flopscope.numpy.hypot

fnp.hypot(*args, **kwargs)[flopscope source][numpy source]

Given the "legs" of a right triangle, return its hypotenuse.

Adapted from NumPy docs np.hypot

Areacore

Typecounted

Cost

16×

\text{numel}(\text{output})

Flopscope Context

Element-wise Euclidean norm sqrt(x1^2 + x2^2).

Equivalent to sqrt(x1**2 + x2**2), element-wise. If x1 or x2 is scalar_like (i.e., unambiguously cast-able to a scalar type), it is broadcast for use with each element of the other argument. (See Examples)

Parameters

x1, x2:array_like: Leg of the triangle(s). If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).
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: This 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.
**kwargs: For other keyword-only arguments, see the ufunc docs.

Returns

z:ndarray: The hypotenuse of the triangle(s). This is a scalar if both x1 and x2 are scalars.

Examples

>>> import flopscope.numpy as fnp
>>> flops.hypot(3*flops.ones((3, 3)), 4*flops.ones((3, 3)))
array([[ 5.,  5.,  5.],
       [ 5.,  5.,  5.],
       [ 5.,  5.,  5.]])

Example showing broadcast of scalar_like argument:

>>> flops.hypot(3*flops.ones((3, 3)), [4])
array([[ 5.,  5.,  5.],
       [ 5.,  5.,  5.],
       [ 5.,  5.,  5.]])