.. PVAnalytics documentation master file, created by
   sphinx-quickstart on Tue Feb 18 11:16:33 2020.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

PVAnalytics
===========

PVAnalytics is a python library that supports analytics for PV
systems. It provides functions for quality control, filtering, and
feature labeling and other tools supporting the analysis of PV
system-level data. It can be used as a standalone analysis package
and as a data cleaning "front end" for other PV analysis packages.

PVAnalytics is free and open source under a
`permissive license <https://github.com/pvlib/pvanalytics/blob/main/LICENSE>`_.
The source code for PVAnalytics is hosted on `github
<https://github.com/pvlib/pvanalytics>`_.

Library Overview
----------------

The functions provided by PVAnalytics are organized in submodules based
on their anticipated use. The list below provides a general overview; however,
not all modules have functions at this time, see the API reference for current
library status.

- :py:mod:`quality` contains submodules for different kinds of data quality
  checks.

  - :py:mod:`quality.data_shifts` contains quality checks for detecting and 
    isolating data shifts in PV time series data.
  - :py:mod:`quality.irradiance` contains quality checks for irradiance
    measurements.
  - :py:mod:`quality.weather` contains quality checks for weather data (e.g.
    tests for physically plausible values of temperature, wind speed,
    humidity).
  - :py:mod:`quality.outliers` contains functions for identifying outliers.
  - :py:mod:`quality.gaps` contains functions for identifying gaps in the data
    (i.e. missing values, stuck values, and interpolation).
  - :py:mod:`quality.time` quality checks related to time (e.g. timestamp
    spacing, time shifts).
  - :py:mod:`quality.util` general purpose quality functions (e.g. simple
    range checks).

- :py:mod:`features` contains submodules with different methods for
  identifying and labeling salient features.

  - :py:mod:`features.clipping` functions for labeling inverter clipping.
  - :py:mod:`features.clearsky` functions for identifying periods of clear sky
    conditions.
  - :py:mod:`features.daytime` functions for identifying periods of day and night.
  - :py:mod:`features.orientation` functions for identifying
    orientation-related features in the data (e.g. days where the data looks
    like there is a functioning tracker). These functions are distinct from the
    functions in the :py:mod:`system` module in that we are identifying
    features of data rather than properties of the system that produced the
    data.
  - :py:mod:`features.shading` functions for identifying shadows.

- :py:mod:`system` identification of PV system characteristics from data
  (e.g. nameplate power, tilt, azimuth)
- :py:mod:`metrics` contains functions for computing PV system-level metrics
  (e.g. performance ratio)

Dependencies
------------

This project follows the guidelines laid out in
`NEP-29 <https://numpy.org/neps/nep-0029-deprecation_policy.html>`_.
It supports:

- All minor versions of Python released 42 months prior to the project,
  and at minimum the two latest minor versions.
- All minor versions of numpy released in the 24 months prior to the project,
  and at minimum the last three minor versions
- The latest release of `pvlib <https://pvlib-python.readthedocs.io>`_.

Additionally, PVAnalytics relies on several other packages in the open
source scientific python ecosystem.  For details on dependencies and versions,
see our `setup.py <https://github.com/pvlib/pvanalytics/blob/main/setup.py>`_.


.. toctree::
   :hidden:
   :caption: Contents:

   api
   generated/gallery/index
   whatsnew/index