 0 -71 10 1 1 Ni-58 0 0 -72 10 1 1 Ni-60 0 0 -73 10 1 1 Ni-61 0 0 -74 10 1 1 Ni-62 0 0 -75 10 1 1 Ni-64 0 0 -76 10 1 1 Mn-55 0 0 -77 10 1 1 Si-28 0 0 -78 10 1 1 Si-29 0 0 -79 10 1 1 Si-30 0 0 -80 10 1 1 Cr-50 0 0 -81 10 1 1 Cr-52 0 0 -82 10 1 1 Cr-53 0 0 -83 10 1 1 Cr-54 0 0 -42 10 1 2 H-1 0 0 -43 10 1 2 O-16 0 0 -44 10 1 2 B-10 0 0 -45 10 1 2 B-11 0 0 -46 10 1 2 Fe-54 0 0 -47 10 1 2 Fe-56 0 0 -48 10 1 2 Fe-57 0 0 -49 10 1 2 Fe-58 0 0 -50 10 1 2 Ni-58 0 0 -51 10 1 2 Ni-60 0 0 -52 10 1 2 Ni-61 0 0 -53 10 1 2 Ni-62 0 0 -54 10 1 2 Ni-64 0 0 -55 10 1 2 Mn-55 0 0 -56 10 1 2 Si-28 0 0 -57 10 1 2 Si-29 0 0 -58 10 1 2 Si-30 0 0 -59 10 1 2 Cr-50 0 0 -60 10 1 2 Cr-52 0 0 -61 10 1 2 Cr-53 0 0 -62 10 1 2 Cr-54 0 0 -21 10 2 1 H-1 0 0 -22 10 2 1 O-16 0 0 -23 10 2 1 B-10 0 0 -24 10 2 1 B-11 0 0 -25 10 2 1 Fe-54 0 0 -26 10 2 1 Fe-56 0 0 -27 10 2 1 Fe-57 0 0 -28 10 2 1 Fe-58 0 0 -29 10 2 1 Ni-58 0 0 -30 10 2 1 Ni-60 0 0 -31 10 2 1 Ni-61 0 0 -32 10 2 1 Ni-62 0 0 -33 10 2 1 Ni-64 0 0 -34 10 2 1 Mn-55 0 0 -35 10 2 1 Si-28 0 0 -36 10 2 1 Si-29 0 0 -37 10 2 1 Si-30 0 0 -38 10 2 1 Cr-50 0 0 -39 10 2 1 Cr-52 0 0 -40 10 2 1 Cr-53 0 0 -41 10 2 1 Cr-54 0 0 -0 10 2 2 H-1 0 0 -1 10 2 2 O-16 0 0 -2 10 2 2 B-10 0 0 -3 10 2 2 B-11 0 0 -4 10 2 2 Fe-54 0 0 -5 10 2 2 Fe-56 0 0 -6 10 2 2 Fe-57 0 0 -7 10 2 2 Fe-58 0 0 -8 10 2 2 Ni-58 0 0 -9 10 2 2 Ni-60 0 0 -10 10 2 2 Ni-61 0 0 -11 10 2 2 Ni-62 0 0 -12 10 2 2 Ni-64 0 0 -13 10 2 2 Mn-55 0 0 -14 10 2 2 Si-28 0 0 -15 10 2 2 Si-29 0 0 -16 10 2 2 Si-30 0 0 -17 10 2 2 Cr-50 0 0 -18 10 2 2 Cr-52 0 0 -19 10 2 2 Cr-53 0 0 -20 10 2 2 Cr-54 0 0 material group out nuclide mean std. dev. -21 10 1 H-1 0 0 -22 10 1 O-16 0 0 -23 10 1 B-10 0 0 -24 10 1 B-11 0 0 -25 10 1 Fe-54 0 0 -26 10 1 Fe-56 0 0 -27 10 1 Fe-57 0 0 -28 10 1 Fe-58 0 0 -29 10 1 Ni-58 0 0 -30 10 1 Ni-60 0 0 -31 10 1 Ni-61 0 0 -32 10 1 Ni-62 0 0 -33 10 1 Ni-64 0 0 -34 10 1 Mn-55 0 0 -35 10 1 Si-28 0 0 -36 10 1 Si-29 0 0 -37 10 1 Si-30 0 0 -38 10 1 Cr-50 0 0 -39 10 1 Cr-52 0 0 -40 10 1 Cr-53 0 0 -41 10 1 Cr-54 0 0 -0 10 2 H-1 0 0 -1 10 2 O-16 0 0 -2 10 2 B-10 0 0 -3 10 2 B-11 0 0 -4 10 2 Fe-54 0 0 -5 10 2 Fe-56 0 0 -6 10 2 Fe-57 0 0 -7 10 2 Fe-58 0 0 -8 10 2 Ni-58 0 0 -9 10 2 Ni-60 0 0 -10 10 2 Ni-61 0 0 -11 10 2 Ni-62 0 0 -12 10 2 Ni-64 0 0 -13 10 2 Mn-55 0 0 -14 10 2 Si-28 0 0 -15 10 2 Si-29 0 0 -16 10 2 Si-30 0 0 -17 10 2 Cr-50 0 0 -18 10 2 Cr-52 0 0 -19 10 2 Cr-53 0 0 -20 10 2 Cr-54 0 0 material group in nuclide mean std. dev. -9 11 1 H-1 0.138558 0.260695 -10 11 1 O-16 0.042575 0.049271 -11 11 1 B-10 0.000000 0.000000 -12 11 1 B-11 0.000000 0.000000 -13 11 1 Zr-90 0.041034 0.049102 -14 11 1 Zr-91 0.027328 0.021092 -15 11 1 Zr-92 0.009788 0.009282 -16 11 1 Zr-94 0.043543 0.036697 -17 11 1 Zr-96 0.000000 0.000000 -0 11 2 H-1 0.824153 0.917955 -1 11 2 O-16 0.041986 0.060727 -2 11 2 B-10 0.048216 0.042726 -3 11 2 B-11 0.000000 0.000000 -4 11 2 Zr-90 0.048596 0.067712 -5 11 2 Zr-91 0.000000 0.000000 -6 11 2 Zr-92 0.000000 0.000000 -7 11 2 Zr-94 0.043195 0.041363 -8 11 2 Zr-96 0.000000 0.000000 material group in nuclide mean std. dev. -9 11 1 H-1 0 0 -10 11 1 O-16 0 0 -11 11 1 B-10 0 0 -12 11 1 B-11 0 0 -13 11 1 Zr-90 0 0 -14 11 1 Zr-91 0 0 -15 11 1 Zr-92 0 0 -16 11 1 Zr-94 0 0 -17 11 1 Zr-96 0 0 -0 11 2 H-1 0 0 -1 11 2 O-16 0 0 -2 11 2 B-10 0 0 -3 11 2 B-11 0 0 -4 11 2 Zr-90 0 0 -5 11 2 Zr-91 0 0 -6 11 2 Zr-92 0 0 -7 11 2 Zr-94 0 0 -8 11 2 Zr-96 0 0 material group in group out nuclide mean std. dev. -27 11 1 1 H-1 0.111411 0.247294 -28 11 1 1 O-16 0.042575 0.049271 -29 11 1 1 B-10 0.000000 0.000000 -30 11 1 1 B-11 0.000000 0.000000 -31 11 1 1 Zr-90 0.041034 0.049102 -32 11 1 1 Zr-91 0.027328 0.021092 -33 11 1 1 Zr-92 0.009788 0.009282 -34 11 1 1 Zr-94 0.043543 0.036697 -35 11 1 1 Zr-96 0.000000 0.000000 -18 11 1 2 H-1 0.027147 0.020009 -19 11 1 2 O-16 0.000000 0.000000 -20 11 1 2 B-10 0.000000 0.000000 -21 11 1 2 B-11 0.000000 0.000000 -22 11 1 2 Zr-90 0.000000 0.000000 -23 11 1 2 Zr-91 0.000000 0.000000 -24 11 1 2 Zr-92 0.000000 0.000000 -25 11 1 2 Zr-94 0.000000 0.000000 -26 11 1 2 Zr-96 0.000000 0.000000 -9 11 2 1 H-1 0.000000 0.000000 -10 11 2 1 O-16 0.000000 0.000000 -11 11 2 1 B-10 0.000000 0.000000 -12 11 2 1 B-11 0.000000 0.000000 -13 11 2 1 Zr-90 0.000000 0.000000 -14 11 2 1 Zr-91 0.000000 0.000000 -15 11 2 1 Zr-92 0.000000 0.000000 -16 11 2 1 Zr-94 0.000000 0.000000 -17 11 2 1 Zr-96 0.000000 0.000000 -0 11 2 2 H-1 0.824153 0.917955 -1 11 2 2 O-16 0.041986 0.060727 -2 11 2 2 B-10 0.000000 0.000000 -3 11 2 2 B-11 0.000000 0.000000 -4 11 2 2 Zr-90 0.048596 0.067712 -5 11 2 2 Zr-91 0.000000 0.000000 -6 11 2 2 Zr-92 0.000000 0.000000 -7 11 2 2 Zr-94 0.043195 0.041363 -8 11 2 2 Zr-96 0.000000 0.000000 material group out nuclide mean std. dev. -9 11 1 H-1 0 0 -10 11 1 O-16 0 0 -11 11 1 B-10 0 0 -12 11 1 B-11 0 0 -13 11 1 Zr-90 0 0 -14 11 1 Zr-91 0 0 -15 11 1 Zr-92 0 0 -16 11 1 Zr-94 0 0 -17 11 1 Zr-96 0 0 -0 11 2 H-1 0 0 -1 11 2 O-16 0 0 -2 11 2 B-10 0 0 -3 11 2 B-11 0 0 -4 11 2 Zr-90 0 0 -5 11 2 Zr-91 0 0 -6 11 2 Zr-92 0 0 -7 11 2 Zr-94 0 0 -8 11 2 Zr-96 0 0 material group in nuclide mean std. dev. -9 12 1 H-1 0.151924 0.200147 -10 12 1 O-16 0.039280 0.026086 -11 12 1 B-10 0.000000 0.000000 -12 12 1 B-11 0.000000 0.000000 -13 12 1 Zr-90 0.017578 0.022079 -14 12 1 Zr-91 0.039984 0.025285 -15 12 1 Zr-92 0.001172 0.006230 -16 12 1 Zr-94 0.001668 0.005966 -17 12 1 Zr-96 0.004328 0.005325 -0 12 2 H-1 0.942412 0.866849 -1 12 2 O-16 0.047438 0.048161 -2 12 2 B-10 0.041655 0.031202 -3 12 2 B-11 0.000000 0.000000 -4 12 2 Zr-90 0.021193 0.017456 -5 12 2 Zr-91 0.007901 0.009268 -6 12 2 Zr-92 0.009422 0.012802 -7 12 2 Zr-94 0.043324 0.027551 -8 12 2 Zr-96 0.000000 0.000000 material group in nuclide mean std. dev. -9 12 1 H-1 0 0 -10 12 1 O-16 0 0 -11 12 1 B-10 0 0 -12 12 1 B-11 0 0 -13 12 1 Zr-90 0 0 -14 12 1 Zr-91 0 0 -15 12 1 Zr-92 0 0 -16 12 1 Zr-94 0 0 -17 12 1 Zr-96 0 0 -0 12 2 H-1 0 0 -1 12 2 O-16 0 0 -2 12 2 B-10 0 0 -3 12 2 B-11 0 0 -4 12 2 Zr-90 0 0 -5 12 2 Zr-91 0 0 -6 12 2 Zr-92 0 0 -7 12 2 Zr-94 0 0 -8 12 2 Zr-96 0 0 material group in group out nuclide mean std. dev. -27 12 1 1 H-1 0.122301 0.187298 -28 12 1 1 O-16 0.039280 0.026086 -29 12 1 1 B-10 0.000000 0.000000 -30 12 1 1 B-11 0.000000 0.000000 -31 12 1 1 Zr-90 0.017578 0.022079 -32 12 1 1 Zr-91 0.039984 0.025285 -33 12 1 1 Zr-92 0.001172 0.006230 -34 12 1 1 Zr-94 0.001668 0.005966 -35 12 1 1 Zr-96 0.004328 0.005325 -18 12 1 2 H-1 0.029622 0.017760 -19 12 1 2 O-16 0.000000 0.000000 -20 12 1 2 B-10 0.000000 0.000000 -21 12 1 2 B-11 0.000000 0.000000 -22 12 1 2 Zr-90 0.000000 0.000000 -23 12 1 2 Zr-91 0.000000 0.000000 -24 12 1 2 Zr-92 0.000000 0.000000 -25 12 1 2 Zr-94 0.000000 0.000000 -26 12 1 2 Zr-96 0.000000 0.000000 -9 12 2 1 H-1 0.000000 0.000000 -10 12 2 1 O-16 0.000000 0.000000 -11 12 2 1 B-10 0.000000 0.000000 -12 12 2 1 B-11 0.000000 0.000000 -13 12 2 1 Zr-90 0.000000 0.000000 -14 12 2 1 Zr-91 0.000000 0.000000 -15 12 2 1 Zr-92 0.000000 0.000000 -16 12 2 1 Zr-94 0.000000 0.000000 -17 12 2 1 Zr-96 0.000000 0.000000 -0 12 2 2 H-1 0.942412 0.866849 -1 12 2 2 O-16 0.047438 0.048161 -2 12 2 2 B-10 0.000000 0.000000 -3 12 2 2 B-11 0.000000 0.000000 -4 12 2 2 Zr-90 0.021193 0.017456 -5 12 2 2 Zr-91 0.007901 0.009268 -6 12 2 2 Zr-92 0.009422 0.012802 -7 12 2 2 Zr-94 0.043324 0.027551 -8 12 2 2 Zr-96 0.000000 0.000000 material group out nuclide mean std. dev. -9 12 1 H-1 0 0 -10 12 1 O-16 0 0 -11 12 1 B-10 0 0 -12 12 1 B-11 0 0 -13 12 1 Zr-90 0 0 -14 12 1 Zr-91 0 0 -15 12 1 Zr-92 0 0 -16 12 1 Zr-94 0 0 -17 12 1 Zr-96 0 0 -0 12 2 H-1 0 0 -1 12 2 O-16 0 0 -2 12 2 B-10 0 0 -3 12 2 B-11 0 0 -4 12 2 Zr-90 0 0 -5 12 2 Zr-91 0 0 -6 12 2 Zr-92 0 0 -7 12 2 Zr-94 0 0 -8 12 2 Zr-96 0 0 \ No newline at end of file +a631b8a347f344d822e6300ed2576caa7c05a74daedeb4aaaabfb89570942cff1bbd47ad7f81306e668e12266404f7abdcf680fdfeb5a4835579892e32bf57e8 \ No newline at end of file diff --git a/tests/test_mgxs_library_nuclides/test_mgxs_library_nuclides.py b/tests/test_mgxs_library_nuclides/test_mgxs_library_nuclides.py index 173043cf0..da613d78a 100644 --- a/tests/test_mgxs_library_nuclides/test_mgxs_library_nuclides.py +++ b/tests/test_mgxs_library_nuclides/test_mgxs_library_nuclides.py @@ -6,48 +6,45 @@ import glob import hashlib sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness +from input_set import PinCellInputSet import openmc import openmc.mgxs class MGXSTestHarness(PyAPITestHarness): def _build_inputs(self): - - # The openmc.mgxs module needs a summary.h5 file - self._input_set.settings.output = {'summary': True} + # Set the input set to use the pincell model + self._input_set = PinCellInputSet() # Generate inputs using parent class routine super(MGXSTestHarness, self)._build_inputs() # Initialize a two-group structure - energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, 20.]) + energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6, + 20.]) # Initialize MGXS Library for a few cross section types - self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry.geometry) + self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry) self.mgxs_lib.by_nuclide = True - self.mgxs_lib.mgxs_types = ['transport', 'nu-fission', - 'nu-scatter matrix', 'chi'] + # Test all MGXS types + self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES self.mgxs_lib.energy_groups = energy_groups + self.mgxs_lib.legendre_order = 3 self.mgxs_lib.domain_type = 'material' self.mgxs_lib.build_library() # Initialize a tallies file - self._input_set.tallies = openmc.TalliesFile() + self._input_set.tallies = openmc.Tallies() self.mgxs_lib.add_to_tallies_file(self._input_set.tallies, merge=False) self._input_set.tallies.export_to_xml() - def _get_results(self, hash_output=False): + def _get_results(self, hash_output=True): """Digest info in the statepoint and return as a string.""" # Read the statepoint file. statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the MGXS library from the statepoint self.mgxs_lib.load_from_statepoint(sp) @@ -57,7 +54,7 @@ class MGXSTestHarness(PyAPITestHarness): for mgxs_type in self.mgxs_lib.mgxs_types: mgxs = self.mgxs_lib.get_mgxs(domain, mgxs_type) df = mgxs.get_pandas_dataframe() - outstr += df.to_string() + outstr += df.to_string() + '\n' # Hash the results if necessary if hash_output: diff --git a/tests/test_natural_element/results_true.dat b/tests/test_natural_element/results_true.dat index 1c8668e12..cc4a12f74 100644 --- a/tests/test_natural_element/results_true.dat +++ b/tests/test_natural_element/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.013112E+00 2.551515E-02 +1.034427E+00 1.583807E-02 diff --git a/tests/test_output/results_true.dat b/tests/test_output/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_output/results_true.dat +++ b/tests/test_output/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_particle_restart_eigval/results_true.dat b/tests/test_particle_restart_eigval/results_true.dat index f34397853..2bc463293 100644 --- a/tests/test_particle_restart_eigval/results_true.dat +++ b/tests/test_particle_restart_eigval/results_true.dat @@ -1,16 +1,16 @@ current batch: -9.000000E+00 +1.000000E+01 current gen: 1.000000E+00 particle id: -5.550000E+02 +1.030000E+03 run mode: k-eigenvalue particle weight: 1.000000E+00 particle energy: -2.831611E-01 +3.158576E+00 particle xyz: -4.973847E+01 6.971699E+00 -5.201827E+01 +5.846530E+01 -3.717881E+01 -3.787515E+00 particle uvw: -6.945105E-01 6.295355E-01 -3.483393E-01 +6.197114E-01 -2.450461E-01 -7.455939E-01 diff --git a/tests/test_particle_restart_eigval/test_particle_restart_eigval.py b/tests/test_particle_restart_eigval/test_particle_restart_eigval.py index 139cb2b9f..59f76d93b 100644 --- a/tests/test_particle_restart_eigval/test_particle_restart_eigval.py +++ b/tests/test_particle_restart_eigval/test_particle_restart_eigval.py @@ -7,5 +7,5 @@ from testing_harness import ParticleRestartTestHarness if __name__ == '__main__': - harness = ParticleRestartTestHarness('particle_9_555.