On Thu, Mar 15, 2012 at 1:12 PM, Pierre GM <pgmdevl...@gmail.com> wrote:
> Ciao Gökhan, > AFAIR, shrink is used only to force a collapse of a mask full of False, > not to force the creation of such a mask. > Now, it should work as you expected, meaning that it needs to be fixed. > Could you open a ticket? And put me in copy, just in case. > Anyhow: > Your trick is a tad dangerous, as it erases the previous mask. I'd prefer > to create x w/ a full mask, then use masked_values w/ shrink=False... Now, > if you're sure there's x= no masked values, go for it. > Cheers > This condition checking should make it stronger: I7 x = np.array([1, 1.1, 2, 1.1, 3]) I8 y = np.ma.masked_values(x, 1.5) I9 if y.mask == False: y.mask = np.zeros(len(x), dtype=np.bool)*True ...: I10 y.mask O10 array([False, False, False, False, False], dtype=bool) I11 y O11 masked_array(data = [1.0 1.1 2.0 1.1 3.0], mask = [False False False False False], fill_value = 1.5) How do you create "x w/ a full mask"? -- Gökhan
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