def plot_pos_data(self, title: str, y_label: str, kine_var: str, fig_num: int, add_sd: bool = True,
clip_graph: bool = False) -> matplotlib.figure.Figure:
"""Plot overlayed raw, filled, and smoothed marker position data."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 1, sharex=True)
lines_filled = marker_graph_init(ax, self.filled.means.pos, y_label, x_data=self.frames, color='red')
lines_raw = marker_graph_add(ax, self.raw.means.pos, self.frames, color='indigo', marker='.')
lines_smoothed = marker_graph_add(ax, getattr(self.smoothed.means, kine_var), self.filtered_frames,
color='limegreen', lw=1)
if add_sd:
marker_graph_add_cov(ax, self.smoothed.means.pos, self.smoothed.covars.pos, self.filtered_frames,
'limegreen')
if clip_graph:
for c_ax in ax:
c_ax.set_xlim(self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
else:
add_vicon_start_stop(ax, self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
plt.tight_layout(pad=1.0, w_pad=1.0, h_pad=0)
fig.suptitle(title, x=0.25, fontsize=11, fontweight='bold')
plt.subplots_adjust(top=0.94)
fig.legend((lines_raw[0], lines_filled[0], lines_smoothed[0]), ('Raw', 'Filled', 'Smoothed'), 'upper right',
labelspacing=0.1, ncol=3, columnspacing=0.3)
make_interactive()
return fig
def plot_marker_data_diff_hist(self, title: str, x_label: str, fig_num: int, clip_graph: bool = True) \
-> matplotlib.figure.Figure:
"""Plot histogram of smoothed marker positions - raw marker positions."""
if clip_graph:
endpts = np.zeros((2,), dtype=np.int)
if self.vicon_endpts[0] > self.filtered.endpts[0]:
endpts[0] = self.vicon_endpts[0] - self.filtered.endpts[0]
if self.vicon_endpts[1] < self.filtered.endpts[1]:
endpts[1] = self.vicon_endpts[1] - self.filtered.endpts[0]
else:
endpts[1] = self.filtered.endpts[1] - self.filtered.endpts[0]
smoothed_diff = self.smoothed_pos_diff[endpts[0]:endpts[1]]
else:
smoothed_diff = self.smoothed_pos_diff
fig = plt.figure(num=fig_num)
ax = fig.subplots(1, 3, sharey=True)
lines_smoothed = marker_diff_his_init(ax, smoothed_diff, x_label, 'limegreen')
fig.legend([lines_smoothed[0]], ['Smoothed'], 'upper right', labelspacing=0.1)
marker_graph_title(fig, title)
make_interactive()
return fig
def plot_marker_data(self, title: str, y_label: str, kine_var: str, fig_num: int, add_sd: bool = True,
clip_graph: bool = False, marker: str = '') -> matplotlib.figure.Figure:
"""Plot raw, filtered, and smoothed kinematic (position, velocity, acceleration) marker data, allowing the
addition of confidence bounds."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 1, sharex=True)
lines_raw = marker_graph_init(ax, getattr(self.raw.means, kine_var), y_label, x_data=self.frames,
color='indigo', marker=marker)
lines_filtered = marker_graph_add(ax, getattr(self.filtered.means, kine_var), self.filtered_frames, color='red')
lines_smoothed = marker_graph_add(ax, getattr(self.smoothed.means, kine_var), self.filtered_frames,
color='limegreen')
if add_sd:
marker_graph_add_cov(ax, getattr(self.filtered.means, kine_var), getattr(self.filtered.covars, kine_var),
self.filtered_frames, 'red')
marker_graph_add_cov(ax, getattr(self.smoothed.means, kine_var), getattr(self.smoothed.covars, kine_var),
self.filtered_frames, 'limegreen')
if clip_graph:
for c_ax in ax:
c_ax.set_xlim(self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
else:
add_vicon_start_stop(ax, self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
fig.legend((lines_raw[0], lines_filtered[0], lines_smoothed[0]), ('Raw', 'Filtered', 'Smoothed'), 'upper right',
labelspacing=0.1)
marker_graph_title(fig, title)
make_interactive()
return fig
def plot_biplane_vicon(self, title: str, fig_num: int, vicon_field: str, vicon_type: str) \
-> matplotlib.figure.Figure:
"""Plot overlayed marker position data as measured via Vicon and biplane fluoroscopy."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 1, sharex=True)
lines_vicon = marker_graph_init(ax,
getattr(self, vicon_field),
'Distance (mm)',
self.vicon_frames,
color='limegreen',
marker='.',
lw=1,
ms=2)
lines_biplane = marker_graph_add(ax,
self.biplane_data,
self.vicon_frames,
color='indigo',
marker='.')
fig.legend((lines_biplane[0], lines_vicon[0]),
('Biplane', vicon_type + ' Vicon'),
'upper right',
ncol=3,
columnspacing=0.3,
handlelength=1.0)
marker_graph_title(fig, title)
make_interactive()
return fig
def plot(self) -> List[matplotlib.figure.Figure]:
"""Plot marker_data onto 3 row subplots on Figure 0."""
