from_align_vectors#

classmethod Quaternion.from_align_vectors(other: Union[Vector3d, tuple, list], initial: Union[Vector3d, tuple, list], weights: Optional[ndarray] = None, return_rmsd: bool = False, return_sensitivity: bool = False) → Union[Quaternion, Tuple[Quaternion, float], Tuple[Quaternion, ndarray], Tuple[Quaternion, float, ndarray]][source]#

Initialize an estimated quaternion to optimally align two sets of vectors.

This method wraps align_vectors(). See that method for further explanations of parameters and returns.

Parameters:

other: Vectors of shape (n,) in the other reference frame.
initial: Vectors of shape (n,) in the initial reference frame.
weights: Relative importance of the different vectors.
return_rmsd: Whether to return the (weighted) root mean square distance between other and initial after alignment. Default is False.
return_sensitivity: Whether to return the sensitivity matrix. Default is False.

Returns:

estimated_quaternion: Best estimate of the quaternion that transforms initial to other.
rmsd: Returned when return_rmsd=True.
sensitivity: Returned when return_sensitivity=True.

Examples

>>> from orix.quaternion import Quaternion
>>> from orix.vector import Vector3d
>>> v1 = Vector3d([[1, 0, 0], [0, 1, 0]])
>>> v2 = Vector3d([[0, -1, 0], [0, 0, 1]])
>>> q12 = Quaternion.from_align_vectors(v2, v1)
>>> q12 * v1
Vector3d (2,)
[[ 0. -1.  0.]
 [ 0.  0.  1.]]
>>> q21, dist = Quaternion.from_align_vectors(v1, v2, return_rmsd=True)
>>> dist
0.0
>>> q21 * v2
Vector3d (2,)
[[1. 0. 0.]
 [0. 1. 0.]]

Examples using `Quaternion.from_align_vectors`#

from_align_vectors#

Examples using Quaternion.from_align_vectors#

Examples using `Quaternion.from_align_vectors`#