def generate_target_line(self, n_samples=100):
"""
Using object trajectory (self.poses), build a line to compare to for frechet distance.
Updates this attribute on object.
:param n_samples: number of samples for target line. Defaults to 100
"""
x_vals, y_vals = aplt.get_direction(self.trial_translation, n_samples)
target_line = np.column_stack((x_vals, y_vals))
# get last object pose and use it for determining how far target line should go
last_obj_pose = self.poses.tail(1).to_numpy()[0]
target_line_length = acalc.narrow_target(last_obj_pose, target_line)
if target_line_length:
distance_travelled = acalc.t_distance(
[0, 0], target_line[target_line_length + 1])
final_target_ln = target_line[:target_line_length]
else:
distance_travelled = acalc.t_distance([0, 0], target_line[0])
final_target_ln = target_line[:1]
# TODO: distance travelled has error because it is built of target line... maybe use last_obj_pose instead?
return final_target_ln, distance_travelled
def plot_direction(self,
translation,
rotation="n",
show_plot=True,
save_plot=False):
"""
Plot the average path for each hand data object contained in this object for a specific
translation rotation pair.
"""
colors = [
"tab:blue", "tab:purple", "tab:red", "tab:olive", "tab:cyan",
"tab:green", "tab:pink", "tab:orange"
]
# grab the average values from all hands
avg_label = f"{translation}_{rotation}"
averages_to_plot = []
hand_order = []
for h in self.hands:
hand_order.append(h.hand.get_name())
for a in h.averages:
a_label = f"{a.trial_translation}_{a.trial_rotation}"
if a_label == avg_label:
averages_to_plot.append(a)
for i, a in enumerate(averages_to_plot):
a_x, a_y, _ = a.get_poses()
plt.plot(a_x, a_y, color=colors[i], label=hand_order[i])
# plot the straight line
t_x, t_y = AsteriskPlotting.get_direction(translation)
plt.plot(t_x, t_y, color="r", linestyle="dashed")
if save_plot:
# added the zero to guarantee that it comes first
plt.savefig(f"pics/0all_{rotation}.jpg", format='jpg')
# name -> tuple: subj, hand names
print("Figure saved.")
print(" ")
if show_plot:
plt.legend()
plt.show()
return plt