numpy.isinf — NumPy v1.15 Manual (original) (raw)

numpy. isinf(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, _subok=True_[, signature, _extobj_]) = <ufunc 'isinf'>¶

Test element-wise for positive or negative infinity.

Returns a boolean array of the same shape as x, True where x == +/-inf, otherwise False.

Parameters:	x : array_like Input values out : ndarray, None, or tuple of ndarray and None, optional A 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, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see theufunc docs.
Returns:	y : bool (scalar) or boolean ndarray True where x is positive or negative infinity, false otherwise. This is a scalar if x is a scalar.

Parameters:

x : array_like Input values out : ndarray, None, or tuple of ndarray and None, optional A 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, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see theufunc docs.

Returns:

y : bool (scalar) or boolean ndarray True where x is positive or negative infinity, false otherwise. This is a scalar if x is a scalar.

Notes

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

Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.

Examples

np.isinf(np.inf) True np.isinf(np.nan) False np.isinf(np.NINF) True np.isinf([np.inf, -np.inf, 1.0, np.nan]) array([ True, True, False, False])

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