This is documentation for an old release of NumPy (version 1.13.0). Read this page in the documentation of the latest stable release (version > 1.17).
numpy.ma.masked_outside¶
-
numpy.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.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)