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removed unneeded notebooks, allowed openmc.Settings.max_order to take a None parameter, and revised notebooks according to comments from @paulromano, @wbinventor and @smharper.
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.. _examples:
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=========================
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Example Jupyter Notebooks
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=========================
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=================
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Example Notebooks
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=================
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The following series of Jupyter Notebooks provide examples for usage of OpenMC
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features via the `Python API`_.
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The following series of Jupyter_ Notebooks provide examples for usage of OpenMC
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features via the :ref:`pythonapi`.
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.. _Python API: ../pythonapi/index.html
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.. _Jupyter: https://jupyter.org/
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.. toctree::
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:maxdepth: 1
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.. _notebook_mdgxs_part_i:
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==========================
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MDGXS Part I: Introduction
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==========================
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===================================================================
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Multi-Group (Delayed) Cross Section Generation Part I: Introduction
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===================================================================
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.. only:: html
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@ -1,8 +1,8 @@
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.. _notebook_mdgxs_part_ii:
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================================
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MDGXS Part II: Advanced Features
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================================
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=========================================================================
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Multi-Group (Delayed) Cross Section Generation Part II: Advanced Features
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=========================================================================
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.. only:: html
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.. _notebook_mgxs_part_iv:
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====================================================
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MGXS Part IV: Multi-Group Mode Cross-Section Library
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====================================================
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.. only:: html
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.. notebook:: mgxs-part-iv.ipynb
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.. only:: latex
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IPython notebooks must be viewed in the online HTML documentation.
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@ -6,12 +6,13 @@ Python API
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OpenMC includes a rich Python API that enables programmatic pre- and
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post-processing. The easiest way to begin using the API is to take a look at the
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example Jupyter_ notebooks provided. However, this assumes that you are already
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familiar with Python and common third-party packages such as NumPy_. If you have
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never programmed in Python before, there are many good tutorials available
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online. We recommend going through the modules from Codecademy_ and/or the
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`Scipy lectures`_. The full API documentation serves to provide more information
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on a given module or class.
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example Jupyter_ notebooks provided in the :ref:`examples` section of the
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documentation. However, this assumes that you are already familiar with Python
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and common third-party packages such as NumPy_. If you have never programmed in
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Python before, there are many good tutorials available online. We recommend
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going through the modules from Codecademy_ and/or the `Scipy lectures`_. The
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full API documentation serves to provide more information on a given module or
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class.
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------------------------------------
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:mod:`openmc` -- Basic Functionality
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@ -60,7 +60,7 @@ class Settings(object):
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type are 'variance', 'std_dev', and 'rel_err'. The threshold value
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should be a float indicating the variance, standard deviation, or
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relative error used.
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max_order : int
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max_order : None or int
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Maximum scattering order to apply globally when in multi-group mode.
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multipole_library : str
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Indicates the path to a directory containing a windowed multipole
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@ -456,8 +456,10 @@ class Settings(object):
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@max_order.setter
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def max_order(self, max_order):
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cv.check_type('maximum scattering order', max_order, Integral)
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cv.check_greater_than('maximum scattering order', max_order, 0, True)
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if max_order is not None:
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cv.check_type('maximum scattering order', max_order, Integral)
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cv.check_greater_than('maximum scattering order', max_order, 0,
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True)
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self._max_order = max_order
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@source.setter
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