dask.array.ma.fix_invalid

dask.array.ma.fix_invalid¶

dask.array.ma.fix_invalid(a, fill_value=None)[source]¶

Return input with invalid data masked and replaced by a fill value.

This docstring was copied from numpy.ma.fix_invalid.

Some inconsistencies with the Dask version may exist.

Invalid data means values of nan, inf, etc.

Parameters

aarray_like: Input array, a (subclass of) ndarray.
masksequence, optional (Not supported in Dask): 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 (Not supported in Dask): 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])

dask.array.ma.filled

dask.array.ma.getdata