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

[Frank Breitling]

Hi,

So I registered an account, but I have to request write permission by
email to scipy-dev at 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
>
>
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