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    "info": {
        "author": "S. Brewster Malevich",
        "author_email": "malevich@email.arizona.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering"
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        "description": "baysparpy\n=========\n\n.. image:: https://travis-ci.org/brews/baysparpy.svg?branch=master\n    :target: https://travis-ci.org/brews/baysparpy\n\n\nAn Open Source Python package for TEX86 calibration.\n\nThis package is based on the original BAYSPAR (BAYesian SPAtially-varying Regression) for MATLAB (https://github.com/jesstierney/BAYSPAR).\n\n\nQuick example\n-------------\n\nFirst, load key packages and an example dataset:\n\n.. code-block:: python\n\n    import numpy as np\n    import bayspar as bsr\n\n    example_file = bsr.get_example_data('castaneda2010.csv')\n    d = np.genfromtxt(example_file, delimiter=',', names=True)\n\nThis dataset (from `Casta\u00f1eda et al. 2010 <https://doi.org/10.1029/2009PA001740>`_)\nhas two columns giving sediment age (calendar years BP) and TEX86.\n\nWe can make a \"standard\" prediction of sea-surface temperature (SST) with ``predict_seatemp()``:\n\n.. code-block:: python\n\n    prediction = bsr.predict_seatemp(d['tex86'], lon=34.0733, lat=31.6517,\n                                     prior_std=6, temptype='sst')\n\nTo see actual numbers from the prediction, directly parse ``prediction.ensemble`` or use ``prediction.percentile()`` to get the 5%, 50% and 95% percentiles.\n\nYou can also plot your prediction with ``bsr.predictplot()`` or ``bsr.densityplot()``.\n\nFor further details, examples, and additional prediction functions, see the online documentation (https://baysparpy.readthedocs.io).\n\n\nInstallation\n------------\n\nTo install **baysparpy** with pip, run:\n\n.. code-block:: bash\n\n    $ pip install git+git://github.com/brews/baysparpy.git@stable\n\nUnfortunately, **baysparpy** is not compatible with Python 2.\n\nSupport and development\n-----------------------\n\n- Documentation is available online (https://baysparpy.readthedocs.io).\n\n- Please feel free to report bugs and issues or view the source code on GitHub (https://github.com/brews/baysparpy).\n\n\nLicense\n-------\n\n**baysparpy** is available under the Open Source GPLv3 (https://www.gnu.org/licenses).\n\n\n\n",
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        "keywords": "marine paleoclimate tex86 calibration",
        "license": "GPLv3",
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        "name": "baysparpy",
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