In sparselybin switch q array to floats before applying divide and floor#21
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The same is done in binned histograms. If not, numpy throws TypeError on trivial integer array cases such as: >>> q = numpy.array([1,2,3,4]) >>> np.divide(q,1,q) >>> np.floor(q,q) which can easily happen if default binning is 1.
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One more request I'm afraid, I hope it's the last one.
Could you turn this into tag 1.0.8 as well? Many thanks!
In sparselybin I switched the q array to floats before applying divide and floor.
(In fact I see that the same is done for normally binned histograms.)
If not, for some reason numpy throws TypeError on trivial integer array cases such as:
which can easily happen if your default binwidth is 1.
In fact, unless specified this is my default binning.
So any sparse histograms filled with integers fail for me.