jax.numpy.linalg.cross#

jax.numpy.linalg.cross(x1,x2,/,*,axis=-1)[source]#

Compute the cross-product of two 3D vectors

JAX implementation ofnumpy.linalg.cross()

Parameters:

• x1 (ArrayLike) – N-dimensional array, withx1.shape[axis]==3

• x2 (ArrayLike) – N-dimensional array, withx2.shape[axis]==3, and other axesbroadcast-compatible withx1.

• axis – axis along which to take the cross product (default: -1).

Returns:

array containing the result of the cross-product

See also

jax.numpy.cross(): more flexible cross-product API.

Examples

Showing that\(\hat{x} \times \hat{y} = \hat{z}\):

>>>x=jnp.array([1.,0.,0.])>>>y=jnp.array([0.,1.,0.])>>>jnp.linalg.cross(x,y)Array([0., 0., 1.], dtype=float32)

Cross product of\(\hat{x}\) with all three standard unit vectors,via broadcasting:

>>>xyz=jnp.eye(3)>>>jnp.linalg.cross(x,xyz,axis=-1)Array([[ 0.,  0.,  0.],       [ 0.,  0.,  1.],       [ 0., -1.,  0.]], dtype=float32)