`scipy.spatial.transform._rigid_transform:RigidTransform.from_dual_quat`

source: /scipy/spatial/transform/_rigid_transform.py:849

Signature

staticmethoddef from_dual_quat(dual_quat: ArrayLike, *, scalar_first: bool = False) → RigidTransform

Summary

Initialize from a unit dual quaternion.

Extended Summary

Unit dual quaternions encode orientation in a real unit quaternion and translation in a dual quaternion. There is a double cover, i.e., the unit dual quaternions q and -q represent the same transform.

Unit dual quaternions must have a real quaternion with unit norm and a dual quaternion that is orthogonal to the real quaternion to satisfy the unit norm constraint. This function will enforce both properties through normalization.

Parameters

dual_quat : array_like, shape (..., 8): Unit dual quaternions. Each dual_quat[..., :] represents a unit dual quaternion. The real part is stored in the first four components and the dual part in the last four components.
scalar_first : bool, optional: Whether the scalar component goes first or last in the two individual quaternions that represent the real and the dual part. Default is False, i.e. the scalar-last order is used.

Returns

transform : `RigidTransform` instance: Rigid transform objects with the same leading dimensions as the input.

Examples

from scipy.spatial.transform import RigidTransform as Tf
import numpy as np

✓

Creating from a single unit dual quaternion:

tf = Tf.from_dual_quat([
    0.0617101, -0.06483886, 0.31432811, 0.94508498,
    0.04985168, -0.26119618, 0.1691491, -0.07743254])

✓

tf.as_matrix()

✗

array([[ 0.79399, -0.60214, -0.08376,  0.24605],
       [ 0.58613,  0.79478, -0.1574 , -0.49328],
       [ 0.16135,  0.07588,  0.98398,  0.34263],
       [ 0.     ,  0.     ,  0.     ,  1.     ]])

tf.single

✓

True

Aliases

scipy.spatial.transform.RigidTransform.from_dual_quat