fig = plt.figure(num=0)
ax = fig.subplots(3, 1, sharex=True)
marker_graph_init(ax, self.marker_pos_labeled, 'Pos (mm)', x_data=self.frame_nums, color='blue')
add_vicon_start_stop(ax, self.vicon_endpts[0] + 1, self.vicon_endpts[1])
marker_graph_title(fig, self.trial_name + ' ' + self.marker_name)
make_interactive()
return [fig]
def plot_marker_data_diff(self, title: str, y_label: str, fig_num: int) -> matplotlib.figure.Figure:
"""Plot smoothed marker positions - raw marker positions."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 1, sharex=True)
lines_smoothed = marker_graph_init(ax, self.smoothed_pos_diff, y_label, x_data=self.filtered_frames,
color='limegreen')
fig.legend([lines_smoothed[0]], ['Smoothed'], 'upper right', labelspacing=0.1)
add_vicon_start_stop(ax, self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
marker_graph_title(fig, title)
make_interactive()
return fig
def plot_marker_data_smooth(self, title: str, y_label: str, kine_var: str, fig_num: int) \
-> matplotlib.figure.Figure:
"""Plot smoothed kinematic (position, velocity, acceleration) marker data."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 1, sharex=True)
lines_smoothed = marker_graph_init(ax, getattr(self.smoothed.means, kine_var), y_label,
x_data=self.filtered_frames, color='limegreen')
fig.legend([lines_smoothed[0]], ['Smoothed'], 'upper right', labelspacing=0.1)
add_vicon_start_stop(ax, self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
marker_graph_title(fig, title)
make_interactive()
return fig
def plot_cov(self, title: str, y_labels: Sequence[str], fig_num: int) -> matplotlib.figure.Figure:
"""Plot overlayed variance of filtered and smoothed kinematic variables (position, velocity, acceleration) in
separate rows with 3 columns for each spatial dimension (3x3). """
fig = plt.figure(num=fig_num)
ax = fig.subplots(3, 3, sharex='all', sharey='row')
lines_filtered = cov_trend_graph_init(ax, self.filtered.covars, self.filtered_frames, y_labels, np.sqrt,
color='red')
lines_smooth = cov_trend_graph_add(ax, self.smoothed.covars, self.filtered_frames, np.sqrt, color='limegreen')
fig.legend((lines_filtered[0][0], lines_smooth[0][0]), ('Filtered', 'Smoothed'), 'upper right',
labelspacing=0.1, ncol=2)
add_vicon_start_stop(ax, self.vicon_frame_endpts[0], self.vicon_frame_endpts[1])
marker_graph_title(fig, title)
make_interactive()
return fig
def plot_all_diff(self, title: str,
fig_num: int) -> matplotlib.figure.Figure:
"""Overlay plot differences in marker position as measured via Vicon and biplane fluoroscopy, and differences
in marker position as measured Vicon (then smoothed) and biplane fluoroscopy."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(2,
1,
sharex=True,
gridspec_kw={'height_ratios': [2, 1]})
lines_xyz_raw = marker_diff_graph(ax[0],
self._diff_raw,
'Distance (mm)',
x_label=None,
x_data=self.vicon_frames,
ls='--')
line_scalar_raw = marker_diff_graph(ax[1],
self._diff_raw_scalar,
'Distance (mm)',
'Frame Number',
self.vicon_frames,
color='indigo',
ls=':')
# reset colors
ax[0].set_prop_cycle(None)
lines_xyz_smooth = marker_diff_graph(ax[0],
self._diff_smoothed,
'Distance (mm)',
x_label=None,
x_data=self.vicon_frames)
line_scalar_smooth = marker_diff_graph(ax[1],
self._diff_smoothed_scalar,
'Distance (mm)',
'Frame Number',
self.vicon_frames,
color='indigo')
leg1 = fig.legend(lines_xyz_raw + line_scalar_raw,
('X (Raw)', 'Y', 'Z', '$\\mid \\mid$'),
loc='lower left',
handletextpad=0.1,
ncol=4,
columnspacing=0.5,
handlelength=1.0,
bbox_to_anchor=(0.0, 0.0))
fig.legend(lines_xyz_smooth + line_scalar_smooth,
('X (Smooth)', 'Y', 'Z', '$\\mid \\mid$'),
loc='lower right',
handletextpad=0.1,
ncol=4,
columnspacing=0.5,
handlelength=1.0,
bbox_to_anchor=(1.0, 0.0))
fig.add_artist(leg1)
fig.suptitle(title, fontsize=11, fontweight='bold')
plt.tight_layout(pad=1.0, h_pad=0, rect=(0, 0.015, 1, 1))
# add RMS, MAE, Max
raw_text = 'RMS: {:.2f} MAE: {:.2f} Max: {:.2f}'\
.format(self.biplane_vicon_diff.raw_rms_scalar, self.biplane_vicon_diff.raw_mae_scalar,
self.biplane_vicon_diff.raw_max_scalar)
smooth_text = 'RMS: {:.2f} MAE: {:.2f} Max: {:.2f}'\
.format(self.biplane_vicon_diff.smoothed_rms_scalar, self.biplane_vicon_diff.smoothed_mae_scalar,
self.biplane_vicon_diff.smoothed_max_scalar)
ax[0].text(0.01,
0.99,
raw_text,
ha='left',
va='top',
transform=fig.transFigure,
fontweight='bold',
bbox=dict(ec='indigo',
fc='None',
boxstyle='round',
ls=':',
lw=2))
ax[0].text(0.99,
0.99,
smooth_text,
ha='right',
va='top',
transform=fig.transFigure,
fontweight='bold',
bbox=dict(ec='indigo', fc='None', boxstyle='round', lw=2))
make_interactive()
return fig
def plot_diff(self, title: str, fig_num: int, vicon_fields: Sequence[str], diff_field: str) \
-> matplotlib.figure.Figure:
"""Plot difference between marker position data as measured via Vicon and biplane fluoroscopy."""
