We are glad to announce the final release of PCRaster-4.0.1! We fixed several bugs, some of them might affect model outcomes. Please read the changes document carefully. In addition, this is the first release fully supporting 64-bit Windows systems.
For more information, visit the PCRaster 4.0.1 download page:
We have updated our course material. Have a look at the Courses section for two new distance learning courses on PCRaster Python; without tutor support the courses are free of charge.
Users interested in a convenient development and analysis environment for PCRaster Python models could consider the Enthought Python distribution. On this page we show how you can use the PCRaster 4.0 release with Enthought Canopy.
We are happy to announce the final release of PCRaster-4.0.0! For more information, visit the PCRaster 4.0.0 download page.
It is possible that your PCRaster models are not executing as fast as the could on your Linux system. That can happen because the default memory allocation and de-allocation rules that are in effect on Linux are optimized for system wide efficiency, instead of raw performance. For more information about this, see this document.
You can tune the memory allocation and de-allocation logic using environment variables (note the trailing underscore):
You may want to check if these values help you to squeeze a bit of extra performance out of your models.
I have released a second test version of the upcoming PCRaster-4.0.0 release. See the PCRaster 4.0.0 download page for more information. This version has a much faster numpy2pcr operation and we fixed a bug in the resample command. Unless an important issue is found with this release, the next release will be the final 4.0.0 release.
I have released a test version of the upcoming PCRaster-4.0.0 release. See the PCRaster 4.0.0 download page for more information.
As of now, all PCRaster sources are distributed under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. All source code is stored on SourceForge.
The PCRaster team has a vacancy for a PhD student Meta Modelling of Sustainable City Systems. Apply here before 30-04-2013.
I uploaded installers for BlockAnalyst to the Sourceforge download page. Check the BlockAnalyst project page for a link.