I have a homogeneous transformation matrix of size (4x4) and a trajectory of size (nx3). Each row of this trajectory is a vector.

I want to multiply homogeneous transformation matrix by each row of trajectory. Below is the code:

#append zero column at last trajectory = np.hstack((trajectory, np.zeros((trajectory.shape[0], 1)))) #(nx3)->(nx4) trajectory_new = np.zeros((1, 3)) #(1x3) for row in trajectory: vect = row.reshape((-1,1)) #convert (1x4) to (4x1) vect = np.dot(HTM, vect) #(4x4) x (4x1) = (4x1) vect = vect.T #(1x4) vect = np.delete(vect, -1, axis=1) #remove last element from vector trajectory_new = np.vstack((trajectory_new, vect)) #(nx3) trajectory_new = np.delete(trajectory_new, 0, axis=0)#remove first row 

The above code works. However, I am looking for simpler solution, such as following:

trajectory_new = np.apply_along_axis(np.multiply, 0, trajectory, HTM) 

Any help, please.

I have a homogeneous transformation matrix of size (4x4) and a trajectory of size (nx3). Each row of this trajectory is a vector.

I want to multiply homogeneous transformation matrix by each row of trajectory. Below is the code:

#append zero column at last trajectory = np.hstack((trajectory, np.zeros((trajectory.shape[0], 1)))) #(nx3)->(nx4) trajectory_new = np.zeros((1, 3)) #(1x3) for row in trajectory: vect = row.reshape((-1,1)) #convert (1x4) to (4x1) vect = np.dot(HTM, vect) #(4x4) x (4x1) = (4x1) vect = vect.T #(1x4) vect = np.delete(vect, -1, axis=1) #remove last element from vector trajectory_new = np.vstack((trajectory_new, vect)) #(nx3) trajectory_new = np.delete(trajectory_new, 0, axis=0)#remove first row 

The above code works. However, I am looking for simpler solution, such as following:

trajectory_new = np.apply_along_axis(np.multiply, 0, trajectory, HTM) 

Any help, please.

Answer:

trajectory = np.hstack((trajectory, np.ones((trajectory.shape[0], 1))))#(nx3)->(nx4) trajectory_new = trajectory.dot(HTM.T)[:,:-1]