*') + harness = ParticleRestartTestHarness('particle_10_1030.*') harness.main() diff --git a/tests/test_periodic/inputs_true.dat b/tests/test_periodic/inputs_true.dat new file mode 100644 index 000000000..d50d0b859 --- /dev/null +++ b/tests/test_periodic/inputs_true.dat @@ -0,0 +1 @@ +af589996f2930337afe34ba9894098ff5efe3b29b6e927117220b718bf29b630ffdbc931754d465a8e8100125a8aa997dbe10aab322b43f69d59710573996a6d \ No newline at end of file diff --git a/tests/test_periodic/results_true.dat b/tests/test_periodic/results_true.dat new file mode 100644 index 000000000..b0bdb22c7 --- /dev/null +++ b/tests/test_periodic/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +1.040109E+00 6.527490E-02 diff --git a/tests/test_periodic/tallies.xml b/tests/test_periodic/tallies.xml new file mode 100644 index 000000000..595d7c0dd --- /dev/null +++ b/tests/test_periodic/tallies.xml @@ -0,0 +1,14 @@ + + + + regular + -200. -1e50 + 200. 1e50 + 50 1 + + + collision + + fission + + diff --git a/tests/test_periodic/test_periodic.py b/tests/test_periodic/test_periodic.py new file mode 100644 index 000000000..558514575 --- /dev/null +++ b/tests/test_periodic/test_periodic.py @@ -0,0 +1,60 @@ +#!/usr/bin/env python + +import os +import sys +sys.path.insert(0, os.pardir) +from testing_harness import PyAPITestHarness +import openmc + + +class PeriodicTest(PyAPITestHarness): + def _build_inputs(self): + # Define materials + water = openmc.Material(1) + water.add_nuclide('H-1', 2.0) + water.add_nuclide('O-16', 1.0) + water.add_s_alpha_beta('HH2O', '71t') + water.set_density('g/cc', 1.0) + + fuel = openmc.Material(2) + fuel.add_nuclide('U-235', 1.0) + fuel.set_density('g/cc', 4.5) + + materials = openmc.Materials((water, fuel)) + materials.default_xs = '71c' + materials.export_to_xml() + + # Define geometry + x_min = openmc.XPlane(1, x0=-5., boundary_type='periodic') + x_max = openmc.XPlane(2, x0=5., boundary_type='periodic') + x_max.periodic_surface = x_min + + y_min = openmc.YPlane(3, y0=-5., boundary_type='periodic') + y_max = openmc.YPlane(4, y0=5., boundary_type='periodic') + + z_min = openmc.ZPlane(5, z0=-5., boundary_type='reflective') + z_max = openmc.ZPlane(6, z0=5., boundary_type='reflective') + z_cyl = openmc.ZCylinder(7, x0=-2.5, y0=2.5, R=2.0) + + outside_cyl = openmc.Cell(1, fill=water, region=( + +x_min & -x_max & +y_min & -y_max & +z_min & -z_max & +z_cyl)) + inside_cyl = openmc.Cell(2, fill=fuel, region=+z_min & -z_max & -z_cyl) + root_universe = openmc.Universe(0, cells=(outside_cyl, inside_cyl)) + + geometry = openmc.Geometry() + geometry.root_universe = root_universe + geometry.export_to_xml() + + # Define settings + settings = openmc.Settings() + settings.particles = 1000 + settings.batches = 4 + settings.inactive = 0 + settings.source = openmc.Source(space=openmc.stats.Box( + *outside_cyl.region.bounding_box)) + settings.export_to_xml() + + +if __name__ == '__main__': + harness = PeriodicTest('statepoint.4.h5') + harness.main() diff --git a/tests/test_plot/test_plot.py b/tests/test_plot/test_plot.py index 015577d21..606a1fd64 100644 --- a/tests/test_plot/test_plot.py +++ b/tests/test_plot/test_plot.py @@ -9,7 +9,7 @@ from testing_harness import TestHarness import h5py -from openmc import Executor +import openmc class PlotTestHarness(TestHarness): @@ -19,8 +19,7 @@ class PlotTestHarness(TestHarness): self._plot_names = plot_names def _run_openmc(self): - executor = Executor() - returncode = executor.plot_geometry(openmc_exec=self._opts.exe) + returncode = openmc.plot_geometry(openmc_exec=self._opts.exe) assert returncode == 0, 'OpenMC did not exit successfully.' def _test_output_created(self): diff --git a/tests/test_quadric_surfaces/results_true.dat b/tests/test_quadric_surfaces/results_true.dat index b2e02fdbb..1f0dd5426 100644 --- a/tests/test_quadric_surfaces/results_true.dat +++ b/tests/test_quadric_surfaces/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.706301E-01 4.351374E-02 +9.570770E-01 2.513234E-02 diff --git a/tests/test_reflective_plane/results_true.dat b/tests/test_reflective_plane/results_true.dat index c5ba8e63f..4860c1ed9 100644 --- a/tests/test_reflective_plane/results_true.dat +++ b/tests/test_reflective_plane/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.276127E+00 4.678320E-03 +2.271202E+00 3.876146E-03 diff --git a/tests/test_resonance_scattering/geometry.xml b/tests/test_resonance_scattering/geometry.xml deleted file mode 100644 index bc56030e1..000000000 --- a/tests/test_resonance_scattering/geometry.xml +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/tests/test_resonance_scattering/inputs_true.dat b/tests/test_resonance_scattering/inputs_true.dat new file mode 100644 index 000000000..f2a875c7e --- /dev/null +++ b/tests/test_resonance_scattering/inputs_true.dat @@ -0,0 +1 @@ +ece83bb075ed8144af89ce7cebf1577dcb2489d2e9ce4afbe61a3e4398837e7a9aaa2ae0cea0a6542f51ca5e0d119b570c675ed1dca0d74237cd5fdce0b606a3 \ No newline at end of file diff --git a/tests/test_resonance_scattering/materials.xml b/tests/test_resonance_scattering/materials.xml deleted file mode 100644 index 52a8c04be..000000000 --- a/tests/test_resonance_scattering/materials.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - - - - - - diff --git a/tests/test_resonance_scattering/results_true.dat b/tests/test_resonance_scattering/results_true.dat index 0dda991ca..e7056e4fa 100644 --- a/tests/test_resonance_scattering/results_true.dat +++ b/tests/test_resonance_scattering/results_true.dat @@ -1,2 +1,2 @@ k-combined: -6.842112E-02 8.480934E-04 +1.440556E+00 6.383274E-02 diff --git a/tests/test_resonance_scattering/settings.xml b/tests/test_resonance_scattering/settings.xml deleted file mode 100644 index 7ce4f23ac..000000000 --- a/tests/test_resonance_scattering/settings.xml +++ /dev/null @@ -1,27 +0,0 @@ - - - - - - U-238 - cxs - 92238.71c - 92238.71c - 5.0e-6 - 40.0e-6 - - - - - 10 - 5 - 1000 - - - - - -4 -4 -4 4 4 4 - - - - diff --git a/tests/test_resonance_scattering/test_resonance_scattering.py b/tests/test_resonance_scattering/test_resonance_scattering.py index 2a595f3e6..b752cf7f3 100644 --- a/tests/test_resonance_scattering/test_resonance_scattering.py +++ b/tests/test_resonance_scattering/test_resonance_scattering.py @@ -3,9 +3,78 @@ import os import sys sys.path.insert(0, os.pardir) -from testing_harness import TestHarness +from testing_harness import PyAPITestHarness +import openmc + + +class ResonanceScatteringTestHarness(PyAPITestHarness): + def _build_inputs(self): + # Materials + mat = openmc.Material(material_id=1) + mat.set_density('g/cc', 1.0) + mat.add_nuclide('U-238', 1.0) + mat.add_nuclide('U-235', 0.02) + mat.add_nuclide('Pu-239', 0.02) + mat.add_nuclide('H-1', 20.0) + + mats_file = openmc.Materials([mat]) + mats_file.default_xs = '71c' + mats_file.export_to_xml() + + # Geometry + dumb_surface = openmc.XPlane(x0=100) + dumb_surface.boundary_type = 'reflective' + + c1 = openmc.Cell(cell_id=1) + c1.fill = mat + c1.region = -dumb_surface + + root_univ = openmc.Universe(universe_id=0) + root_univ.add_cell(c1) + + geometry = openmc.Geometry() + geometry.root_universe = root_univ + geometry.export_to_xml() + + # Settings + nuclide = openmc.Nuclide('U-238', '71c') + nuclide.zaid = 92238 + res_scatt_dbrc = openmc.ResonanceScattering() + res_scatt_dbrc.nuclide = nuclide + res_scatt_dbrc.nuclide_0K = nuclide # This is a bad idea! Just for tests + res_scatt_dbrc.method = 'DBRC' + res_scatt_dbrc.E_min = 1e-6 + res_scatt_dbrc.E_max = 210e-6 + + nuclide = openmc.Nuclide('U-235', '71c') + nuclide.zaid = 92235 + res_scatt_wcm = openmc.ResonanceScattering() + res_scatt_wcm.nuclide = nuclide + res_scatt_wcm.nuclide_0K = nuclide + res_scatt_wcm.method = 'WCM' + res_scatt_wcm.E_min = 1e-6 + res_scatt_wcm.E_max = 210e-6 + + nuclide = openmc.Nuclide('Pu-239', '71c') + nuclide.zaid = 94239 + res_scatt_ares = openmc.ResonanceScattering() + res_scatt_ares.nuclide = nuclide + res_scatt_ares.nuclide_0K = nuclide + res_scatt_ares.method = 'ARES' + res_scatt_ares.E_min = 1e-6 + res_scatt_ares.E_max = 210e-6 + + sets_file = openmc.Settings() + sets_file.batches = 10 + sets_file.inactive = 5 + sets_file.particles = 1000 + sets_file.source = openmc.source.Source( + space=openmc.stats.Box([-4, -4, -4], [4, 4, 4])) + sets_file.resonance_scattering = [res_scatt_dbrc, res_scatt_wcm, + res_scatt_ares] + sets_file.export_to_xml() if __name__ == '__main__': - harness = TestHarness('statepoint.10.*') + harness = ResonanceScatteringTestHarness('statepoint.10.