Sample Transforms

import numpy as np
import matplotlib.pyplot as plt
import pytransform3d.transformations as pt


mean = pt.transform_from(R=np.eye(3), p=np.array([0.0, 0.0, 0.5]))
cov = np.diag([0.001, 0.001, 0.5, 0.001, 0.001, 0.001])
rng = np.random.default_rng(0)
ax = None
poses = np.array([
    pt.random_transform(rng=rng, mean=mean, cov=cov) for _ in range(1000)])
for pose in poses:
    ax = pt.plot_transform(ax=ax, A2B=pose, s=0.3)
plt.show()