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chore(main,environment): Remove spaces
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@jacksonpradolima
jacksonpradolima committed Mar 10, 2024
1 parent c4e1ae4 commit 255276b
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Showing 2 changed files with 29 additions and 29 deletions.
22 changes: 11 additions & 11 deletions coleman4hcs/environment.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ class Environment:
def __init__(self, agents, scenario_provider, evaluation_metric):
self.agents = agents
self.scenario_provider = scenario_provider
self.evaluation_metric = evaluation_metric
self.evaluation_metric = evaluation_metric
self.reset()

def reset(self):
Expand All @@ -54,7 +54,7 @@ def reset(self):
self.reset_agents_memory()
# Monitor saves the feedback during the process
self.monitor = MonitorCollector()

self.variant_monitors = {}

if isinstance(self.scenario_provider, IndustrialDatasetHCSScenarioProvider) and \
Expand All @@ -71,13 +71,13 @@ def reset_agents_memory(self):

def run_single(self,
experiment,
trials=100,
trials=100,
bandit_type: DynamicBandit = EvaluationMetricBandit,
restore=True):
"""
Execute a single simulation experiment
:param experiment: Current Experiment
:param trials: The max number of scenarios that will be analyzed
:param trials: The max number of scenarios that will be analyzed
:param bandit_type:
:param restore: restore the experiment if fail (i.e., energy down)
"""
Expand Down Expand Up @@ -158,7 +158,7 @@ def run_prioritization(self, agent, bandit, bandit_duration, experiment, t, vsc)
:param agent: The agent that is being used for the prioritization.
:param bandit: The bandit mechanism used for choosing actions.
:param bandit_duration: Time taken by the bandit process.
:param experiment: The current experiment number.
:param experiment: The current experiment number.
:param t: The current step or iteration of the simulation.
:param vsc: The virtual scenario being considered.
:return: tuple containing the chosen action by the agent, the ending time of the process,
Expand Down Expand Up @@ -193,7 +193,7 @@ def run_prioritization(self, agent, bandit, bandit_duration, experiment, t, vsc)

# Compute end time
end = time.time()

logging.debug(f"Exp: {experiment} - Ep: {t} - Name: {exp_name} ({str(agent.get_reward_function())}) - " +
f"NAPFD/APFDc: {metric.fitness:.4f}/{metric.cost:.4f}")

Expand Down Expand Up @@ -299,7 +299,7 @@ def run(self, experiments=1, trials=100, bandit_type: DynamicBandit = Evaluation
"""
Execute a simulation
:param experiments: Number of experiments
:param trials: The max number of scenarios that will be analyzed
:param trials: The max number of scenarios that will be analyzed
:param bandit_type:
:param restore: restore the experiment if fail (i.e., energy down)
:return:
Expand All @@ -312,7 +312,7 @@ def run(self, experiments=1, trials=100, bandit_type: DynamicBandit = Evaluation
def create_file(self, name):
"""
Create a file to store the results obtained during the experiment
"""
"""
self.monitor.create_file(name)

# If we are working with HCS scenario, we create a file for each variant in a specific directory
Expand All @@ -331,10 +331,10 @@ def create_file(self, name):
def store_experiment(self, csv_file_name):
"""
Save the results obtained during the experiment
"""
"""
# Collect from temp and save a file (backup and easy sharing/auditing)
self.monitor.save(csv_file_name)

if isinstance(self.scenario_provider, IndustrialDatasetHCSScenarioProvider):
if self.scenario_provider.get_total_variants() > 0:
# Ignore the extension
Expand All @@ -347,7 +347,7 @@ def store_experiment(self, csv_file_name):
# Collect from temp and save a file (backup and easy sharing/auditing)
self.variant_monitors[variant].save(
f"{name2}/{csv_file_name.split('/')[-1].split('@')[0]}@{variant.replace('/', '-')}.csv")

def load_experiment(self, experiment):
"""
Load the backup
Expand Down
36 changes: 18 additions & 18 deletions main.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,7 @@ def exp_run_industrial_dataset(iteration, trials, env: Environment, experiment_d
csv_file_name = f"{experiment_directory}{str(env.scenario_provider)}_{iteration}.csv"
env.create_file(csv_file_name)
env.run_single(iteration, trials)
env.store_experiment(csv_file_name)
env.store_experiment(csv_file_name)


def load_class_from_module(module, class_name: str):
Expand Down Expand Up @@ -196,10 +196,10 @@ def merge_csv(files, output_file):
"""
# Merge all CSV files into one DataFrame
df = pd.concat([pd.read_csv(file, sep=';') for file in files], ignore_index=True)

