Re: [Numpy-discussion] Using matplotlib's prctile on masked arrays

On Wed, Oct 28, 2009 at 9:52 AM, Gökhan Sever wrote:

On Tue, Oct 27, 2009 at 12:23 PM, Pierre GM wrote:

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On Oct 27, 2009, at 7:56 AM, Gökhan Sever wrote:

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Unfortunately, matplotlib.mlab's prctile cannot handle this division:

Actually, the division's OK, it's mlab.prctile which is borked. It uses the length of the input array instead of its count to compute the nb of valid data. The easiest workaround in your case is probably to use:  >>> prctile((am/bm).compressed(), p=[5,25,50,75,95]) HIH P.

Great. Exact solution. I should have asked this last week :)

One simple method solves all the riddle. I had manually masked the MVCs using NaN's.

My guess is using compressed() masked arrays could be used with any of regularly defined numpy and scipy functions, right?

Yes, however it only works for 1d or with ravel(). You cannot compress a 2d array, and preserve a rectangular shape (with unequal numbers of missing numbers.) I some cases removing rows or columns with missing values might be more appropriate, or finding a "neutral" fill value. Josef

Thanks for the tip.

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-- Gökhan

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