documenting dtype of hist counts #12800
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timhoffm
approved these changes
Nov 17, 2018
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I'd prefer that hist has the same behavior as numpy.histogram, i.e. returning int counts for non-normed values and float for normed values.
In [20]: data = np.exp(np.linspace(0, 3, 101))
In [21]: np.histogram(data, bins=4)
Out[21]:
(array([59, 20, 12, 10]),
array([ 1. , 5.77138423, 10.54276846, 15.31415269, 20.08553692]))
In [22]: np.histogram(data, bins=4, normed=True)
Out[22]:
(array([0.12242955, 0.04150154, 0.02490093, 0.02075077]),
array([ 1. , 5.77138423, 10.54276846, 15.31415269, 20.08553692]))
However, documenting the current behavior is an incremental improvement and therefore I approve.
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PR Summary
closes #12784
Updating the documentation for
histto clarify that the dtype of values of histogram i.e. counts being returned will always be float (even when no weighting or normalization is used).Reviewers --
(1) please let me know if the explanation for this behavior needs to be added in the documentation (since this is a "side-effect" of accommodating numpy.histogram's inconsistent behavior, I am not sure how much detail should go in the docstring).
(2) Please have a look at #12802 for an alternative solutionI am not sure which approach should be preferred.PR Checklist
[ ] Has Pytest style unit tests[ ] New features are documented, with examples if plot related[ ] Added an entry to doc/users/next_whats_new/ if major new feature (follow instructions in README.rst there)[ ] Documented in doc/api/api_changes.rst if API changed in a backward-incompatible way