numpy.nan_to_num(x, copy=True)
[source]
Replace nan with zero and inf with finite numbers.
Returns an array or scalar replacing Not a Number (NaN) with zero, (positive) infinity with a very large number and negative infinity with a very small (or negative) number.
Parameters: |
x : array_like Input data. copy : bool, optional Whether to create a copy of New in version 1.13. |
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Returns: |
out : ndarray New Array with the same shape as |
See also
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.
>>> np.set_printoptions(precision=8) >>> x = np.array([np.inf, -np.inf, np.nan, -128, 128]) >>> np.nan_to_num(x) array([ 1.79769313e+308, -1.79769313e+308, 0.00000000e+000, -1.28000000e+002, 1.28000000e+002])
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https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.nan_to_num.html