On Thu, Mar 15, 2012 at 12:56 PM, Gökhan Sever <[email protected]>wrote:
If not so, how can I return a set of False values if my masking condition
> is not met?
>
Self-answer: I can force the mask to be filled with False's, however unsure
if this is a safe operation.
I50 x = np.array([1, 1.1, 2, 1.1, 3])
I51 y = np.ma.masked_values(x, 1.5, shrink=0)
I52 y
O52
masked_array(data = [1.0 1.1 2.0 1.1 3.0],
mask = False,
fill_value = 1.5)
I53 y.mask = np.zeros(len(x), dtype=np.bool)*True
I54 y
O54
masked_array(data = [1.0 1.1 2.0 1.1 3.0],
mask = [False False False False False],
fill_value = 1.5)
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