def plot_rotary_heights(csv_data):
keys = ['radius', 'bottom', 'top', 'type', 'name', 'repetition']
llists = expand(extract_keys(csv_data, keys), keys)
types = llists[3]
names = np.array(llists[4])
print 'Handle bottom edge types', set(types)
bottom_pts = np.array([float(f) for f in llists[1]])/100.
top_pts = []
for i,f in enumerate(llists[2]):
if f == '':
f = llists[1][i]
top_pts.append(float(f)/100.)
top_pts = np.array(top_pts)
print 'total number of doors:', len(top_pts)
mid_pts = (bottom_pts + top_pts)/2.
types_arr = np.array(types)
cabinet_mid_pts = mid_pts[np.where(types_arr == 'C')[0]]
other_mid_pts = mid_pts[np.where(types_arr != 'C')[0]]
other_names = names[np.where(types_arr != 'C')[0]]
print 'other names', other_names
# Hai, Advait apologizes for changing code without making a copy.
# He didn't realise. He'll make a copy from an earlier revision in
# subversion soon.
ymax = 85
handle_height_histogram_advait(mid_pts, plot_title='Handle Heights', ymax=ymax, label = 'All')
mpu.legend(display_mode = 'less_space', handlelength=1.)
handle_height_histogram_advait(mid_pts, plot_title='Handle Heights', ymax=ymax, color = 'g', label = 'Cabinets')
handle_height_histogram_advait(other_mid_pts, plot_title='Handle Heights', ymax=ymax, color = 'y', new_figure = False, label = 'Other')
mpu.legend(display_mode = 'less_space', handlelength=1.)
def check_time_sync(ft_time_list, mechanism_time_list, hand_time_list):
mpu.plot_yx(np.zeros(len(ft_time_list))+1, ft_time_list,
color = mpu.random_color(), label='ft\_time\_list',
axis=None, linewidth=0.5, scatter_size=10)
mpu.plot_yx(np.zeros(len(mechanism_time_list))+2, mechanism_time_list,
color = mpu.random_color(), label='mechanism\_time\_list',
axis=None, linewidth=0.5, scatter_size=10)
mpu.plot_yx(np.zeros(len(hand_time_list))+3, hand_time_list,
color = mpu.random_color(), label='hand\_time\_list',
axis=None, linewidth=0.5, scatter_size=10)
mpu.legend()
def plot_cartesian(traj, xaxis=None, yaxis=None, zaxis=None, color='b',label='_nolegend_',
linewidth=2, scatter_size=10, plot_velocity=False):
import matplotlib_util.util as mpu
import arm_trajectories as at
#if traj.__class__ == at.JointTrajectory:
if isinstance(traj,at.JointTrajectory):
traj = joint_to_cartesian(traj)
pts = np.matrix(traj.p_list).T
label_list = ['X coord (m)', 'Y coord (m)', 'Z coord (m)']
x = pts[xaxis,:].A1.tolist()
y = pts[yaxis,:].A1.tolist()
if plot_velocity:
vels = np.matrix(traj.v_list).T
xvel = vels[xaxis,:].A1.tolist()
yvel = vels[yaxis,:].A1.tolist()
if zaxis == None:
mpu.plot_yx(y, x, color, linewidth, '-', scatter_size, label,
axis = 'equal', xlabel = label_list[xaxis],
ylabel = label_list[yaxis],)
if plot_velocity:
mpu.plot_quiver_yxv(y, x, np.matrix([xvel,yvel]),
width = 0.001, scale = 1.)
mpu.legend()
else:
from numpy import array
from enthought.mayavi.api import Engine
engine = Engine()
engine.start()
if len(engine.scenes) == 0:
engine.new_scene()
z = pts[zaxis,:].A1.tolist()
time_list = [t-traj.time_list[0] for t in traj.time_list]
mlab.plot3d(x,y,z,time_list,tube_radius=None,line_width=4)
mlab.axes()
mlab.xlabel(label_list[xaxis])
mlab.ylabel(label_list[yaxis])
mlab.zlabel(label_list[zaxis])
mlab.colorbar(title='Time')
# -------------------------------------------
axes = engine.scenes[0].children[0].children[0].children[1]
axes.axes.position = array([ 0., 0.])
axes.axes.label_format = '%-#6.2g'
axes.title_text_property.font_size=4
def angle_between_hooktip_mechanism_radial_vectors(mech_mat, hand_mat):
kin_dict = ke.fit(hand_mat, tup)
print 'kin_dict from hook tip:', kin_dict
print 'measured radius:', cd['radius']
center_hand = np.matrix((kin_dict['cx'], kin_dict['cy'],
kin_dict['cz'])).T
kin_dict = ke.fit(mech_mat, tup)
print 'kin_dict from mechanism:', kin_dict
center_mech = np.matrix((kin_dict['cx'], kin_dict['cy'],
kin_dict['cz'])).T
# working with the projected coordinates.
directions_hand = hand_mat - center_hand
directions_hand = directions_hand / ut.norm(directions_hand)
directions_mech = mech_mat - center_mech
directions_mech = directions_mech / ut.norm(directions_mech)
#import pdb; pdb.set_trace()
ang = np.degrees(np.arccos(np.sum(np.multiply(directions_mech, directions_hand), 0))).A1
mpu.plot_yx(ang, label = 'angle between hooktip-radial and mechanism radial')
mpu.legend()
mpu.show()
def plot_eq_pt_motion_tl():
vec_list = []
for i in range(len(ee_tl.p_list)):
# for i in range(5):
curr_pos_tl = np.matrix(ee_tl.p_list[i]).T
eq_pt_tl = np.matrix(eq_tl.p_list[i]).T
pts_ts = np.matrix(ee_ts.p_list[0:i+1]).T
pts_2d_ts = pts_ts[0:2,:]
# rad_opt,cx_ts,cy_ts = at.fit_circle(rad_guess,x_guess,y_guess,pts_2d_ts,
# method='fmin_bfgs',verbose=False)
rad_opt = 1.0
cx_ts,cy_ts = 0.5,-1.3
c_ts = np.matrix([cx_ts,cy_ts,0.]).T
x,y,a = st.x_list[i],st.y_list[i],st.a_list[i]
c_tl = smc.tlTts(c_ts,x,y,a)
cx_tl,cy_tl = c_tl[0,0],c_tl[1,0]
t0 = time.time()
vt,a = smc.segway_motion_repulse(curr_pos_tl,cx_tl,cy_tl,cy_ts,
start_pos_ts,eq_pt_tl,bndry,wrkspc_pts)
t1 = time.time()
# print 'time to segway_motion_repulse:',t1-t0
nrm = np.linalg.norm(vt)
# if nrm > 0.005:
vt = vt/nrm
vec_list.append(vt.A1.tolist())
v = np.matrix(vec_list).T
eq_pts = np.matrix(eq_tl.p_list).T
ee_pts = np.matrix(ee_tl.p_list).T
mpu.plot_yx(eq_pts[1,:].A1,eq_pts[0,:].A1,linewidth=1,color='g',label='eq')
mpu.plot_yx(ee_pts[1,:].A1,ee_pts[0,:].A1,linewidth=1,color='b',label='FK')
mpu.plot_yx(bndry[1,:].A1,bndry[0,:].A1,linewidth=0,color='y')
mpu.plot_quiver_yxv(eq_pts[1,:].A1,eq_pts[0,:].A1,v,scale=30)
mpu.legend()
mpu.show()
def plot_radial_tangential(mech_dict, savefig, fig_name=''):
radial_mech = mech_dict['force_rad_list']
tangential_mech = mech_dict['force_tan_list']
typ = mech_dict['mech_type']
mech_x = mech_dict['mechanism_x']
if typ == 'rotary':
mech_x_degrees = np.degrees(mech_x)
xlabel = 'angle (degrees)'
else:
mech_x_degrees = mech_x
xlabel = 'distance (meters)'
mpu.pl.clf()
mpu.plot_yx(radial_mech, mech_x_degrees, axis=None, label='radial force',
xlabel=xlabel, ylabel='N', color='r')
mpu.plot_yx(tangential_mech, mech_x_degrees, axis=None, label='tangential force',
xlabel=xlabel, ylabel='N', color='g')
mpu.legend()
if typ == 'rotary':
mpu.figure()
rad = mech_dict['radius']
torques_1 = rad * np.array(tangential_mech)
torques_3 = np.array(mech_dict['moment_tip_list']) + torques_1
mpu.plot_yx(torques_1, mech_x_degrees, axis=None,
label='torque from tangential',
xlabel=xlabel, ylabel='moment', color='r')
mpu.plot_yx(torques_3, mech_x_degrees, axis=None,
label='total torque',
xlabel=xlabel, ylabel='moment', color='y')
mpu.legend()
if savefig:
mpu.savefig(opt.dir+'/%s_force_components.png'%fig_name)
else:
mpu.show()
def plot_radii(csv_data, color='#3366FF'):
keys = ['radius', 'type', 'name', 'repetition']
llists = expand(extract_keys(csv_data, keys), keys)
rad_list = np.array([float(r) for r in llists[0]]) / 100.0
types = llists[1]
names = np.array(llists[2])
all_types = set(types)
print 'Radii types', all_types
types_arr = np.array(types)
# np.where(types_arr == 'C')
cabinet_rad_list = rad_list[np.where(types_arr == 'C')[0]]
others_rad_list = rad_list[np.where(types_arr != 'C')[0]]
other_names = names[np.where(types_arr != 'C')[0]]
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
print 'radii other names'
for i, n in enumerate(other_names):
print n, others_rad_list[i]
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
rad_lists = [rad_list, cabinet_rad_list, others_rad_list]
titles = ['Radii of Rotary Mechanisms', 'Radii of Cabinets', 'Radii of Other Mechanisms']
bin_width = 0.05
max_radius = np.max(rad_list)
print 'MIN RADIUS', np.min(rad_list)
print 'MAX RADIUS', max_radius
mpu.set_figure_size(5.,5.)
for idx, radii in enumerate(rad_lists):
f = pb.figure()
f.set_facecolor('w')
bins = np.arange(0.-bin_width/2., max_radius+2*bin_width, bin_width)
hist, bin_edges = np.histogram(radii, bins)
h = mpu.plot_histogram(bin_edges[:-1]+bin_width/2., hist,
width=0.8*bin_width, xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title=titles[idx],
color=color, label='All')
pb.xlim(.1, 1.)
pb.ylim(0, 55)
mpu.legend(display_mode = 'less_space', handlelength=1.)
#-- different classes in different colors in the same histogram.
f = pb.figure()
f.set_facecolor('w')
bins = np.arange(0.-bin_width/2., max_radius+2*bin_width, bin_width)
hist, bin_edges = np.histogram(rad_lists[0], bins)
h = mpu.plot_histogram(bin_edges[:-1]+bin_width/2., hist,
width=0.8*bin_width, xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title=titles[1],
color='g', label='Cabinets')
hist, bin_edges = np.histogram(rad_lists[2], bins)
h = mpu.plot_histogram(bin_edges[:-1]+bin_width/2., hist,
width=0.8*bin_width, xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title='Cabinets and Other Mechanisms',
color='y', label='Other')
pb.xlim(.1, 1.)
pb.ylim(0, 55)
mpu.legend(display_mode = 'less_space', handlelength=1.)
color_list = ['g', 'b', 'r']
marker_list = ['s', '^', 'v']
label_list = ['All', 'Cabinets', 'Other']
scatter_size_list = [8, 5, 5]
mpu.set_figure_size(5.,5.)
