bundles / numpy latest / numpy / isfinite
ufunc
numpy:isfinite
source: /dev/numpy/build-install/usr/lib/python3.14/site-packages/numpy/__init__.py
Summary
Test element-wise for finiteness (not infinity and not Not a Number).
Extended Summary
The result is returned as a boolean array.
Parameters
x: array_likeInput values.
out: ndarray, None, or tuple of ndarray and None, optionalA location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where: array_like, optionalThis condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default
out=None, locations within it where the condition is False will remain uninitialized.**kwargsFor other keyword-only arguments, see the
ufunc docs <ufuncs.kwargs>.
Returns
y: ndarray, boolTrue where
xis not positive infinity, negative infinity, or NaN; false otherwise. This is a scalar if x is a scalar.
Notes
Not a Number, positive infinity and negative infinity are considered to be non-finite.
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not equivalent to negative infinity. But infinity is equivalent to positive infinity. Errors result if the second argument is also supplied when x is a scalar input, or if first and second arguments have different shapes.
Examples
import numpy as np
✓np.isfinite(1) np.isfinite(0) np.isfinite(np.nan) np.isfinite(np.inf) np.isfinite(-np.inf)✗
np.isfinite([np.log(-1.),1.,np.log(0)])
✓x = np.array([-np.inf, 0., np.inf]) y = np.array([2, 2, 2]) np.isfinite(x, y) y✓
See also
- isinf
- isnan
- isneginf
- isposinf
Aliases
-
numpy.isfinite