# jax.numpy.isposinf¶

jax.numpy.isposinf(x, out=None)

Test element-wise for positive infinity, return result as bool array.

LAX-backend implementation of isposinf(). Original docstring below.

Parameters
• x (array_like) – The input array.

• out (array_like, optional) – A location into which the result is stored. If provided, it must have a shape that the input broadcasts to. If not provided or None, a freshly-allocated boolean array is returned.

Returns

• out (ndarray) – A boolean array with the same dimensions as the input. If second argument is not supplied then a boolean array is returned with values True where the corresponding element of the input is positive infinity and values False where the element of the input is not positive infinity.

• If a second argument is supplied the result is stored there. If the

• type of that array is a numeric type the result is represented as zeros

• and ones, if the type is boolean then as False and True.

• The return value out is then a reference to that array.

Notes

NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).

Errors result if the second argument is also supplied when x is a scalar input, if first and second arguments have different shapes, or if the first argument has complex values

Examples

>>> np.isposinf(np.PINF)
True
>>> np.isposinf(np.inf)
True
>>> np.isposinf(np.NINF)
False
>>> np.isposinf([-np.inf, 0., np.inf])
array([False, False,  True])

>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isposinf(x, y)
array([0, 0, 1])
>>> y
array([0, 0, 1])