def run_orch(log, n_workers, checkpoint_freq, job_dir, job_name, narration, configuration,
n_cycle_steps, run_time, start_hash, orchestrator):
"""
\b
Parameters
----------
log :
n_workers :
checkpoint_freq :
job_dir :
job_name :
narration :
n_cycle_steps :
run_time :
start_hash :
orchestrator :
\b
Returns
-------
"""
set_loglevel(log)
# settle what the defaults etc. are for the different options as they are interdependent
job_dir, job_name, narration, config = settle_run_options(n_workers=n_workers,
job_dir=job_dir,
job_name=job_name,
narration=narration,
configuration=configuration,
start_hash=start_hash)
# Open a wrapper around the orchestrator database that provides
# the inputs for the simulation
orch = Orchestrator(orchestrator, mode='r')
logging.info("Orchestrator loaded")
logging.info("Running snapshot by time")
run_orch = orch.orchestrate_snapshot_run_by_time(start_hash,
run_time,
n_cycle_steps,
checkpoint_freq=checkpoint_freq,
work_dir=job_dir,
config_name=job_name,
narration=narration,
configuration=config,
)
logging.info("Finished running snapshot by time")
start_hash, end_hash = run_orch.run_hashes()[0]
logging.info("Closing the resultant orchestrator")
run_orch.close()
# write the run tuple out to the log
run_line_str = "Run start and end hashes: {}, {}".format(start_hash, end_hash)
# log it
logging.info(run_line_str)
# also put it to the terminal
click.echo(run_line_str)
logging.info("Closing the orchestrating orch")
orch.close()
def run_snapshot(log, n_workers, checkpoint_freq, job_dir, job_name, narration,
n_cycle_steps, run_time, configuration, snapshot):
"""
\b
Parameters
----------
log :
n_workers :
checkpoint_freq :
job_dir :
job_name :
narration :
n_cycle_steps :
run_time :
start_hash :
orchestrator :
\b
Returns
-------
"""
set_loglevel(log)
logging.info("Loading the starting snapshot file")
# read the config and snapshot in
serial_snapshot = snapshot.read()
logging.info("Creating orchestrating orch database")
# make the orchestrator for this simulation in memory to start
orch = Orchestrator()
logging.info("Adding the starting snapshot to database")
start_hash = orch.add_serial_snapshot(serial_snapshot)
# settle what the defaults etc. are for the different options as they are interdependent
job_dir, job_name, narration, config = settle_run_options(n_workers=n_workers,
job_dir=job_dir,
job_name=job_name,
narration=narration,
configuration=configuration,
start_hash=start_hash)
# add the parametrized configuration to the orchestrator
# config_hash = orch.add_serial_configuration(config)
logging.info("Orchestrator loaded")
logging.info("Running snapshot by time")
run_orch = orch.orchestrate_snapshot_run_by_time(start_hash,
run_time,
n_cycle_steps,
checkpoint_freq=checkpoint_freq,
work_dir=job_dir,
config_name=job_name,
narration=narration,
configuration=config,
)
logging.info("Finished running snapshot by time")
start_hash, end_hash = run_orch.run_hashes()[0]
run_orch.close()
logging.info("Closed the resultant orch")
# write the run tuple out to the log
run_line_str = "Run start and end hashes: {}, {}".format(start_hash, end_hash)
# log it
logging.info(run_line_str)
# also put it to the terminal
click.echo(run_line_str)
orch.close()
logging.info("closed the orchestrating orch database")
