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Merge branch 'release-0.6.0' into develop
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ec21addbee
6 changed files with 22 additions and 24 deletions
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@ -46,9 +46,9 @@ copyright = u'2011-2014, Massachusetts Institute of Technology'
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# built documents.
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#
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# The short X.Y version.
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version = "0.5"
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version = "0.6"
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# The full version, including alpha/beta/rc tags.
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release = "0.5.3"
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release = "0.6.0"
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.
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@ -28,23 +28,25 @@ Publications
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- Paul K. Romano, Benoit Forget, Kord Smith, and Andrew Siegel, "On the use of
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tally servers in Monte Carlo simulations of light-water reactors,"
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*Proc. Joint International Conference on Supercomputing in Nuclear
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Applications and Monte Carlo*, Paris, France, Oct. 27--31 (2013).
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Applications and Monte Carlo*, Paris, France, Oct. 27--31
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(2013). `<http://dx.doi.org/10.1051/snamc/201404301>`_
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- Paul K. Romano, Nicholas E. Horelik, Bryan R. Herman, Adam G. Nelson, Benoit
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Forget, and Kord Smith, "OpenMC: A State-of-the-Art Monte Carlo Code for
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Research and Development," *Proc. Joint International Conference on
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Supercomputing in Nuclear Applications and Monte Carlo*, Paris, France,
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Oct. 27--31 (2013).
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Oct. 27--31 (2013). `<http://dx.doi.org/10.1051/snamc/201406016>`_
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- Kyle G. Felker, Andrew R. Siegel, Kord S. Smith, Paul K. Romano, and Benoit
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Forget, "The energy band memory server algorithm for parallel Monte Carlo
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calculations," *Proc. Joint International Conference on Supercomputing in
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Nuclear Applications and Monte Carlo*, Paris, France, Oct. 27--31 (2013).
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Nuclear Applications and Monte Carlo*, Paris, France, Oct. 27--31
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(2013). `<http://dx.doi.org/10.1051/snamc/201404207>`_
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- John R. Tramm and Andrew R. Siegel, "Memory Bottlenecks and Memory Contention
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in Multi-Core Monte Carlo Transport Codes," *Proc. Joint International
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Conference on Supercomputing in Nuclear Applications and Monte Carlo*, Paris,
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France, Oct. 27--31 (2013).
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France, Oct. 27--31 (2013). `<http://dx.doi.org/10.1051/snamc/201404208>`_
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- Andrew R. Siegel, Kord Smith, Paul K. Romano, Benoit Forget, and Kyle Felker,
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"Multi-core performance studies of a Monte Carlo neutron transport code,"
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@ -494,4 +494,3 @@ schemas.xml file in your own OpenMC source directory.
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.. _validation: http://en.wikipedia.org/wiki/XML_validation
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.. _RELAX NG: http://relaxng.org/
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.. _ctest: http://www.cmake.org/cmake/help/v2.8.12/ctest.html
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.. _NNDC: http://http://www.nndc.bnl.gov/endf/b7.1/acefiles.html
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@ -17,7 +17,6 @@ for your Python installation to contain:
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* [3]_ `Matplotlib <http://matplotlib.org/>`_
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* [3]_ `Silomesh <https://github.com/nhorelik/silomesh>`_
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* [3]_ `VTK <http://www.vtk.org/>`_
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* [4]_ `PyQt <http://www.riverbankcomputing.com/software/pyqt>`_
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Most of these are easily obtainable in Ubuntu through the package manager, or
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are easily installed with distutils.
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@ -25,7 +24,6 @@ are easily installed with distutils.
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.. [1] Required for tally data extraction from statepoints with statepoint.py
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.. [2] Required only if reading HDF5 statepoint files.
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.. [3] Optional for plotting utilities
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.. [4] Optional for interactive GUIs
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----------------------
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Geometry Visualization
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@ -94,9 +92,9 @@ After running OpenMC to obtain PPM files, images should be saved to another
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format before using them elsewhere. This cuts down the size of the file by
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orders of magnitude. Most image viewers and editors that can view PPM images
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can also save to other formats (e.g. `Gimp <http://www.gimp.org/>`_, `IrfanView
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<http://www.irfanview.com/>`_, etc.). However, more likey the user will want to
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<http://www.irfanview.com/>`_, etc.). However, more likely the user will want to
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convert to another format on the command line. This is easily accomplished with
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the ``convert`` command available on most linux distributions as part of the
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the ``convert`` command available on most Linux distributions as part of the
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`ImageMagick <http://www.imagemagick.org/script/convert.php>`_ package. (On
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Ubuntu: ``sudo apt-get install imagemagick``). Images are then converted like:
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@ -172,7 +170,7 @@ doing this will depend on the 3D viewer, but should be straightforward.
