This is documentation for an old release of SciPy (version 1.7.0). Read this page in the documentation of the latest stable release (version 1.15.1).

scipy.spatial.transform.Rotation.random

Rotation.random()

Generate uniformly distributed rotations.

Parameters
numint or None, optional

Number of random rotations to generate. If None (default), then a single rotation is generated.

random_state{None, int, numpy.random.Generator,

If seed is None (or np.random), the numpy.random.RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a Generator or RandomState instance then that instance is used.

Returns
random_rotationRotation instance

Contains a single rotation if num is None. Otherwise contains a stack of num rotations.

Notes

This function is optimized for efficiently sampling random rotation matrices in three dimensions. For generating random rotation matrices in higher dimensions, see scipy.stats.special_ortho_group.

Examples

>>> from scipy.spatial.transform import Rotation as R

Sample a single rotation:

>>> R.random().as_euler('zxy', degrees=True)
array([-110.5976185 ,   55.32758512,   76.3289269 ])  # random

Sample a stack of rotations:

>>> R.random(5).as_euler('zxy', degrees=True)
array([[-110.5976185 ,   55.32758512,   76.3289269 ],  # random
       [ -91.59132005,  -14.3629884 ,  -93.91933182],
       [  25.23835501,   45.02035145, -121.67867086],
       [ -51.51414184,  -15.29022692, -172.46870023],
       [ -81.63376847,  -27.39521579,    2.60408416]])