On Wed, Aug 12, 2009 at 3:12 AM, Danny Handoko <danny.hand...@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 ? David > 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.hand...@asml.com > > > -- The information contained in this communication and any attachments is > confidential and may be privileged, and is for the sole use of the intended > recipient(s). Any unauthorized review, use, disclosure or distribution is > prohibited. Unless explicitly stated otherwise in the body of this > communication or the attachment thereto (if any), the information is > provided on an AS-IS basis without any express or implied warranties or > liabilities. To the extent you are relying on this information, you are > doing so at your own risk. If you are not the intended recipient, please > notify the sender immediately by replying to this message and destroy all > copies of this message and any attachments. ASML is neither liable for the > proper and complete transmission of the information contained in this > communication, nor for any delay in its receipt. > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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