numpy.ma.masked_invalid¶
-
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.See also
masked_where
- Mask where a condition is met.
Examples
>>> import numpy.ma as ma >>> a = np.arange(5, dtype=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)