numpy.nan_to_num — NumPy v1.11 Manual (original) (raw)
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. |
|---|---|
| Returns: | out : ndarray New Array with the same shape as x and dtype of the element in_x_ with the greatest precision. If x is inexact, then NaN is replaced by zero, and infinity (-infinity) is replaced by the largest (smallest or most negative) floating point value that fits in the output dtype. If x is not inexact, then a copy of x is returned. |
See also
Shows which elements are negative or negative infinity.
Shows which elements are negative infinity.
Shows which elements are positive infinity.
Shows which elements are Not a Number (NaN).
Shows which elements are finite (not NaN, not infinity)
Notes
Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.
Examples
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])