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-1.17.0/reference/generated/numpy.ma.masked_inside.html