Why windkit?
Wind resource assessment often involves wrangling large, complex datasets from various sources. This can mean writing a lot of boilerplate code to handle different file formats, coordinate systems, and data structures before you can even begin your analysis.
windkit is a Python library designed to streamline these workflows. It provides a high-level, user-friendly interface for common wind analysis tasks, letting you focus on the science, not the software engineering.
What can you do with windkit?
Data-structures: Easily load and work with diverse WRA data types, including wind climate data, GIS and terrain maps, and wind turbine specifications. windkit handles the complexities of different file formats and coordinate systems internally.
Wind Analysis: Perform common calculations like Weibull fitting, wind speed extrapolation, and sector management with simple commands.
Spatial Operations: Utilize tools for regridding, masking, and clipping spatial data.
Built for the Scientific Python Ecosystem
windkit is built on top of the powerful xarray library and integrates smoothly with the scientific Python ecosystem, including pandas and dask. This provides a robust, high-performance foundation for your work.
By handling complexities like spatial projections and data unit conversions internally, windkit helps prevent common errors and promotes correctness. When you need more control or want to perform custom analysis, you can easily drop down to the underlying xarray objects.
In short, windkit provides the building blocks for robust and reproducible wind analysis workflows. Whether you are a seasoned professional, a researcher, or a student, windkit can help you get to your results faster and with more confidence.