def calc_final_error(dt):
tStartTracker = tracker_times.min() - owl_times.min() - dt
if args.item == "cloth":
used_leds = [i for pair in led_pairs for i in pair]
led2ind = {}
for (ind, led) in enumerate(used_leds):
led2ind[led] = ind
ind_pairs = [(led2ind[led0], led2ind[led1])
for (led0, led1) in led_pairs]
marker2info = ev.calculate_cloth_tracking_score1(
tracker_arr, tracker_times - tStartTracker, tracker_triangles,
owl_arr[:, used_leds, :], owl_times, ind_pairs)
elif args.item == "rope":
used_leds = rope_leds
marker2info = ev.calculate_rope_tracking_score(
tracker_arr, tracker_times - tStartTracker,
owl_arr[:, used_leds, :], owl_times, used_leds)
errors = []
for info in marker2info:
err_q = ev.norms(info["position_relative"], 1)
errors.extend(err_q.tolist())
final_error = np.median(errors)
print dt, final_error
return final_error
def calc_final_error(dt):
tStartTracker = tracker_times.min() - owl_times.min() - dt
if args.item == "cloth":
used_leds = [i for pair in led_pairs for i in pair]
led2ind = {}
for (ind,led) in enumerate(used_leds):
led2ind[led] = ind
ind_pairs = [(led2ind[led0], led2ind[led1]) for (led0, led1) in led_pairs]
marker2info = ev.calculate_cloth_tracking_score1(tracker_arr, tracker_times-tStartTracker, tracker_triangles, owl_arr[:,used_leds,:], owl_times, ind_pairs)
elif args.item == "rope":
used_leds = rope_leds
marker2info = ev.calculate_rope_tracking_score(tracker_arr, tracker_times-tStartTracker, owl_arr[:,used_leds,:], owl_times, used_leds)
errors = []
for info in marker2info:
err_q = ev.norms(info["position_relative"],1)
errors.extend(err_q.tolist())
final_error = np.median(errors)
print dt, final_error
return final_error
marker2info = ev.calculate_cloth_tracking_score1(tracker_arr,
tracker_times,
tracker_triangles,
owl_arr[:, used_leds, :],
owl_times, ind_pairs)
elif args.item == "rope":
used_leds = rope_leds
marker2info = ev.calculate_rope_tracking_score(tracker_arr, tracker_times,
owl_arr[:, used_leds, :],
owl_times, used_leds)
if 1:
errors = []
median_errors = []
for info in marker2info:
err_q = ev.norms(info["position_relative"], 1)
errors.extend(err_q.tolist())
median_errors.append(np.median(err_q))
import scipy.stats as ss
per_errors = []
for per in xrange(0, 101, 10):
per_errors.append(ss.scoreatpercentile(errors, per))
print per, ss.scoreatpercentile(errors, per)
np.savetxt(osp.join(osp.dirname(args.bagfile), "per_errors.txt"),
per_errors)
#err_q = err_q3[:,0]
#plt.plot(info["times"], err_q,'.')
plt.xlabel('seconds')
tracker_times,
tracker_triangles,
owl_arr[:, used_leds, :],
owl_times,
ind_pairs,
demean_at_beginning=False)
elif args.item == "rope":
used_leds = rope_leds
marker2info = ev.calculate_rope_tracking_score(tracker_arr, tracker_times,
owl_arr[:, used_leds, :],
owl_times, used_leds)
if 1:
median_errors = []
for info in marker2info:
err_q = ev.norms(info["position_demeaned"], 1)
median_errors.append(np.median(err_q))
#err_q = err_q3[:,0]
plt.plot(info["times"], err_q, '.')
plt.xlabel('seconds')
plt.ylabel('error (m)')
plt.legend([str(led) for led in used_leds])
print "median erros", median_errors
print "median median error:", np.median(median_errors)
if 1:
import mayavi.mlab as mlab
mlab.figure(1)
mlab.clf()
print "nodes"
if args.item == "cloth":
used_leds = [i for pair in led_pairs for i in pair]
led2ind = {}
for (ind,led) in enumerate(used_leds):
led2ind[led] = ind
ind_pairs = [(led2ind[led0], led2ind[led1]) for (led0, led1) in led_pairs]
marker2info = ev.calculate_cloth_tracking_score1(tracker_arr, tracker_times, tracker_triangles, owl_arr[:,used_leds,:], owl_times, ind_pairs)
elif args.item == "rope":
used_leds = rope_leds
marker2info = ev.calculate_rope_tracking_score(tracker_arr, tracker_times, owl_arr[:,used_leds,:], owl_times, used_leds)
if 1:
errors = []
median_errors = []
for info in marker2info:
err_q = ev.norms(info["position_relative"],1)
errors.extend(err_q.tolist())
median_errors.append(np.median(err_q))
import scipy.stats as ss
per_errors = []
for per in xrange(0,101,10):
per_errors.append(ss.scoreatpercentile(errors, per))
print per, ss.scoreatpercentile(errors, per)
np.savetxt(osp.join(osp.dirname(args.bagfile),"per_errors.txt"), per_errors)
#err_q = err_q3[:,0]
#plt.plot(info["times"], err_q,'.')
