numpy.ma.masked_outside#

ma.masked_outside(x, v1, v2, copy=True)[source]#

Mask an array outside a given interval.

Shortcut to masked_where, where condition is True for x outside the interval [v1,v2] (x < v1)|(x > v2). The boundaries v1 and v2 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 as np
>>> import numpy.ma as ma
>>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1]
>>> ma.masked_outside(x, -0.3, 0.3)
masked_array(data=[--, --, 0.01, 0.2, --, --],
             mask=[ True,  True, False, False,  True,  True],
       fill_value=1e+20)

The order of v1 and v2 doesn’t matter.

>>> ma.masked_outside(x, 0.3, -0.3)
masked_array(data=[--, --, 0.01, 0.2, --, --],
             mask=[ True,  True, False, False,  True,  True],
       fill_value=1e+20)