On Tue, Oct 27, 2009 at 8:25 AM, <josef.p...@gmail.com> wrote: > This should not be the correct results if you use > scipy.stats.scoreatpercentile, > it doesn't have correct missing value handling, it treats nans or > mask/fill values as regular numbers sorted to the end. > > stats.mstats.scoreatpercentile is the corresponding function for > masked arrays. > > Thanks for the suggestion. I forgot the existence of such module. It yields better results.
I[14]: st.mstats.scoreatpercentile(r, per=25) O[14]: masked_array(data = 0.401055201111, mask = False, fill_value = 1e+20) I[17]: st.scoreatpercentile(r, per=25) O[17]: masked_array(data = --, mask = True, fill_value = 1e+20) I usually fall into traps using masked arrays. Hopefully I will figure out these before I make funnier mistakes in my analysis. Besides, it would be nice to have the "per" argument accepts a sequence instead of a one item. Like matplotlib's prctile. Using it as: ...(array, per=[5,25,50,75,95]) in a one call. > (BTW I wasn't able to quickly copy and past your example because > MaskedArrays don't seem to have a constructive __repr__, i.e. > no commas) > > You can copy and paste the sample data from this link. When I copied from a txt file into gmail into somehow distorted the original look of the data. http://code.google.com/p/ccnworks/source/browse/trunk/sample.data > I don't know anything about the matplotlib story. > > Josef > > > > > I[55]: stats.scoreatpercentile(am/bm, per=5) > > O[55]: 0.40877012449846228 > > > > I[49]: stats.scoreatpercentile(am/bm, per=25) > > O[49]: > > masked_array(data = --, > > mask = True, > > fill_value = 1e+20) > > > > I[56]: stats.scoreatpercentile(am/bm, per=95) > > O[56]: > > masked_array(data = --, > > mask = True, > > fill_value = 1e+20) > > > > > > Any confirmation? > > > > > > > > > > > > > > > > -- > > Gökhan > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > -- Gökhan
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