numpy.ma.masked_inside¶
- 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
- 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 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)