[Numpy-discussion] np.histogramdd of empty data

Nils Becker n.becker@amolf...
Thu Mar 31 05:33:17 CDT 2011


Hi Ralf,

I cloned numpy/master and played around a little.

when giving the bins explicitely, now histogram2d and histogramdd work
as expected in all tests i tried.


However, some of the cases with missing bin specification appear
somewhat inconsistent.

The first question is if creating arbitrary bins for empty data and
empty bin specification is better than raising an Exception:

Specifically:

numpy.histogram2d([],[],bins=[0,0])
> (array([ 0.,  0.]), array([ 0.]), array([ 0.]))

numpy.histogram([],bins=0)
> ValueError: zero-size array to minimum.reduce without identity

so 1-d and 2-d behave not quite the same.

also, these work (although with arbitrary bin edges):

numpy.histogram2d([],[],bins=[1,1])
> (array([ 0.,  0.]), array([ 0.,  1.]), array([ 0.,  1.]))

numpy.histogram2d([],[],bins=[0,1])
> (array([ 0.,  0.]), array([ 0.]), array([ 0.,  1.]))

while this raises an error:

numpy.histogram([],bins=1)
> ValueError: zero-size array to minimum.reduce without identity

another thing with non-empty data:

numpy.histogram([1],bins=1)
> (array([1]), array([ 0.5,  1.5]))

numpy.histogram([1],bins=0)
> (array([], dtype=int64), array([ 0.5]))

while

numpy.histogram2d([1],[1],bins=A)
> ValueError: zero-size array to minimum.reduce without identity

(here A==[0,0] or A==[0,1] but not A==[1,1] which gives a result)

Nils


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