def test_srea_case_uniform_2(self):
"""Test two agent sync with uniform dists, no solution."""
stn = stntools.load_stn_from_json_file(STN4)["stn"]
result = srea.srea(stn)
# We expect this one to never give a guide. It's impossible
# to succeed, and thus inconsistent.
self.assertEqual(result, None)
def test_srea_sim_1(self):
stn = stntools.load_stn_from_json_file(STN1)["stn"]
sim = Simulator(42)
successes = 0
res = 50
for i in range(res):
result = sim.simulate(stn, execution_strat="srea")
if result:
successes += 1
robustness = successes / res
self.assertTrue(0.60 < robustness < 0.80)
def test_early_sim(self):
stn = stntools.load_stn_from_json_file(STN1)["stn"]
sim = Simulator(42)
successes = 0
res = 100
for i in range(res):
result = sim.simulate(stn, execution_strat="early")
if result:
successes += 1
robustness = successes / res
self.assertTrue(0.10 < robustness < 0.20)
def test_srea_case_uniform_1(self):
"""Test two agent sync with uniform dists, easy solution."""
stn = stntools.load_stn_from_json_file(STN3)["stn"]
alpha, guide = srea.srea(stn)
self.assertEqual(guide.get_assigned_time(1), 0.0)
self.assertEqual(alpha, 0.0)
def test_srea_case_2(self):
stn = stntools.load_stn_from_json_file(STN2)["stn"]
alpha, guide = srea.srea(stn)
self.assertEqual(guide.get_assigned_time(1), 0.0)
self.assertEqual(alpha, 0.481)
def test_srea_case_1(self):
stn = stntools.load_stn_from_json_file(STN1)["stn"]
alpha, guide = srea.srea(stn)
self.assertTrue(0.504 < alpha < 0.508)
def across_paths(stn_paths,
execution,
threads,
sim_count,
sim_options,
output=None,
live_updates=True,
random_seed=None,
mitparse=False,
start_index=0,
stop_index=None,
ordering_pairs=None):
"""Runs multiple simulations for each STN in the provided iterable.
Args:
stn_paths (iterable): iterable (like a List) of strings.
execution (str): Execution strategy to use on each STN.
threads (int): Number of threads to use.
sim_count (int): Number of simulations (samples) to use.
sim_options (dict): Dictionary of simulation options to use.
output (str, optional): Output file path. Default no output.
live_updates (boolean, optional): Whether to provide live updates.
random_seed (int, optional): The random seed to start out with,
defaults to a random... random seed.
mitparse (boolean, optional): Parse STN JSON files as MIT format.
ordering_pairs (list, optional): List of tuples of AR and SC settings.
Each STN will be run with a separate simulation for each tuple.
"""
stn_pairs = []
# Collect the STNs from all the passed in paths
# Make sure we keep the path around though, and keep them in the pair.
for i, path in enumerate(stn_paths):
if mitparse:
mitstns = mitparser.mit2stn(path, add_z=True, connect_origin=True)
stn_pairs += [(path, k) for k in mitstns]
else:
stn = load_stn_from_json_file(path)["stn"]
stn_pairs.append((path, stn))
# We must separate these for loops because MIT stns can hold several
# instances in a single file.
for i, pair in enumerate(stn_pairs):
if i < start_index:
continue
if stop_index is not None:
if i >= stop_index:
break
if ordering_pairs is not None:
for j, execution_setting in enumerate(ordering_pairs):
sim_option_instance = sim_options.copy()
sim_option_instance["ar_threshold"] = execution_setting[0]
sim_option_instance["si_threshold"] = execution_setting[1]
results_dict = _run_stage(pair, execution, sim_count, threads,
random_seed, sim_option_instance)
if live_updates:
_print_results(results_dict,
j + len(ordering_pairs) * i + 1,
len(stn_pairs) * len(ordering_pairs))
if output is not None:
sim2csv.save_csv_row(results_dict, output)
else:
results_dict = _run_stage(pair, execution, sim_count, threads,
random_seed, sim_options)
if live_updates:
_print_results(results_dict, i + 1, len(stn_pairs))
if output is not None:
sim2csv.save_csv_row(results_dict, output)
def test_stn_interagent_edges(self):
stn = stntools.load_stn_from_json_file(STN1)["stn"]
self.assertEqual(list(stn.interagent_edges.keys()), [(2, 4)])
self.assertTrue(True)
def test_decouple_sim_3(self):
stn = stntools.load_stn_from_json_file(STN3)["stn"]
sim = DecoupledSimulator(random_seed=1000)
self.assertTrue(sim.simulate(stn))
def test_opt_case_2(self):
stn = stntools.load_stn_from_json_file(STN2)["stn"]
alpha, subproblems = optdecouple.decouple_agents(stn, fidelity=0.001)
self.assertTrue(0.0 <= alpha <= 0.01)
for g in subproblems:
self.assertEqual(g.get_assigned_time(0), 0)