fig = plt.figure(num=fig_num)
ax = fig.subplots(2,
1,
sharex=True,
gridspec_kw={'height_ratios': [2, 1]})
lines_xyz = marker_diff_graph(ax[0],
getattr(self, vicon_fields[0]),
'Distance (mm)',
x_label=None,
x_data=self.vicon_frames)
line_scalar = marker_diff_graph(ax[1],
getattr(self, vicon_fields[1]),
'Distance (mm)',
None,
self.vicon_frames,
color='indigo')
fig.legend(lines_xyz + line_scalar, ('X', 'Y', 'Z', '| |'),
loc='lower center',
ncol=4,
columnspacing=0.3,
handlelength=1.0)
fig.suptitle(title, fontsize=11, fontweight='bold')
plt.tight_layout(pad=1.0, h_pad=0, rect=(0, 0.015, 1, 1))
# add RMS, MAE, Max for each individual x, y, z
text_align = [(0.01, 0.99, 'left', 'top'),
(0.99, 0.99, 'right', 'top'),
(0.01, 0.01, 'left', 'bottom')]
cc = plt.rcParams['axes.prop_cycle'].by_key()['color']
for n in range(3):
xyz_text = 'RMS: {:.2f} MAE: {:.2f} Max: {:.2f}'\
.format(getattr(self.biplane_vicon_diff, diff_field + '_rms')[n],
getattr(self.biplane_vicon_diff, diff_field + '_mae')[n],
getattr(self.biplane_vicon_diff, diff_field + '_max')[n])
ax[0].text(text_align[n][0],
text_align[n][1],
xyz_text,
ha=text_align[n][2],
va=text_align[n][3],
transform=fig.transFigure,
fontweight='bold',
bbox=dict(ec=cc[n], fc='None', boxstyle='round', lw=2))
# add RMS, MAE, Max for scalar
scalar_text = 'RMS: {:.2f} MAE: {:.2f} Max: {:.2f}'\
.format(getattr(self.biplane_vicon_diff, diff_field + '_rms_scalar'),
getattr(self.biplane_vicon_diff, diff_field + '_mae_scalar'),
getattr(self.biplane_vicon_diff, diff_field + '_max_scalar'))
ax[0].text(0.99,
0.01,
scalar_text,
ha='right',
va='bottom',
transform=fig.transFigure,
fontweight='bold',
bbox=dict(ec='indigo', fc='None', boxstyle='round', lw=2))
make_interactive()
return fig
tracking_markers = np.stack([
trial.filled[marker] for marker in StaticTorsoSegment.TRACKING_MARKERS
], 0)
torso_vicon = compute_trajectory(
trial.subject.torso.static_markers_intrinsic, tracking_markers)
torso_fluoro = change_cs(trial.subject.f_t_v, torso_vicon)
torso_truncated = torso_fluoro[trial.vicon_endpts[0]:trial.vicon_endpts[1]]
quat = quaternion.as_float_array(
quaternion.from_rotation_matrix(torso_truncated[:, :3, :3],
nonorthogonal=False))
torso_pos_quat = np.concatenate((torso_truncated[:, :3, 3], quat), 1)
# retrieve reference data
ref_data = pd.read_csv(
Path(params.matlab_threejs_dir) / subject_id /
(params.trial_name + '.csv'))
# since the negative of a quaternions represents the same orientation make the appropriate sign flip so graphs align
mask = extended_dot(torso_pos_quat[:, 3:],
ref_data.iloc[:, 3:7].to_numpy()) < 0
torso_pos_quat[mask, 3:] = -torso_pos_quat[mask, 3:]
# graph
init_graphing()
for n in range(7):
plt.figure(n + 1)
plt.plot(torso_pos_quat[:, n], 'r')
plt.plot(ref_data.iloc[:, n], 'g')
make_interactive()
plt.show()
