This library provides a framework for assessing wind plant performance using operational assessment (OA) methodologies that consume time series data from wind plants. The goal of the project is to provide an open source implementation of common data structures, analysis methods, and utility functions relevant to wind plant OA.
This PR refactors each module in openoa/utils/power_curve/ for the following:
Public facing methods use the new dataframe/series API
Minor speed improvements under the hood
Better documentation and type hinting throughout
Additionally:
A bug in examples/project_ENGIE.py is fixed in how a boolean series is used for indexing because of odd behavior with 1-column dataframes having a 1-column series boolean filter
The dataframe/series converters also now have a flag that passes through the column name arguments in case Series that need to be concatenated don't have column names, so they get renamed to the argument's name
This PR refactors each module in
openoa/utils/power_curve/for the following:Additionally:
examples/project_ENGIE.pyis fixed in how a boolean series is used for indexing because of odd behavior with 1-column dataframes having a 1-column series boolean filter