numpy.ma.fix_invalid#
- ma.fix_invalid(a, mask=np.False_, copy=True, fill_value=None)[source]#
Return input with invalid data masked and replaced by a fill value.
Invalid data means values of
nan
,inf
, etc.- Parameters:
- aarray_like
Input array, a (subclass of) ndarray.
- masksequence, optional
Mask. Must be convertible to an array of booleans with the same shape as data. True indicates a masked (i.e. invalid) data.
- copybool, optional
Whether to use a copy of a (True) or to fix a in place (False). Default is True.
- fill_valuescalar, optional
Value used for fixing invalid data. Default is None, in which case the
a.fill_value
is used.
- Returns:
- bMaskedArray
The input array with invalid entries fixed.
Notes
A copy is performed by default.
Examples
>>> x = np.ma.array([1., -1, np.nan, np.inf], mask=[1] + [0]*3) >>> x masked_array(data=[--, -1.0, nan, inf], mask=[ True, False, False, False], fill_value=1e+20) >>> np.ma.fix_invalid(x) masked_array(data=[--, -1.0, --, --], mask=[ True, False, True, True], fill_value=1e+20)
>>> fixed = np.ma.fix_invalid(x) >>> fixed.data array([ 1.e+00, -1.e+00, 1.e+20, 1.e+20]) >>> x.data array([ 1., -1., nan, inf])