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Merge pull request #1371 from paulromano/doc-updates
Documentation fixes and updates
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docs/source/conf.py

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'scipy.interpolate', 'scipy.integrate', 'scipy.optimize', 'scipy.special',
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'scipy.stats', 'scipy.spatial', 'h5py', 'pandas', 'uncertainties',
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'matplotlib', 'matplotlib.pyplot', 'openmoc',
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'openmc.data.reconstruct'
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'openmc.data.reconstruct', 'openmc.checkvalue'
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]
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sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES)
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docs/source/devguide/docbuild.rst

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=============================
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In order to build the documentation in the ``docs`` directory, you will need to
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have the `Sphinx <http://openmc.readthedocs.io/en/latest/>`_ third-party Python
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have the `Sphinx <https://www.sphinx-doc.org/en/master/>`_ third-party Python
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package. The easiest way to install Sphinx is via pip:
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.. code-block:: sh
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sudo pip install sphinx
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pip install sphinx
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Additionally, you will also need a Sphinx extension for numbering figures. The
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`Numfig <http://openmc.readthedocs.io/en/latest/>`_ package can be installed
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Additionally, you will need several Sphinx extensions that can be installed
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directly with pip:
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.. code-block:: sh
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sudo pip install sphinx-numfig
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pip install sphinx-numfig
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pip install sphinxcontrib-katex
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pip install sphinxcontrib-svg2pdfconverter
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-----------------------------------
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Building Documentation as a Webpage
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-----------------------------------
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To build the documentation as a webpage (what appears at
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http://openmc.readthedocs.io), simply go to the ``docs`` directory and run:
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https://docs.openmc.org), simply go to the ``docs`` directory and run:
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.. code-block:: sh
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docs/source/devguide/docker.rst

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MPICH and parallel HDF5 in the ``/opt/openmc`` directory, and
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`Miniconda3 <https://conda.io/miniconda.html>`_ with all of the Python
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pre-requisites (NumPy, SciPy, Pandas, etc.) installed. The
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`NJOY2016 <http://www.njoy21.io/NJOY2016/>`_ codebase is installed in
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`NJOY2016 <https://www.njoy21.io/NJOY2016/>`_ codebase is installed in
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``/opt/NJOY2016`` to support full functionality and testing of the
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``openmc.data`` Python module. The publicly available nuclear data libraries
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necessary to run OpenMC's test suite -- including NNDC and WMP cross sections
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.. _Docker container: https://www.docker.com/resources/what-container
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.. _options: https://docs.docker.com/engine/reference/commandline/run/
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.. _mounting volumes: https://docs.docker.com/storage/volumes/
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docs/source/devguide/styleguide.rst

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-------------
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Classes, structs, and functions are to be annotated for the `Doxygen
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<http://www.stack.nl/~dimitri/doxygen/>`_ documentation generation tool. Use the
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``\`` form of Doxygen commands, e.g., ``\brief`` instead of ``@brief``.
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<http://www.doxygen.nl/>`_ documentation generation tool. Use the ``\`` form of
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Doxygen commands, e.g., ``\brief`` instead of ``@brief``.
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------
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Python
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.. _C++ Core Guidelines: http://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines
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.. _PEP8: https://www.python.org/dev/peps/pep-0008/
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.. _numpydoc: https://numpydoc.readthedocs.io/en/latest/format.html
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.. _numpy: http://www.numpy.org/
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.. _numpy: https://numpy.org/
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.. _scipy: https://www.scipy.org/
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.. _matplotlib: https://matplotlib.org/
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.. _pandas: https://pandas.pydata.org/

docs/source/devguide/workflow.rst

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.. _GitHub: https://github.com/
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.. _git flow: http://nvie.com/git-model
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.. _valgrind: http://valgrind.org/
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.. _style guide: http://openmc.readthedocs.io/en/latest/devguide/styleguide.html
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.. _style guide: https://docs.openmc.org/en/latest/devguide/styleguide.html
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.. _pull request: https://help.github.com/articles/using-pull-requests
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.. _openmc-dev/openmc: https://github.com/openmc-dev/openmc
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.. _paid plan: https://github.com/plans

docs/source/index.rst

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The OpenMC Monte Carlo Code
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===========================
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OpenMC is a Monte Carlo particle transport simulation code focused on neutron
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criticality calculations. It is capable of simulating 3D models based on
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constructive solid geometry with second-order surfaces. OpenMC supports either
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continuous-energy or multi-group transport. The continuous-energy particle
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OpenMC is a community-developed Monte Carlo neutron and photon transport
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simulation code. It is capable of performing fixed source, k-eigenvalue, and
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subcritical multiplication calculations on models built using either a
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constructive solid geometry or CAD representation. OpenMC supports both
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continuous-energy and multigroup transport. The continuous-energy particle
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interaction data is based on a native HDF5 format that can be generated from ACE
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files used by the MCNP and Serpent Monte Carlo codes.
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files produced by NJOY. Parallelism is enabled via a hybrid MPI and OpenMP
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programming model.
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OpenMC was originally developed by members of the `Computational Reactor Physics
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Group <http://crpg.mit.edu>`_ at the `Massachusetts Institute of Technology

