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On 2014/03/02 1:02 AM, ChaoYue wrote:
> 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?

I don't understand what feature you are referring to; evidently I don't 
understand what the problem is, so I don't know what part remains unsolved.

Eric


>
> Cheers,
>
> Chao
>
>
> On Sat, Mar 1, 2014 at 10:39 PM, Eric Firing [via matplotlib] <[hidden
> email] </user/SendEmail.jtp?type=node&node=42956&i=0>> 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
>
>     ------------------------------------------------------------------------------

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-...@n5...> 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
>
> ------------------------------------------------------------------------------
>
> Flow-based real-time traffic analytics software. Cisco certified tool.
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-- 
***********************************************************************************
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16
************************************************************************************




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Hi,

I am trying to insert a .png image to the right side of the plot and
following the code mentioned here:Combine picture and plot with Python
Matplotlib<http://stackoverflow.com/questions/3765056/combine-picture-and-plot-with-python-matplotlib>
Here is what I have tried:

import numpy as npfrom matplotlib.colors import
LinearSegmentedColormapimport matplotlib.pyplot as pltimport
matplotlib as mplimport matplotlib.cbook as cbookfrom matplotlib._png
import read_pngfrom matplotlib.offsetbox import OffsetImage
cmap = mpl.cm.hot
norm = mpl.colors.Normalize(vmin=-1 * outlier, vmax=outlier)
cmap.set_over('green')
cmap.set_under('green')
cmap.set_bad('green')
plt.xlim(0,35)
plt.ylim(0,35)
fig, ax = plt.subplots()
ax.set_aspect('equal')
cb_ax=fig.add_axes([0.85, 0.1, 0.03, 0.8])
img = ax.imshow(np.ma.masked_values(data, outlier), cmap=cmap,
norm=norm, interpolation='none',vmax=outlier)
cb = mpl.colorbar.ColorbarBase(cb_ax, cmap=cmap, norm=norm,
extend='both')##axim = plt.subplot2grid(shape, loc, rowspan=1)
## phlo tree
image_file = cbook.get_sample_data('mytree.png',asfileobj=False)
image = plt.imread(image_file)
phyl_ax=fig.add_axes([0.10,0.1, 0.03, 0.8])
phyl_ax.imshow(image,interpolation='nearest')

Th heat map would be on the left side and the image of a tree will be
inserted on the right side. The above code gives me the required heat
map but the image I am trying to add on the right side isn't
appearing. Can someone lead me as to how I can go about this?

Thanks