On Thu, Mar 15, 2012 at 1:24 PM, Gökhan Sever <gokhansever@gmail.com> wrote:

On Thu, Mar 15, 2012 at 1:12 PM, Pierre GM <pgmdevlist@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

--
Gökhan