Hi Dirk,
If you haven't already done so, look at the numpy.ma module. It provides a
masked array object that deals gracefully with missing values. To the best
of my knowledge, most matplotlib functions understand masked arrays and deal
with it accordingly, exception made of those requiring a full matrix (such
as contour). Take a look at examples/image_masked.py. Also, in the Basemap
toolkit, there is at least one example showing how to plot a masked array on
a map.
Cheers,
David
2007/9/26, Dirk Zickermann <[EMAIL PROTECTED]>:
>
> Dear matplotlib group,
>
> for the represenation of 2d measurement data I use the contourplot
> function from matplotlib. Some points in this map are not measurabel,
> therefore I get a non numerical value (nan) output.
>
> From this data I want to generate a map and a histogram plot. This works
> fine, as long as I use regular matrix/array data structure without any
> voids.
>
> My questions are:
> (1) How can I make use of plotting data with NAN values as contour and
> asigns such values eg as black points?
> (2) How can I use the matplotlib hist() function with this data, that also
> include such missing data points?
> Maybe there is an easy workaround for this.
>
> Thanks a lot for your support,
> Dirk
>
> (python2.51 /matplotlib-0.90.1, win32)
>
> my code:
> ...
> import matplotlib
> ...
> my2dData=[[1,2,3,4,5.0 ,NaN,7,8,9,10],[10,9,8,7,6,5,4,3,2,1]]
> ...
> figure(1)
> imshow(my2dData)
> pylab.show()
> ..
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