scipy.spatial.transform.

Slerp#

class scipy.spatial.transform.Slerp(times, rotations)[source]#

Spherical Linear Interpolation of Rotations.

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:
timesarray_like, shape (N,)

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

rotationsRotation instance

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

Methods

__call__(times)

Interpolate rotations.

See also

Rotation

Notes

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

Added in version 1.2.0.

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 Support for the array API standard for more information.

References

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([[ 14.31443779, -27.50095894,  -3.7275787 ],
       [ -1.79924227, -24.69421529, 164.57701743],
       [146.15020772,  43.22849451, -31.34891088],
       [ 46.39959442,  11.62126073, -45.99719267],
       [-88.94647804, -49.64400082, -65.80546984]])

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([[  14.31443779,  -27.50095894,   -3.7275787 ],
       [   4.74588574,  -32.44683966,   81.25139984],
       [  10.71094749,  -31.56690154,   38.06896408],
       [  -1.79924227,  -24.69421529,  164.57701743],
       [  11.72796022,   51.64207311, -171.7374683 ],
       [ 146.15020772,   43.22849451,  -31.34891088],
       [  68.10921869,   20.67625074,  -48.74886034],
       [  46.39959442,   11.62126073,  -45.99719267],
       [  12.35552615,    4.21525086,  -64.89288124],
       [ -30.08117143,  -19.90769513,  -78.98121326],
       [ -88.94647804,  -49.64400082,  -65.80546984]])
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