def compute_probability(self, number_of_executions, sum_execution_time_sq, sum_execution_times):
n = TypeConversion.get_float(number_of_executions)
sum_xi = TypeConversion.get_float(sum_execution_times)
sum_xi_2 = TypeConversion.get_float(sum_execution_time_sq)
self.number_of_executions = n
if n is None:
Logger.error("Cannot compute std deviation! Malformed input data!")
self.mean = None
self.deviation = None
return
if n == 0:
self.mean = None
self.deviation = None
return
if n == 1 and sum_xi is not None:
self.mean = sum_xi
self.deviation = 0
return
if n > 0 and sum_xi is None or sum_xi_2 is None:
Logger.error("Cannot compute standard deviation! Malformed input data!")
return
#calculation of standard deviation
tmp = sum_xi_2 - (1/n) * sum_xi ** 2
s = math.sqrt((1/(n - 1)) * tmp)
self.deviation = s
#calculation of mean
mean = (1/n) * sum_xi
self.mean = mean
def run_optimization_process(args, parameters):
ts = time.time()
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d-%H:%M:%S')
try:
job = deserialize(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
results, extremes = process_job_parallel("PPPolicies", job, TypeConversion.get_int(args.cores), TypeConversion.get_int(args.iter), parameters=parameters)
parameters["results"] = results
pickle.dump(parameters, open(args.out_folder + st + ".pickle", "wb"))
def schedulerForName(name):
schedulers = {ReferenceScheduler.__name__ : ReferenceScheduler, OptimizedDependencyScheduler.__name__ : OptimizedDependencyScheduler,
PPPolicies.__name__ : PPPolicies,
JFPol.__name__ : JFPol}
if name is None:
scheduler = ReferenceScheduler
else:
try:
scheduler = schedulers[name]
except KeyError:
Logger.error("The scheduler specified does not exist.")
sys.exit(127)
return scheduler
def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("file", help="The pickle file containing the simulation result")
arg_parser.add_argument("--pdf", help="specifies that the visualization should be written to a pdf file. Followed \
by a path")
args = arg_parser.parse_args()
try:
simulation_result = load_simulation_result(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
visualize(simulation_result)
if args.pdf is not None:
plt.savefig(args.pdf)
else:
plt.show()
def run_optimization_process(args, parameters):
ts = time.time()
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d-%H:%M:%S')
try:
job = deserialize(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
results, extremes = process_job_parallel("PPPolicies",
job,
TypeConversion.get_int(
args.cores),
TypeConversion.get_int(args.iter),
parameters=parameters)
parameters["results"] = results
pickle.dump(parameters, open(args.out_folder + st + ".pickle", "wb"))
def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument(
"file", help="The pickle file containing the simulation result")
arg_parser.add_argument(
"--pdf",
help=
"specifies that the visualization should be written to a pdf file. Followed \
by a path")
args = arg_parser.parse_args()
try:
simulation_result = load_simulation_result(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
visualize(simulation_result)
if args.pdf is not None:
plt.savefig(args.pdf)
else:
plt.show()
def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("file", help="The pickle file containing the simulation data")
arg_parser.add_argument("--cores", help="The number of cores to be used.")
arg_parser.add_argument("--iter", help="The number of iterations per core.")
arg_parser.add_argument("--out_extremes", help="The file the extreme values should be written to.")
arg_parser.add_argument("--out_results", help="The file all the lambdas should be written to.")
arg_parser.add_argument("--scheduler", help="specifies the scheduler to be used. Default is referenceScheduler. \
Other possible values: optimizedDependencyScheduler")
args = arg_parser.parse_args()
try:
job = deserialize(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
results, extremes = process_job_parallel(args.scheduler, job, TypeConversion.get_int(args.cores), TypeConversion.get_int(args.iter))
if args.out_extremes is not None:
pickle.dump(extremes, open(args.out_extremes, "wb"))
if args.out_results is not None:
pickle.dump(results, open(args.out_results, "wb"))
def compute_probability(self, number_of_executions, sum_execution_time_sq,
sum_execution_times):
n = TypeConversion.get_float(number_of_executions)
sum_xi = TypeConversion.get_float(sum_execution_times)
sum_xi_2 = TypeConversion.get_float(sum_execution_time_sq)
self.number_of_executions = n
if n is None:
Logger.error("Cannot compute std deviation! Malformed input data!")
