`numpy.linalg:cross`

Signature

def cross ( x1 , x2 , / , axis = -1 )

Returns the cross product of 3-element vectors.

If x1 and/or x2 are multi-dimensional arrays, then the cross-product of each pair of corresponding 3-element vectors is independently computed.

This function is Array API compatible, contrary to numpy.cross.

x1 : array_like: The first input array.
x2 : array_like: The second input array. Must be compatible with x1 for all non-compute axes. The size of the axis over which to compute the cross-product must be the same size as the respective axis in x1.
axis : int, optional: The axis (dimension) of x1 and x2 containing the vectors for which to compute the cross-product. Default: -1.

Vector cross-product.

x = np.array([1, 2, 3])
y = np.array([4, 5, 6])
np.linalg.cross(x, y)

✓

Multiple vector cross-products. Note that the direction of the cross product vector is defined by the *right-hand rule*.

x = np.array([[1,2,3], [4,5,6]])
y = np.array([[4,5,6], [1,2,3]])
np.linalg.cross(x, y)

✓

x = np.array([[1, 2], [3, 4], [5, 6]])
y = np.array([[4, 5], [6, 1], [2, 3]])

✓

np.linalg.cross(x, y, axis=0)