nialov
commented
9 months ago Ready for review. The main function, distance_to_anomaly, works on all platforms while distance_to_anomaly_gdal only works on Linux and MacOS. Based on initial tests I thought the GDAL utility functions would work on all platforms but found out later they are inconsistent on Windows. The main problem on Windows is the lack of osgeo_utils module in the conda environment.
Anyway, thought it best to keep the GDAL method for later reference. I just marked the corresponding test as an xfail when run on Windows. It is orders of magnitude faster and at least somewhat more memory-efficient (filtering to anomalous values is still done in-memory).
If distance_computation, which the main function relies on, requires optimization later, you should check out the original branch by @tomironkko here: https://github.com/GispoCoding/eis_toolkit/compare/master...209-add-distance-to-anomaly. The "raster" distance math approach is more efficient but it can obviously only handle raster data while the current distance_computation handles vector data as well. You could rasterize first and then use raster math. Alternatively the missing osgeo_utils could be investigated.
em-t
nmaarnio
Performance issues are a problem which can be solved by using the alternative functionality that uses gdal_proximity function instead of existing distance_computation implementation. The GDAL implementation is orders of magnitude faster.
Draft for now until I clean up the implementation.
@tomironkko made an initial draft of this function which might have been better than the current
shapelydistance calculation that uses the existingdistance_computationone but more than likely much worse than thegdal_proximitymethod.