numpy.ma.masked_inside(x, v1, v2, copy=True)
[source]
Mask an array inside a given interval.
Shortcut to masked_where
, where condition
is True for x
inside the interval [v1,v2] (v1 <= x <= v2). The boundaries v1
and v2
can be given in either order.
See also
masked_where
The array x
is prefilled with its filling value.
>>> import numpy.ma as ma >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1] >>> ma.masked_inside(x, -0.3, 0.3) masked_array(data = [0.31 1.2 -- -- -0.4 -1.1], mask = [False False True True False False], fill_value=1e+20)
The order of v1
and v2
doesn’t matter.
>>> ma.masked_inside(x, 0.3, -0.3) masked_array(data = [0.31 1.2 -- -- -0.4 -1.1], mask = [False False True True False False], fill_value=1e+20)
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.masked_inside.html