*') harness.main() diff --git a/tests/test_rotation/results_true.dat b/tests/test_rotation/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_rotation/results_true.dat +++ b/tests/test_rotation/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_salphabeta/results_true.dat b/tests/test_salphabeta/results_true.dat index 926af89bc..fb691f168 100644 --- a/tests/test_salphabeta/results_true.dat +++ b/tests/test_salphabeta/results_true.dat @@ -1,2 +1,2 @@ k-combined: -8.350634E-01 6.010639E-02 +8.331430E-01 3.074913E-03 diff --git a/tests/test_score_current/results_true.dat b/tests/test_score_current/results_true.dat index 936e2d04b..d3ac03a70 100644 --- a/tests/test_score_current/results_true.dat +++ b/tests/test_score_current/results_true.dat @@ -1 +1 @@ -1e6945632c55491d4584f4976cc6f5c7340874703cfaf739dd956b7124b4260955efb5b6ba041b32536f9a74572d071e0293dced55a41ea305223f698b734c2a \ No newline at end of file +a9310752363eb059ff40f16ac9716b41ccab6ec6607d29f498069318745e485d18d784264304cc2586865bd58cef7587203cc22a1d485c58ddd63c14c0defdb9 \ No newline at end of file diff --git a/tests/test_seed/results_true.dat b/tests/test_seed/results_true.dat index df79ce1ce..35e9c968b 100644 --- a/tests/test_seed/results_true.dat +++ b/tests/test_seed/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.951164E-01 2.504580E-03 +3.131925E-01 7.639726E-03 diff --git a/tests/test_source/inputs_true.dat b/tests/test_source/inputs_true.dat index 01130ed2e..69a1e2ea8 100644 --- a/tests/test_source/inputs_true.dat +++ b/tests/test_source/inputs_true.dat @@ -1 +1 @@ -5c2fdde85affcd44c1b02c07c300acb8e5c189c1adbf7aa079e37a68e8b8313678fc292bd7f6e0d0957f723e05b8146bd165cf3315dde5f6b2f88ebc954cd65e \ No newline at end of file +526c91551d9a80dc01216e5cb04162253f12ec684cc2b4912ca18cfc510f1ea2e5303029f1c1607882082b0c2c8a47f25dd5be14678f449a1579e3601d1bdec5 \ No newline at end of file diff --git a/tests/test_source/results_true.dat b/tests/test_source/results_true.dat index 18fb895f7..e7ef218ad 100644 --- a/tests/test_source/results_true.dat +++ b/tests/test_source/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.014392E-01 7.185055E-03 +3.026614E-01 3.952004E-03 diff --git a/tests/test_source/test_source.py b/tests/test_source/test_source.py index 9d303b06b..0abae4344 100644 --- a/tests/test_source/test_source.py +++ b/tests/test_source/test_source.py @@ -9,8 +9,6 @@ import numpy as np sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness import openmc -import openmc.stats -from openmc.source import Source class SourceTestHarness(PyAPITestHarness): @@ -18,8 +16,7 @@ class SourceTestHarness(PyAPITestHarness): mat1 = openmc.Material(material_id=1) mat1.set_density('g/cm3', 4.5) mat1.add_nuclide(openmc.Nuclide('U-235', '71c'), 1.0) - materials = openmc.MaterialsFile() - materials.add_material(mat1) + materials = openmc.Materials([mat1]) materials.export_to_xml() sphere = openmc.Sphere(surface_id=1, R=10.0, boundary_type='vacuum') @@ -31,9 +28,7 @@ class SourceTestHarness(PyAPITestHarness): root.add_cell(inside_sphere) geometry = openmc.Geometry() geometry.root_universe = root - geometry_xml = openmc.GeometryFile() - geometry_xml.geometry = geometry - geometry_xml.export_to_xml() + geometry.export_to_xml() # Create an array of different sources x_dist = openmc.stats.Uniform(-3., 3.) @@ -56,11 +51,11 @@ class SourceTestHarness(PyAPITestHarness): energy2 = openmc.stats.Watt(0.988, 2.249) energy3 = openmc.stats.Tabular(E, p, interpolation='histogram') - source1 = Source(spatial1, angle1, energy1, strength=0.5) - source2 = Source(spatial2, angle2, energy2, strength=0.3) - source3 = Source(spatial3, angle3, energy3, strength=0.2) + source1 = openmc.Source(spatial1, angle1, energy1, strength=0.5) + source2 = openmc.Source(spatial2, angle2, energy2, strength=0.3) + source3 = openmc.Source(spatial3, angle3, energy3, strength=0.2) - settings = openmc.SettingsFile() + settings = openmc.Settings() settings.batches = 10 settings.inactive = 5 settings.particles = 1000 diff --git a/tests/test_source_file/results_true.dat b/tests/test_source_file/results_true.dat index fee61dda2..782e47176 100644 --- a/tests/test_source_file/results_true.dat +++ b/tests/test_source_file/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.962911E-01 4.073420E-03 +2.939526E-01 6.311736E-03 diff --git a/tests/test_sourcepoint_latest/results_true.dat b/tests/test_sourcepoint_latest/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_sourcepoint_latest/results_true.dat +++ b/tests/test_sourcepoint_latest/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_sourcepoint_restart/results_true.dat b/tests/test_sourcepoint_restart/results_true.dat index 0e4eef9a9..49afeb1d5 100644 --- a/tests/test_sourcepoint_restart/results_true.dat +++ b/tests/test_sourcepoint_restart/results_true.dat @@ -1,16 +1,16 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 tally 1: -7.000000E-03 -2.100000E-05 -1.127639E-03 -7.464355E-07 --1.264355E-03 -1.192757E-06 -8.769846E-04 -1.117508E-06 -3.359153E-03 -4.366438E-06 +1.100000E-02 +3.700000E-05 +1.307570E-03 +2.851451E-06 +1.564980E-03 +2.368303E-06 +3.138136E-03 +5.769887E-06 +7.719235E-03 +2.632583E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -19,50 +19,38 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -6.107648E-04 -3.730336E-07 +2.976389E-04 +8.858892E-08 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +8.816169E-04 +7.772484E-07 1.000000E-03 1.000000E-06 -6.713061E-04 -4.506518E-07 -1.759778E-04 -3.096817E-08 --2.506458E-04 -6.282332E-08 -6.069794E-04 -3.684240E-07 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 +8.782909E-04 +7.713950E-07 +6.570925E-04 +4.317705E-07 +3.763366E-04 +1.416293E-07 0.000000E+00 0.000000E+00 7.000000E-03 1.500000E-05 -4.398928E-03 -8.198908E-06 -1.784486E-03 -3.422315E-06 -8.494423E-04 -9.262242E-07 -4.566637E-03 -5.646039E-06 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -6.069794E-04 -3.684240E-07 -0.000000E+00 -0.000000E+00 +3.445754E-03 +3.819507E-06 +2.124056E-03 +1.976201E-06 +1.542203E-03 +1.531669E-06 +4.135720E-03 +4.532612E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -71,6 +59,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +5.874391E-04 +1.725424E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -79,18 +69,28 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +3.079655E-04 +9.484274E-08 +1.000000E-03 +1.000000E-06 +9.451745E-04 +8.933548E-07 +8.400323E-04 +7.056542E-07 +6.931788E-04 +4.804969E-07 0.000000E+00 0.000000E+00 3.000000E-03 3.000000E-06 --1.419189E-03 -9.791601E-07 --3.125982E-05 -5.086129E-07 -3.291570E-04 -1.943609E-07 -1.525426E-03 -8.346311E-07 +1.134842E-03 +1.040850E-06 +6.127525E-05 +3.988312E-07 +4.938488E-05 +2.738492E-07 +1.484493E-03 +9.722888E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -121,18 +121,136 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.700000E-02 +7.100000E-05 +5.492922E-03 +1.013834E-05 +5.773309E-04 +3.561549E-06 +2.550048E-03 +3.841061E-06 +8.048523E-03 +1.583844E-05 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +5.915762E-04 +1.749886E-07 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.200000E-02 +4.600000E-05 +9.302157E-04 +3.853850E-06 +1.874541E-03 +3.092623E-06 +-1.511552E-03 +4.053466E-06 +5.941986E-03 +9.853873E-06 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.186549E-03 +5.291648E-07 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +2.935668E-04 +8.618149E-08 1.000000E-03 1.000000E-06 --1.542107E-05 -2.378095E-10 --4.996433E-04 -2.496434E-07 -2.312244E-05 -5.346472E-10 -3.053824E-04 -9.325841E-08 +9.893707E-04 +9.788543E-07 +9.682814E-04 +9.375689E-07 +9.370683E-04 +8.780970E-07 0.000000E+00 0.000000E+00 +8.000000E-03 +2.000000E-05 +3.721382E-03 +4.736982E-06 +-1.037031E-04 +6.648392E-07 +-5.996856E-04 +9.642316E-07 +3.248622E-03 +4.063214E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -141,6 +259,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.938723E-04 +8.636093E-08 0.000000E+00 0.000000E+00 0.000000E+00 @@ -161,16 +281,16 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -2.000000E-02 -8.600000E-05 -3.995253E-03 -1.648172E-05 -3.349403E-03 -1.166653E-05 -4.208940E-03 -7.077664E-06 -1.033905E-02 -2.197265E-05 +2.000000E-03 +2.000000E-06 +1.502634E-03 +1.146555E-06 +7.198331E-04 +3.484978E-07 +-3.426513E-05 +1.342349E-07 +1.511030E-03 +1.198311E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -179,8 +299,6 @@ tally 1: 0.000000E+00 0.000000E+00 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-4.000000E-06 --1.284380E-03 -9.356368E-07 --5.965448E-04 -6.643272E-07 -3.352677E-04 -2.956621E-07 -1.526686E-03 -6.527074E-07 +1.316884E-03 +2.894217E-06 +2.095957E-03 +1.439521E-06 +1.013831E-04 +8.405300E-07 +2.404012E-03 +1.641294E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2363,14 +2363,14 @@ tally 1: 0.000000E+00 1.000000E-03 1.000000E-06 --3.965739E-04 -1.572709E-07 --2.640937E-04 -6.974547E-08 -4.389371E-04 -1.926657E-07 -3.053824E-04 -9.325841E-08 +-3.865739E-04 +1.494394E-07 +-2.758409E-04 +7.608820E-08 +4.354374E-04 +1.896058E-07 +5.871337E-04 +3.447260E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2402,11 +2402,11 @@ tally 1: 0.000000E+00 0.000000E+00 tally 2: -5.720364E-01 -6.548043E-02 -6.217988E-01 -7.736906E-02 -3.624477E+00 -2.628737E+00 -4.047526E+01 -3.278231E+02 +5.656887E-01 +6.401442E-02 +6.158976E-01 +7.588371E-02 +3.588479E+00 +2.575762E+00 +4.003041E+01 +3.205440E+02 diff --git a/tests/test_statepoint_batch/results_true.dat b/tests/test_statepoint_batch/results_true.dat index 95b536997..dd5195ef0 100644 --- a/tests/test_statepoint_batch/results_true.dat +++ b/tests/test_statepoint_batch/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.051173E-01 6.930168E-04 +3.003258E-01 3.388059E-03 diff --git a/tests/test_statepoint_interval/results_true.dat b/tests/test_statepoint_interval/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_statepoint_interval/results_true.dat +++ b/tests/test_statepoint_interval/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_statepoint_restart/results_true.dat b/tests/test_statepoint_restart/results_true.dat index 0e4eef9a9..49afeb1d5 100644 --- a/tests/test_statepoint_restart/results_true.dat +++ b/tests/test_statepoint_restart/results_true.dat @@ -1,16 +1,16 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 tally 1: -7.000000E-03 -2.100000E-05 -1.127639E-03 -7.464355E-07 --1.264355E-03 -1.192757E-06 -8.769846E-04 -1.117508E-06 -3.359153E-03 -4.366438E-06 +1.100000E-02 +3.700000E-05 +1.307570E-03 +2.851451E-06 +1.564980E-03 +2.368303E-06 +3.138136E-03 +5.769887E-06 +7.719235E-03 +2.632583E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -19,50 +19,38 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -6.107648E-04 -3.730336E-07 +2.976389E-04 +8.858892E-08 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +8.816169E-04 +7.772484E-07 1.000000E-03 1.000000E-06 -6.713061E-04 -4.506518E-07 -1.759778E-04 -3.096817E-08 --2.506458E-04 -6.282332E-08 -6.069794E-04 -3.684240E-07 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 +8.782909E-04 +7.713950E-07 +6.570925E-04 +4.317705E-07 +3.763366E-04 +1.416293E-07 0.000000E+00 0.000000E+00 7.000000E-03 1.500000E-05 -4.398928E-03 -8.198908E-06 -1.784486E-03 -3.422315E-06 -8.494423E-04 -9.262242E-07 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-4.172846E-04 -1.892148E-06 -7.276646E-04 -1.085417E-06 -6.092709E-03 -8.907893E-06 +6.000000E-03 +8.000000E-06 +2.104495E-03 +2.749678E-06 +8.451272E-04 +9.362821E-07 +5.355137E-04 +3.419837E-07 +2.683856E-03 +1.512640E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1979,8 +1979,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.053824E-04 -9.325841E-08 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1991,6 +1989,28 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 +2.976389E-04 +8.858892E-08 +1.000000E-03 +1.000000E-06 +9.374310E-04 +8.787769E-07 +8.181653E-04 +6.693944E-07 +6.533352E-04 +4.268468E-07 +2.976389E-04 +8.858892E-08 +8.000000E-03 +1.600000E-05 +5.411154E-03 +8.076329E-06 +3.145940E-03 +4.212660E-06 +2.637510E-03 +3.210372E-06 +3.866944E-03 +3.257876E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2001,16 +2021,6 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -5.000000E-03 -7.000000E-06 -1.580450E-03 -1.753085E-06 -3.349602E-04 -3.639488E-07 -2.690006E-04 -2.374932E-07 -1.830811E-03 -9.321096E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2019,8 +2029,16 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.102008E-04 -9.622454E-08 +1.175489E-03 +1.381775E-06 +1.000000E-03 +1.000000E-06 +7.809681E-04 +6.099112E-07 +4.148668E-04 +1.721145E-07 +1.935089E-05 +3.744570E-10 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2049,8 +2067,150 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.034897E-04 -9.210600E-08 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.000000E-02 +3.400000E-05 +4.840884E-03 +1.080853E-05 +3.402096E-03 +4.113972E-06 +1.374077E-03 +2.333511E-06 +4.754696E-03 +7.172310E-06 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +3.079655E-04 +9.484274E-08 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +2.900000E-02 +2.030000E-04 +6.527719E-03 +1.422798E-05 +1.560049E-03 +2.934829E-06 +1.548553E-03 +8.929308E-06 +1.108618E-02 +3.019578E-05 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.174573E-03 +8.619943E-07 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +4.000000E-03 +8.000000E-06 +1.520286E-03 +4.076900E-06 +2.191143E-03 +3.717004E-06 +1.161623E-03 +3.726099E-06 +3.570376E-03 +5.251427E-06 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +2.000000E-03 +2.000000E-06 +1.447007E-04 +7.721849E-07 +1.582773E-04 +4.841114E-08 +1.981705E-04 +2.166687E-07 +9.135699E-04 +4.679599E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2082,15 +2242,15 @@ tally 1: 0.000000E+00 0.000000E+00 1.900000E-02 -1.250000E-04 -2.138118E-03 -8.791773E-06 -2.868574E-03 -9.339641E-06 -5.807501E-04 -1.660344E-06 -8.165982E-03 -2.226036E-05 +1.030000E-04 +1.035735E-02 +3.119381E-05 +6.483551E-03 +1.164471E-05 +3.924334E-03 +6.047577E-06 +9.748673E-03 +2.956634E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2099,8 +2259,8 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.102008E-04 -9.622454E-08 +3.079655E-04 +9.484274E-08 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2109,28 +2269,48 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -6.044609E-04 -3.653729E-07 +2.935668E-04 +8.618149E-08 1.000000E-03 1.000000E-06 -2.312419E-04 -5.347280E-08 --4.197908E-04 -1.762243E-07 --3.159499E-04 -9.982435E-08 +8.623139E-04 +7.435852E-07 +6.153778E-04 +3.786899E-07 +3.095388E-04 +9.581428E-08 +0.000000E+00 +0.000000E+00 +1.900000E-02 +9.900000E-05 +7.385212E-03 +2.033270E-05 +6.336514E-03 +2.028060E-05 +3.967026E-03 +1.027239E-05 +1.066281E-02 +2.937591E-05 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +2.976389E-04 +8.858892E-08 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 0.000000E+00 0.000000E+00 -2.100000E-02 -1.070000E-04 -2.216472E-03 -6.388960E-06 -4.896969E-03 -6.428816E-06 -2.155707E-03 -2.884510E-06 -1.038058E-02 -2.477423E-05 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2139,198 +2319,18 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -3.007686E-04 -9.046177E-08 -1.000000E-03 -1.000000E-06 -7.019813E-04 -4.927778E-07 -2.391667E-04 -5.720072E-08 --1.881699E-04 -3.540793E-08 -2.131373E-03 -2.696833E-06 -1.000000E-03 -1.000000E-06 -9.937981E-04 -9.876347E-07 -9.814521E-04 -9.632483E-07 -9.630767E-04 -9.275168E-07 0.000000E+00 0.000000E+00 6.000000E-03 1.000000E-05 -2.774441E-03 -2.455060E-06 --4.125360E-04 -1.557128E-06 --9.369606E-04 -2.349382E-06 -3.666415E-03 -4.871762E-06 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -6.057201E-04 -1.834492E-07 -1.000000E-03 -1.000000E-06 -8.429685E-04 -7.105959E-07 -5.658938E-04 -3.202358E-07 -2.330721E-04 -5.432261E-08 -6.015373E-04 -3.618471E-07 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -3.000000E-03 -5.000000E-06 -1.596397E-03 -1.275630E-06 -4.822532E-04 -1.627925E-07 -2.983020E-04 -9.401537E-08 -1.221939E-03 -7.467452E-07 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -8.000000E-03 -4.000000E-05 --7.915490E-05 -1.150292E-07 -2.293529E-03 -2.932682E-06 -1.356149E-03 -9.471925E-07 -4.579650E-03 -7.918475E-06 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -3.022304E-04 -9.134324E-08 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -1.100000E-02 -3.300000E-05 -5.093647E-03 -1.217545E-05 -1.852586E-03 -4.478970E-06 -9.768799E-04 -1.395189E-06 -4.578572E-03 -5.491453E-06 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -3.102008E-04 -9.622454E-08 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -3.053824E-04 -9.325841E-08 -1.000000E-03 -1.000000E-06 -9.817451E-04 -9.638234E-07 -9.457351E-04 -8.944149E-07 -8.929546E-04 -7.973680E-07 -0.000000E+00 -0.000000E+00 -4.000000E-03 -4.000000E-06 --1.284380E-03 -9.356368E-07 --5.965448E-04 -6.643272E-07 -3.352677E-04 -2.956621E-07 -1.526686E-03 -6.527074E-07 +1.316884E-03 +2.894217E-06 +2.095957E-03 +1.439521E-06 +1.013831E-04 +8.405300E-07 +2.404012E-03 +1.641294E-06 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2363,14 +2363,14 @@ tally 1: 0.000000E+00 1.000000E-03 1.000000E-06 --3.965739E-04 -1.572709E-07 --2.640937E-04 -6.974547E-08 -4.389371E-04 -1.926657E-07 -3.053824E-04 -9.325841E-08 +-3.865739E-04 +1.494394E-07 +-2.758409E-04 +7.608820E-08 +4.354374E-04 +1.896058E-07 +5.871337E-04 +3.447260E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -2402,11 +2402,11 @@ tally 1: 0.000000E+00 0.000000E+00 tally 2: -5.720364E-01 -6.548043E-02 -6.217988E-01 -7.736906E-02 -3.624477E+00 -2.628737E+00 -4.047526E+01 -3.278231E+02 +5.656887E-01 +6.401442E-02 +6.158976E-01 +7.588371E-02 +3.588479E+00 +2.575762E+00 +4.003041E+01 +3.205440E+02 diff --git a/tests/test_statepoint_restart/test_statepoint_restart.py b/tests/test_statepoint_restart/test_statepoint_restart.py index c842689d9..d39bf7cd5 100644 --- a/tests/test_statepoint_restart/test_statepoint_restart.py +++ b/tests/test_statepoint_restart/test_statepoint_restart.py @@ -5,8 +5,7 @@ import os import sys sys.path.insert(0, os.pardir) from testing_harness import TestHarness -from openmc.statepoint import StatePoint -from openmc.executor import Executor +import openmc class StatepointRestartTestHarness(TestHarness): @@ -50,17 +49,15 @@ class StatepointRestartTestHarness(TestHarness): statepoint = statepoint[0] # Run OpenMC - executor = Executor() - if self._opts.mpi_exec is not None: - returncode = executor.run_simulation(mpi_procs=self._opts.mpi_np, - restart_file=statepoint, - openmc_exec=self._opts.exe, - mpi_exec=self._opts.mpi_exec) + returncode = openmc.run(mpi_procs=self._opts.mpi_np, + restart_file=statepoint, + openmc_exec=self._opts.exe, + mpi_exec=self._opts.mpi_exec) else: - returncode = executor.run_simulation(openmc_exec=self._opts.exe, - restart_file=statepoint) + returncode = openmc.run(openmc_exec=self._opts.exe, + restart_file=statepoint) assert returncode == 0, 'OpenMC did not exit successfully.' diff --git a/tests/test_statepoint_sourcesep/results_true.dat b/tests/test_statepoint_sourcesep/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_statepoint_sourcesep/results_true.dat +++ b/tests/test_statepoint_sourcesep/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_survival_biasing/results_true.dat b/tests/test_survival_biasing/results_true.dat index 3e327841a..e44ec289a 100644 --- a/tests/test_survival_biasing/results_true.dat +++ b/tests/test_survival_biasing/results_true.dat @@ -1,20 +1,20 @@ k-combined: -9.997733E-01 2.995572E-02 +9.686215E-01 1.511499E-02 tally 1: -4.354055E+01 -3.793645E+02 -1.808636E+01 -6.546005E+01 -2.234465E+00 -9.989832E-01 -1.937431E+00 -7.510380E-01 -5.021671E+00 -5.045425E+00 -3.506791E-02 -2.460654E-04 -3.752351E+02 -2.817188E+04 +4.243782E+01 +3.604528E+02 +1.770205E+01 +6.273029E+01 +2.176094E+00 +9.477949E-01 +1.881775E+00 +7.087350E-01 +4.868971E+00 +4.744828E+00 +3.400887E-02 +2.314715E-04 +3.644408E+02 +2.658287E+04 tally 2: -1.808636E+01 -6.546005E+01 +1.770205E+01 +6.273029E+01 diff --git a/tests/test_tallies/inputs_true.dat b/tests/test_tallies/inputs_true.dat index 657a9e77d..e3d37be30 100644 --- a/tests/test_tallies/inputs_true.dat +++ b/tests/test_tallies/inputs_true.dat @@ -1 +1 @@ -5e168146d91b7b5fadecb80a32df9edc906718fb2d70b68b4c18dbed0641739251a1c16177c9f4d47516dfd528ec930879534292ff0eb82af89eca2c3fa4a3e0 \ No newline at end of file +ea09926d8f5c6c96529bf5529f4deb3be78eda2da80adbbf3440147c337587358c2b1823bc72df9463676135573eb481dcd361b735f18365216645ee81092f1e \ No newline at end of file diff --git a/tests/test_tallies/results_true.dat b/tests/test_tallies/results_true.dat index 4f8b3956b..ff3a82845 100644 --- a/tests/test_tallies/results_true.dat +++ b/tests/test_tallies/results_true.dat @@ -1 +1 @@ -5be9b80ecc189d4ee3a6a228d97b0c76b6b47e5204a86ecf03b8faa65c499f6861ffd85c153084bafd0835d10dfacc14f28802901ce966c8a803d60d0c2f42e5 \ No newline at end of file +a0c7d6ca246ecd7dd5fed06373af142390971401c4e97744f29e55810ab9c231c97c4d8947cdf0b3d2df0ae829a9ddf768e5b2d889bbea34f2b6db0e567db884 \ No newline at end of file diff --git a/tests/test_tallies/test_tallies.py b/tests/test_tallies/test_tallies.py index 9fca93bca..9e40d4185 100644 --- a/tests/test_tallies/test_tallies.py +++ b/tests/test_tallies/test_tallies.py @@ -4,7 +4,7 @@ import os import sys sys.path.insert(0, os.pardir) from testing_harness import PyAPITestHarness -from openmc import Filter, Mesh, Tally, TalliesFile +from openmc import Filter, Mesh, Tally, Tallies from openmc.source import Source from openmc.stats import Box @@ -23,205 +23,163 @@ class TalliesTestHarness(PyAPITestHarness): azimuthal_bins = (-3.1416, -1.8850, -0.6283, 0.6283, 1.8850, 3.1416) azimuthal_filter1 = Filter(type='azimuthal', bins=azimuthal_bins) azimuthal_tally1 = Tally() - azimuthal_tally1.add_filter(azimuthal_filter1) - azimuthal_tally1.add_score('flux') + azimuthal_tally1.filters = [azimuthal_filter1] + azimuthal_tally1.scores = ['flux'] azimuthal_tally1.estimator = 'tracklength' azimuthal_tally2 = Tally() - azimuthal_tally2.add_filter(azimuthal_filter1) - azimuthal_tally2.add_score('flux') + azimuthal_tally2.filters = [azimuthal_filter1] + azimuthal_tally2.scores = ['flux'] azimuthal_tally2.estimator = 'analog' azimuthal_filter2 = Filter(type='azimuthal', bins=(5,)) azimuthal_tally3 = Tally() - azimuthal_tally3.add_filter(azimuthal_filter2) - azimuthal_tally3.add_score('flux') + azimuthal_tally3.filters = [azimuthal_filter2] + azimuthal_tally3.scores = ['flux'] azimuthal_tally3.estimator = 'tracklength' mesh_2x2 = Mesh(mesh_id=1) mesh_2x2.lower_left = [-182.07, -182.07] mesh_2x2.upper_right = [182.07, 182.07] mesh_2x2.dimension = [2, 2] - mesh_filter = Filter(type='mesh', bins=(1,)) + mesh_filter = Filter(type='mesh') + mesh_filter.mesh = mesh_2x2 azimuthal_tally4 = Tally() - azimuthal_tally4.add_filter(azimuthal_filter2) - azimuthal_tally4.add_filter(mesh_filter) - azimuthal_tally4.add_score('flux') + azimuthal_tally4.filters = [azimuthal_filter2, mesh_filter] + azimuthal_tally4.scores = ['flux'] azimuthal_tally4.estimator = 'tracklength' cellborn_tally = Tally() - cellborn_tally.add_filter(Filter(type='cellborn', bins=(10, 21, 22, 23))) - cellborn_tally.add_score('total') + cellborn_tally.filters = [Filter(type='cellborn', bins=(10, 21, 22, 23))] + cellborn_tally.scores = ['total'] dg_tally = Tally() - dg_tally.add_filter(Filter(type='delayedgroup', bins=(1, 2, 3, 4, 5, 6))) - dg_tally.add_score('delayed-nu-fission') + dg_tally.filters = [Filter(type='delayedgroup', bins=(1, 2, 3, 4, 5, 6))] + dg_tally.scores = ['delayed-nu-fission'] four_groups = (0.0, 0.253e-6, 1.0e-3, 1.0, 20.0) energy_filter = Filter(type='energy', bins=four_groups) energy_tally = Tally() - energy_tally.add_filter(energy_filter) - energy_tally.add_score('total') + energy_tally.filters = [energy_filter] + energy_tally.scores = ['total'] energyout_filter = Filter(type='energyout', bins=four_groups) energyout_tally = Tally() - energyout_tally.add_filter(energyout_filter) - energyout_tally.add_score('scatter') + energyout_tally.filters = [energyout_filter] + energyout_tally.scores = ['scatter'] transfer_tally = Tally() - transfer_tally.add_filter(energy_filter) - transfer_tally.add_filter(energyout_filter) - transfer_tally.add_score('scatter') - transfer_tally.add_score('nu-fission') + transfer_tally.filters = [energy_filter, energyout_filter] + transfer_tally.scores = ['scatter', 'nu-fission'] material_tally = Tally() - material_tally.add_filter(Filter(type='material', bins=(1, 2, 3, 4))) - material_tally.add_score('total') + material_tally.filters = [Filter(type='material', bins=(1, 2, 3, 4))] + material_tally.scores = ['total'] mu_tally1 = Tally() - mu_tally1.add_filter(Filter(type='mu', bins=(-1.0, -0.5, 0.0, 0.5, 1.0))) - mu_tally1.add_score('scatter') - mu_tally1.add_score('nu-scatter') + mu_tally1.filters = [Filter(type='mu', bins=(-1.0, -0.5, 0.0, 0.5, 1.0))] + mu_tally1.scores = ['scatter', 'nu-scatter'] mu_filter = Filter(type='mu', bins=(5,)) mu_tally2 = Tally() - mu_tally2.add_filter(mu_filter) - mu_tally2.add_score('scatter') - mu_tally2.add_score('nu-scatter') + mu_tally2.filters = [mu_filter] + mu_tally2.scores = ['scatter', 'nu-scatter'] mu_tally3 = Tally() - mu_tally3.add_filter(mu_filter) - mu_tally3.add_filter(mesh_filter) - mu_tally3.add_score('scatter') - mu_tally3.add_score('nu-scatter') + mu_tally3.filters = [mu_filter, mesh_filter] + mu_tally3.scores = ['scatter', 'nu-scatter'] polar_bins = (0.0, 0.6283, 1.2566, 1.8850, 2.5132, 3.1416) polar_filter = Filter(type='polar', bins=polar_bins) polar_tally1 = Tally() - polar_tally1.add_filter(polar_filter) - polar_tally1.add_score('flux') + polar_tally1.filters = [polar_filter] + polar_tally1.scores = ['flux'] polar_tally1.estimator = 'tracklength' polar_tally2 = Tally() - polar_tally2.add_filter(polar_filter) - polar_tally2.add_score('flux') + polar_tally2.filters = [polar_filter] + polar_tally2.scores = ['flux'] polar_tally2.estimator = 'analog' polar_filter2 = Filter(type='polar', bins=(5,)) polar_tally3 = Tally() - polar_tally3.add_filter(polar_filter2) - polar_tally3.add_score('flux') + polar_tally3.filters = [polar_filter2] + polar_tally3.scores = ['flux'] polar_tally3.estimator = 'tracklength' polar_tally4 = Tally() - polar_tally4.add_filter(polar_filter2) - polar_tally4.add_filter(mesh_filter) - polar_tally4.add_score('flux') + polar_tally4.filters = [polar_filter2, mesh_filter] + polar_tally4.scores = ['flux'] polar_tally4.estimator = 'tracklength' universe_tally = Tally() - universe_tally.add_filter(Filter(type='universe', bins=(1, 2, 3, 4))) - universe_tally.add_score('total') + universe_tally.filters = [Filter(type='universe', bins=(1, 2, 3, 4))] + universe_tally.scores = ['total'] cell_filter = Filter(type='cell', bins=(10, 21, 22, 23)) score_tallies = [Tally(), Tally(), Tally()] for t in score_tallies: - t.add_filter(cell_filter) - t.add_score('absorption') - t.add_score('delayed-nu-fission') - t.add_score('events') - t.add_score('fission') - t.add_score('inverse-velocity') - t.add_score('kappa-fission') - t.add_score('(n,2n)') - t.add_score('(n,n1)') - t.add_score('(n,gamma)') - t.add_score('nu-fission') - t.add_score('scatter') - t.add_score('elastic') - t.add_score('total') + t.filters = [cell_filter] + t.scores = ['absorption', 'delayed-nu-fission', 'events', 'fission', + 'inverse-velocity', 'kappa-fission', '(n,2n)', '(n,n1)', + '(n,gamma)', 'nu-fission', 'scatter', 'elastic', 'total'] score_tallies[0].estimator = 'tracklength' score_tallies[1].estimator = 'analog' score_tallies[2].estimator = 'collision' cell_filter2 = Filter(type='cell', bins=(21, 22, 23, 27, 28, 29)) flux_tallies = [Tally() for i in range(4)] - [t.add_filter(cell_filter2) for t in flux_tallies] - flux_tallies[0].add_score('flux') - [t.add_score('flux-y5') for t in flux_tallies[1:]] + for t in flux_tallies: + t.filters = [cell_filter2] + flux_tallies[0].scores = ['flux'] + for t in flux_tallies[1:]: + t.scores = ['flux-y5'] flux_tallies[1].estimator = 'tracklength' flux_tallies[2].estimator = 'analog' flux_tallies[3].estimator = 'collision' scatter_tally1 = Tally() - scatter_tally1.add_filter(cell_filter) - scatter_tally1.add_score('scatter') - scatter_tally1.add_score('scatter-1') - scatter_tally1.add_score('scatter-2') - scatter_tally1.add_score('scatter-3') - scatter_tally1.add_score('scatter-4') - scatter_tally1.add_score('nu-scatter') - scatter_tally1.add_score('nu-scatter-1') - scatter_tally1.add_score('nu-scatter-2') - scatter_tally1.add_score('nu-scatter-3') - scatter_tally1.add_score('nu-scatter-4') + scatter_tally1.filters = [cell_filter] + scatter_tally1.scores = ['scatter', 'scatter-1', 'scatter-2', 'scatter-3', + 'scatter-4', 'nu-scatter', 'nu-scatter-1', + 'nu-scatter-2', 'nu-scatter-3', 'nu-scatter-4'] scatter_tally2 = Tally() - scatter_tally2.add_filter(cell_filter) - scatter_tally2.add_score('scatter-p4') - scatter_tally2.add_score('scatter-y4') - scatter_tally2.add_score('nu-scatter-p4') - scatter_tally2.add_score('nu-scatter-y3') + scatter_tally2.filters = [cell_filter] + scatter_tally2.scores = ['scatter-p4', 'scatter-y4', 'nu-scatter-p4', + 'nu-scatter-y3'] total_tallies = [Tally() for i in range(4)] - [t.add_filter(cell_filter) for t in total_tallies] - total_tallies[0].add_score('total') - [t.add_score('total-y4') for t in total_tallies[1:]] - [t.add_nuclide('U-235') for t in total_tallies[1:]] - [t.add_nuclide('total') for t in total_tallies[1:]] + for t in total_tallies: + t.filters = [cell_filter] + total_tallies[0].scores = ['total'] + for t in total_tallies[1:]: + t.scores = ['total-y4'] + t.nuclides = ['U-235', 'total'] total_tallies[1].estimator = 'tracklength' total_tallies[2].estimator = 'analog' total_tallies[3].estimator = 'collision' - questionable_tally = Tally() - questionable_tally.add_score('transport') - questionable_tally.add_score('n1n') - all_nuclide_tallies = [Tally(), Tally()] for t in all_nuclide_tallies: - t.add_filter(cell_filter) - t.add_nuclide('all') - t.add_score('total') + t.filters = [cell_filter] + t.nuclides = ['all'] + t.scores = ['total'] all_nuclide_tallies[0].estimator = 'tracklength' all_nuclide_tallies[0].estimator = 'collision' - self._input_set.tallies = TalliesFile() - self._input_set.tallies.add_tally(azimuthal_tally1) - self._input_set.tallies.add_tally(azimuthal_tally2) - self._input_set.tallies.add_tally(azimuthal_tally3) - self._input_set.tallies.add_tally(azimuthal_tally4) - self._input_set.tallies.add_tally(cellborn_tally) - self._input_set.tallies.add_tally(dg_tally) - self._input_set.tallies.add_tally(energy_tally) - self._input_set.tallies.add_tally(energyout_tally) - self._input_set.tallies.add_tally(transfer_tally) - self._input_set.tallies.add_tally(material_tally) - self._input_set.tallies.add_tally(mu_tally1) - self._input_set.tallies.add_tally(mu_tally2) - self._input_set.tallies.add_tally(mu_tally3) - self._input_set.tallies.add_tally(polar_tally1) - self._input_set.tallies.add_tally(polar_tally2) - self._input_set.tallies.add_tally(polar_tally3) - self._input_set.tallies.add_tally(polar_tally4) - self._input_set.tallies.add_tally(universe_tally) - [self._input_set.tallies.add_tally(t) for t in score_tallies] - [self._input_set.tallies.add_tally(t) for t in flux_tallies] - self._input_set.tallies.add_tally(scatter_tally1) - self._input_set.tallies.add_tally(scatter_tally2) - [self._input_set.tallies.add_tally(t) for