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Miscellaneous doc and module cleanup (#145)
* delete placeholder modules * update README * make order consistent * make descriptions consistent * remove hypothetical modules from index.rst too * other index.rst updates * typo * more placeholder removal * whatsnew * fix typo
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README.md

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@@ -10,22 +10,30 @@ systems. It provides functions for quality control, filtering, and
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feature labeling and other tools supporting the analysis of PV
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system-level data.
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Documentation is available at
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PVAnalytics is available at [PyPI](https://pypi.org/project/pvanalytics/)
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and can be installed using `pip`:
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pip install pvanalytics
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Documentation and example usage is available at
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[pvanalytics.readthedocs.io](https://pvanalytics.readthedocs.io).
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## Library Overview
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The functions provided by PVAnalytics are organized in modules based
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on their anticipated use. The structure/organization below is likely
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to change as use cases are identified and refined and as package
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content evolves. The functions in `quality`, `filtering`, and
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`features` will take a series of data and return a series of booleans.
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content evolves. The functions in `quality` and
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`features` take a series of data and return a series of booleans.
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For more detailed descriptions, see our
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[API Reference](https://pvanalytics.readthedocs.io/en/stable/api.html).
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* `quality` contains submodules for different kinds of data quality
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checks.
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* `data_shifts` contains quality checks for detecting and
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isolating data shifts in PV time series data.
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* `irradiance` provides quality checks for irradiance
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measurements. This will initially contain an implementation of the
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QCRad algorithm, but any other quality tests for irradiance data
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should be added here.
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measurements.
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* `weather` has quality checks for weather data (for example tests
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for physically plausible values of temperature, wind speed,
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humidity, etc.)
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* `time` quality checks related to time (e.g. timestamp spacing)
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* `util` general purpose quality functions.
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Other quality checks such as detecting timestamp errors will also be
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included in `quality`.
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* `filtering` as the name implies, contains functions for data
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filtering (e.g. day/night or solar position)
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* `features` contains submodules with different methods for
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identifying and labeling salient features.
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* `clipping` functions for labeling inverter clipping.
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* `clearsky` functions for identifying periods of clear sky
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conditions.
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* `daytime` functions for for identifying periods of day and night.
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* `orientation` functions for labeling data as corresponding to
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a rotating solar tracker or a fixed tilt structure.
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* `shading` functions for identifying shadows.
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* `system` identification of PV system characteristics from data
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(e.g. nameplate power, orientation, azimuth)
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* `translate` contains functions for translating data to other
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conditions (e.g. IV curve translators, temperature adjustment,
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irradiance adjustment)
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* `metrics` contains functions for computing PV system-level metrics
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* `fitting` contains submodules for different types of models that can
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be fit to data (e.g. temperature models)
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* `dataclasses` contains classes for normalizing data (e.g. an
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`IVCurve` class)

docs/index.rst

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PVAnalytics is a python library that supports analytics for PV
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systems. It provides functions for quality control, filtering, and
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feature labeling and other tools supporting the analysis of PV
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system-level data.
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system-level data. It can be used as a standalone analysis package
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and as a data cleaning "front end" for other PV analysis packages.
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PVAnalytics is free and open source under a
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`permissive license <https://github.com/pvlib/pvanalytics/blob/master/LICENSE>`_.
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The source code for PVAnalytics is hosted on `github
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<https://github.com/pvlib/pvanalytics>`_.
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- :py:mod:`quality.util` general purpose quality functions (e.g. simple
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range checks).
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- :py:mod:`filtering` as the name implies, contains functions for data
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filtering.
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- :py:mod:`features` contains submodules with different methods for
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identifying and labeling salient features.
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- :py:mod:`system` identification of PV system characteristics from data
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(e.g. nameplate power, tilt, azimuth)
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- :py:mod:`translate` contains functions for translating data to other
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conditions (e.g. IV curve translators, temperature adjustment,
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irradiance adjustment)
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- :py:mod:`metrics` contains functions for computing PV system-level metrics
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(e.g. performance ratio)
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- :py:mod:`fitting` contains submodules for different types of models that can
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be fit to data (e.g. temperature models)
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- :py:mod:`dataclasses` contains classes for normalizing data (e.g. an
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``IVCurve`` class)
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Dependencies
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------------
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and at minimum the two latest minor versions.
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- All minor versions of numpy released in the 24 months prior to the project,
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and at minimum the last three minor versions
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- The latest release of `PVLib <https://pvlib-python.readthedocs.io>`_.
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- The latest release of `pvlib <https://pvlib-python.readthedocs.io>`_.
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Additionally, PVAnalytics relies on several other packages in the open
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source scientific python ecosystem. For details on dependencies and versions,
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see our `setup.py <https://github.com/pvlib/pvanalytics/blob/master/setup.py>`_.
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Contents
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========

docs/whatsnew/0.1.2.rst

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0.1.2 (TBD)
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-------------------------
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* Removed empty modules ``pvanalytics.filtering`` and ``pvanalytics.fitting``
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until the relevant functionality is added to the package. (:pull:`145`)
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Enhancements
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~~~~~~~~~~~~
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* Detect data shifts in daily summed time series with
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~~~~~~~~~~~~
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* Kirsten Perry (:ghuser:`kperrynrel`)
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* Cliff Hansen (:ghuser:`cwhanse`)
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* Kevin Anderson (:ghuser:`kanderso-nrel`)

pvanalytics/__init__.py

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from pvanalytics import features # noqa: F401
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from pvanalytics import filtering # noqa: F401
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from pvanalytics import fitting # noqa: F401
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from pvanalytics import metrics # noqa: F401
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from pvanalytics import quality # noqa: F401
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from pvanalytics import system # noqa: F401

pvanalytics/filtering.py

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pvanalytics/fitting/__init__.py

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pvanalytics/fitting/temperature.py

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