Dear Eric,
This solved part of my problem. thanks a lot.
I think I will revisit this issue when I have time (not promised).
do you think this could be some feature desirable?
Cheers,
Chao
On Sat, Mar 1, 2014 at 10:39 PM, Eric Firing [via matplotlib] <
ml-node+s1069221n42952...@n5.nabble.com> wrote:
> On 2014/03/01 11:03 AM, ChaoYue wrote:
> > The most correct way might be to design a new colormap with white color
> > exactly in the middle, however this is very tedious, especially if I
> > want to try
> > different colormaps. so the alternative approach would be to set the
> values
> > falling in (-1,1) as being masked, so they will be the same as the axes
> > background color as you mentioned (in our case it's white). My question
> is,
> > how can I put this background color (which shows maksed data) in the
> > colorbar,
> > by avoiding design a new colormap?
>
> It's not the answer you want to hear, but I think the correct answer is
> that you should do this via the colormap, and not by masking the low
> values. It doesn't have to be painful. If, in contourf, you use a
> diverging colormap with white already in the middle
> (http://matplotlib.org/examples/color/colormaps_reference.html) and a
> norm with symmetric limits (vmin and vmax; you can let them be set
> automatically after you specify your symmetric set of contour boundaries
> appropriately) then it will be done for you.
>
> e.g.,
>
> z = 10 * np.random.randn(20, 30)
> clevs = [-10, -5, -2, -1, 1, 2, 5, 10]
> cs = plt.contourf(z, levels=clevs, cmap=plt.get_cmap('PRGn'),
> extend='both')
> cbar = plt.colorbar(cs, spacing='uniform')
>
> Eric
>
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