def plot_overall_odometry_errors(odo_err_col, algorithm_names, rel_e_distances,
plot_settings, output_dir):
for et in odo_err_col:
if et == 'rel_trans_perc':
ylabel = 'Translation error (\%)'
elif et == 'rel_rot_deg_per_m':
ylabel = 'Rotation error (deg / m)'
else:
assert False
cur_err = odo_err_col[et]
assert sorted(algorithm_names) == sorted(list(cur_err.keys()))
colors = []
labels = []
for alg in algorithm_names:
colors.append(plot_settings['algo_colors'][alg])
labels.append(plot_settings['algo_labels'][alg])
distances = sorted(rel_e_distances)
errors = []
for alg in algorithm_names:
errors.append([cur_err[alg][d] for d in distances])
fig = plt.figure(figsize=(12, 3))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel=ylabel)
pu.boxplot_compare(ax, distances, errors, labels, colors, legend=True)
fig.tight_layout()
fig.savefig(output_dir + '/' + 'overall_{}'.format(et) + FORMAT,
bbox_inches="tight",
dpi=args.dpi)
plt.close(fig)
def _boxplotOrientDiffs(orient_diffs, names, nm_to_label, top_save_dir):
xlabels = kMetricsLabels
data_labels = [nm_to_label[v] for v in names]
colors = [kPallete[i] for i, v in enumerate(names)]
data = []
for nm in names:
data_i = []
for m in kMetrics:
data_i.append(orient_diffs[nm][m])
data.append(data_i)
fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(111)
pu.boxplot_compare(ax, xlabels, data, data_labels, colors)
ax.set_ylabel("Orientation diff. (deg)")
plt.tight_layout()
fig.savefig(os.path.join(top_save_dir, 'orient_diffs_boxplot.png'),
bbox_inches='tight')
def plot_odometry_error_per_dataset(dataset_rel_err, dataset_names,
algorithm_names, datasets_outdir,
plot_settings):
for dataset_idx, dataset_nm in enumerate(dataset_names):
output_dir = datasets_outdir[dataset_nm]
print("Plotting {0}...".format(dataset_nm))
rel_err = dataset_rel_err[dataset_idx]
assert sorted(algorithm_names) == sorted(
list(rel_err['trans_err'].keys()))
distances = rel_err['subtraj_len']
config_labels = []
config_colors = []
for v in algorithm_names:
config_labels.append(plot_settings['algo_labels'][v])
config_colors.append(plot_settings['algo_colors'][v])
fig = plt.figure(figsize=(12, 3))
ax = fig.add_subplot(121,
xlabel='Distance traveled (m)',
ylabel='Translation error (\%)')
pu.boxplot_compare(
ax,
distances, [rel_err['trans_err_perc'][v] for v in algorithm_names],
config_labels,
config_colors,
legend=False)
ax = fig.add_subplot(122,
xlabel='Distance traveled (m)',
ylabel='Rotation error (deg / m)')
pu.boxplot_compare(
ax,
distances, [rel_err['rot_deg_per_m'][v] for v in algorithm_names],
config_labels,
config_colors,
legend=True)
fig.tight_layout()
fig.savefig(output_dir + '/' + dataset_nm + '_trans_rot_error' +
FORMAT,
bbox_inches="tight",
dpi=args.dpi)
plt.close(fig)
def _boxplotFIMDiffs(nm_to_fim_diff_perc, names, nm_to_label, top_save_dir):
xlabels = [nm_to_label[v] for v in names]
data_labels = ['FIM Diff']
colors = [kPallete[0]]
data = []
for nm in names:
data.append(nm_to_fim_diff_perc[nm])
fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(111)
pu.boxplot_compare(ax, xlabels, [data], data_labels, colors, legend=False)
ax.set_ylabel("FIM diff. (\%)")
plt.setp(ax.get_xticklabels(),
rotation=45,
ha="right",
rotation_mode="anchor")
plt.tight_layout()
fig.savefig(os.path.join(top_save_dir, 'fim_diffs_boxplot.png'),
bbox_inches='tight')
def plot_rel_traj_error(self, FORMAT='.png'):
print(">>> Plotting relative (odometry) error...")
