[SciPy-Dev] 2D histogram: request for plotting variable bin size

Frank Breitling fbreitling@aip...
Tue Mar 26 05:15:02 CDT 2013


Hi,

And how can I add or update images of the numpy doc (e.g. at 
http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html)?
Meanwhile I have created an example for histograms with variable bin 
size at
http://www.scipy.org/Cookbook/Histograms
and would like to add this to the numpy doc, too. Therefore I need to 
replace the image.

Frank


On 02.02.2013 21:52, Sturla Molden wrote:
> That is not how it works.
>
> If you have a suggestion for changing the NumPy (including docs) you
> fork NumPy on GitHub.com and post a pull-request with your changes. And
> that would be after asking on the NumPy list (not on scipy-dev!).
> They might also want you to open an issue on their GitHub tracker.
>
> All users on scipy.org should be able to update the cookbook. At least
> that it how it worked before. If you want to create a new page on the
> wiki you just navigate to it with your browser.
>
> Sturla
>
>
> On 02.02.2013 20:59, Frank Breitling wrote:
>> Hi,
>>
>> So I registered an account, but I have to request write permission by
>> email to scipy-dev@scipy.org first.
>> So could somebody give me write permission to the page
>> http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html
>> and maybe also to http://www.scipy.org/Cookbook/Matplotlib ?
>>
>> Or otherwise could somebody add the example below for me?
>>
>> Frank
>>
>> ---
>> import numpy as np, matplotlib.pyplot as plt
>>
>> x = np.random.normal(3, 2, 1000)
>> y = np.random.normal(3, 1, 1000)
>>
>> yedges=xedges=[0,2,3,4,6]
>>
>> H, yedges, xedges = np.histogram2d(y,x, bins=(yedges,xedges))
>> extent = [xedges[0], xedges[-1], yedges[-1], yedges[0]]
>>
>> #If bin size is equal imshow can be used. It is fast and provides
>> interpolation.
>> #plt.imshow(H, extent=extent, interpolation='None',
>> aspect='auto')
>>
>> #To display variable bin size pcolar can be used
>> X,Y = np.meshgrid(xedges, yedges)
>> plt.pcolor(X, Y,
>> H)
>>
>> #If interpolation is needed in addition matplotlib provides the
>> NonUniformImage:
>> #http://matplotlib.org/examples/pylab_examples/image_nonuniform.html
>>
>> plt.colorbar()
>> plt.show()
>>
>>
>>
>> On 2013-02-02 16:44, Sturla Molden wrote:
>>> On 02.02.2013 10:53, Frank Breitling wrote:
>>>> Hi,
>>>>
>>>>     From the matplotlib developers it was pointed out, that there is a
>>>> NonUniformImage which might be suite for representing interpolated
>>>> variable bin size 2D histograms
>>>> (https://github.com/matplotlib/matplotlib/issues/1729#issuecomment-13014723).
>>>> There even exists an example
>>>> (http://matplotlib.org/examples/pylab_examples/image_nonuniform.html)
>>>> but it is very isolated and therefore not well known.
>>>> It would be very useful to explain its usage or at least link to it in
>>>> the histogram2d example at
>>>> http://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram2d.html.
>>>>
>>>> In addition a pcolor example (attached below) shouldn't be missing. Even
>>>> though it is slow and can't do interpolation, it can at least do a
>>>> correct representation for academic purposes.
>>>>
>>>> Can anybody do that or would you like me to do that myself?
>>>>
>>>> Frank
>>> Since it is at the top of your head, why don't you do it?
>>>
>>> But it might be better for the SciPy Cookbook's matplotlib section
>>> than the NumPy docs. I'm not sure if they want matplotlib examples in
>>> the NumPy documentation (ask on the NumPy list before you waste your
>>> time on it).
>>>
>>>
>>> http://www.scipy.org/Cookbook/Matplotlib
>>>
>>>
>>>
>>> Sturla
>>>
>>>
>>> _______________________________________________
>>> SciPy-Dev mailing list
>>> SciPy-Dev@scipy.org
>>> http://mail.scipy.org/mailman/listinfo/scipy-dev
>>>
>> _______________________________________________
>> SciPy-Dev mailing list
>> SciPy-Dev@scipy.org
>> http://mail.scipy.org/mailman/listinfo/scipy-dev
>>
> _______________________________________________
> SciPy-Dev mailing list
> SciPy-Dev@scipy.org
> http://mail.scipy.org/mailman/listinfo/scipy-dev
>



More information about the SciPy-Dev mailing list