Go to the source code of this file.
| Namespaces | |
| namespace | analyse_logs | 
| Functions | |
| def | analyse_logs.angle_between_hooktip_mechanism_radial_vectors | 
| def | analyse_logs.check_time_sync | 
| plot to ensure that the time stamps in the different logs are reasonable. | |
| def | analyse_logs.compare_tip_mechanism_trajectories | 
| sanity check - fitting circle to mechanism and hook tip trajectories, computing the angle between the initial radial direction of the mechanism and the radial directions for the hook tip. | |
| def | analyse_logs.compute_hook_tip_trajectory | 
| def | analyse_logs.compute_mech_angle_1 | 
| use method 1 to compute the mechanism angle from combined dict. | |
| def | analyse_logs.compute_mech_angle_2 | 
| use method 2 to compute the mechanism angle from combined dict. | |
| def | analyse_logs.compute_mech_rot_list | 
| def | analyse_logs.compute_mechanism_properties | 
| def | analyse_logs.ft_to_camera | 
| transform forces to camera coord frame. | |
| def | analyse_logs.ft_to_camera_3 | 
| transform force to camera coord frame. | |
| def | analyse_logs.fts_to_camera | 
| returns force and moment at the tip of the hook in camera coordinates. | |
| def | analyse_logs.plot | 
| def | analyse_logs.plot_forces | 
| def | analyse_logs.plot_hooktip_trajectory_and_force | 
| def | analyse_logs.plot_radial_tangential | 
| def | analyse_logs.plot_trajectories | 
| def | analyse_logs.project_points_plane | 
| def | analyse_logs.split_forces_hooktip_test | 
| def | analyse_logs.split_open_close | 
| take the open + close trajectory and split it into two separate trajectories and save them as pkls. | |
| def | analyse_logs.synchronize | 
| Variables | |
| tuple | analyse_logs.ang = np.array(ang) | 
| analyse_logs.bias_ft = True,tuptup, | |
| tuple | analyse_logs.cd = ut.load_pickle(glob.glob(opt.dir + '/combined_log*.pkl')[0]) | 
| analyse_logs.cd_pkl_name = pkl_name) | |
| string | analyse_logs.color = 'b' | 
| tuple | analyse_logs.d = synchronize(ft_dict, mechanism_dict, hand_dict) | 
| string | analyse_logs.dest = 'mech_prop_ros' | 
| tuple | analyse_logs.end_idx = np.argmax(mech_angle_l) | 
| tuple | analyse_logs.fig1 = mpu.figure() | 
| tuple | analyse_logs.fmag = np.linalg.norm(f) | 
| list | analyse_logs.force_mat = ft_mat[0:3, :] | 
| tuple | analyse_logs.ft_dict = ut.load_pickle(ft_pkl) | 
| tuple | analyse_logs.ft_mat = np.matrix(cd['ft_list']) | 
| tuple | analyse_logs.ft_pkl = glob.glob(opt.dir + '/ft_log*.pkl') | 
| list | analyse_logs.ft_time_list = ft_dict['time_list'] | 
| list | analyse_logs.hand_dict = poses_dict['hand'] | 
| tuple | analyse_logs.hand_mat = np.column_stack(hook_tip_l) | 
| list | analyse_logs.hand_time_list = hand_dict['time_list'] | 
| string | analyse_logs.help = 'plot to check the consistency of time stamps' | 
| list | analyse_logs.hook_rot_l = cd['hand_rot_list'] | 
| tuple | analyse_logs.hook_tip_l = compute_hook_tip_trajectory(cd) | 
| list | analyse_logs.incr = ang[1:] | 
| string | analyse_logs.lab1 = 'orientation only' | 
| string | analyse_logs.lab2 = 'checker origin position + circle fit' | 
| string | analyse_logs.lab3 = 'checker origin position + PCA projection + circle fit' | 
| int | analyse_logs.label = 1 | 
| int | analyse_logs.linewidth = 1 | 
| tuple | analyse_logs.ma1 = compute_mech_angle_1(cd) | 
| tuple | analyse_logs.ma2 = compute_mech_angle_2(cd, tup, project_plane=False) | 
| tuple | analyse_logs.ma3 = compute_mech_angle_2(cd, tup, project_plane=True) | 
| tuple | analyse_logs.mag = abs(incr[i] - incr[i+1]) | 
| tuple | analyse_logs.max_idx = np.argmax(ang) | 
| tuple | analyse_logs.md = ut.load_pickle(mech_pkl_name) | 
| tuple | analyse_logs.mech_angle_l = compute_mech_angle_2(cd, tup, project_plane=False) | 
| tuple | analyse_logs.mech_mat = np.column_stack(cd['mech_pos_list']) | 
| tuple | analyse_logs.mech_pkl_name = glob.glob(opt.dir + '/open_mechanism_trajectories_*.pkl') | 
| list | analyse_logs.mechanism_dict = poses_dict['mechanism'] | 
| list | analyse_logs.mechanism_time_list = mechanism_dict['time_list'] | 
| tuple | analyse_logs.moment_axis = np.array(moment_axis[:max_idx+1]) | 
| list | analyse_logs.moment_mat = ft_mat[3:6, :] | 
| tuple | analyse_logs.moment_tip = np.array(moment_tip[:max_idx+1]) | 
| list | analyse_logs.n_pts = ang.shape[0] | 
| tuple | analyse_logs.p = optparse.OptionParser() | 
| tuple | analyse_logs.pkl_name = glob.glob(opt.dir + '/combined_log*.pkl') | 
| tuple | analyse_logs.poses_dict = ut.load_pickle(poses_pkl) | 
| tuple | analyse_logs.poses_pkl = glob.glob(opt.dir + '/poses_dict*.pkl') | 
| tuple | analyse_logs.rad = np.array(rad[:max_idx+1]) | 
| list | analyse_logs.sgn = incr[i] | 
| tuple | analyse_logs.tan = np.array(tan[:max_idx+1]) | 
| tuple | analyse_logs.tup = ke.init_ros_node() | 
| string | analyse_logs.type = 'string' | 
| tuple | analyse_logs.vel1 = ma.compute_velocity(ma1, cd['time_list'], 1) | 
| tuple | analyse_logs.vel2 = ma.compute_velocity(ma2, cd['time_list'], 1) | 
| tuple | analyse_logs.vel3 = ma.compute_velocity(ma3, cd['time_list'], 1) |