distances = self.preset_boxplot_distances
rel_trans_err = [[self.rel_errors[d]['rel_trans'] for d in distances]]
rel_trans_err_perc = [[self.rel_errors[d]['rel_trans_perc']
for d in distances]]
rel_yaw_err = [[self.rel_errors[d]['rel_yaw'] for d in distances]]
labels = ['Estimate']
colors = ['k', 'b']
# plot relative translation error (in meters)
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111, xlabel='Distance traveled [m]', ylabel='Translation error [m]')
pu.boxplot_compare(ax, distances, rel_trans_err, labels, colors)
fig.tight_layout()
fig.savefig(self.plots_dir + '/rel_translation_error' + FORMAT, bbox_inches="tight")
plt.close(fig)
# plot relative translation error (in %)
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot( 111, xlabel='Distance traveled [m]',ylabel='Translation error [\%]')
pu.boxplot_compare(ax, distances, rel_trans_err_perc, labels, colors)
fig.tight_layout()
fig.savefig(self.plots_dir + '/rel_translation_error_perc' + FORMAT,
bbox_inches="tight")
plt.close(fig)
# plot relative rotation error (in degrees)
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111, xlabel='Distance traveled [m]', ylabel='Yaw error [deg]')
pu.boxplot_compare(ax, distances, rel_yaw_err, labels, colors)
fig.tight_layout()
fig.savefig(self.plots_dir + '/rel_yaw_error' + FORMAT, bbox_inches="tight")
plt.close(fig)
def plot_rmse_per_dataset(algorithm_rmse, dataset_names, algorithm_names,
output_dir, plot_settings):
config_labels = []
config_colors = []
assert sorted(algorithm_names) == sorted(
list(algorithm_rmse['trans_err'].keys()))
for v in algorithm_names:
config_labels.append(plot_settings['algo_labels'][v])
config_colors.append(plot_settings['algo_colors'][v])
assert len(datasets_labels) == len(datasets)
labels = [plot_settings['datasets_labels'][v] for v in dataset_names]
# check
n_data = len(datasets)
for v in algorithm_names:
assert len(algorithm_rmse['trans_err'][v]) == n_data
assert len(algorithm_rmse['rot_err'][v]) == n_data
fig = plt.figure(figsize=(6, 3))
ax = fig.add_subplot(111, xlabel='Datasets', ylabel='Translation RMSE (m)')
pu.boxplot_compare(
ax, labels, [algorithm_rmse['trans_err'][v] for v in algorithm_names],
config_labels, config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/' + 'all_translation_rmse' + FORMAT,
bbox_inches="tight",
dpi=args.dpi)
plt.close(fig)
fig = plt.figure(figsize=(6, 3))
ax = fig.add_subplot(111, xlabel='Datasets', ylabel='Rotation RMSE (deg)')
pu.boxplot_compare(ax, labels,
[algorithm_rmse['rot_err'][v] for v in algorithm_names],
config_labels, config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/' + 'all_rotation_rmse' + FORMAT,
bbox_inches="tight",
dpi=args.dpi)
plt.close(fig)
def plot_overall_odometry_errors(overall_err, output_dir):
print("Plotting overall error...")
