Files
MDAF/SourceCode/AlgorithmAnalyser.py

67 lines
2.6 KiB
Python

# directly running the DOE because existing surrogates can be explored with another workflow
from numpy import random as r
import time
import importlib.util
import multiprocessing
# initialise the logic helpers
r.seed(int(time.time()))
heuristicpath = "/home/remi/Documents/MDAF-GitLAB/SourceCode/SampleAlgorithms/SimmulatedAnnealing.py"
heuristic_name = "SimmulatedAnnealing"
testfunctionpaths = ["/home/remi/Documents/MDAF-GitLAB/SourceCode/TestFunctions/Bukin2.py", "/home/remi/Documents/MDAF-GitLAB/SourceCode/TestFunctions/Bukin4.py", "/home/remi/Documents/MDAF-GitLAB/SourceCode/TestFunctions/Brown.py"]
funcnames = ["Bukin2", "Bukin4", "Brown"]
# testfunctionpaths = ["/home/remi/Documents/MDAF-GitLAB/SourceCode/TestFunctions/Brown.py"]
# funcnames = ["Brown"]
objs = 0
args = {"high": 200, "low": -200, "t": 1000, "p": 0.95}
scale = 2.5
def doe(heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale):
spec = importlib.util.spec_from_file_location(heuristic_name, heuristicpath)
heuristic = importlib.util.module_from_spec(spec)
spec.loader.exec_module(heuristic)
proc = list()
connections = []
#heuristic.MyClass()
for idx, funcpath in enumerate(testfunctionpaths):
testspec = importlib.util.spec_from_file_location(funcnames[idx], funcpath)
func = importlib.util.module_from_spec(testspec)
testspec.loader.exec_module(func)
#func.MyClass()
initpoint = [r.random() * scale, r.random() * scale]
connections.append(multiprocessing.Pipe(duplex=False))
proc.append(multiprocessing.Process(target=heuristic.main, name=funcnames[idx], args=(func, objs, initpoint, args, connections[idx][1])))
responses = []
failedfunctions = []
processtiming = []
for idx,process in enumerate(proc):
# processtiming.append(time.tic())
process.start()
# connections[idx][1].close()
# Waiting for all the runs to be done
for process in proc: process.join()
for idx,conn in enumerate(connections):
if proc[idx].exitcode == 0: responses.append(conn[0].recv())
else:
responses.append("this run was mot successful")
failedfunctions.append((funcnames[idx], proc[idx].exitcode))
conn[0].close()
conn[1].close()
# display output
print("\n\n||||| Responses |||||")
for idx,response in enumerate(responses): print(funcnames[idx] + "____\n" + "started :" + str(initpoint) + "\nEnded :" + str(responses[idx]) + "\n_________________")
doe (heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale)