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analyse_logs.py File Reference

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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)


2010_biorob_everyday_mechanics
Author(s): Advait Jain, Hai Nguyen, Charles C. Kemp (Healthcare Robotics Lab, Georgia Tech)
autogenerated on Wed Nov 27 2013 11:58:43