PCRaster 4.3.0 is the currently maintained version.
These are the most important changes:
- PCRaster is available on conda-forge and can be installed using conda. Supported platforms are Linux, macOS and Windows. Supported Python versions are 3.6, 3.7 and 3.8.
- We no longer provide support for Python 2.
- We fixed a bug occurring when pickling PCRaster maps. Note that PCRaster maps pickled with previous versions cannot be opened with this version.
- We fixed an incorrect return value while using a nonspatial condition in
- We fixed several minor inconsistencies in the
- We added the Python functions
- We added a
plotfunction to create basic plots of PCRaster maps in case the matplotlib module is installed.
- On Windows,
legendshow the menu again.
- We fixed the incorrect rendering of directional rasters in Aguila.
- PCRaster Modflow now supports the GHB package.
- PCRaster Modflow BCF package received an optional flag to directly pass hcond and vcond values to Modflow.
- Command line applications now show version numbers instead of a build date.
- The exit value of applications only showing the usage information changed from 1 (EXIT_FAILURE) to 0 (EXIT_SUCCESS).
For a brief list of the changes check the changes page.
Straightforward with conda, see our tutorial.
The PCRaster package includes:
- The PCRaster library offering about 250 optimized functions for the construction of spatio-temporal models
pcrastermodule to build environmental models in the Python programming language (Python 2.7, Python 3.6)
- Local and focal operations supporting multicore CPUs
- A Python modelling framework allowing for dynamic modelling, stochastic modelling and data assimilation
- The Aguila program for visualization of uncertain spatio-temporal data
- The PCRaster Modflow extension for groundwater modelling
- The PCRcalc environmental modelling language
- Several programs for data conversion
Source code package
PCRaster source code package: pcraster-4.2.1.tar.bz2
Information about the PCRaster Python module including the function reference, the spatio-temporal modelling framework, command line applications and and an introduction to PCRaster can be found in our online documentation.
PCRaster is an open-source project, and there are a few options how you can contribute! If you are familiar with coding, help us eliminating known bugs. Whether you are experienced with packaging software for Linux distributions, or you just want to provide fixes to the documentation: we are looking forward to your pull requests on our GitHub page.
Please post questions regarding installation, applications or operations of the PCRaster package on our mailing list.