def save_results(fldr_name, f_name, data_array, save_plots=False):
"""
Saves figure. Basename should be the model name without voxel or angle info appended.
"""
data_io.save_array(fldr_name, f_name, data_array)
if save_plots:
render_results.save_heatmap(fldr_name, f_name, data_array, label="% collisions with walls")
def save_results(fldr_name, f_name, data_array, save_plots=False):
"""
Saves figure. Basename should be the model name without voxel or angle info appended.
"""
data_io.save_array(fldr_name, f_name, data_array)
if save_plots:
render_results.save_heatmap(fldr_name,
f_name,
data_array,
label="% collisions with walls")
def save_results(data_array, result_folder, save_basename, plot=False, plot_options=None):
"""
Save (and plot) results as appropriate
"""
plot_options = plot_options or {}
data_io.save_array(result_folder,
save_basename,
data_array)
if plot:
render_results.save_heatmap(result_folder,
save_basename,
data_array,
**plot_options)
def main(settings):
"""
Determine the best pose of the manikin for each position and orientation.
"""
basename = "{}_{}"
# Get one matrix per pose, representing the best possible fit of that pose at a given point
# in the vehicle
walkability_by_pose_name = {manikin_name: load_fit_of_pose_in_vehicle(
basename.format(settings["run_id"], manikin_name),
settings)
for manikin_name in settings["manikin_poses"]}
# TODO: number of best pose may be superfluous. Can probably disable saving this info.
best_pose_number_by_point = score_from_list(walkability_by_pose_name,
settings["manikin_poses"],
settings,
score_key='num',
orientation="overall")
best_score_by_point = score_from_list(walkability_by_pose_name,
settings["manikin_poses"],
settings,
score_key='score',
orientation="overall")
best_pose_for_orientation = {}
best_score_for_orientation = {}
for ang in settings["manikin_orientations"]:
best_pose_for_orientation[str(ang)] = score_from_list(walkability_by_pose_name,
settings["manikin_poses"],
settings,
score_key='num',
orientation=ang)
best_score_for_orientation[str(ang)] = score_from_list(walkability_by_pose_name,
settings["manikin_poses"],
settings,
score_key='score',
orientation=ang)
# Save results
result_folder = "results/{}/{}".format(settings["run_id"], settings["voxel_size"])
saved_file_basename = "{}_vox{}_best_scores".format(
settings["run_id"], settings["voxel_size"])
save_results(best_score_by_point,
result_folder,
saved_file_basename,
plot=settings["show_2d"],
plot_options={"label": "Walkability scores",
"tick_labels": sorted([v['score'] for k, v
in settings["manikin_poses"].items()])})
saved_file_basename = "{}_vox{}_best_poses".format(
settings["run_id"], settings["voxel_size"])
save_results(best_pose_number_by_point,
result_folder,
saved_file_basename,
plot=settings["show_2d"],
plot_options={"label": "Best pose at point",
"tick_labels": sorted([v['num'] for k, v in
settings["manikin_poses"].items()])})
# Also save the best scores per orientation
data_io.save_multi_array(result_folder,
"{}_vox{}_best_poses_by_orientation".format(settings["run_id"],
settings["voxel_size"]),
best_pose_for_orientation)
data_io.save_multi_array(result_folder,
"{}_vox{}_best_scores_by_orientation".format(settings["run_id"],
settings["voxel_size"]),
best_score_for_orientation)
if settings["show_2d"]:
# After saving score data to one big npz file, make the individual plots to match
for ang in settings["manikin_orientations"]:
saved_file_basename = "{}_vox{}_best_scores_ang{}".format(settings["run_id"],
settings["voxel_size"], ang)
render_results.save_heatmap(result_folder,
saved_file_basename,
best_score_for_orientation[str(ang)],
label="Best score for orientation {}".format(ang),
tick_labels=sorted([v['score']
for k, v in settings["manikin_poses"].items()]))