n_config = len(overall_err['trans_err'])
assert n_config == len(overall_err['trans_err_perc'])
assert n_config == len(overall_err['yaw_err'])
config_labels = []
config_colors = []
for v in overall_err['trans_err'].keys():
config_labels.append(PLOT_LABELS[v])
config_colors.append(COLORS[v])
# absolute error
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [m]')
pu.boxplot_compare(ax,
overall_err['distances'],
overall_err['trans_err'].values(),
config_labels,
config_colors,
ymax=0.15)
fig.tight_layout()
fig.savefig(output_dir + '/overall_rel_translation_error' + FORMAT,
bbox_inches="tight")
plt.close(fig)
# relative error
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [\%]')
pu.boxplot_compare(ax, overall_err['distances'],
overall_err['trans_err_perc'].values(), config_labels,
config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/overall_rel_translation_error_percentage' +
FORMAT,
bbox_inches="tight")
plt.close(fig)
# yaw orientation error
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Yaw error [deg]')
pu.boxplot_compare(ax, overall_err['distances'],
overall_err['yaw_err'].values(), config_labels,
config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/overall_rel_yaw_error' + FORMAT,
bbox_inches="tight")
plt.close(fig)
def plot_odometry_error_per_dataset(dataset_rel_err, dataset_names, out_dir):
for dataset_idx, dataset_nm in enumerate(dataset_names):
print("Plotting {0}...".format(dataset_nm))
rel_err = dataset_rel_err[dataset_idx]
distances = rel_err['subtraj_len']
config_labels = []
config_colors = []
for v in rel_err['trans_err'].keys():
config_labels.append(PLOT_LABELS[v])
config_colors.append(COLORS[v])
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [m]')
pu.boxplot_compare(ax,
distances,
rel_err['trans_err'].values(),
config_labels,
config_colors,
ymax=0.15)
fig.tight_layout()
fig.savefig(output_dir + '/' + dataset_nm + '_translation_error' +
FORMAT,
bbox_inches="tight")
plt.close(fig)
# relative error
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [\%]')
pu.boxplot_compare(ax, distances, rel_err['trans_err_perc'].values(),
config_labels, config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/' + dataset_nm +
'_translation_error_percentage' + FORMAT,
bbox_inches="tight")
plt.close(fig)
# yaw orientation error
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Yaw error [deg]')
pu.boxplot_compare(ax, distances, rel_err['ang_yaw_err'].values(),
config_labels, config_colors)
fig.tight_layout()
fig.savefig(output_dir + '/' + dataset_nm + '_yaw_error' + FORMAT,
bbox_inches="tight")
plt.close(fig)
print(">>> Plotting relative (odometry) error...")
distances = traj.preset_boxplot_distances
rel_trans_err = [[traj.rel_errors[d]['rel_trans'] for d in distances]]
rel_trans_err_perc = [[
traj.rel_errors[d]['rel_trans_perc'] for d in distances
]]
rel_yaw_err = [[traj.rel_errors[d]['rel_yaw'] for d in distances]]
labels = ['Estimate']
colors = ['b']
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [m]')
pu.boxplot_compare(ax, distances, rel_trans_err, labels, colors)
fig.tight_layout()
fig.savefig(plots_dir + '/rel_translation_error' + FORMAT,
bbox_inches="tight")
plt.close(fig)
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [\%]')
pu.boxplot_compare(ax, distances, rel_trans_err_perc, labels, colors)
fig.tight_layout()
fig.savefig(plots_dir + '/rel_translation_error_perc' + FORMAT,
bbox_inches="tight")
plt.close(fig)
suffix = ''
if n_trials > 1:
suffix = '_mt'
plot_types = ['rel_trans', 'rel_trans_perc', 'rel_yaw']
rel_errors, distances = mt_error.get_relative_errors_and_distances(
error_types=plot_types)
labels = ['Estimate']
colors = ['b']
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [m]')
pu.boxplot_compare(ax, distances, rel_errors['rel_trans'], labels,
colors)
fig.tight_layout()
fig.savefig(plot_dir_i + '/rel_translation_error' + suffix + FORMAT,
bbox_inches="tight")
plt.close(fig)
fig = plt.figure(figsize=(6, 2.5))
ax = fig.add_subplot(111,
xlabel='Distance traveled [m]',
ylabel='Translation error [\%]')
pu.boxplot_compare(ax, distances, rel_errors['rel_trans_perc'], labels,
colors)
fig.tight_layout()
fig.savefig(plot_dir_i + '/rel_translation_error_perc' + suffix +
FORMAT,
bbox_inches="tight")