t in total_tallies] - self._input_set.tallies.add_tally(questionable_tally) - [self._input_set.tallies.add_tally(t) for t in all_nuclide_tallies] - self._input_set.tallies.add_mesh(mesh_2x2) + self._input_set.tallies = Tallies() + self._input_set.tallies += ( + [azimuthal_tally1, azimuthal_tally2, azimuthal_tally3, + azimuthal_tally4, cellborn_tally, dg_tally, energy_tally, + energyout_tally, transfer_tally, material_tally, mu_tally1, + mu_tally2, mu_tally3, polar_tally1, polar_tally2, polar_tally3, + polar_tally4, universe_tally]) + self._input_set.tallies += score_tallies + self._input_set.tallies += flux_tallies + self._input_set.tallies += (scatter_tally1, scatter_tally2) + self._input_set.tallies += total_tallies + self._input_set.tallies += all_nuclide_tallies self._input_set.export() diff --git a/tests/test_tally_aggregation/inputs_true.dat b/tests/test_tally_aggregation/inputs_true.dat index 7b4276f59..055ac76fd 100644 --- a/tests/test_tally_aggregation/inputs_true.dat +++ b/tests/test_tally_aggregation/inputs_true.dat @@ -1 +1 @@ -530a5e969901e153531f74aed46246b1e8783a0e2f347e472f7554c9970152f45d85499f17d7df9c35c74fed6f78d449aa70bf0c1f8947cd34d3a829483a0055 \ No newline at end of file +f819f1b3564ca1df1e235f120f4bd65003cd80935fa8261f0a5982b7e7ec5b2e7497716673c142fab99f3fb26c174ac7a12e145b9a6f2caf707d2a07702f6eb2 \ No newline at end of file diff --git a/tests/test_tally_aggregation/results_true.dat b/tests/test_tally_aggregation/results_true.dat index cde3e281c..6c2d7a519 100644 --- a/tests/test_tally_aggregation/results_true.dat +++ b/tests/test_tally_aggregation/results_true.dat @@ -1 +1 @@ -ba8bfe764fcc0484a4fdab8fdc4ff8ad0e4a98b1ff33e8687899c8cc6bf80cb28b3a59aeaec84bd74681b8b5f19f714292ccaa9c9d4ba852b2cc29872f612e10 \ No newline at end of file +840d2648f9ba782926c71baa84e5a2ad31331e156740a3d1e9d86af8f1f0d301ef8c0f69474975d365dbcf8d229a68c62d3e60286d18045e5254373f4e1010bf \ No newline at end of file diff --git a/tests/test_tally_aggregation/test_tally_aggregation.py b/tests/test_tally_aggregation/test_tally_aggregation.py index a5c8d9414..fdc086e68 100644 --- a/tests/test_tally_aggregation/test_tally_aggregation.py +++ b/tests/test_tally_aggregation/test_tally_aggregation.py @@ -15,9 +15,6 @@ class TallyAggregationTestHarness(PyAPITestHarness): # The summary.h5 file needs to be created to read in the tallies self._input_set.settings.output = {'summary': True} - # Initialize the tallies file - tallies_file = openmc.TalliesFile() - # Initialize the nuclides u235 = openmc.Nuclide('U-235') u238 = openmc.Nuclide('U-238') @@ -30,14 +27,10 @@ class TallyAggregationTestHarness(PyAPITestHarness): # Initialized the tallies tally = openmc.Tally(name='distribcell tally') - tally.add_filter(energy_filter) - tally.add_filter(distrib_filter) - tally.add_score('nu-fission') - tally.add_score('total') - tally.add_nuclide(u235) - tally.add_nuclide(u238) - tally.add_nuclide(pu239) - tallies_file.add_tally(tally) + tally.filters = [energy_filter, distrib_filter] + tally.scores = ['nu-fission', 'total'] + tally.nuclides = [u235, u238, pu239] + tallies_file = openmc.Tallies([tally]) # Export tallies to file self._input_set.tallies = tallies_file @@ -50,11 +43,6 @@ class TallyAggregationTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Extract the tally of interest tally = sp.get_tally(name='distribcell tally') diff --git a/tests/test_tally_arithmetic/inputs_true.dat b/tests/test_tally_arithmetic/inputs_true.dat index 1b6046f1a..d7b854a51 100644 --- a/tests/test_tally_arithmetic/inputs_true.dat +++ b/tests/test_tally_arithmetic/inputs_true.dat @@ -1 +1 @@ -57384883e37964076aa82c19fa542434331cdb09735d710485b5aa0ca3445d543729e40cb9c7b6a70e7101ef186923eb1ff6315c73b01ff257052838add68fc7 \ No newline at end of file +bb7e730630f7bb4694a27fd77c3c0171f70c78df2681acc26b0ef88bcff367523b11335f487b46269325adbcee7faeb756484af64055c3c91b0103f7ed962053 \ No newline at end of file diff --git a/tests/test_tally_arithmetic/results_true.dat b/tests/test_tally_arithmetic/results_true.dat index ded2efa66..ef2741cc1 100644 --- a/tests/test_tally_arithmetic/results_true.dat +++ b/tests/test_tally_arithmetic/results_true.dat @@ -1,134 +1,134 @@ -[[[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] +[[[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] ..., - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]]][[[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]]][[[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 8.90240785e-05 8.31464209e-11 4.41507090e-05 4.12357364e-11] - [ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 4.69276830e-05 4.38293656e-11 2.35903380e-05 2.20328275e-11] - [ 3.84607356e-05 3.15690405e-05 1.93340411e-05 1.58696166e-05]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] ..., - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]]][[[ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]]][[[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 7.29618709e-05 5.98879928e-05 3.61847984e-05 2.97009235e-05] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] ..., - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00]]][[[ 0.00000000e+00 4.41507090e-05 0.00000000e+00] - [ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 2.35903380e-05 0.00000000e+00] - [ 0.00000000e+00 1.93340411e-05 0.00000000e+00]] + [[ 0. 0. 0. 0.] + [ 0. 0. 0. 0.] + [ 0. 0. 0. 0.]]][[[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 4.41507090e-05 0.00000000e+00] - [ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 2.35903380e-05 0.00000000e+00] - [ 0.00000000e+00 1.93340411e-05 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 4.41507090e-05 0.00000000e+00] - [ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 2.35903380e-05 0.00000000e+00] - [ 0.00000000e+00 1.93340411e-05 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] ..., - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]]][[[ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]]][[[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 3.61847984e-05 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] ..., - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]] + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]] - [[ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [ 0.00000000e+00 0.00000000e+00 0.00000000e+00]]] \ No newline at end of file + [[ 0. 0. 0.] + [ 0. 0. 0.] + [ 0. 0. 0.]]] \ No newline at end of file diff --git a/tests/test_tally_arithmetic/test_tally_arithmetic.py b/tests/test_tally_arithmetic/test_tally_arithmetic.py index 1954334b7..a5919909f 100644 --- a/tests/test_tally_arithmetic/test_tally_arithmetic.py +++ b/tests/test_tally_arithmetic/test_tally_arithmetic.py @@ -16,7 +16,7 @@ class TallyArithmeticTestHarness(PyAPITestHarness): self._input_set.settings.output = {'summary': True} # Initialize the tallies file - tallies_file = openmc.TalliesFile() + tallies_file = openmc.Tallies() # Initialize the nuclides u235 = openmc.Nuclide('U-235') @@ -40,24 +40,16 @@ class TallyArithmeticTestHarness(PyAPITestHarness): # Initialized the tallies tally = openmc.Tally(name='tally 1') - tally.add_filter(material_filter) - tally.add_filter(energy_filter) - tally.add_filter(distrib_filter) - tally.add_score('nu-fission') - tally.add_score('total') - tally.add_nuclide(u235) - tally.add_nuclide(pu239) - tallies_file.add_tally(tally) + tally.filters = [material_filter, energy_filter, distrib_filter] + tally.scores = ['nu-fission', 'total'] + tally.nuclides = [u235, pu239] + tallies_file.append(tally) tally = openmc.Tally(name='tally 2') - tally.add_filter(energy_filter) - tally.add_filter(mesh_filter) - tally.add_score('total') - tally.add_score('fission') - tally.add_nuclide(u238) - tally.add_nuclide(u235) - tallies_file.add_tally(tally) - tallies_file.add_mesh(mesh) + tally.filters = [energy_filter, mesh_filter] + tally.scores = ['total', 'fission'] + tally.nuclides = [u238, u235] + tallies_file.append(tally) # Export tallies to file self._input_set.tallies = tallies_file @@ -70,11 +62,6 @@ class TallyArithmeticTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Load the tallies tally_1 = sp.get_tally(name='tally 1') tally_2 = sp.get_tally(name='tally 2') diff --git a/tests/test_tally_assumesep/results_true.dat b/tests/test_tally_assumesep/results_true.dat index 4835227f2..7262a88a0 100644 --- a/tests/test_tally_assumesep/results_true.dat +++ b/tests/test_tally_assumesep/results_true.dat @@ -1,11 +1,11 @@ k-combined: -1.005983E+00 2.248579E-02 +9.581522E-01 4.261830E-02 tally 1: -1.423676E+01 -4.330937E+01 +1.529084E+01 +4.769011E+01 tally 2: -2.914798E+00 -1.831649E+00 +3.198905E+00 +2.114129E+00 tally 3: -4.088282E+01 -3.662539E+02 +4.510603E+01 +4.183089E+02 diff --git a/tests/test_tally_nuclides/results_true.dat b/tests/test_tally_nuclides/results_true.dat index b8e903049..36250aba7 100644 --- a/tests/test_tally_nuclides/results_true.dat +++ b/tests/test_tally_nuclides/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.851180E-01 1.587642E-02 +9.752414E-01 4.425137E-02 tally 1: -7.516940E+00 -1.149356E+01 -1.700884E+00 -5.835345E-01 -1.635327E+00 -5.385674E-01 -5.816056E+00 -6.901370E+00 -7.516940E+00 -1.149356E+01 -1.700884E+00 -5.835345E-01 -1.635327E+00 -5.385674E-01 -5.816056E+00 -6.901370E+00 +6.903183E+00 +9.661095E+00 +1.569337E+00 +4.971849E-01 +1.521894E+00 +4.673221E-01 +5.333846E+00 +5.778631E+00 +6.903183E+00 +9.661095E+00 +1.569337E+00 +4.971849E-01 +1.521894E+00 +4.673221E-01 +5.333846E+00 +5.778631E+00 tally 2: -7.516940E+00 -1.149356E+01 -1.700884E+00 -5.835345E-01 -1.635327E+00 -5.385674E-01 -5.816056E+00 -6.901370E+00 +6.903183E+00 +9.661095E+00 +1.569337E+00 +4.971849E-01 +1.521894E+00 +4.673221E-01 +5.333846E+00 +5.778631E+00 diff --git a/tests/test_tally_slice_merge/inputs_true.dat b/tests/test_tally_slice_merge/inputs_true.dat index 29f0f1d82..be2ec63dc 100644 --- a/tests/test_tally_slice_merge/inputs_true.dat +++ b/tests/test_tally_slice_merge/inputs_true.dat @@ -1 +1 @@ -8d1ab9e4add51b99045e990ac9c3dad9447e9720d811bc430d4bfdd7c2c035424bcb7750e4a4d0ec0460ea1ef4be46ac58372ed01d55f5d8cfeebbce75559066 \ No newline at end of file +bb4ae3b75445846bd5db05a06cc20e7589990154ccef8302f276cd8356630d585c513ebb6bfa99f9fc93dd2d30c42bfbb67dd3454134f4c9fcb3bac128d1f1c5 \ No newline at end of file diff --git