PCRaster 4.4.0

This page refers to an outdated version of PCRaster, an up-to-date version is available.

What's new

PCRaster now supports the ARM architecture, packages for Apple M1 (#341) are available on conda-forge.

Other updates relevant for users:

  • You can compile PCRaster on your HPC with EasyBuild. Use or adapt our easyconfig files.

  • The sources can be compiled on aarch64 Linux systems as well.

  • Aguila was again refactored to reduce runtime library dependencies, notably the command line interface. The functionality should remain the same. In case you experience any differences to previous Aguila versions consider it as a defect and please report it at our issues page.

  • We fixed an issue where Aguila could hang on Windows (#333).

  • We fixed an incorrect image plotting of LDD raster (#362).

  • We fixed another segmentation fault at script exit when using modules from PCRaster, GDAL and QGIS (#361).

We further improved the code quality and the build system to ensure an ongoing creation of PCRaster packages, amongst others:

  • Building against the latest Python 3 version. Supported are 3.8 - 3.11

  • Replacing Boost.Filesystem by std::filesystem

  • Boost is no longer a runtime dependency

  • Further modernisation of the source code and build system.

  • Various improvements to support gcc-12, clang-14, Visual Studio 2019 and 2022.

For a list of solved issues see our 4.4 milestone.

Installation

Straightforward with conda, see our tutorial.

Documentation

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.

Package overview

The PCRaster package includes:

  • The PCRaster library offering about 250 optimized functions for the construction of spatio-temporal models

  • The pcraster module to build environmental models in the Python programming language (Python 3.8+)

  • 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-4.4.0.tar.bz2

SHA256: 55e7eff211a6777c0703157b03f33dc09a0bd0f509046ca4c508df0aadf76a0e

Contribute!

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.

Questions?

Please post questions regarding installation, applications or operations of the PCRaster package on our mailing list.