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warnings.warn("node spacing should be identical {}".format((dx,dy)), RuntimeWarning)
Would be nice to use np.allclose(dx, dy) instead of hardcoding a minumum difference that could raise some unwanted results. For example, if you have a very dense survey with one measurement every 10m and dx is around 1m different from dy, you'll finally get a significant error on the wavenumbers and therefore on the estimated depths even that error won't be reflected on the statistical errors for these depths.
Do you agree?
Besides, wouldn't be better to raise an error instead of a warning? Using non equal spaced grids is acceptable for further computations?
The text was updated successfully, but these errors were encountered:
Yes this makes sense. I haven't encountered such an issue, but that's not to say it won't happen to someone else. This has been addressed in 585fd43 thanks!
Part of openjournals/joss-reviews#1544.
When checking if the node spacing is equal on both northing and easting directions, a maximum difference of 1 meter has been hardcoded:
pycurious/pycurious/grid.py
Lines 74 to 75 in 759fc52
Would be nice to use
np.allclose(dx, dy)
instead of hardcoding a minumum difference that could raise some unwanted results. For example, if you have a very dense survey with one measurement every 10m anddx
is around 1m different fromdy
, you'll finally get a significant error on the wavenumbers and therefore on the estimated depths even that error won't be reflected on the statistical errors for these depths.Do you agree?
Besides, wouldn't be better to raise an error instead of a warning? Using non equal spaced grids is acceptable for further computations?
The text was updated successfully, but these errors were encountered: