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RdTools is an open-source library to support reproducible technical analysis of
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time series data from photovoltaic energy systems. The library aims to provide
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best practice analysis routines along with the building blocks for users to
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- tailor their own analyses.
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- Current applications include the evaluation of PV production over several years to obtain
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- rates of performance degradation and soiling loss. RdTools can handle
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- both high frequency (hourly or better) or low frequency (daily, weekly,
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- etc.) datasets. Best results are obtained with higher frequency data.
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+ tailor their own analyses. Current applications include the evaluation of PV
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+ production over several years to obtain rates of performance degradation and
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+ soiling loss. RdTools can handle both high frequency (hourly or better) or low
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+ frequency (daily, weekly, etc.) datasets. Best results are obtained with higher
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+ frequency data.
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RdTools can be installed automatically into Python from PyPI using the
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command line:
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For API documentation and full examples, please see the [ documentation] ( https://rdtools.readthedocs.io ) .
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- RdTools currently is tested on Python 3.7 +.
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+ RdTools currently is tested on Python 3.9 +.
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## Citing RdTools
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@@ -36,8 +36,8 @@ and the specific DOI coresponding to that version from [Zenodo](https://doi.org/
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- Michael G. Deceglie, Ambarish Nag, Adam Shinn, Gregory Kimball,
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Daniel Ruth, Dirk Jordan, Jiyang Yan, Kevin Anderson, Kirsten Perry,
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- Mark Mikofski, Matthew Muller, Will Vining, and Chris Deline
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- RdTools, version {insert version}, Compuer Software,
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+ Mark Mikofski, Matthew Muller, Will Vining, and Chris Deline,
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+ RdTools, version {insert version}, Computer Software,
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https://github.com/NREL/rdtools . DOI:{insert DOI}
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The underlying workflow of RdTools has been published in several places.
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