John,
It sounds like you are not using the latest *released* version of mpl,
which is 0.87.3; the only thing in my example that requires svn is the
colorbar command. If you did install 0.87.3, then you must have an
earlier installation still in place and being found.
imshow requires a uniform rectangular grid. pcolor is much more general
and colors rectangles specified by their boundaries, not their centers.
pcolormesh is similar (though not identical) but faster.
As you described it, your application seems most natural for imshow,
except for the problem with masked areas not being transparent. I
suggested pcolor only as a workaround for that, if you really need that
transparency.
Eric
John Pye wrote:
> Hi Eric,
>
> Thanks for your suggestion. The colorbar(shrink) command throws me an
> error, as you said it would. But I get another error with the '0.3',
> '0.5', etc. I had to replace those with (0.3,0.3,0.3) etc -- RGB tuples.
>
> Finally, my plot only shows white, grey red. I don't get any other
> colors -- do you? Is that because of the colorbar(shrink) thing, or is
> something else not working? Do I *need* your SVN changes?
>
> Also, when should I be using pcolor versus imshow? If my image is
> constructed of colors at specified sample points, is it better that I
> use pcolor? The pcolor command isn't mentioned at all in the matplotlib
> user's guide...
>
> Cheers
> JP
>
> Eric Firing wrote:
>
>
>>John,
>>
>>Something like this might be what you want:
>>
>>from pylab import *
>>import matplotlib.numerix.ma as ma
>>import matplotlib.colors as colors
>>xx = rand(10,15)
>>xxx = (xx*15 - 5).astype(Int)
>>xxx = ma.masked_where(xxx < 0, xxx)
>>xxx.set_fill_value(-1) #(not necessary)
>>cmap = colors.ListedColormap(('r', 'g', 'b',
>> 'c', 'y', 'm',
>> 'k', '0.3', '0.5',
>> '0.7'))
>>#cmap.set_bad((1,1,1,0)) # setting alpha to zero does not work, at least
>> # for imshow
>>im = imshow(xxx, interpolation='nearest',
>> cmap=cmap, norm=colors.no_norm())
>>cb = colorbar(shrink=0.6)
>>
>>
>>What we are doing here is making a custom colormap from a list of
>>colors (using any valid mpl color specification), and then indexing
>>directly into it with values from a (masked) integer array. Note the
>>use of "norm=colors.no_norm()" so that the array values are passed
>>directly to the colormap as integers.
>>
>>Caution: the colorbar command works correctly in this example only
>>with the modifications that I committed to svn a few minutes ago.
>>
>>As noted, the masked regions will have a specified color; they will
>>not be transparent. If you need transparent masked regions, then try
>>pcolor instead of imshow. Pcolor plots nothing at all in masked
>>cells. Pcolormesh, on the other hand, is like imshow in plotting the
>>assigned bad color and in using a single alpha for everything.
>>
>>Eric
>>
>>
>>John Pye wrote:
>>
>>
>>>Hi all
>>>
>>>I have some data with enumerated values in an array. Values are like
>>>1,2,7,9 spread around in the array. I want to plot those values so that
>>>I can see the 'regions' in my data, then I want to overlay this with
>>>some contour lines drawn from other data.
>>>
>>>I want to be able to specify the colors for each of the enumerated
>>>values, as they need to be consistent throughout my work. My array of
>>>enumerated values is *masked* so that there are areas where I don't want
>>>to show anything (this would plot as transparent pixels).
>>>
>>>Has anyone got suggestions on the best way of doing this? It seems that
>>>the technique in
>>>http://www.scipy.org/Cookbook/Matplotlib/Plotting_Images_with_Special_Values
>>>
>>>might be overkill, right? It also seemed that it had some problems with
>>>masked arrays.
>>>
>>>Cheers
>>>
>>>JP
>>>
>>
>>
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