def planner_comparison(seed):
the_seed = seed
print("seed: " + str(the_seed))
params = get_data_random(the_seed,
map_res=8,
map_fill_perc=30,
agent_n=5,
job_n=5,
idle_goals_n=0)
agent_pos, grid, idle_goals, jobs = params
mapstr= get_map_str(grid)
print(mapstr)
maphash = str(hashlib.md5(mapstr.encode('utf-8')).hexdigest())[:8]
print(maphash)
fname = "planner/eval/cache/" + str(maphash) + '.pkl' # unique filename based on map
pre_calc_paths(jobs, idle_goals, grid, fname)
config_opt = generate_config()
config_opt['params'] = params
config_opt['filename_pathsave'] = fname
config_opt['finished_agents_block'] = True
config_milp = config_opt.copy()
config_milp['milp'] = 1
config_cobra = config_opt.copy()
config_cobra['cobra'] = 1
config_greedy = config_opt.copy()
config_greedy['greedy'] = 1
config_nn = config_opt.copy()
config_nn['number_nearest'] = 2
config_col = config_nn.copy()
config_col['all_collisions'] = True
if is_cch():
print("Configs: [config_opt, config_nn, config_milp, config_cobra, config_greedy]")
configs = [config_opt, config_nn, config_milp, config_cobra, config_greedy]
sizes = [2, 3, 4]
timeout = 10000
else: # travis
print("Configs: [config_opt, config_nn, config_milp, config_greedy]")
configs = [config_opt, config_nn, config_milp, config_greedy]
sizes = [2, 3, 4]
timeout = 500
ts, ress = benchmark(one_planner, [configs, sizes], samples=1, timeout=timeout)
return ts, ress
def test_cobra_random(plot=False):
agent_pos, grid, idle_goals, jobs = get_data_random(seed=1,
map_res=8,
map_fill_perc=20,
agent_n=3,
job_n=3,
idle_goals_n=0)
res_agent_job, res_paths = plan_cobra(agent_pos, jobs, grid,
generate_config())
print(res_agent_job)
all_alloc = reduce(lambda a, b: a + b, res_agent_job, tuple())
jobs_is = list(range(len(jobs)))
for i_j in all_alloc:
jobs_is.remove(i_j)
assert not jobs_is, "Not all jobs allocated"
if plot:
fig = plt.figure()
ax = fig.add_subplot(121)
plot_inputs(ax, agent_pos, idle_goals, jobs, grid)
ax2 = fig.add_subplot(122, projection='3d')
plot_results(ax2, [], res_paths, res_agent_job, agent_pos, grid, [],
jobs)
plt.show()
import hashlib
from planner.tcbs_test import get_data_random
from planner.eval.display import plot_inputs, plot_results
from planner.tcbs.plan import plan, generate_config
from planner.milp.milp import plan_milp
import matplotlib.pyplot as plt
from tools import get_map_str
params = get_data_random(330,
map_res=8,
map_fill_perc=30,
agent_n=4,
job_n=4,
idle_goals_n=0)
agent_pos, grid, idle_goals, jobs = params
mapstr = get_map_str(grid)
maphash = str(hashlib.md5(mapstr.encode('utf-8')).hexdigest())[:8]
fname = "planner/eval/cache/" + str(maphash) + '.pkl' # unique filename based on map
config = generate_config()
config['finished_agents_block'] = True
config['filename_pathsave'] = fname
tcbs_agent_job, tcbs_agent_idle, tcbs_paths = plan(agent_pos, jobs, [], [], grid, config, plot=False)
f = plt.figure()
ax0= f.add_subplot(111)
plot_results(ax0, tcbs_agent_idle, tcbs_paths, tcbs_agent_job, agent_pos, grid, [], jobs, "tcbs")
from planner.tcbs_test import get_data_random
agent_n_s = [2, 4, 6]
map_res_s = [10, 14]
results_mean = np.zeros([len(agent_n_s), len(map_res_s)])
results_std = np.zeros([len(agent_n_s), len(map_res_s)])
for agent_n, map_res in product(agent_n_s, map_res_s):
print("\n---------\nagent_n:", agent_n, "map_res", map_res)
duration = []
for i in range(8):
print("test", i)
agent_pos, grid, idle_goals, jobs = get_data_random(map_res=map_res,
map_fill_perc=5,
agent_n=agent_n,
job_n=agent_n,
idle_goals_n=agent_n)
try:
fname = ''
fname = pre_calc_paths(jobs, idle_goals, grid)
start_time = datetime.datetime.now()
res_agent_job, res_agent_idle, res_paths = plan(agent_pos, jobs, [], idle_goals, grid, filename=fname)
d = (datetime.datetime.now() - start_time).total_seconds()
# print("computation time:", d, "s")
duration.append(d)
# print("RESULTS:\nres_agent_job", res_agent_job)
# print("res_agent_idle", res_agent_idle)
n_tests = 10
n_agent = [1, 2, 3, 4, 5]
res = np.zeros([len(n_agent), n_tests])
res2 = np.zeros([len(n_agent), n_tests])
for i_agents in range(len(n_agent)):
print("i_agents", i_agents)
for i_test in range(n_tests):
print("i_test", i_test)
if os.path.exists(fname):
os.remove(fname)
assert not os.path.exists(fname), "File exists already"
agent_pos, grid, idle_goals, jobs = get_data_random(
10, 5, n_agent[i_agents], n_agent[i_agents], 5)
start_time = datetime.datetime.now()
try:
plan_cbsext(agent_pos, jobs, [], idle_goals, grid, filename=fname)
except RuntimeError:
print("NO SOLUTION")
time1 = (datetime.datetime.now() - start_time).total_seconds()
assert os.path.isfile(fname), "Algorithm has not created a file"
start_time = datetime.datetime.now()
try:
plan_cbsext(agent_pos, jobs, [], idle_goals, grid, filename=fname)
except RuntimeError:
print("NO SOLUTION")
time2 = (datetime.datetime.now() - start_time).total_seconds()