How to use the pytransform3d.transformations.concat function in pytransform3d

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github rock-learning / pytransform3d / examples / plot_transform_concatenation.py View on Github external
import numpy as np
import matplotlib.pyplot as plt
import pytransform3d.rotations as pyrot
import pytransform3d.transformations as pytr


p = np.array([0.0, 0.0, -0.5])
a = np.array([0.0, 0.0, 1.0, np.pi])
B2A = pytr.transform_from(pyrot.matrix_from_axis_angle(a), p)

p = np.array([0.3, 0.4, 0.5])
a = np.array([0.0, 0.0, 1.0, -np.pi / 2.0])
C2B = pytr.transform_from(pyrot.matrix_from_axis_angle(a), p)

C2A = pytr.concat(C2B, B2A)
p = pytr.transform(C2A, np.ones(4))

ax = pytr.plot_transform(A2B=B2A)
pytr.plot_transform(ax, A2B=C2A)
ax.scatter(p[0], p[1], p[2])
plt.show()
github rock-learning / pytransform3d / pytransform3d / transform_manager.py View on Github external
def _path_transform(self, path):
        A2B = np.eye(4)
        for from_f, to_f in zip(path[:-1], path[1:]):
            A2B = concat(A2B, self.get_transform(from_f, to_f))
        return A2B
github rock-learning / pytransform3d / pytransform3d / urdf.py View on Github external
Parameters
        ----------
        joint_name : string
            Name of the joint

        angle : float
            Joint angle in radians
        """
        if joint_name not in self._joints:
            raise KeyError("Joint '%s' is not known" % joint_name)
        from_frame, to_frame, child2parent, axis, limits = self._joints[joint_name]
        angle = np.clip(angle, limits[0], limits[1])
        joint_rotation = matrix_from_axis_angle(np.hstack((axis, [angle])))
        joint2A = transform_from(joint_rotation, np.zeros(3))
        self.add_transform(from_frame, to_frame, concat(joint2A, child2parent))
github rock-learning / pytransform3d / examples / animate_trajectory.py View on Github external
def update_trajectory(step, n_frames, trajectory):
    progress = float(step + 1) / float(n_frames)
    H = np.zeros((100, 4, 4))
    H0 = transform_from(R_id, np.zeros(3))
    H_mod = np.eye(4)
    for i, t in enumerate(np.linspace(0, progress, len(H))):
        H0[:3, 3] = np.array([t, 0, t])
        H_mod[:3, :3] = matrix_from_angle(2, 8 * np.pi * t)
        H[i] = concat(H0, H_mod)

    trajectory.set_data(H)
    return trajectory