numpy.ma.masked_inside
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numpy.ma.masked_inside(x, v1, v2, copy=True)
[source] -
Mask an array inside a given interval.
Shortcut to
masked_where
, wherecondition
is True forx
inside the interval [v1,v2] (v1 <= x <= v2). The boundariesv1
andv2
can be given in either order.See also
-
masked_where
- Mask where a condition is met.
Notes
The array
x
is prefilled with its filling value.Examples
>>> 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
andv2
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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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ma.masked_inside.html