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update comparison with matlab
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‎docs/sphinx/source/comparison_pvlib_matlab.rst

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.. _comparison_pvlib_matlab:
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****************************
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Comparison with PVLIB_MATLAB
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Comparison with PVLIB MATLAB
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****************************
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This document is under construction.
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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 abstract <https://github.com/UARENForecasting/pvlib-pvsc2015/blob/master/pvlib_pvsc_42.pdf?raw=true>`_
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for more information.
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PVLIB was originally developed as a library for MATLAB at Sandia
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National Lab, and Sandia remains the official maintainer of the MATLAB
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library. Sandia supported the initial Python port and
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then released further project maintenance and development to the
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`pvlib-python maintainers <https://github.com/orgs/pvlib/people>`_.
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The pvlib-python license is BSD 3-clause,
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the PVLIB\_MATLAB license is ??.
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The pvlib-python maintainers collaborate with the PVLIB MATLAB
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maintainers but operate independently. We'd all like to keep the core
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functionality of the Python and MATLAB projects synchronized, but this
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will require the efforts of the larger pvlib-python community, not just
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the maintainers. Therefore, do not expect feature parity between the
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libaries, only similarity.
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We want to keep developing the core functionality and algorithms
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of the Python and MATLAB projects roughly in parallel,
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but we're not making any promises at this point.
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The PVLIB\_MATLAB and pvlib-python projects are currently developed
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by different teams that do not regularly work together.
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We hope to grow this collaboration in the future.
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Do not expect feature parity between the libaries, only similarity.
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Major differences
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~~~~~~~~~~~~~~~~~
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Here are some of the major differences between the latest pvlib-python build
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and the original Sandia PVLIB\_Python project, but many of these
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comments apply to the difference between pvlib-python and PVLIB\_MATLAB.
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* pvlib-python uses git version control to track all changes
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to the code. A summary of changes is included in the whatsnew file
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for each release. PVLIB MATLAB documents changes in Changelog.docx
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* pvlib-python has a comprehensive test suite, whereas PVLIB MATLAB does
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not have a test suite at all. Specifically, pvlib-python
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* Uses TravisCI for automated testing on Linux.
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* Uses Appveyor for automated testing on Windows.
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* Uses Coveralls to measure test coverage.
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Library wide changes
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~~~~~~~~~~~~~~~~~~~~
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* Using readthedocs for automated documentation building and hosting.
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* Removed ``pvl_`` from module/function names.
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* Consolidated similar functions into topical modules.
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For example, functions from ``pvl_clearsky_ineichen.m`` and
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``pvl_clearsky_haurwitz.m`` have been consolidated into ``clearsky.py``.
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* PVLIB MATLAB uses ``location`` structs as the input to some functions.
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pvlib-python just uses the lat, lon, etc. as inputs to the functions.
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Furthermore, pvlib-python replaces the structs with classes, and these classes
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have methods, such as :py:func:`~pvlib.location.Location.get_solarposition`,
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that automatically reference the appropriate data.
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See :ref:`modeling-paradigms` for more information.
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* pvlib-python implements a handful of class designed to simplify the
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PV modeling process. These include :py:class:`~pvlib.location.Location`,
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:py:class:`~pvlib.pvsystem.PVSystem`,
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:py:class:`~pvlib.pvsystem.LocalizedPVSystem`,
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:py:class:`~pvlib.tracking.SingleAxisTracker`,
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and
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:py:class:`~pvlib.modelchain.ModelChain`.
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* Remove ``pvl_`` from module names.
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* Consolidation of similar modules. For example, functions from ``pvl_clearsky_ineichen.py`` and ``pvl_clearsky_haurwitz.py`` have been consolidated into ``clearsky.py``.
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* Removed ``Vars=Locals(); Expect...; var=pvl\_tools.Parse(Vars,Expect);`` pattern. Very few tests of input validitity remain. Garbage in, garbage or ``nan`` out.
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* Removing unnecssary and sometimes undesired behavior such as setting maximum zenith=90 or airmass=0. Instead, we make extensive use of ``nan`` values.
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* Changing function and module names so that they do not conflict.
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* Added ``/pvlib/data`` for lookup tables, test, and tutorial data.
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Other differences
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~~~~~~~~~~~~~~~~~
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More specific changes
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~~~~~~~~~~~~~~~~~~~~~
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* Add PyEphem option to solar position calculations.
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* ``irradiance.py`` has more AOI, projection, and irradiance sum and calculation functions
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* Locations are now ``pvlib.location.Location`` objects, not structs.
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* Specify time zones using a string from the standard IANA Time Zone Database naming conventions or using a pytz.timezone instead of an integer GMT offset. We may add dateutils support in the future.
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* ``clearsky.ineichen`` supports interpolating monthly Linke Turbidities to daily resolution.
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* Very few tests of input validitity exist in the Python code.
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We believe that the vast majority of these tests were not necessary.
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We also make use of Python's robust support for raising and catching
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exceptions.
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* Removed unnecessary and sometimes undesired behavior such as setting
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maximum zenith=90 or airmass=0. Instead, we make extensive use of
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``nan`` values in returned arrays.
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* Implemented the NREL solar position calculation algorithm.
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Also added a PyEphem option to solar position calculations.
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* Specify time zones using a string from the standard IANA Time Zone
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Database naming conventions or using a pytz.timezone instead of an
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integer GMT offset.
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* ``clearsky.ineichen`` supports interpolating monthly
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Linke Turbidities to daily resolution.
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* Instead of requiring effective irradiance as an input, ``pvsystem.sapm``
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calculates and returns it based on input POA irradiance, AM, and AOI.
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* pvlib-python does not come with as much example data.
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* pvlib-python does not currently implement as many algorithms as
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PVLIB MATLAB.
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Documentation
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~~~~~~~~~~~~~
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* Using readthedocs for documentation hosting.
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* Many typos and formatting errors corrected.
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* Documentation source code and tutorials live in ``/`` rather than ``/pvlib/docs``.
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* Additional tutorials in ``/docs/tutorials``.
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Testing
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~~~~~~~
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* Tests are cleaner and more thorough. They are still no where near complete.
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* Using Coveralls to measure test coverage.
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* Using TravisCI for automated testing.
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* Using ``nosetests`` for more concise test code.
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* Using Sphinx to build the documentation,
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including dynamically created inline examples.
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* Additional Jupyter tutorials in ``/docs/tutorials``.

‎docs/sphinx/source/package_overview.rst

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pvlib-python provides several modeling paradigms.
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.. _modeling-paradigms:
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Modeling paradigms
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------------------
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