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        "author": "Keurfon Luu",
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            "Development Status :: 5 - Production/Stable",
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            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
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            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Programming Language :: Python :: 3.9",
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        "description": "toughio\n=======\n\n|License| |Stars| |Pyversions| |Version| |Downloads| |Code style: black| |Codacy Badge| |Codecov| |Build| |Travis| |DOI| |JOSS|\n\n`TOUGH <https://tough.lbl.gov/>`__ (Transport Of Unsaturated Groundwater and Heat) is a general purpose numerical simulation software designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media developed at Lawrence Berkeley National Laboratory. It solves mass and energy balance equations that describe fluid and heat flow in multiphase and multicomponent systems. TOUGH handles all types of multiphase and multicomponent flow systems since the governing equations for fluid and heat flow have the same mathematical form. The nature and properties of fluid mixtures are described by thermophysical variables (e.g., density, viscosity, enthalpy) which are provided by an equation-of-state (EOS) module.\n\n**toughio** is an open-source library that provides tools to facilitate pre- and post-processing for TOUGH using the latest Python standards. It aims to make setting up of a TOUGH simulation user-friendly by relying on existing well-established Python packages:\n\n-  `numpy <https://numpy.org/>`__: vectorized calculation of N-dimensional arrays,\n-  `meshio <https://github.com/nschloe/meshio>`__: input/output for many mesh formats,\n-  `pyvista <https://github.com/pyvista/pyvista>`__: 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK).\n\nNote that the results of a TOUGH simulation are sensitive to the quality of the mesh (ideally, it should satisfy the orthogonality condition). A mesh that contains too many ill-shaped cells can potentially lead to unexpected results although the simulation converged successfully. **toughio** does not verify the quality of the mesh which is left to the discretion of the user.\n\n.. figure:: https://raw.githubusercontent.com/keurfonluu/toughio/master/.github/sample.gif\n   :alt: sample-co2\n   :width: 50%\n   :align: center\n\n   Simulation of CO\\ :sub:`2`\\  leakage along a fault. Mesh generated with Gmsh and animation exported by PyVista.\n\nFeatures\n--------\n\nMeshing:\n\n-  Create simple 2D cylindric or 2D/3D structured meshes similarly to TOUGH's built-in *MESHMAKER*,\n-  Import mesh generated by external softwares (e.g., `Abaqus <https://www.3ds.com/products-services/simulia/products/abaqus/>`__, `FLAC3D <https://www.itascacg.com/software/flac3d>`__, `Gmsh <http://gmsh.info/>`__, `LaGriT <https://meshing.lanl.gov/>`__),\n-  Export imported or generated mesh to a *MESH* file for TOUGH assuming `conformity <https://www.quora.com/What-is-non-conformal-mesh-in-CFD>`__ (and optionally write initial condition file *INCON*).\n\nPre-processing:\n\n-  Easily add initial conditions, boundary conditions or other physical properties (e.g., porosity, permeability) using the convenient class ``toughio.Mesh``,\n-  Import previous TOUGH simulation input file into Python or define simulation parameters in a human-readable and `JSON <http://json.org/>`__\\ able dictionary,\n-  Export simulation parameters dictionary to a TOUGH input file.\n\nPost-processing:\n\n-  Import outputs of a TOUGH simulation into Python,\n-  Visualize results directly in Python using `pyvista <https://github.com/pyvista/pyvista>`__ or export the results to another format supported by `meshio <https://github.com/nschloe/meshio>`__ (e.g., VTK, Tecplot...),\n-  Create animations (GIF or MP4) or export results for all time steps to a XDMF file to be visualized in ParaView.\n\nInstallation\n------------\n\nThe recommended way to install **toughio** and all its dependencies is through the Python Package Index:\n\n.. code:: bash\n\n   pip install toughio[full] --user\n\nOtherwise, clone and extract the package, then run from the package location:\n\n.. code:: bash\n\n   pip install .[full] --user\n\nTo test the integrity of the installed package, check out this repository and run:\n\n.. code:: bash\n\n   git lfs pull\n   pytest\n\nDocumentation\n-------------\n\nRefer to the online `documentation <https://keurfonluu.github.io/toughio//>`__ for detailed description of the API and examples.