mpu.figure()
for idx, radii in enumerate(rad_lists):
bins = np.arange(0.-bin_width/2., max_radius+2*bin_width, bin_width)
hist, bin_edges = np.histogram(radii, bins)
bin_midpoints = np.arange(0., max_radius+bin_width, bin_width)
mpu.plot_yx(hist, bin_midpoints, color = color_list[idx],
alpha = 0.6, marker = marker_list[idx],
scatter_size = scatter_size_list[idx], xlabel='Radius (meters)',
ylabel='\# of mechanisms', label = label_list[idx])
mpu.legend(display_mode = 'less_space')
cd = ut.load_pickle(pkl_name)
cd['hook_checker_number'] = md['checkerboard_number']
cd['radius'] = md['radius']
rad, tan, ang, typ = al.compute_mechanism_properties(cd)
rad, tan_b, ang, typ = al.compute_mechanism_properties(cd,
bias_ft=True)
#------------ plot spring scale and FT data -------------
spring_pkl = glob.glob(opt.dir+'/spring_scale*.pkl')[0]
spring_list = ut.load_pickle(spring_pkl)
mpu.plot_yx(spring_list, label='Spring Scale', color='b', axis=None)
mpu.plot_yx(rad, label='Measured Radial force (unbiased)', color='r',
xlabel='Reading number', ylabel='Force (N)', axis=None)
mpu.plot_yx(tan, label='Measured Tangential force (unbiased)', color='g',
xlabel='Reading number', ylabel='Force (N)', axis=None)
mpu.plot_yx(tan_b, label='Measured Tangential force (biased)', color='y',
xlabel='Reading number', ylabel='Force (N)',
axis=None, plot_title=opt.dir)
mpu.legend()
mpu.savefig(opt.dir.split('/')[0]+'.png')
mpu.show()
def plot_radii(csv_data, color='#3366FF'):
keys = ['radius', 'type', 'name', 'repetition']
llists = expand(extract_keys(csv_data, keys), keys)
rad_list = np.array([float(r) for r in llists[0]]) / 100.0
types = llists[1]
names = np.array(llists[2])
all_types = set(types)
print 'Radii types', all_types
types_arr = np.array(types)
# np.where(types_arr == 'C')
cabinet_rad_list = rad_list[np.where(types_arr == 'C')[0]]
others_rad_list = rad_list[np.where(types_arr != 'C')[0]]
other_names = names[np.where(types_arr != 'C')[0]]
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
print 'radii other names'
for i, n in enumerate(other_names):
print n, others_rad_list[i]
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
rad_lists = [rad_list, cabinet_rad_list, others_rad_list]
titles = [
'Radii of Rotary Mechanisms', 'Radii of Cabinets',
'Radii of Other Mechanisms'
]
bin_width = 0.05
max_radius = np.max(rad_list)
print 'MIN RADIUS', np.min(rad_list)
print 'MAX RADIUS', max_radius
mpu.set_figure_size(5., 5.)
for idx, radii in enumerate(rad_lists):
f = pb.figure()
f.set_facecolor('w')
bins = np.arange(0. - bin_width / 2., max_radius + 2 * bin_width,
bin_width)
hist, bin_edges = np.histogram(radii, bins)
h = mpu.plot_histogram(bin_edges[:-1] + bin_width / 2.,
hist,
width=0.8 * bin_width,
xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title=titles[idx],
color=color,
label='All')
pb.xlim(.1, 1.)
pb.ylim(0, 55)
mpu.legend(display_mode='less_space', handlelength=1.)
#-- different classes in different colors in the same histogram.
f = pb.figure()
f.set_facecolor('w')
bins = np.arange(0. - bin_width / 2., max_radius + 2 * bin_width,
bin_width)
hist, bin_edges = np.histogram(rad_lists[0], bins)
h = mpu.plot_histogram(bin_edges[:-1] + bin_width / 2.,
hist,
width=0.8 * bin_width,
xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title=titles[1],
color='g',
label='Cabinets')
hist, bin_edges = np.histogram(rad_lists[2], bins)
h = mpu.plot_histogram(bin_edges[:-1] + bin_width / 2.,
hist,
width=0.8 * bin_width,
xlabel='Radius (meters)',
ylabel='\# of mechanisms',
plot_title='Cabinets and Other Mechanisms',
color='y',
label='Other')
pb.xlim(.1, 1.)
pb.ylim(0, 55)
mpu.legend(display_mode='less_space', handlelength=1.)
color_list = ['g', 'b', 'r']
marker_list = ['s', '^', 'v']
label_list = ['All', 'Cabinets', 'Other']
scatter_size_list = [8, 5, 5]
mpu.set_figure_size(5., 5.)
mpu.figure()
for idx, radii in enumerate(rad_lists):
bins = np.arange(0. - bin_width / 2., max_radius + 2 * bin_width,
bin_width)
hist, bin_edges = np.histogram(radii, bins)
bin_midpoints = np.arange(0., max_radius + bin_width, bin_width)
mpu.plot_yx(hist,
bin_midpoints,
color=color_list[idx],
alpha=0.6,
marker=marker_list[idx],
scatter_size=scatter_size_list[idx],
xlabel='Radius (meters)',
ylabel='\# of mechanisms',
label=label_list[idx])
mpu.legend(display_mode='less_space')
def split_forces_hooktip_test(hand_mat):
kin_dict = ke.fit(hand_mat, tup)
center_hand = np.matrix((kin_dict['cx'], kin_dict['cy'],
kin_dict['cz'])).T
print 'kin_dict:', kin_dict
# radial vectors.
radial_mat = hand_mat - center_hand
radial_mat = radial_mat / ut.norm(radial_mat)