a/tests/test_tally_slice_merge/results_true.dat b/tests/test_tally_slice_merge/results_true.dat index f66f17427..ed04152d4 100644 --- a/tests/test_tally_slice_merge/results_true.dat +++ b/tests/test_tally_slice_merge/results_true.dat @@ -1,36 +1,36 @@ energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 21 U-235 fission 9.86e-02 9.19e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 21 U-235 nu-fission 2.40e-01 2.24e-02 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 21 U-238 fission 1.37e-07 1.28e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 21 U-238 nu-fission 3.42e-07 3.20e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 21 U-235 fission 2.79e-02 6.02e-04 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 21 U-235 nu-fission 6.82e-02 1.46e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 21 U-238 fission 1.66e-02 1.15e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 21 U-238 nu-fission 4.58e-02 3.34e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 27 U-235 fission 5.78e-02 4.82e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 27 U-235 nu-fission 1.41e-01 1.17e-02 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 27 U-238 fission 8.18e-08 7.06e-09 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 27 U-238 nu-fission 2.04e-07 1.76e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 27 U-235 fission 1.76e-02 1.94e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 27 U-235 nu-fission 4.31e-02 4.74e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 27 U-238 fission 9.88e-03 1.93e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 6.25e-07 2.00e+01 27 U-238 nu-fission 2.71e-02 5.21e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. -0 0.00e+00 6.25e-07 21 U-235 fission 9.86e-02 9.19e-03 -1 0.00e+00 6.25e-07 21 U-235 nu-fission 2.40e-01 2.24e-02 -2 0.00e+00 6.25e-07 21 U-238 fission 1.37e-07 1.28e-08 -3 0.00e+00 6.25e-07 21 U-238 nu-fission 3.42e-07 3.20e-08 -4 0.00e+00 6.25e-07 27 U-235 fission 5.78e-02 4.82e-03 -5 0.00e+00 6.25e-07 27 U-235 nu-fission 1.41e-01 1.17e-02 -6 0.00e+00 6.25e-07 27 U-238 fission 8.18e-08 7.06e-09 -7 0.00e+00 6.25e-07 27 U-238 nu-fission 2.04e-07 1.76e-08 -8 6.25e-07 2.00e+01 21 U-235 fission 2.79e-02 6.02e-04 -9 6.25e-07 2.00e+01 21 U-235 nu-fission 6.82e-02 1.46e-03 -10 6.25e-07 2.00e+01 21 U-238 fission 1.66e-02 1.15e-03 -11 6.25e-07 2.00e+01 21 U-238 nu-fission 4.58e-02 3.34e-03 -12 6.25e-07 2.00e+01 27 U-235 fission 1.76e-02 1.94e-03 -13 6.25e-07 2.00e+01 27 U-235 nu-fission 4.31e-02 4.74e-03 -14 6.25e-07 2.00e+01 27 U-238 fission 9.88e-03 1.93e-03 -15 6.25e-07 2.00e+01 27 U-238 nu-fission 2.71e-02 5.21e-03 sum(distribcell) energy low [MeV] energy high [MeV] nuclide score mean std. dev. +0 0.00e+00 6.25e-07 21 U-235 fission 1.08e-01 7.94e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 21 U-235 nu-fission 2.64e-01 1.94e-02 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 21 U-238 fission 1.51e-07 1.00e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 21 U-238 nu-fission 3.76e-07 2.50e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 21 U-235 fission 3.12e-02 2.56e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 21 U-235 nu-fission 7.65e-02 6.24e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 21 U-238 fission 2.00e-02 1.30e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 21 U-238 nu-fission 5.56e-02 3.78e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 27 U-235 fission 4.43e-02 7.21e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 27 U-235 nu-fission 1.08e-01 1.76e-02 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 27 U-238 fission 6.14e-08 9.64e-09 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 27 U-238 nu-fission 1.53e-07 2.40e-08 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 27 U-235 fission 1.39e-02 1.06e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 27 U-235 nu-fission 3.40e-02 2.61e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 27 U-238 fission 9.72e-03 1.21e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 6.25e-07 2.00e+01 27 U-238 nu-fission 2.71e-02 3.80e-03 energy low [MeV] energy high [MeV] cell nuclide score mean std. dev. +0 0.00e+00 6.25e-07 21 U-235 fission 1.08e-01 7.94e-03 +1 0.00e+00 6.25e-07 21 U-235 nu-fission 2.64e-01 1.94e-02 +2 0.00e+00 6.25e-07 21 U-238 fission 1.51e-07 1.00e-08 +3 0.00e+00 6.25e-07 21 U-238 nu-fission 3.76e-07 2.50e-08 +4 0.00e+00 6.25e-07 27 U-235 fission 4.43e-02 7.21e-03 +5 0.00e+00 6.25e-07 27 U-235 nu-fission 1.08e-01 1.76e-02 +6 0.00e+00 6.25e-07 27 U-238 fission 6.14e-08 9.64e-09 +7 0.00e+00 6.25e-07 27 U-238 nu-fission 1.53e-07 2.40e-08 +8 6.25e-07 2.00e+01 21 U-235 fission 3.12e-02 2.56e-03 +9 6.25e-07 2.00e+01 21 U-235 nu-fission 7.65e-02 6.24e-03 +10 6.25e-07 2.00e+01 21 U-238 fission 2.00e-02 1.30e-03 +11 6.25e-07 2.00e+01 21 U-238 nu-fission 5.56e-02 3.78e-03 +12 6.25e-07 2.00e+01 27 U-235 fission 1.39e-02 1.06e-03 +13 6.25e-07 2.00e+01 27 U-235 nu-fission 3.40e-02 2.61e-03 +14 6.25e-07 2.00e+01 27 U-238 fission 9.72e-03 1.21e-03 +15 6.25e-07 2.00e+01 27 U-238 nu-fission 2.71e-02 3.80e-03 sum(distribcell) energy low [MeV] energy high [MeV] nuclide score mean std. dev. 0 (0, 100, 2000, 30000) 0.00e+00 6.25e-07 U-235 fission 0.00e+00 0.00e+00 1 (0, 100, 2000, 30000) 0.00e+00 6.25e-07 U-235 nu-fission 0.00e+00 0.00e+00 2 (0, 100, 2000, 30000) 0.00e+00 6.25e-07 U-238 fission 0.00e+00 0.00e+00 diff --git a/tests/test_tally_slice_merge/test_tally_slice_merge.py b/tests/test_tally_slice_merge/test_tally_slice_merge.py index 79acf182d..4dbb993d5 100644 --- a/tests/test_tally_slice_merge/test_tally_slice_merge.py +++ b/tests/test_tally_slice_merge/test_tally_slice_merge.py @@ -17,7 +17,7 @@ class TallySliceMergeTestHarness(PyAPITestHarness): self._input_set.settings.output = {'summary': True} # Initialize the tallies file - tallies_file = openmc.TalliesFile() + tallies_file = openmc.Tallies() # Define nuclides and scores to add to both tallies self.nuclides = ['U-235', 'U-238'] @@ -69,10 +69,8 @@ class TallySliceMergeTestHarness(PyAPITestHarness): for nuclide in self.nuclides: distribcell_tally.add_nuclide(nuclide) - # Add tallies to a TalliesFile - tallies_file = openmc.TalliesFile() - tallies_file.add_tally(tallies[0]) - tallies_file.add_tally(distribcell_tally) + # Add tallies to a Tallies object + tallies_file = openmc.Tallies((tallies[0], distribcell_tally)) # Export tallies to file self._input_set.tallies = tallies_file @@ -85,17 +83,12 @@ class TallySliceMergeTestHarness(PyAPITestHarness): statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] sp = openmc.StatePoint(statepoint) - # Read the summary file. - summary = glob.glob(os.path.join(os.getcwd(), 'summary.h5'))[0] - su = openmc.Summary(summary) - sp.link_with_summary(su) - # Extract the cell tally tallies = [sp.get_tally(name='cell tally')] # Slice the tallies by cell filter bins cell_filter_prod = itertools.product(tallies, self.cell_filters) - tallies = map(lambda tf: tf[0].get_slice(filters=[tf[1].type], + tallies = map(lambda tf: tf[0].get_slice(filters=[tf[1].type], filter_bins=[tf[1].get_bin(0)]), cell_filter_prod) # Slice the tallies by energy filter bins @@ -133,11 +126,11 @@ class TallySliceMergeTestHarness(PyAPITestHarness): # Extract the distribcell tally distribcell_tally = sp.get_tally(name='distribcell tally') - # Sum up a few subdomains from the distribcell tally - sum1 = distribcell_tally.summation(filter_type='distribcell', + # Sum up a few subdomains from the distribcell tally + sum1 = distribcell_tally.summation(filter_type='distribcell', filter_bins=[0,100,2000,30000]) # Sum up a few subdomains from the distribcell tally - sum2 = distribcell_tally.summation(filter_type='distribcell', + sum2 = distribcell_tally.summation(filter_type='distribcell', filter_bins=[500,5000,50000]) # Merge the distribcell tally slices diff --git a/tests/test_trace/results_true.dat b/tests/test_trace/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_trace/results_true.dat +++ b/tests/test_trace/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_translation/results_true.dat b/tests/test_translation/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_translation/results_true.dat +++ b/tests/test_translation/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_trigger_batch_interval/results_true.dat b/tests/test_trigger_batch_interval/results_true.dat index c901e1e54..af6eea623 100644 --- a/tests/test_trigger_batch_interval/results_true.dat +++ b/tests/test_trigger_batch_interval/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.875001E-01 3.961945E-03 +9.722624E-01 1.010453E-02 tally 1: -2.128147E+01 -3.021699E+01 -4.842434E+00 -1.563989E+00 -4.695086E+00 -1.470132E+00 -1.643904E+01 -1.803258E+01 -2.128147E+01 -3.021699E+01 -4.842434E+00 -1.563989E+00 -4.695086E+00 -1.470132E+00 -1.643904E+01 -1.803258E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 tally 2: -2.128147E+01 -3.021699E+01 -4.842434E+00 -1.563989E+00 -4.695086E+00 -1.470132E+00 -1.643904E+01 -1.803258E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 diff --git a/tests/test_trigger_batch_interval/test_trigger_batch_interval.py b/tests/test_trigger_batch_interval/test_trigger_batch_interval.py index 59b900e50..a0b2119de 100644 --- a/tests/test_trigger_batch_interval/test_trigger_batch_interval.py +++ b/tests/test_trigger_batch_interval/test_trigger_batch_interval.py @@ -7,5 +7,5 @@ from testing_harness import TestHarness if __name__ == '__main__': - harness = TestHarness('statepoint.20.*', True) + harness = TestHarness('statepoint.15.*', True) harness.main() diff --git a/tests/test_trigger_no_batch_interval/results_true.dat b/tests/test_trigger_no_batch_interval/results_true.dat index d06a91646..af6eea623 100644 --- a/tests/test_trigger_no_batch_interval/results_true.dat +++ b/tests/test_trigger_no_batch_interval/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.853099E-01 3.825057E-03 +9.722624E-01 1.010453E-02 tally 1: -2.409492E+01 -3.417475E+01 -5.477076E+00 -1.765385E+00 -5.309347E+00 -1.658803E+00 -1.861784E+01 -2.040621E+01 -2.409492E+01 -3.417475E+01 -5.477076E+00 -1.765385E+00 -5.309347E+00 -1.658803E+00 -1.861784E+01 -2.040621E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 tally 2: -2.409492E+01 -3.417475E+01 -5.477076E+00 -1.765385E+00 -5.309347E+00 -1.658803E+00 -1.861784E+01 -2.040621E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 diff --git a/tests/test_trigger_no_batch_interval/test_trigger_no_batch_interval.py b/tests/test_trigger_no_batch_interval/test_trigger_no_batch_interval.py index f9cb68d62..a0b2119de 100644 --- a/tests/test_trigger_no_batch_interval/test_trigger_no_batch_interval.py +++ b/tests/test_trigger_no_batch_interval/test_trigger_no_batch_interval.py @@ -7,5 +7,5 @@ from testing_harness import TestHarness if __name__ == '__main__': - harness = TestHarness('statepoint.22.