Try this:
from pylab import *
from numpy import *
Z = random.randn(100,100)
figure()
subplot(1,2,1)
imgHandle = imshow(Z, cmap=cm.gray)
scatter(random.rand(10)*100,random.rand(10)*100)
colorbar(imgHandle)
title('Hello')
show()
By the way, I find jet a bad colormap to represent scientific data: it
suggests bands in the data that aren't there and when reduced to
luminance (eg. students printing/copying in black/white or in the eyes
of all your colorblind colleagues) the two halves of the scale are
identical, rendering all graphs completely ambiguous. ;)
Claus wrote:
> Hi,
> I've got two questions:
> 1) one is related to colorbar() on multiple subfigures (see code example
> below): how do I add a scatterplot if I wanted multiple subfigures? Or, what
> am I doing wrong in the second code example
> 2) in either of the examples, how can I increase the distance between the top
> of the plot (imshow) and the bottom of the title?
>
>
> # code example 1: this works
> fig = plt.figure()
> plt.title('Hello')
> plt.imshow(interpolValsRas, cmap=cm.jet, interpolation='nearest', origin =
> 'lower', extent=[5,95,5,95]) # ,
> plt.scatter(measurementLoc[:,0], measurementLoc[:,1], 10, messwerte,
> cmap=cm.jet)
> plt.colorbar();
>
>
> # code example 2: this works generally, but only if the second last line is
> commented out
> # Q: how do I add a scatterplot if I wanted multiple subfigures?
> fig = plt.figure()
> ax = fig.add_subplot(111)
> plt.title('Hello')
> ax.imshow(interpolValsRas, cmap=cm.jet, interpolation='nearest', origin =
> 'lower', extent=[5,95,5,95]) # ,
> ax.scatter(measurementLoc[:,0], measurementLoc[:,1], 10, messwerte,
> cmap=cm.jet)
> # plt.colorbar();
> plt.show()
>
> Thanks for your help,
> Claus
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proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta.
http://p.sf.net/sfu/intel-sw-dev
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