# cannot use hook tip to compute mechanism angle because I
# don't have a way of knowing when the hook starts opening the
# mechanism. (Think hook makes contact with door, moves in
# freespace and then makes contact with the handle.)
#start_rad = radial_mat[:,0]
#ct = (start_rad.T * radial_mat).A1
#st = ut.norm(np.matrix(np.cross(start_rad.A1, radial_mat.T.A)).T).A1
#mech_angle_l = np.arctan2(st, ct).tolist()
_, nrm_hand = project_points_plane(hand_mat)
print 'nrm_hand:', nrm_hand.A1
f_cam_l = []
m_cam_l = []
m_base_l = []
frad_l = []
ftan_l = []
hook_num = cd['hook_checker_number']
print 'hook_num:', hook_num
for i, f in enumerate(force_mat.T):
f = f.T
m = moment_mat[:,i]
f_cam, m_cam, m_base = ft_to_camera_3(f, m, hook_rot_l[i], hook_num,
return_moment_cam = True)
f_cam_l.append(f_cam)
m_cam_l.append(abs((m_cam.T*nrm_hand)[0,0]))
m_base_l.append(abs((m_base.T*nrm_hand)[0,0]))
#m_base_l.append(np.linalg.norm(f))
tangential_vec = np.matrix(np.cross(radial_mat[:,i].A1, nrm_hand.A1)).T
ftan = (f_cam.T * tangential_vec)[0,0]
ftan_l.append(ftan)
#frad = np.linalg.norm(f_cam - tangential_vec * ftan)
frad = (f_cam.T*radial_mat[:,i])[0,0]
frad_l.append(abs(frad))
fig1 = mpu.figure()
mech_ang_deg = np.degrees(mech_angle_l)
mpu.plot_yx(ftan_l, mech_ang_deg, label='Tangential Force (hook tip)', color='b')
mpu.plot_yx(frad_l, mech_ang_deg, label='Radial Force (hook tip)', color='y')
mech_pkl_name = glob.glob(opt.dir + '/open_mechanism_trajectories_*.pkl')[0]
md = ut.load_pickle(mech_pkl_name)
radial_mech = md['force_rad_list']
tangential_mech = md['force_tan_list']
mech_x = np.degrees(md['mechanism_x'])
mpu.plot_yx(tangential_mech, mech_x, label='Tangential Force (mechanism checker)', color='g')
mpu.plot_yx(radial_mech, mech_x, label='Radial Force (mechanism checker)', color='r')
mpu.legend()
fig2 = mpu.figure()
mpu.plot_yx(m_cam_l, mech_ang_deg, label='\huge{$m_{axis}$}')
mpu.plot_yx(m_base_l, mech_ang_deg, label='\huge{$m^s$}',
color = 'r')
mpu.legend()
mpu.show()
# ma4 = compute_mech_angle_1(cd, min_evec)
lab1 = 'orientation only'
lab2 = 'checker origin position + circle fit'
lab3 = 'checker origin position + PCA projection + circle fit'
# lab4 = 'PCA projection + orientation'
mpu.figure()
mpu.plot_yx(np.degrees(ma3), color='r', label=lab3,
linewidth = 1, scatter_size = 5)
mpu.plot_yx(np.degrees(ma2), color='b', label=lab2,
linewidth = 1, scatter_size = 5)
mpu.plot_yx(np.degrees(ma1), color='y', label=lab1,
linewidth = 1, scatter_size = 5)
mpu.legend()
vel3 = ma.compute_velocity(ma3, cd['time_list'], 1)
vel2 = ma.compute_velocity(ma2, cd['time_list'], 1)
vel1 = ma.compute_velocity(ma1, cd['time_list'], 1)
mpu.figure()
mpu.plot_yx(np.degrees(vel3), np.degrees(ma3), color='r',
label=lab3, linewidth = 1, scatter_size = 5)
mpu.plot_yx(np.degrees(vel2), np.degrees(ma2), color='b',
label=lab2, linewidth = 1, scatter_size = 5)
mpu.plot_yx(np.degrees(vel1), np.degrees(ma1), color='y',
label=lab1, linewidth = 1, scatter_size = 5)
mpu.legend()
# acc3 = ma.compute_velocity(vel3, cd['time_list'], 1)
# mpu.figure()