*', True) + harness = TestHarness('statepoint.15.*', True) harness.main() diff --git a/tests/test_trigger_no_status/results_true.dat b/tests/test_trigger_no_status/results_true.dat index 0b541099b..c7f1b407a 100644 --- a/tests/test_trigger_no_status/results_true.dat +++ b/tests/test_trigger_no_status/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.906276E-01 1.800527E-03 +9.733783E-01 1.678094E-02 tally 1: -7.043320E+00 -9.922203E+00 -1.610208E+00 -5.185662E-01 -1.564118E+00 -4.893096E-01 -5.433111E+00 -5.904259E+00 -7.043320E+00 -9.922203E+00 -1.610208E+00 -5.185662E-01 -1.564118E+00 -4.893096E-01 -5.433111E+00 -5.904259E+00 +6.901811E+00 +9.536643E+00 +1.572259E+00 +4.947922E-01 +1.527087E+00 +4.667459E-01 +5.329553E+00 +5.686973E+00 +6.901811E+00 +9.536643E+00 +1.572259E+00 +4.947922E-01 +1.527087E+00 +4.667459E-01 +5.329553E+00 +5.686973E+00 tally 2: -7.043320E+00 -9.922203E+00 -1.610208E+00 -5.185662E-01 -1.564118E+00 -4.893096E-01 -5.433111E+00 -5.904259E+00 +6.901811E+00 +9.536643E+00 +1.572259E+00 +4.947922E-01 +1.527087E+00 +4.667459E-01 +5.329553E+00 +5.686973E+00 diff --git a/tests/test_trigger_tallies/results_true.dat b/tests/test_trigger_tallies/results_true.dat index 0519260dd..af6eea623 100644 --- a/tests/test_trigger_tallies/results_true.dat +++ b/tests/test_trigger_tallies/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.875396E-01 4.095985E-03 +9.722624E-01 1.010453E-02 tally 1: -1.415943E+01 -2.006888E+01 -3.225529E+00 -1.040975E+00 -3.128858E+00 -9.794019E-01 -1.093390E+01 -1.196901E+01 -1.415943E+01 -2.006888E+01 -3.225529E+00 -1.040975E+00 -3.128858E+00 -9.794019E-01 -1.093390E+01 -1.196901E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 tally 2: -1.415943E+01 -2.006888E+01 -3.225529E+00 -1.040975E+00 -3.128858E+00 -9.794019E-01 -1.093390E+01 -1.196901E+01 +1.392936E+01 +1.941888E+01 +3.159556E+00 +9.989777E-01 +3.063616E+00 +9.391667E-01 +1.076980E+01 +1.160931E+01 diff --git a/tests/test_uniform_fs/results_true.dat b/tests/test_uniform_fs/results_true.dat index a29a363b2..d27d63f56 100644 --- a/tests/test_uniform_fs/results_true.dat +++ b/tests/test_uniform_fs/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.546115E-01 2.982307E-03 +3.634132E-01 6.507584E-03 diff --git a/tests/test_union_energy_grids/results_true.dat b/tests/test_union_energy_grids/results_true.dat index 9556a981b..0a607592c 100644 --- a/tests/test_union_energy_grids/results_true.dat +++ b/tests/test_union_energy_grids/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.155788E-01 7.559348E-03 +3.330789E-01 2.216495E-03 diff --git a/tests/test_universe/results_true.dat b/tests/test_universe/results_true.dat index 5263a6b7f..7b2fbf37f 100644 --- a/tests/test_universe/results_true.dat +++ b/tests/test_universe/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.021779E-01 3.813358E-03 +2.943619E-01 3.309635E-03 diff --git a/tests/test_void/results_true.dat b/tests/test_void/results_true.dat index 4e99b8676..48be2778a 100644 --- a/tests/test_void/results_true.dat +++ b/tests/test_void/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.045350E+00 2.750547E-02 +1.062505E+00 2.674375E-02 diff --git a/tests/testing_harness.py b/tests/testing_harness.py index 7d6dbc914..d36018404 100644 --- a/tests/testing_harness.py +++ b/tests/testing_harness.py @@ -6,20 +6,18 @@ import hashlib from optparse import OptionParser import os import shutil -from subprocess import Popen, STDOUT, PIPE, call import sys import numpy as np sys.path.insert(0, os.path.join(os.pardir, os.pardir)) from input_set import InputSet, MGInputSet -from openmc.statepoint import StatePoint -from openmc.executor import Executor -import openmc.particle_restart as pr +import openmc class TestHarness(object): """General class for running OpenMC regression tests.""" + def __init__(self, statepoint_name, tallies_present=False): self._sp_name = statepoint_name self._tallies = tallies_present @@ -63,34 +61,32 @@ class TestHarness(object): self._cleanup() def _run_openmc(self): - executor = Executor() - if self._opts.mpi_exec is not None: - returncode = executor.run_simulation(mpi_procs=self._opts.mpi_np, - openmc_exec=self._opts.exe, - mpi_exec=self._opts.mpi_exec) + returncode = openmc.run(mpi_procs=self._opts.mpi_np, + openmc_exec=self._opts.exe, + mpi_exec=self._opts.mpi_exec) else: - returncode = executor.run_simulation(openmc_exec=self._opts.exe) + returncode = openmc.run(openmc_exec=self._opts.exe) assert returncode == 0, 'OpenMC did not exit successfully.' def _test_output_created(self): """Make sure statepoint.* and tallies.out have been created.""" statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name)) - assert len(statepoint) == 1, 'Either multiple or no statepoint files ' \ - 'exist.' + assert len(statepoint) == 1, 'Either multiple or no statepoint files' \ + ' exist.' assert statepoint[0].endswith('h5'), \ - 'Statepoint file is not a HDF5 file.' + 'Statepoint file is not a HDF5 file.' if self._tallies: assert os.path.exists(os.path.join(os.getcwd(), 'tallies.out')), \ - 'Tally output file does not exist.' + 'Tally output file does not exist.' def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" # Read the statepoint file. statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] - sp = StatePoint(statepoint) + sp = openmc.StatePoint(statepoint) # Write out k-combined. outstr = 'k-combined:\n' @@ -102,7 +98,7 @@ class TestHarness(object): tally_num = 1 for tally_ind in sp.tallies: tally = sp.tallies[tally_ind] - results = np.zeros((tally.sum.size*2, )) + results = np.zeros((tally.sum.size * 2, )) results[0::2] = tally.sum.ravel() results[1::2] = tally.sum_sq.ravel() results = ['{0:12.6E}'.format(x) for x in results] @@ -137,9 +133,10 @@ class TestHarness(object): def _cleanup(self): """Delete statepoints, tally, and test files.""" - output = glob.glob(os.path.join(os.getcwd(), 'statepoint.*.*')) + output = glob.glob(os.path.join(os.getcwd(), 'statepoint.*.h5')) output.append(os.path.join(os.getcwd(), 'tallies.out')) output.append(os.path.join(os.getcwd(), 'results_test.dat')) + output.append(os.path.join(os.getcwd(), 'summary.h5')) for f in output: if os.path.exists(f): os.remove(f) @@ -147,6 +144,7 @@ class TestHarness(object): class HashedTestHarness(TestHarness): """Specialized TestHarness that hashes the results.""" + def _get_results(self): """Digest info in the statepoint and return as a string.""" return super(HashedTestHarness, self)._get_results(True) @@ -154,11 +152,12 @@ class HashedTestHarness(TestHarness): class CMFDTestHarness(TestHarness): """Specialized TestHarness for running OpenMC CMFD tests.""" + def _get_results(self): """Digest info in the statepoint and return as a string.""" # Read the statepoint file. statepoint = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] - sp = StatePoint(statepoint) + sp = openmc.StatePoint(statepoint) # Write out the eigenvalue and tallies. outstr = super(CMFDTestHarness, self)._get_results() @@ -187,6 +186,7 @@ class CMFDTestHarness(TestHarness): class ParticleRestartTestHarness(TestHarness): """Specialized TestHarness for running OpenMC particle restart tests.""" + def _run_openmc(self): # Set arguments args = {'openmc_exec': self._opts.exe} @@ -195,28 +195,27 @@ class ParticleRestartTestHarness(TestHarness): 'mpi_exec': self._opts.mpi_exec}) # Initial run - executor = Executor() - returncode = executor.run_simulation(**args) + returncode = openmc.run(**args) assert returncode == 0, 'OpenMC did not exit successfully.' # Run particle restart args.update({'restart_file': self._sp_name}) - returncode = executor.run_simulation(**args) + returncode = openmc.run(**args) assert returncode == 0, 'OpenMC did not exit successfully.' def _test_output_created(self): """Make sure the restart file has been created.""" particle = glob.glob(os.path.join(os.getcwd(), self._sp_name)) assert len(particle) == 1, 'Either multiple or no particle restart ' \ - 'files exist.' + 'files exist.' assert particle[0].endswith('h5'), \ - 'Particle restart file is not a HDF5 file.' + 'Particle restart file is not a HDF5 file.' def _get_results(self): """Digest info in the statepoint and return as a string.""" # Read the particle restart file. particle = glob.glob(os.path.join(os.getcwd(), self._sp_name))[0] - p = pr.Particle(particle) + p = openmc.Particle(particle) # Write out the properties. outstr = '' @@ -233,10 +232,10 @@ class ParticleRestartTestHarness(TestHarness): outstr += 'particle energy:\n' outstr += "{0:12.6E}\n".format(p.energy) outstr += 'particle xyz:\n' - outstr += "{0:12.6E} {1:12.6E} {2:12.6E}\n".format(p.xyz[0],p.xyz[1], + outstr += "{0:12.6E} {1:12.6E} {2:12.6E}\n".format(p.xyz[0], p.xyz[1], p.xyz[2]) outstr += 'particle uvw:\n' - outstr += "{0:12.6E} {1:12.6E} {2:12.6E}\n".format(p.uvw[0],p.uvw[1], + outstr += "{0:12.6E} {1:12.6E} {2:12.6E}\n".format(p.uvw[0], p.uvw[1], p.uvw[2]) return outstr @@ -244,13 +243,15 @@ class ParticleRestartTestHarness(TestHarness): class PyAPITestHarness(TestHarness): def __init__(self, statepoint_name, tallies_present=False, mg=False): - super(PyAPITestHarness, self).__init__(statepoint_name, tallies_present) + super(PyAPITestHarness, self).__init__(statepoint_name, + tallies_present) self.parser.add_option('--build-inputs', dest='build_only', action='store_true', default=False) if mg: self._input_set = MGInputSet() else: self._input_set = InputSet() + def main(self): """Accept commandline arguments and either run or update tests.""" (self._opts, self._args) = self.parser.parse_args() @@ -325,7 +326,8 @@ class PyAPITestHarness(TestHarness): compare = filecmp.cmp('inputs_test.dat', 'inputs_true.dat') if not compare: f = open('inputs_test.dat') - for line in f.readlines(): print(line) + for line in f.readlines(): + print(line) f.close() os.rename('inputs_test.dat', 'inputs_error.dat') assert compare, 'Input files are broken.'