numpy.ma.masked_invalid — NumPy v1.11 Manual (original) (raw)

numpy.ma.masked_invalid(a, copy=True)[source]¶

Mask an array where invalid values occur (NaNs or infs).

This function is a shortcut to masked_where, with_condition_ = ~(np.isfinite(a)). Any pre-existing mask is conserved. Only applies to arrays with a dtype where NaNs or infs make sense (i.e. floating point types), but accepts any array_like object.

Examples

import numpy.ma as ma a = np.arange(5, dtype=np.float) a[2] = np.NaN a[3] = np.PINF a array([ 0., 1., NaN, Inf, 4.]) ma.masked_invalid(a) masked_array(data = [0.0 1.0 -- -- 4.0], mask = [False False True True False], fill_value=1e+20)