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# 2026.1.1
## New feature
- Tutorial notebook to process BIOMASS data on the MAAP platform
## Bugfix and improvements
- Added some missing S matrix channels in `polmat_to_netcdf`
- Updated the unit test accordingly
- Improved the unit test by using simulated data
- Simulated data fixture now returns chunked datasets
- Added a link to the sample dataset in the docs
# 2026.1.0
## New features
- Cameron decomposition
- Pauli RGB visualization for S, C3 and T3 matrices (`util.pauli_rgb`)
- Multilooking operator (`util.multilook`) for all C and T matrices
- Updated docs
## Other improvements
- Moved the legacy PSP bin reading functions to the `dev` module
- Created `conftest.py` to share fake data generation across all unit tests
# 2025.12.2
## Features
- Freeman-Durden decomposition
- Yamaguchi 4 & 3 component decompositions
- Touzi's TSVM decomposition
- Van Zyl (1992) 3 component decomposition
- Refined Lee speckle filter
- PWF (Polarimetric Whitening Filter)
- New function: `polmat_to_netcdf` to write polarimetric matrices to NetCDF files (complex values are not natively handled in NetCDF ). Files written with this function can be read with `open_netcdf_beam`
- PolSARPro is now available as a package on the conda-forge channel
- Updated San Francisco ALOS-1 datasets with the latest JAXA version. Data will be distributed on STEP.
## Improvements
- Function for automatic data generation to test more polarimetric types for each algorithm (unit tests)
- Add test notebooks for all decompositions for geocoded data
- Protecting decompositions against division by zero warnings when using geocoded data
# 2025.12.1
## Bugfixes
- Updated `pyptoject.toml` for conda-forge packaging.
# 2025.12.0
## Bugfixes
- Updated dependencies to match conda recipe.
# 2025.10.0
## Features
- Definition of and Xarray dataset based structure including: named matrix elements, coordinates (geocoded or SAR geometry), polarimetric type (e.g. S, T3, C4)
- Reader for NetCDF-BEAM files exported from SNAP
- Documentation using mkdocs and hosted on ReadTheDocs https://polsarpro.readthedocs.io
- Installation guide
- Tutorials
- API reference
- Theoretical background
- Adapted H/A/Alpha decomposition for the new data structure
- Visualization of data points in the H/Alpha plane
- Conversion utilities between different polarimetric representations (e.g. S, T3, C4)
- Boxcar filter using 2-D convolutions
- Tutorial notebooks for basic usage and H/A/Alpha
- Updated installation instructions
## Misc
- Unit tests for decompositions, utilities and readers
- Data validation function ensuring correct structure of input datasets
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