def save_matrices(self):
"""
saves the matrices so these can be used to cluster in the gmm etc.
:return:
"""
save_pickle('/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env/', self.matrices, str(self.num_schedules) + 'test_matrices.pkl')
return self.matrices
def save_performance_results(self, top1, top3, special_string):
"""
saves performance of top1 and top3
:return:
"""
print('top1_mean for ', self.alpha, ' is : ', np.mean(top1))
data = {'top1_mean': np.mean(top1),
'top3_mean': np.mean(top3),
'top1_stderr': np.std(top1) / np.sqrt(len(top1)),
'top3_stderr': np.std(top3) / np.sqrt(len(top3))}
save_pickle(file=data, file_location=self.home_dir + '/saved_models/pairwise_saved_models/', special_string=special_string)
def save_performance_results(self, top1):
"""
saves performance of top1 and top3
:return:
"""
print('top1_mean for ', self.alpha, ' is : ', np.mean(top1))
data = {
'top1_mean': np.mean(top1),
'top1_stderr': np.std(top1) / np.sqrt(len(top1)),
'embedding': self.bayesian_embedding_dim
}
save_pickle(file=data,
file_location=self.home_dir +
'/saved_models/naive_saved_models/',
special_string=str(self.bayesian_embedding_dim) +
'baydim_naivetest.pkl')
def save_performance_results(top1, top3, special_string):
"""
saves performance of top1 and top3
:return:
"""
print('top1_mean: ', np.mean(top1))
data = {
'top1_mean': np.mean(top1),
'top3_mean': np.mean(top3),
'top1_stderr': np.std(top1) / np.sqrt(len(top1)),
'top3_stderr': np.std(top3) / np.sqrt(len(top3))
}
save_pickle(
file=data,
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/saved_models/pairwise_saved_models/',
special_string=special_string)
def main(str_for_naive, str_for_pickle):
"""
entry point of the file
:return:
"""
total_schedule = []
total_schedule_pairwise = []
n = 0
num_scheds = 1500
test = False
if test:
np.random.seed(50)
random.seed(50)
else:
np.random.seed(150)
random.seed(150)
while n < num_scheds:
world = World(num_scheds, n)
# 2 cases this breaks, either t > max duration, or 19 tasks are scheduled.
while not world.data_done_generating:
is_feasible = world.update_floyd_warshall_and_all_vectors()
world.print_all_features()
if is_feasible == False:
print('constraint was infeasible')
break
for counter, agent in enumerate(world.agents):
world.compute_task_to_schedule(counter)
is_feasible = world.update_floyd_warshall_and_all_vectors()
world.add_constraints_based_on_task()
world.check_if_schedule_finished()
print('current finish times', world.agents[0].getFinishTime(),
world.agents[1].getFinishTime())
# Next Time Step
world.t += 1
print('current time is ', world.t)
world.update_based_on_time()
if world.did_schedule_fail:
pass
else:
# temp = []
# temp_pairwise = []
# with open(world.filepath, 'r') as csvfile:
# data = (csv.reader(csvfile))
# for row in data:
# temp.append(row)
#
# with open(world.second_file_path, 'r') as csvfile:
# data = (csv.reader(csvfile))
# for row in data:
# temp_pairwise.append(row)
total_schedule.append(world.naive_total_data)
total_schedule_pairwise.append(world.pairwise_total_data)
n += 1
print('on schedule ', n)
if n == 100:
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule,
special_string=str(100) + str_for_naive + '.pkl')
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule_pairwise,
special_string=str(100) + str_for_pickle + '.pkl')
if n == 250:
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule,
special_string=str(250) + str_for_naive + '.pkl')
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule_pairwise,
special_string=str(250) + str_for_pickle + '.pkl')
if n == 500:
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule,
special_string=str(500) + str_for_naive + '.pkl')
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule_pairwise,
special_string=str(500) + str_for_pickle + '.pkl')
if n == 1500:
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule,
special_string=str(1500) + str_for_naive + '.pkl')
save_pickle(
file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule_pairwise,
special_string=str(1500) + str_for_pickle + '.pkl')
save_pickle(file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule,
special_string=str(num_scheds) + str_for_naive + '.pkl')
save_pickle(file_location=
'/home/ghost/PycharmProjects/bayesian_prolo/scheduling_env',
file=total_schedule_pairwise,
special_string=str(num_scheds) + str_for_pickle + '.pkl')