\n\nAlternatively, the documentation can be built using `Sphinx <https://www.sphinx-doc.org/en/master/>`__:\n\n.. code:: bash\n\n   pip install -r doc/requirements.txt\n   sphinx-build -b html doc/source doc/build\n\nNote that some sample files are stored with LFS, so you may have to run the following command beforehand:\n\n.. code:: bash\n\n   git lfs pull\n\nUsage\n-----\n\nIn Python, to read a mesh and write the corresponding TOUGH *MESH* file (without any pre-processing), simply do\n\n.. code:: python\n\n   import toughio\n\n   mesh = toughio.read_mesh(\n      filename,\n      file_format=\"flac3d\",  # Optional, inferred from file extension otherwise\n   )\n   mesh.write_tough()  # Write MESH file\n\nParameters of a TOUGH simulation can be defined as a dictionary with specific keywords following the JSON standard, for instance\n\n.. code:: python\n\n   parameters = {\n      \"title\": \"Sample title\",\n      \"eos\": \"eco2n\",\n      \"isothermal\": False,\n      \"default\": {  # Default rock properties\n         \"density\": 2600.0,\n         \"porosity\": 0.1,\n         # \"permeability\", \"conductivity\", \"specific_heat\"...\n      },\n      \"rocks\": {\n         \"shale\": {  # To overwrite default rock properties\n            \"capillarity\": {\n               \"id\": 1,\n               \"parameters\": [0.0, 0.0, 1.0],\n            },\n            # same keywords as in \"default\"\n         },\n         # other materials\n      },\n      \"options\": {\n         \"n_cycle\": 100,\n         \"t_max\": 3.0 * 365.25 * 24.0 * 3600.0,\n         # \"t_ini\", \"t_steps\", \"t_step_max\", \"gravity\", \"eps1\", \"eps2\"...\n      },\n      # \"extra_options\", \"selections\", \"solver\", \"generators\"...\n   }\n   toughio.write_input(\"INFILE\", parameters)\n\nTOUGH simulation output can also be imported into Python as a list of *namedtuple* (``type``, ``format``, ``time``, ``labels``, ``data``)\n\n.. code:: python\n\n   output = toughio.read_output(filename)\n\n**toughio** is mainly intended to be used as a Python scripting library for TOUGH. Nevertheless, several utility command line scripts are available for users who are not familiar with Python. From a console or terminal, the user can execute the following scripts:\n\n-  ``toughio-co2tab``: copy file *CO2TAB* to the target directory,\n-  ``toughio-export``: export TOUGH simulation results to a file for visualization (VTK, VTU, Tecplot or XDMF),\n-  ``toughio-extract``: extract results from TOUGH main output file and reformat as a TOUGH3 element or connection output file (mostly useful for TOUGH2 output *before* calling ``toughio-export``),\n-  ``toughio-merge``: merge input file, MESH and/or INCON into a single file (for storage or sharing),\n-  ``toughio-save2incon``: convert a *SAVE* file to an *INCON* file (mostly useful to automatically restart a simulation and reset the counters).\n\nContributing\n------------\n\nPlease refer to the `Contributing\nGuidelines <https://github.com/keurfonluu/toughio/blob/master/CONTRIBUTING.rst>`__ to see how you can help. This project is released with a `Code of Conduct <https://github.com/keurfonluu/toughio/blob/master/CODE_OF_CONDUCT.rst>`__ which you agree to abide by when contributing.\n\nNotice\n------\n\ntoughio Copyright (c) 2020, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.\nIf you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at `IPO@lbl.gov <mailto:IPO@lbl.gov>`__.\n\nThis Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit others to do so.\n\n.. |License| image:: https://img.shields.io/badge/license-BSD--3--Clause-green\n   :target: https://github.com/keurfonluu/toughio/blob/master/LICENSE\n\n.. |Stars| image:: https://img.shields.io/github/stars/keurfonluu/toughio?logo=github\n   :target: https://github.com/keurfonluu/toughio\n\n.. |Pyversions| image:: https://img.shields.io/pypi/pyversions/toughio.svg?style=flat\n   :target: https://pypi.org/pypi/toughio/\n\n.. |Version| image:: https://img.shields.io/pypi/v/toughio.svg?style=flat\n   :target: https://pypi.org/project/toughio\n\n.. |Downloads| image:: https://pepy.tech/badge/toughio\n   :target: https://pepy.tech/project/toughio\n\n.. |Code style: black| image:: https://img.shields.io/badge/code%20style-black-000000.svg?style=flat\n   :target: https://github.com/psf/black\n\n.. |Codacy Badge| image:: https://img.shields.io/codacy/grade/037f16f4e7544afbb1b99bf0d66df4a6.svg?style=flat\n   :target: https://www.codacy.com/manual/keurfonluu/toughio?utm_source=github.com&utm_medium=referral&utm_content=keurfonluu/toughio&utm_campaign=Badge_Grade\n\n.. |Codecov| image:: https://img.shields.io/codecov/c/github/keurfonluu/toughio.svg?style=flat\n   :target: https://codecov.io/gh/keurfonluu/toughio\n\n.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4287673.svg?style=flat\n   :target: https://doi.org/10.5281/zenodo.4287673\n\n.. |Build| image:: https://img.shields.io/github/workflow/status/keurfonluu/toughio/Python%20package\n   :target: https://github.com/keurfonluu/toughio\n\n.. |Travis| image:: https://img.shields.io/travis/com/keurfonluu/toughio/master?label=docs\n   :target: https://keurfonluu.github.io/toughio/\n\n.. |JOSS| image:: https://joss.theoj.org/papers/10.21105/joss.02412/status.svg\n   :target: https://doi.org/10.21105/joss.02412\n\n",
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