files = glob.glob("singleintegrator/orcaR{}*/*obst{}_agents{}_*.npy".format(r,obst,agent), recursive=True)
for file in files:
instance = os.path.splitext(os.path.basename(file))[0]
map_filename = "singleintegrator/instances/{}.yaml".format(instance)
result = stats.stats(map_filename, file)
result["solver"] = "ORCA"
result["Rsense"] = r
if instance in result_by_instance:
result_by_instance[instance].append(result)
else:
result_by_instance[instance] = [result]
# add_bar_agg(pp, result_by_instance, "num_agents_success", "# robots success")
add_line_plot_agg(None, result_by_instance, "percent_agents_success", group_by="Rsense",
ax=axs[0, column])
# add_line_plot_agg(pp, result_by_instance, "control_effort_sum", "control effort")
add_scatter(pp, result_by_instance, "num_collisions", "# collisions")
pp.close()
# create plots
pp = PdfPages("exp2.pdf")
for column in range(0, 2):
axs[0,column].set_xlabel("$r_{sense}$ [m]")
axs[0,0].set_ylabel("robot success [%]")
axs[0,0].set_ylim([25,105])
axs[0,0].set_title("10 % obstacles")
for agent in agents_lst:
files.extend( glob.glob("doubleintegrator/{}*/*obst{}_agents{}_*.npy".format(solver,obst,agent), recursive=True))
for file in files:
instance = os.path.splitext(os.path.basename(file))[0]
map_filename = "singleintegrator/instances/{}.yaml".format(instance)
result = stats.stats(map_filename, file)
result["solver"] = solvers[os.path.basename(result["solver"])]
if instance in result_by_instance:
result_by_instance[instance].append(result)
else:
result_by_instance[instance] = [result]
# create plots
add_line_plot_agg(None, result_by_instance, "percent_agents_success",
ax=axs[0, column])
# add_line_plot_agg(None, result_by_instance, "control_effort_mean",
# ax=axs[1, column], aggregrate_successful_agent=False)
add_line_plot_agg(None, result_by_instance, "control_effort",
ax=axs[1, column], aggregrate_successful_agent=True)
add_scatter(pp, result_by_instance, "num_collisions", "# collisions")
pp.close()
pp = PdfPages("exp1_di.pdf")
for column in range(0, 2):
axs[1,column].set_xlabel("robot density [#robots/64m\u00B2]")
axs[0,0].set_ylabel("robot success [%]")
axs[0,0].set_ylim([25,105])
for agent in agents_lst:
files.extend( glob.glob("doubleintegrator/{}*/*obst{}_agents{}_*.npy".format(solver,obst,agent), recursive=True))
for file in files:
instance = os.path.splitext(os.path.basename(file))[0]
map_filename = "doubleintegrator/instances/{}.yaml".format(instance)
result = stats.stats(map_filename, file)
result["solver"] = solvers[os.path.basename(result["solver"])]
if instance in result_by_instance:
result_by_instance[instance].append(result)
else:
result_by_instance[instance] = [result]
# create plots
add_line_plot_agg(None, result_by_instance, "percent_agents_success",
ax=axs[0, column])
add_line_plot_agg(None, result_by_instance, "control_effort_mean",
ax=axs[1, column])
add_scatter(pp, result_by_instance, "num_collisions", "# collisions")
pp.close()
pp = PdfPages("exp1.pdf")
for column in range(0, 2):
axs[1,column].set_xlabel("number of robots")
axs[0,0].set_ylabel("robot success [%]")
axs[0,0].set_ylim([35,105])
axs[1,0].set_ylabel("control effort")
instance = os.path.splitext(os.path.basename(file))[0]
map_filename = "singleintegrator/instances/{}.yaml".format(instance)
result = stats.stats(map_filename, file)
result["solver"] = solvers[os.path.basename(result["solver"])]
result["filename"] = file
if instance in result_by_instance:
result_by_instance[instance].append(result)
else:
result_by_instance[instance] = [result]
# create plots
pp = PdfPages("exp3_{}.pdf".format(obst))
add_line_plot_agg(pp, result_by_instance, "percent_agents_success",
x_label="number of robots",
y_label="robot success [%]")
add_line_plot_agg(pp, result_by_instance, "control_effort_mean",
x_label="number of robots",
y_label="average control effort of successful robots")
add_scatter(pp, result_by_instance, "num_collisions", "# collisions")
# # TEMP TEMP
# import yaml
# from matplotlib.patches import Rectangle, Circle
# for instance in sorted(result_by_instance):
# print(instance)
# results = result_by_instance[instance]
# # add_bar_chart(pp, results, "percent_agents_reached_goal", instance + " (% reached goal)")
# # add_bar_chart(pp, results, "num_collisions", instance + " (# collisions)")
result = stats.stats(map_filename, file)
result["solver"] = "ORCA"
result["Rsense"] = r
if instance in result_by_instance:
result_by_instance[instance].append(result)
else:
result_by_instance[instance] = [result]
# create plots
pp = PdfPages("exp2_{}.pdf".format(obst))
# add_bar_agg(pp, result_by_instance, "num_agents_success", "# robots success")
add_line_plot_agg(pp, result_by_instance, "percent_agents_success", group_by="Rsense",
x_label="sensing radius [m]",
y_label="robot success [%]")
# add_line_plot_agg(pp, result_by_instance, "control_effort_sum", "control effort")
# add_scatter(pp, result_by_instance, "num_collisions", "# collisions")
pp.close()
exit()
datadir = []
for agents in agents_lst:
for obst in obst_lst:
datadir.extend(glob.glob("singleintegrator/instances/*obst{}_agents{}_*".format(obst,agents)))
instances = sorted(datadir)
for i in range(0,10):