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Actually, ~10 times slower than np.histogram. It has its reasons but (being more general) but in the simple case, we should not add any overhead.
np.histogram
Suggestion: when parameters allow, fall back to np variant.
The text was updated successfully, but these errors were encountered:
Attempt towards fast numpy calculation
4bdd0c3
Addressing #35, but does not work properly yet => wrong errors2, wrong statistics, ...
Related: #48
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For regular binning, it is possible to use this:
contents = linspace(...) indexes = (data - low) / (high - low) # data is an array numpy.add.at(contents, indexes, 1)
As suggested by Jim Pivarski.
janpipek
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Actually, ~10 times slower than
np.histogram
. It has its reasons but (being more general) but in the simple case, we should not add any overhead.Suggestion: when parameters allow, fall back to np variant.
The text was updated successfully, but these errors were encountered: