As @dcdenu4 mentioned, the
WinError is an interesting issue and maybe even an underlying bug in the python language’s standard library. In any case, there’s a good chance that it was just a fluke and running the model once again will avoid the
WinError. We’re looking into a longer-term fix in the meantime.
Based on your logfile, this looks like an extremely fine-scale resolution! The main thing that will affect the HQ model’s runtime is the convolutions, one per threat, where the kernel is based on the
max_dist parameter in your threats table. For the
ag_per threat, for example, the model needs to visit 3.27 million pixels (based on your
max_dist) for every pixel in the threat raster. This number of pixels will impact the disk space used and, of course, computational time, and if you don’t really need the extra resolution, increasing your cell size will dramatically reduce the model’s runtime.
Running on a high-powered computer with solid-state hard disk(s) can help, of course, but you’ll only get linear speedups (as a function of processor speed and disk I/O) when increasing the cell size will have a much more pronounced effect on the algorithmic runtime.