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        "author_email": "kdavies4@gmail.com",
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            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.2",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Topic :: Scientific/Engineering",
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        "description": "#############\n ModelicaRes\n#############\n\n**Set up and analyze Modelica simulations**\n\nModelicaRes is a free, open-source tool that can be used to\n\n- generate simulation scripts,\n- load and browse data,\n- perform custom calculations,\n- filter and sort groups of results,\n- produce various plots and diagrams, and\n- export data to various formats via pandas_.\n\nThe figures are generated via matplotlib_, which offers a rich set of\npublication-quality plotting routines.  ModelicaRes has methods to create and\nautomatically label xy plots, Bode and Nyquist plots, and Sankey diagrams.\nModelicaRes can be scripted or used in an interactive Python_ session with math\nand matrix functions from NumPy_.\n\nThe figures are generated via matplotlib_, which offers a rich set of plotting\nroutines.  ModelicaRes has methods to create and automatically label\n`xy plots`_, Bode_ and Nyquist_ plots, and `Sankey diagrams`_.  ModelicaRes can\nbe scripted or used in an interactive Python_ session with math and matrix\nfunctions from NumPy_.\n\nCurrently, ModelicaRes only loads Dymola/OpenModelica_-formatted results\n(\\*.mat), but the loading functions are modular so that other formats can be\nadded easily.\n\nPlease see the tutorial, which is available as an `IPython notebook\n<https://github.com/kdavies4/ModelicaRes/blob/master/examples/tutorial.ipynb>`_\nor online as a `static page\n<http://nbviewer.ipython.org/github/kdavies4/ModelicaRes/blob/master/examples/tutorial.ipynb>`_.\nFor the full documentation and many more examples, see the `main website`_.\n\nFor a list of changes, please see the `change log\n<http://kdavies4.github.io/ModelicaRes/changelog.html>`_.\n\nInstallation\n~~~~~~~~~~~~\n\nFirst, install the dependencies.  Most are installed automatically if you have\nthe setuptools_ module.  However, SciPy_ >= 0.10.0 must be installed according\nto the instructions at http://www.scipy.org/install.html.  The GUIs require\nQt_, which can be installed via PyQt4_, guidata_, or PySide_.\n\nThen install ModelicaRes.  The easiest way is to use pip_::\n\n    pip install modelicares\n\nOn Linux, it may be necessary to have root privileges::\n\n    sudo pip install modelicares\n\nAnother way to install ModelicaRes is to download and extract a copy of the\npackage.  The `main website`_, the `GitHub repository`_, and the `PyPI page`_\nhave copies which include the source code as well as examples and supporting\nfiles to build the documentation and run tests.  Once you have a copy, run the\nfollowing command from the base folder::\n\n    python setup.py install\n\nOr, on Linux::\n\n    sudo python setup.py install\n\nThe `matplotlibrc file\n<https://github.com/kdavies4/ModelicaRes/blob/master/examples/matplotlibrc>`_\nfile has some recommended revisions to matplotlib_'s defaults.  To use it, copy\nit to the working directory or matplotlib_'s configuration directory.  See\nhttp://matplotlib.org/users/customizing.html for details.\n\nCredits\n~~~~~~~\n\nThe main author is Kevin Davies.  Code has been included from:\n\n- Richard Murray (**control.freqplot**---part of python-control_),\n- Joerg Raedler (method to expand a Modelica_ variable tree---from DyMat_),\n- Jason Grout (`ArrowLine class`_), and\n- Jason Heeris (`efficient base-10 logarithm`_).\n\nSuggestions and bug fixes have been provided by Arnout Aertgeerts, Kevin Bandy,\nThomas Beutlich, Moritz Lauster, Martin Sj\u00f6lund, Mike Tiller, and Michael\nWetter.\n\nLicense terms and development\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nModelicaRes is published under a `BSD-compatible license\n<https://github.com/kdavies4/ModelicaRes/blob/release/LICENSE.txt>`_.  Please\nshare any modifications you make (preferably as a pull request to the ``master``\nbranch of the `GitHub repository`_) in order to help others.  There are useful\ndevelopment scripts in the `hooks folder\n<https://github.com/kdavies4/ModelicaRes/blob/master/hooks/>`_.  If you find a\nbug, please `report it\n<https://github.com/kdavies4/ModelicaRes/issues/new>`_.  If you have\nsuggestions, please `share them\n<https://github.com/kdavies4/ModelicaRes/wiki/Suggestions>`_.\n\nSee also\n~~~~~~~~\n\n- awesim_: helps run simulation experiments and organize results\n- BuildingsPy_: supports unit testing\n- DyMat_: exports Modelica_ simulation data to comma-separated values\n  (CSV_), Gnuplot_, MATLAB\u00ae, and Network Common Data Form (netCDF_)\n- PyFMI_: tools to work with models through the Functional Mock-Up Interface\n  (FMI_) standard\n- PySimulator_: elaborate GUI; supports FMI_\n\n\n.. _main website: http://kdavies4.github.io/ModelicaRes/\n.. _PyPI page: http://pypi.python.org/pypi/ModelicaRes\n.. _GitHub repository: https://github.com/kdavies4/ModelicaRes\n\n.. _xy plots: http://kdavies4.github.io/ModelicaRes/simres.html#modelicares.simres.SimRes.plot\n.. _Bode: http://kdavies4.github.io/ModelicaRes/linres.html#modelicares.linres.LinRes.bode\n.. _Nyquist: http://kdavies4.github.io/ModelicaRes/linres.html#modelicares.linres.LinRes.nyquist\n.. _Sankey diagrams: http://kdavies4.github.io/ModelicaRes/simres.html#modelicares.simres.SimRes.sankey\n\n.. _Modelica: http://www.modelica.org/\n.. _Python: http://www.python.org/\n.. _pandas: http://pandas.pydata.org/\n.. _matplotlib: http://www.matplotlib.org/\n.. _NumPy: http://numpy.scipy.org/\n.. _SciPy: http://www.scipy.org/index.html\n.. _OpenModelica: https://www.openmodelica.org/\n.. _setuptools: https://pypi.python.org/pypi/setuptools\n.. _Qt: http://qt-project.org/\n.. _PyQt4: http://www.riverbankcomputing.co.uk/software/pyqt/\n.. _guidata: https://code.google.com/p/guidata/\n.. _PySide: http://qt-project.org/wiki/pyside\n.. _pip: https://pypi.python.org/pypi/pip\n.. _awesim: https://github.com/saroele/awesim\n.. _BuildingsPy: http://simulationresearch.lbl.gov/modelica/buildingspy/\n.. _DyMat: http://www.j-raedler.de/projects/dymat/\n.. _PyFMI: https://pypi.python.org/pypi/PyFMI\n.. _PySimulator: https://github.com/PySimulator/PySimulator\n.. _Gnuplot: http://www.gnuplot.info\n.. _CSV: http://en.wikipedia.org/wiki/Comma-separated_values\n.. _netCDF: http://www.unidata.ucar.edu/software/netcdf/\n.. _FMI: https://www.fmi-standard.org\n.. _python-control: http://sourceforge.net/apps/mediawiki/python-control\n.. _ArrowLine class: http://old.nabble.com/Arrows-using-Line2D-and-shortening-lines-td19104579.html\n.. _efficient base-10 logarithm: http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg14433.html",
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