docs/source/io_formats/settings.rst

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velocity sampling) or "dbrc" (Doppler broadening rejection correction).
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Descriptions of each of these methods are documented here_.
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.. _here: http://dx.doi.org/10.1016/j.anucene.2017.12.044
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.. _here: https://doi.org/10.1016/j.anucene.2017.12.044
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*Default*: "rvs"
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docs/source/io_formats/statepoint.rst

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**/tallies/tally <uid>/**
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:Attributes: - **internal** (*int*) -- Flag indicating the presence of tally
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:Attributes:
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- **internal** (*int*) -- Flag indicating the presence of tally
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data (0) or absence of tally data (1). All user defined
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tallies will have a value of 0 unless otherwise instructed.
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docs/source/methods/cmfd.rst

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.. rubric:: References
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.. [BEAVRS] Nick Horelik, Bryan Herman. *Benchmark for Evaluation And Verification of Reactor
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Simulations*. Massachusetts Institute of Technology, http://crpg.mit.edu/pub/beavrs
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Simulations*. Massachusetts Institute of Technology, https://crpg.mit.edu/research/beavrs
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, 2013.
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.. [Gill] Daniel F. Gill. *Newton-Krylov methods for the solution of the k-eigenvalue problem in

docs/source/methods/cross_sections.rst

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Continuous-Energy Data
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----------------------
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The data governing the interaction of neutrons with
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various nuclei for continous-energy problems are represented using the ACE
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format which is used by MCNP_ and Serpent_. ACE-format data can be generated
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with the NJOY_ nuclear data processing system which converts raw
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`ENDF/B data`_ into linearly-interpolable data as required by most Monte Carlo
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codes. The use of a standard cross section format allows for a direct comparison
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of OpenMC with other codes since the same cross section libraries can be used.
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In OpenMC, the data governing the interaction of neutrons with various nuclei
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for continous-energy problems are represented using an HDF5 format that can be
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produced by converting files in the ACE format, which is used by MCNP_ and
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Serpent_. ACE-format data can be generated with the NJOY_ nuclear data
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processing system, which converts raw `ENDF/B data`_ into linearly-interpolable
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data as required by most Monte Carlo codes. Since ACE-format data can be
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converted into OpenMC's HDF5 format, it is possible to perform direct comparison
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of OpenMC with other codes using the same underlying nuclear data library.
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The ACE format contains continuous-energy cross sections for the following types
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Energy Grid Methods
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The method by which continuous energy cross sections for each nuclide in a
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The method by which continuous-energy cross sections for each nuclide in a
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problem are stored as a function of energy can have a substantial effect on the
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performance of a Monte Carlo simulation. Since the ACE format is based on
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In addition to the usual pointwise representation of cross sections, OpenMC
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This data format requires less memory than pointwise cross sections, and it
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allows on-the-fly Doppler broadening to arbitrary temperature.
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offers support for a data format called windowed multipole (WMP). This data
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format requires less memory than pointwise cross sections, and it allows
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on-the-fly Doppler broadening to arbitrary temperature.
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The multipole method was introduced by Hwang_ and the faster windowed multipole
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method by Josey_. In the multipole format, cross section resonances are
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Finally, the above options for representing the physics do not have to be
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consistent across the problem. The number of groups and the structure, however,
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consistent across the problem. The number of groups and the structure, however,
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does have to be consistent across the data sets. That is to say that each
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.. _logarithmic mapping technique:
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https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-14-24530.pdf
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.. _Hwang: http://www.ans.org/pubs/journals/nse/a_16381
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.. _Josey: http://dx.doi.org/10.1016/j.jcp.2015.08.013
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.. _Josey: https://doi.org/10.1016/j.jcp.2015.08.013
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.. _WMP Library: https://github.com/mit-crpg/WMP_Library
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.. _MCNP: http://mcnp.lanl.gov
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.. _Serpent: http://montecarlo.vtt.fi
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.. _NJOY: http://t2.lanl.gov/codes.shtml
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.. _ENDF/B data: http://www.nndc.bnl.gov/endf
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.. _Leppanen: http://dx.doi.org/10.1016/j.anucene.2009.03.019
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.. _Leppanen: https://doi.org/10.1016/j.anucene.2009.03.019
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.. _algorithms: http://ab-initio.mit.edu/wiki/index.php/Faddeeva_Package

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