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bundles / scipy 1.18.0 / scipy / spatial / transform / _rotation / Slerp

class

scipy.spatial.transform._rotation:Slerp

source: /scipy/spatial/transform/_rotation.py:2667

Signature

class Slerp(times: ArrayLike, rotations: Rotation)

Members

Summary

Spherical Linear Interpolation of Rotations.

Extended Summary

The interpolation between consecutive rotations is performed as a rotation around a fixed axis with a constant angular velocity [1]. This ensures that the interpolated rotations follow the shortest path between initial and final orientations.

Parameters

times : array_like, shape (N,)

Times of the known rotations. At least 2 times must be specified.

rotations : `Rotation` instance

Rotations to perform the interpolation between. Must contain N rotations.

Methods

__call__

Notes

This class only supports interpolation of rotations with a single leading dimension.

Array API Standard Support

Slerp has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ✅                   
JAX                   ✅                     ✅                   
Dask                  ⛔                     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

from scipy.spatial.transform import Rotation as R
from scipy.spatial.transform import Slerp
✓
Setup the fixed keyframe rotations and times: 
key_rots = R.random(5, random_state=2342345)
key_times = [0, 1, 2, 3, 4]
✓
Create the interpolator object: 
slerp = Slerp(key_times, key_rots)
✓
Interpolate the rotations at the given times: 
times = [0, 0.5, 0.25, 1, 1.5, 2, 2.75, 3, 3.25, 3.60, 4]
interp_rots = slerp(times)
✓
The keyframe rotations expressed as Euler angles: 
key_rots.as_euler('xyz', degrees=True)
✗
array([[ 14.31444, -27.50096,  -3.72758],
       [ -1.79924, -24.69422, 164.57702],
       [146.15021,  43.22849, -31.34891],
       [ 46.39959,  11.62126, -45.99719],
       [-88.94648, -49.644  , -65.80547]])
The interpolated rotations expressed as Euler angles. These agree with the keyframe rotations at both endpoints of the range of keyframe times. 
interp_rots.as_euler('xyz', degrees=True)
✗
array([[  14.31444,  -27.50096,   -3.72758],
       [   4.74589,  -32.44684,   81.2514 ],
       [  10.71095,  -31.5669 ,   38.06896],
       [  -1.79924,  -24.69422,  164.57702],
       [  11.72796,   51.64207, -171.73747],
       [ 146.15021,   43.22849,  -31.34891],
       [  68.10922,   20.67625,  -48.74886],
       [  46.39959,   11.62126,  -45.99719],
       [  12.35553,    4.21525,  -64.89288],
       [ -30.08117,  -19.9077 ,  -78.98121],
       [ -88.94648,  -49.644  ,  -65.80547]])

See also

Rotation

Aliases

  • scipy.spatial.transform.Slerp

Referenced by

This package