I have bogus values I don't want to display in a gridded data set (regions
of non-convergence, for example). pcolor does exactly what I want with a
masked array, except the X and Y arguments must be integer arrays (as far as
I can tell) and my data X and Y points are not integer arrays. An
approximation of what is happening goes like:
x = linspace( 0, pi, 100)
y = linspace( -pi/2, pi/2, 30)
ev = custom_func( x, y)
print sum( isnan( ev))
12 (or whatever)
ev_m = ma.mask_where( isnan( ev), ev)
pcolor( x, y, ev_m) <-- this will fail, with an error like "need more than
one value to unpack" which I think is caused by the non-integer nature of x,
y.
Any suggestions for how can I can address this? My preference is to use
pcolor, because of the transparency. I am not a fan of the scipy
discussion regarding user-driven normalization "sentinels" to catch the
bogus values. Masked arrays seem so much more flexible.
-Park
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