import numpy as np

def qrot(q, v):
    """
    Rotate vector(s) v about the rotation described by quaternion(s) q.
    Expects a tensor of shape (*, 4) for q and a tensor of shape (*, 3) for v,
    where * denotes any number of dimensions.
    Returns a tensor of shape (*, 3).
    """
    assert q.shape[-1] == 4
    assert v.shape[-1] == 3
    assert q.shape[:-1] == v.shape[:-1]

    qvec = q[..., 1:]

    uv = np.cross(qvec, v)
    uuv = np.cross(qvec, uv)
    
    return (v + 2 * (q[..., :1] * uv + uuv))
    
def qinverse(q, inplace=False):
    # We assume the quaternion to be normalized
    if inplace:
        q[..., 1:] *= -1
        return q
    else:
        w = q[..., :1]
        xyz = q[..., 1:]
        return np.hstack((w, -xyz))
 