Great blog, Victor! Thank you! Well actually, a colleague came up with a very simple python script (see attachted splitgrid.py <http://osgeo-org.1560.n6.nabble.com/file/n5018501/splitgrid.py> ). This is no spatial randomisation like eg the v.kcv function in GRASS GIS, but for large enough datasets, it delivers wonderfully fast and with a good spatial spread. Feel free to add it to your blog if you see any added value.
Thanks Andreas, for pointing me to the LAStools! I did not know about them yet and yes, even if we are not doing LiDAR, these tools are superb in crunching big amounts of numbers. I contacted Martin Isenburg concerning a license for using las2dem or blast2dem. His response left me a bit shell shocked. I don't know the guy well enough I guess. But still, everyone has bills to pay. We would have the funds to reward him handsomely for his efforts in the project we would like to use this application in. But I'm sorry, I really cannot endorse the way he is going commercial now. Thanks paulo25, for pointing my to the v.kcv function in GRASS GIS. I tried is through the SEXTANTE toolbox, but with 3 million points, I guess this algorithm gets clotted. I tried it on a machine with plenty of RAM and CPU. The process just dies after some time. But for larger data sets a spatial randomisation is not so important as for smaller ones... Thanks again to you three! Regards, Olav -- View this message in context: http://osgeo-org.1560.n6.nabble.com/split-point-cloud-into-X-randomly-selected-equally-sized-parts-tp5017330p5018501.html Sent from the Quantum GIS - User mailing list archive at Nabble.com. _______________________________________________ Qgis-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/qgis-user
