[SciPy-Dev] 2D histogram: request for plotting variable bin size
Sat Feb 2 14:52:04 CST 2013
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.
On 02.02.2013 20:59, Frank Breitling wrote:
> So I registered an account, but I have to request write permission by
> email to firstname.lastname@example.org first.
> So could somebody give me write permission to the page
> and maybe also to http://www.scipy.org/Cookbook/Matplotlib ?
> Or otherwise could somebody add the example below for me?
> import numpy as np, matplotlib.pyplot as plt
> x = np.random.normal(3, 2, 1000)
> y = np.random.normal(3, 1, 1000)
> H, yedges, xedges = np.histogram2d(y,x, bins=(yedges,xedges))
> extent = [xedges, xedges[-1], yedges[-1], yedges]
> #If bin size is equal imshow can be used. It is fast and provides
> #plt.imshow(H, extent=extent, interpolation='None',
> #To display variable bin size pcolar can be used
> X,Y = np.meshgrid(xedges, yedges)
> plt.pcolor(X, Y,
> #If interpolation is needed in addition matplotlib provides the
> On 2013-02-02 16:44, Sturla Molden wrote:
>> On 02.02.2013 10:53, Frank Breitling wrote:
>>> 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
>>> There even exists an example
>>> 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
>>> 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?
>> 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).
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