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docs/sphinx/source/index.rst

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Welcome to pvlib-python's documentation!
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pvlib-python
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========================================
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pvlib-python provides a set of documented functions for simulating
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the performance of photovoltaic energy systems.
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The toolbox was originally developed in MATLAB at
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Sandia National Laboratories and it implements many of the
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models and methods developed at the Labs.
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More information on Sandia Labs PV performance modeling programs
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can be found at https://pvpmc.sandia.gov/.
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The source code for pvlib-python is hosted on
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`github <https://github.com/pvlib/pvlib-python>`_.
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The github page also contains a valuable
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`wiki <https://github.com/pvlib/pvlib-python/wiki>`_
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with information on how you can contribute to pvlib-python development!
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Please see the links above for details on the status of the pvlib-python
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project. We are at an early stage in the development of this project,
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so expect to see significant API changes in the next few releases.
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This documentation focuses on providing a reference for all of
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the modules and functions available in pvlib-python.
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For examples of how to use pvlib-python, please see the
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`tutorials <http://nbviewer.ipython.org/github/pvlib/pvlib-python/tree/master/docs/tutorials/>`_.
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Some of the tutorials were written with older
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versions of pvlib-python and we would greatly appreciate your
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help updating them!
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.. note::
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This documentation assumes general familiarity with
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Python, NumPy, and Pandas. Google searches will yield many
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excellent tutorials for these packages.
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Please see our
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`PVSC 2014 paper <http://energy.sandia.gov/wp/wp-content/gallery/uploads/PV_LIB_Python_final_SAND2014-18444C.pdf>`_
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and
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`PVSC 2015 paper <https://github.com/pvlib/pvsc2015/blob/master/pvlib_pvsc_42.pdf>`_
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(and the `notebook to reproduce the figures <http://nbviewer.ipython.org/github/pvlib/pvsc2015/blob/master/paper.ipynb>`_) for more information.
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The GitHub wiki also has a page on `Projects and publications that use pvlib python <https://github.com/pvlib/pvlib-python/wiki/Projects-and-publications-that-use-pvlib-python>`_ for inspiration and listing of your application.
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There is a :ref:`variable naming convention <variables_style_rules>` to ensure consistency throughout the library.
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Installation
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============
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1. Follow Pandas'
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`instructions <http://pandas.pydata.org/pandas-docs/stable/install.html>`_
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for installing the scientific python stack, including ``pip``.
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#. ``pip install pvlib-python``
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pvlib-python provides a set of documented functions for simulating the
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performance of photovoltaic energy systems. The toolbox was originally
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developed in MATLAB at Sandia National Laboratories and it implements
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many of the models and methods developed at the Labs. More information
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on Sandia Labs PV performance modeling programs can be found at
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https://pvpmc.sandia.gov/.
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The source code for pvlib-python is hosted on `github
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<https://github.com/pvlib/pvlib-python>`_.
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Please see the :ref:`installation` page for installation help.
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For examples of how to use pvlib-python, please see
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:ref:`package_overview` and our `Jupyter Notebook tutorials
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<http://nbviewer.ipython.org/github/pvlib/pvlib-python/tree/master/docs/
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tutorials/>`_. The documentation assumes general familiarity with
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Python, NumPy, and Pandas. Google searches will yield many
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excellent tutorials for these packages.
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The pvlib-python GitHub wiki has a `Projects and publications that use
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pvlib python
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<https://github.com/pvlib/pvlib-python/wiki/Projects-and-publications-
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that-use-pvlib-python>`_ page for inspiration and listing of your
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application.
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There is a :ref:`variable naming convention <variables_style_rules>` to
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ensure consistency throughout the library.
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Citing pvlib-python
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===================
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Many of the contributors to pvlib-python work in institutions where
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citation metrics are used in performance or career evaluations. If you
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use pvlib-python in a published work, please cite the most appropriate
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of:
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* J. S. Stein, “The photovoltaic performance modeling
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collaborative (PVPMC),” in Photovoltaic Specialists Conference, 2012.
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* R.W. Andrews, J.S. Stein, C. Hansen, and D. Riley, “Introduction
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to the open source pvlib for python photovoltaic system
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modelling package,” in 40th IEEE Photovoltaic Specialist
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Conference, 2014.
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(`paper
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<http://energy.sandia.gov/wp/wp-content/gallery/uploads/PV_LIB_Python_final_SAND2014-18444C.pdf>`_)
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* W.F. Holmgren, R.W. Andrews, A.T. Lorenzo, and J.S. Stein,
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“PVLIB Python 2015,” in 42nd Photovoltaic Specialists Conference, 2015.
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(`paper
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<https://github.com/pvlib/pvsc2015/blob/master/pvlib_pvsc_42.pdf>`_ and
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the `notebook to reproduce the figures
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<http://nbviewer.ipython.org/github/pvlib/pvsc2015/blob/master/paper.ipynb>`_)
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* J.S. Stein, W.F. Holmgren, J. Forbess, and C.W. Hansen,
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"PVLIB: Open Source Photovoltaic Performance Modeling Functions
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for Matlab and Python," in 43rd Photovoltaic Specialists Conference, 2016.
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* W.F. Holmgren and D.G. Groenendyk,
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"An Open Source Solar Power Forecasting Tool Using PVLIB-Python,"
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in 43rd Photovoltaic Specialists Conference, 2016.
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Specific released versions of pvlib-python can be cited using their
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`Zenodo DOI <https://zenodo.org/search?ln=en&p=pvlib&action_search=>`_.
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Contents
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========
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.. toctree::
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:maxdepth: 2
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self
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package_overview
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whatsnew
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installation
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contributing
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modules
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classes
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comparison_pvlib_matlab
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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