{
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        "author": "Martijn Visser",
        "author_email": "martijn.visser@deltares.nl",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Scientific/Engineering"
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        "description": ".. image:: https://gitlab.com/deltares/imod/imod-python/badges/master/pipeline.svg\n   :target: https://gitlab.com/deltares/imod/imod-python/commits/master\n.. image:: https://gitlab.com/deltares/imod/imod-python/badges/master/coverage.svg\n   :target: https://gitlab.com/deltares/imod/imod-python/commits/master\n\nWork with `iMOD <https://oss.deltares.nl/web/imod>`__ MODFLOW models in\nPython.\n\nDocumentation: https://imod.xyz/\n\nSource code: https://gitlab.com/deltares/imod/imod-python\n\nGetting started\n===============\n\n.. code:: python\n\n    import imod\n\n    # read and write IPF files to pandas DataFrame\n    df = imod.ipf.read('wells.ipf')\n    imod.ipf.save('wells-out.ipf', df)\n\n    # get all calculated heads in a xarray DataArray\n    # with dimensions time, layer, y, x\n    da = imod.idf.open('path/to/results/head_*.idf')\n\nIntroduction\n============\n\nThe imod Python package is an addition to iMOD and iMODFLOW, intended to facilitate\nworking with groundwater models from Python. It does this by supporting reading and\nwriting of the different iMOD file formats to existing objects often used in Python\ndata processing.\n\nIDF - iMOD Data Format\n----------------------\nIDF is the binary raster format of iMOD. One file contains a X and Y 2 dimensional grid.\nUsing a set of file name conventions more dimensions such as ``time`` and ``layer`` are\nadded, for example: ``head_20181113_l3.idf`` for layer 3 and timestamp ``2018-11-13``.\nThis package maps IDF files to and from the N dimensional labeled arrays of\n`xarray.DataArray <http://xarray.pydata.org/en/stable/data-structures.html#dataarray>`__,\nusing ``imod.idf.open`` and ``imod.idf.save``, or, to read multiple parameters\nat the same time, ``imod.idf.open_dataset``.\n\nFor more information on how to work with ``xarray.DataArray`` objects, we refer to the\nxarray documentation. Note that converting GIS raster formats to IDF is supported\nthrough `xarray.open_rasterio <http://xarray.pydata.org/en/stable/generated/xarray.open_rasterio.html#xarray.open_rasterio>`__,\nfollowed by ``imod.idf.save``.\n\nIPF - iMOD Point File\n---------------------\nIPF files are text files used for storing tabular point data such as timeseries and\nborehole measurements. In the imod Python package these files are read in as\n`pandas.DataFrame <https://pandas.pydata.org/pandas-docs/stable/>`__. Pandas is a\npopular package that makes analysis and processing of tabular data easy, and provides\nmany input and output options, which in turn enables us to convert for instance\nexisting CSV or Excel files to IPF files. The primary functions for reading and writing\nIPF files are ``imod.ipf.read`` and ``imod.ipf.save``.\n\nAuthors\n=======\nThis Python package was written primarily by Martijn Visser and Huite Bootsma at Deltares.\n\n\n",
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