def nan_to_num(array, fill_value = 0.0, copy = True):
"""
Replace NaNs with another fill value.
Parameters
----------
array : array_like
Input data.
fill_value : float, optional
NaNs will be replaced by ``fill_value``. Default is 0.0, in keeping
with ``numpy.nan_to_num``.
copy : bool, optional
Whether to create a copy of `array` (True) or to replace values
in-place (False). The in-place operation only occurs if
casting to an array does not require a copy.
Returns
-------
out : ndarray
Array without NaNs. If ``array`` was not of floating or complearray type,
``array`` is returned unchanged.
Notes
-----
Contrary to ``numpy.nan_to_num``, this functions does not handle
infinite values.
See Also
--------
numpy.nan_to_num : replace NaNs and Infs with zeroes.
"""
array = np.array(array, subok = True, copy = copy)
dtype = array.dtype.type
# Non-inexact types do not have NaNs
if not np.issubdtype(dtype, np.inexact):
return array
iscomplex = np.issubdtype(dtype, np.complexfloating)
dest = (array.real, array.imag) if iscomplex else (array,)
for d in dest:
np.copyto(d, fill_value, where = np.isnan(d))
return array
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