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        "author": "Mark Mikofski",
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        "description": ".. image:: https://travis-ci.org/SunPower/SolarUtils.svg?branch=master\n    :target: https://travis-ci.org/SunPower/SolarUtils\n\nSolarUtils is set of Python wrappers around the publicly available\n`NREL <http://www.nrel.gov/>`_\n`SOLPOS <http://rredc.nrel.gov/solar/codesandalgorithms/solpos/>`_ and\n`SPECTRL2 <http://rredc.nrel.gov/solar/models/spectral/>`_ C-language computer\nprograms that calculate solar position and spectral decomposition. Please read\nthe `NREL disclaimer and license <http://www.nrel.gov/disclaimer.html>`_. Usage\nof this software implies acceptance of the terms.\n\nInstallation\n============\nUse ``pip`` to install\n`SolarUtils from the PyPI <https://pypi.python.org/pypi/SolarUtils>`_::\n\n    pip install SolarUtils\n\nYou can also download a source distribution from PyPI or clone the repository\nand use Python ``distutils``::\n\n    python setup.py install\n\nRequirements\n============\nSolarUtils has no requirements for usage however for installation, testing and\nto build the documentaiton you will need the following pacakges:\n\n* NumPy\n* PyTest\n* Sphinx\n\nUsage\n=====\nSee `SOLPOS Documentation <http://rredc.nrel.gov/solar/codesandalgorithms/solpos/aboutsolpos.html>`_\nand\n`SPECTRL2 Documentation <http://rredc.nrel.gov/solar/models/spectral/spectrl2/documentation.html>`_\nfor more detail.\n\nExamples\n--------\n\n    >>> from solar_utils import *\n    >>> import pandas as pd\n    >>> location = [35.56836, -119.2022, -8.0]\n    >>> datetime = [2013, 6, 5, 12, 31, 0]\n    >>> weather = [1015.62055, 40.0]\n    >>> (angles, airmass) = solposAM(location, datetime, weather)\n    >>> zenith, azimuth = angles\n    >>> zenith\n    15.074043273925781\n    >>> azimuth\n    213.29042053222656]\n    >>> am, amp = airmass\n    >>> am\n    1.0352272987365723\n    >>> amp\n    1.0379053354263306]\n\n    >>> units = 1\n    >>> location = [33.65, -84.43, -5.0]\n    >>> datetime = [1999, 7, 22, 9, 45, 37]\n    >>> weather = [1006.0, 27.0]\n    >>> orientation = [33.65, 135.0]\n    >>> atmospheric_conditions = [1.14, 0.65, -1.0, 0.2, 1.36]\n    >>> albedo = [0.3, 0.7, 0.8, 1.3, 2.5, 4.0] + ([0.2] * 6)\n    >>> specdif, specdir, specetr, specglo, specx = spectrl2(\n    ...     units, location, datetime, weather, orientation,\n    ...     atmospheric_conditions, albedo\n    ... )\n    >>> spec = pd.DataFrame(\n    ...     {'DIF': specdif, 'DIR': specdir, 'ETR': specetr, 'GLO': specglo},\n    ...     index=specx\n    ... )\n    >>> f = spec.plot()\n    >>> f.set_title('Solar Spectrum Example')\n    >>> f.set_xlabel('Wavelength, $\\lambda [\\mu m]$')\n    >>> f.set_ylabel('Spectral Irradiance, $I_{\\lambda} [W/m^2/\\mu m]$')\n    >>> f.grid(True)\n    >>> f.figure.show()\n\n\n",
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