pyTCR-1.2.3

This release is a minor update from v1.2.2

Improvements:

• Add more physical constants and model parameters
• Remove unused files
• Combine two functions loading GCM data into a single one for consistency
• Fix bugs and scale factors for unit conversion
• Update documentation and API References

pyTCR-1.2.2

This release is a minor update from v1.2.1 that fixes a bug in the I/O functions.

Improvements:

• Restored the original name of the get_bbox_from_shapefile function in iodata, which was unintentionally renamed in the previous version.

pyTCR-1.2.1

This release is a minor update from v1.2 and introduces several improvements, including enhanced testing, packaging, and documentation.

Improvements:

• Added pytest for unit testing.
• Implemented CI workflow to automate testing.
• Included packaging options for both pip and conda distributions.
• Integrated documentation with ReadTheDocs and Jupyter Book.
• Updated tutorials to reflect the latest changes.

pyTCR-1.2

• add functions to load colormaps from cpt files
• switch installation to mamba for speed and efficiency
• add buffer option to track_landfall
• integrate binder for interactive environment
• refine plotting for shapefiles and multiple rain events
• enhance plotting with polygon example and exceedance probability
• expand polygon options
• integrate pyproj and libtiff
• add windswathx function and update code format

pyTCR-1.1

What's Changed

• convert data and i/O functions to netcdf with xarray.
• include loading shapefile option for polygons
• add the windswathx function to wind.py
• update mapping plot functions
• refactor codebase for clarity and performance

Full Changelog: pyTCR-1.0...pyTCR-1.1

pyTCR 1.0

This is the first official release of the pyTCR, a python-based Tropical Cyclone Rainfall model. It includes all core functionalities for calculating and visualizing tropical cyclone-driven rainfall.

• Initial implementation of the pyTCR model.
• Included core functions for estimating tropical cyclone rainfall
• Provided visualization tools to plot tracks and rainfall distribution.
• Included example Jupyter notebooks for users to get started.