[Numpy-discussion] Faulty behavior of numpy.histogram?

David Huard david.huard@gmail....
Wed Aug 12 09:12:59 CDT 2009

On Wed, Aug 12, 2009 at 3:12 AM, Danny Handoko <danny.handoko@asml.com>wrote:

>  Dear all,
> We try to use numpy.histogram with combination of matplotlib.  We are using
> numpy 1.3.0, but a somewhat older matplotlib version of 0.91.2.
> Matplotlib's  axes.hist() function calls the numpy.histogram, passing
> through the 'normed' parameter.  However, this version of matplotlib uses
> '0' as the default value of 'normed' (I see it fixed in higher version).
> What I found strange is that if the 'normed' parameter of numpy.histogram is
> set with other object than 'True' or 'False', the output becomes None, but
> no exceptions are raised.  As a result, the matplotlib code that does
> something like this:
> >>> n, bins = numpy.histogram([1,2,3], 10, range = None, normed = 0)
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
> TypeError: 'NoneType' object is not iterable
> results in the above exception.

This is now fixed. Thanks.

> Secondly, this matplotlib version also expects both outputs to be of the
> same length, which is no longer true with the new histogram semantics.  This
> can be easily reverted using the parameter 'new = False' in numpy.histogram,
> but this parameter is not available for the caller of axes.hist() function
> in matplotlib.  Is there any way to tell numpy to use the old semantics?

Could you go in the numpy source code and change the default value for new ?


> Upgrading to the newer matplotlib is a rather longer term solution, and we
> hope to be able to find some workaround/short-term solution
> Thank you,
> --
> Danny Handoko
> System Architecture and Generics
> Room 7G2.003 -- ph: x2968
> email: danny.handoko@asml.com
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