numpy.ma.fix_invalid¶
-
numpy.ma.
fix_invalid
(a, mask=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: a : array_like
Input array, a (subclass of) ndarray.
mask : sequence, optional
Mask. Must be convertible to an array of booleans with the same shape as data. True indicates a masked (i.e. invalid) data.
copy : bool, optional
Whether to use a copy of a (True) or to fix a in place (False). Default is True.
fill_value : scalar, optional
Value used for fixing invalid data. Default is None, in which case the
a.fill_value
is used.Returns: b : MaskedArray
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([ 1.00000000e+00, -1.00000000e+00, 1.00000000e+20, 1.00000000e+20]) >>> x.data array([ 1., -1., NaN, Inf])