"Re-implementation of selected PolSARpro functions in Python, following the scientific recommendations of PolInSAR 2021 (Work In Progress)."
- Clone the repository and choose one of the install options below.
- Install conda (recommended: miniforge)
- Create and activate the environment
conda env create -f environment.yaml
conda activate psp - Add the toolbox path to
PYTHONPATH
export PYTHONPATH="${PYTHONPATH}:/mypath/to/polsarpo/source"- To check that the module is working,
pytestcan be run from the main directory. All tests should pass.
- This method is recommended for development or advanced users who are familiar with docker.
- Moreover jupyter notebooks are also supported directly in VSCode.
- For development purposes, the docker container installs the C version of PolSARpro. This makes it possible to run the different decompositions from the command line, e.g.
freeman_decomposition.exeto process some data and compare its outputs with the ones of the python version. - To build the container, it is required to download the zip file of the original PolSARpro in the main directory. This file can be found at https://ietr-lab.univ-rennes1.fr/polsarpro-bio/Linux/PolSARpro_v6.0.4_Biomass_Edition_Linux_Installer_20250122.zip
- This assumes
dockeranddocker composeare installed on your system. - Edit
docker-compose.ymlto set volume paths that suit your needs. - Open the directory in VSCode
- Then Ctrl-Shift-P (Cmd-Shift-P on Mac) and look for
Rebuild and reopen in container. This will build the dev container and the development environment may be used.
- This assumes
dockeranddocker composeare installed on your system. - Edit
docker-compose.ymlto set volume paths that suit your needs. - From the main directory type
docker compose up -d - To stop the container
docker compose down
Read this tutorial or use the tutorial notebook in the notebooks/folder.