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Implement acv #100
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I am working on this now. This may be another good candidate for using OpenMP. |
How should we go about testing the function? @wkearn While testing on the randomly generated DEM will work, it won't really prove the function is working as intended. To implement the test, I would have to copy-paste the function into the test, so of course the result would be that all is correct. (Much like Can we create property-based tests for this? With my limited knowledge about the actual use of this function, can't think of a way to test this apart from creating a correct solution and verifying that the function reproduces it. |
The property-based tests may not be the best way to test these sorts of functions. Good properties to test are more general than the implementation, such as testing that Two alternatives come to mind:
The easiest way to use the snapshot testing infrastructure at the moment would probably be to implement things in a branch of libtopotoolbox, point your pytopotoolbox CMakeLists.txt to that branch and then run the comparisons from Python (because things like data loading and comparison of DEMs are readily available in Python). Then at least you could gain some confidence that your implementation works, even if we don't have the same automated tests set up here. You would also have to get snapshots for |
Implement the anisotropic coefficient of variation from
GRIDobj.acv
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