# Save the merged DataFrame to CSV
df.to_csv(output_file, index=False, sep=';', quoting=csv.QUOTE_NONE)
df.to_csv(output_file, index=False, sep=';', quoting=csv.QUOTE_NONE)

# Optionally, clean up temporary files
for file in files:
os.remove(file)
Expand Down Expand Up @@ -232,7 +232,7 @@ def store_experiments(csv_file, scenario):
Example usage:
>>> store_experiments("experiment_results.csv", my_scenario)
"""
# Create/Open a database to store the results
# Create/Open a database to store the results
conn = duckdb.connect('experiments.db')

# Ensure the tables exist with the appropriate schema
Expand Down Expand Up @@ -261,12 +261,12 @@ def store_experiments(csv_file, scenario):
prioritization_order VARCHAR
);
""")

df = conn.read_csv(csv_file, delimiter=';', quotechar='"', header=True)

# Insert the DataFrame into the 'experiments' table
conn.execute("INSERT INTO experiments SELECT * FROM df;")

if isinstance(scenario, IndustrialDatasetHCSScenarioProvider):
if scenario.get_total_variants() > 0:
# Ignore the extension
Expand All @@ -275,9 +275,9 @@ def store_experiments(csv_file, scenario):

Path(name2).mkdir(parents=True, exist_ok=True)

for variant in scenario.get_all_variants():
for variant in scenario.get_all_variants():
csv_file_variant = f"{name2}/{csv_file.split('/')[-1].split('@')[0]}@{variant.replace('/', '-')}.csv"
conn.execute( f"COPY experiments FROM '{csv_file_variant}' (HEADER);")
conn.execute( f"COPY experiments FROM '{csv_file_variant}' (HEADER);")
df = conn.read_csv(csv_file, delimiter=';', quotechar='"', header=True)

# Insert the DataFrame into the 'experiments' table
Expand All @@ -292,11 +292,11 @@ def store_experiments(csv_file, scenario):
# Execution configuration
(
parallel_pool_size,
independent_executions,
independent_executions,
verbose
) = map(config['execution'].get, [
'parallel_pool_size',
'independent_executions',
'independent_executions',
'verbose'
])

Expand Down Expand Up @@ -367,7 +367,7 @@ def store_experiments(csv_file, scenario):
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
else:
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

for tr in sched_time_ratio:
experiment_directory = os.path.join(experiment_dir, f"time_ratio_{int(tr * 100)}/")

Expand All @@ -379,12 +379,12 @@ def store_experiments(csv_file, scenario):

# Stop conditional
trials = scenario.max_builds

# Prepare the experiment
env = Environment(agents, scenario, evaluation_metric)

parameters = [(i + 1, trials, env, experiment_directory) for i in range(independent_executions)]

# Compute time
start = time.time()

Expand All @@ -395,14 +395,14 @@ def store_experiments(csv_file, scenario):
for param in parameters:
exp_run_industrial_dataset(*param)

end = time.time()
end = time.time()

# Read and merge the independent executions
csv_file_names = [f"{experiment_directory}{str(env.scenario_provider)}_{i+1}.csv" for i in range(independent_executions)]
csv_file_names = [f"{experiment_directory}{str(env.scenario_provider)}_{i+1}.csv" for i in range(independent_executions)]
csv_file = f"{experiment_directory}{str(env.scenario_provider)}.csv"
merge_csv(csv_file_names, csv_file)

# Store the results in the duckdb database
store_experiments(csv_file, scenario)

logging.info(f"Time expend to run the experiments: {end - start}\n\n")

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