self.mean = None
self.deviation = None
return
if n == 0:
self.mean = None
self.deviation = None
return
if n == 1 and sum_xi is not None:
self.mean = sum_xi
self.deviation = 0
return
if n > 0 and sum_xi is None or sum_xi_2 is None:
Logger.error(
"Cannot compute standard deviation! Malformed input data!")
return
#calculation of standard deviation
tmp = sum_xi_2 - (1 / n) * sum_xi**2
s = math.sqrt((1 / (n - 1)) * tmp)
self.deviation = s
#calculation of mean
mean = (1 / n) * sum_xi
self.mean = mean
def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument(
"file", help="The pickle file containing the simulation data")
arg_parser.add_argument("--cores", help="The number of cores to be used.")
arg_parser.add_argument("--iter",
help="The number of iterations per core.")
arg_parser.add_argument(
"--out_folder", help="The folder to which result files are written")
args = arg_parser.parse_args()
try:
job = deserialize(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
params = [
{
"listGAGen": 250,
"listGACXp": 1.0,
"listGAMUTp": 0.5,
"listNoList": 10,
"arcGAGen": 100,
"arcGACXp": 0.5,
"arcGAMUTp": 0.01,
"arcGAn_pairs": 7,
"arcGAno_p": 10,
"name": "ArcGA mutp"
},
{
"listGAGen": 250,
"listGACXp": 1.0,
"listGAMUTp": 0.5,
"listNoList": 10,
"arcGAGen": 100,
"arcGACXp": 0.5,
"arcGAMUTp": 0.1,
"arcGAn_pairs": 7,
"arcGAno_p": 10,
"name": "ArcGA mutp"
},
{
"listGAGen": 250,
"listGACXp": 1.0,
"listGAMUTp": 0.5,
"listNoList": 10,
"arcGAGen": 100,
"arcGACXp": 0.5,
"arcGAMUTp": 0.3,
"arcGAn_pairs": 7,
"arcGAno_p": 10,
"name": "ArcGA mutp"
},
{
"listGAGen": 250,
"listGACXp": 1.0,
"listGAMUTp": 0.5,
"listNoList": 10,
"arcGAGen": 100,
"arcGACXp": 0.5,
"arcGAMUTp": 0.5,
"arcGAn_pairs": 7,
"arcGAno_p": 10,
"name": "ArcGA mutp"
},
]
run_multiple_opt(args, params)
def main():
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("file", help="The pickle file containing the simulation data")
arg_parser.add_argument("--cores", help="The number of cores to be used.")
arg_parser.add_argument("--iter", help="The number of iterations per core.")
arg_parser.add_argument("--out_folder", help="The folder to which result files are written")
args = arg_parser.parse_args()
try:
job = deserialize(args.file)
except IOError:
Logger.error("The file specified was not found.")
sys.exit(127)
params = [
{"listGAGen": 250,
"listGACXp" : 1.0,
"listGAMUTp": 0.5,
"listNoList" : 10,
"arcGAGen" : 100,
"arcGACXp" : 0.5,
"arcGAMUTp" : 0.01,
"arcGAn_pairs" : 7,
"arcGAno_p" : 10,
"name" : "ArcGA mutp"
},
{"listGAGen": 250,
"listGACXp" : 1.0,
"listGAMUTp": 0.5,
"listNoList" : 10,
"arcGAGen" : 100,
"arcGACXp" : 0.5,
"arcGAMUTp" : 0.1,
"arcGAn_pairs" : 7,
"arcGAno_p" : 10,
"name" : "ArcGA mutp"
},
{"listGAGen": 250,
"listGACXp" : 1.0,
"listGAMUTp": 0.5,
"listNoList" : 10,
"arcGAGen" : 100,
"arcGACXp" : 0.5,
"arcGAMUTp" : 0.3,
"arcGAn_pairs" : 7,
"arcGAno_p" : 10,
"name" : "ArcGA mutp"
},
{"listGAGen": 250,
"listGACXp" : 1.0,
"listGAMUTp": 0.5,
"listNoList" : 10,
"arcGAGen" : 100,
"arcGACXp" : 0.5,
"arcGAMUTp" : 0.5,
"arcGAn_pairs" : 7,
"arcGAno_p" : 10,
"name" : "ArcGA mutp"
},
]
run_multiple_opt(args, params)