Replace nan with zero and inf with large finite numbers.
If x is inexact, NaN is replaced by zero, and infinity and -infinity replaced by the respectively largest and most negative finite floating point values representable by
For complex dtypes, the above is applied to each of the real and imaginary components of x separately.
If x is not inexact, then no replacements are made.
x : array_like
copy : bool, optional
Whether to create a copy of x (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True.
New in version 1.13.
out : ndarray
x, with the non-finite values replaced. If
copyis False, this may be x itself.
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.
>>> 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]) >>> y = np.array([complex(np.inf, np.nan), np.nan, complex(np.nan, np.inf)]) >>> np.nan_to_num(y) array([ 1.79769313e+308 +0.00000000e+000j, 0.00000000e+000 +0.00000000e+000j, 0.00000000e+000 +1.79769313e+308j])