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:height: 200px
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.. note:: 3D voxel plotting can be very computer intensive for the viewing
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program (Visit, Paraview, etc.) if the number of voxels is large (>10
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program (Visit, ParaView, etc.) if the number of voxels is large (>10
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million or so). Thus if you want an accurate picture that renders
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smoothly, consider using only one voxel in a certain direction. For
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instance, the 3D pin lattice figure at the beginning of this section
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@ -235,13 +233,13 @@ combination:
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filters = [('mesh', (1, 1, 5)), ('energyin', 0)]
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value, error = sp.get_value(tallyid, filters, score)
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In the future more documentaion may become available here for statepoint.py and
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In the future more documentation may become available here for statepoint.py and
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the data extraction functions of StatePoint objects. However, for now it is up
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to the user to explore the classes in statepoint.py to discover what data is
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available in StatePoint objects (we highly recommend interactively exploring
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with `IPython <http://ipython.org/>`_). Many exmaples can be found by looking
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through the other utilies that use statepoint.py, and a few common visualization
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tasks will be described here in the following sections.
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with `IPython <http://ipython.org/>`_). Many examples can be found by looking
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through the other utilities that use statepoint.py, and a few common
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visualization tasks will be described here in the following sections.
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Plotting in 2D
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--------------
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@ -251,8 +249,7 @@ Plotting in 2D
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For simple viewing of 2D slices of a mesh plot, the utility plot_mesh_tally.py
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is provided. This utility provides an interactive GUI to explore and plot
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mesh tallies for any scores and filter bins. It requires statepoint.py, as well
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as `PyQt <http://www.riverbankcomputing.com/software/pyqt>`_.
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mesh tallies for any scores and filter bins. It requires statepoint.py.
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.. image:: ../_images/fluxplot.png
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:height: 200px
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@ -446,14 +443,14 @@ Particle Track Visualization
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OpenMC can dump particle tracks—the position of particles as they are
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transported through the geometry. There are two ways to make OpenMC output
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tracks: all particle tracks through a commandline argument or specific particle
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tracks: all particle tracks through a command line argument or specific particle
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tracks through settings.xml.
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Running OpenMC with the argument "-t", "-track", or "--track" will cause a track
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file to be created for every particle transported in the code.
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The settings.xml file can dictate that specific particle tracks are output.
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These particles are specified withen a ''track'' element. The ''track'' element
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These particles are specified within a ''track'' element. The ''track'' element
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should contain triplets of integers specifying the batch, generation, and
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particle numbers, respectively. For example, to output the tracks for particles
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3 and 4 of batch 1 and generation 2 the settings.xml file should contain:
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@ -474,7 +471,7 @@ describing track files. The default output name is "track.pvtp". A common
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usage of track.py is "track.py track*.binary" which will use the data from all
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binary track files in the directory to write a "track.pvtp" VTK output file.
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The .pvtp file can then be read and plotted by 3d visualization programs such as
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Paraview.
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ParaView.
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----------------------
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Source Site Processing
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@ -7,8 +7,8 @@ module constants
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! OpenMC major, minor, and release numbers
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integer, parameter :: VERSION_MAJOR = 0
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integer, parameter :: VERSION_MINOR = 5
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integer, parameter :: VERSION_RELEASE = 4
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integer, parameter :: VERSION_MINOR = 6
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integer, parameter :: VERSION_RELEASE = 0
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! Revision numbers for binary files
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integer, parameter :: REVISION_STATEPOINT = 12
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@ -3,7 +3,7 @@
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from distutils.core import setup
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setup(name='statepoint',
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version='0.5.4',
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version='0.6.0',
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description='OpenMC StatePoint',
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author='Paul Romano',
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author_email='paul.k.romano@gmail.com',
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