numpy.ma.masked_inside()

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.

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 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)