remi/MDAF
1
0
Fork 0
mirror of https://github.com/ejeanboris/MDAF.git synced 2025-04-29 12:02:31 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

testing the stats

Browse Source
This commit is contained in:
Remi Ehounou
2021-05-15 21:37:16 -04:00
parent 466d7ec7d6
commit e3ff427d76
2 changed files with 11 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

18
SourceCode/AlgorithmAnalyser.py
View File

@ -2,7 +2,6 @@
from os import path
import importlib.util
import multiprocessing
import pathos.multiprocessing as mp
import time
import re
from numpy import random as r
@ -78,7 +77,7 @@ def measure(heuristicpath, heuristic_name, funcpath, funcname, objs, args, scale
# Defining random initial points to start testing the algorithms
initpoints = [[r.random() * scale, r.random() * scale] for run in range(3)] #update the inner as [r.random() * scale for i in range(testfuncDimmensions)]
initpoints = [[r.random() * scale, r.random() * scale] for run in range(30)] #update the inner as [r.random() * scale for i in range(testfuncDimmensions)]
# building the iterable arguments
partfunc = partial(simulate, heuristic_name, heuristicpath, funcname, funcpath, objs, args)
@ -97,7 +96,7 @@ def measure(heuristicpath, heuristic_name, funcpath, funcname, objs, args, scale
results['numCalls'] = array([statistics.mean(numCalls), statistics.stdev(numCalls)])
results['convRate'] = array([statistics.mean(converged), statistics.stdev(converged)])
connection.send(results)
connection.send((results,newRun))
def writerepresentation(funcpath, charas):
# Save a backup copy of the function file
@ -237,7 +236,6 @@ def representfunc(funcpath):
def doe(heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale):
# logic variables to deal with the processes
proc = []
connections = {}
@ -271,10 +269,14 @@ def doe(heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args,
failedfunctions[run] = process.exitcode
connections[run][0].close()
connections[run][1].close()
# display output
print("\n\n||||| Responses: [mean,stdDev] |||||")
for process in proc: print(process.name + "____\n" + str(responses[process.name]) + "\n_________________")
for process in proc: print(process.name + "____\n" + str(responses[process.name][0]) + "\n_________________")
#return output
return responses
if __name__ == '__main__':
heuristicpath = "SampleAlgorithms/SimmulatedAnnealing.py"
@ -288,8 +290,8 @@ if __name__ == '__main__':
args = {"high": 200, "low": -200, "t": 1000, "p": 0.95}
scale = 1
doe (heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale)
data = doe (heuristicpath, heuristic_name, testfunctionpaths, funcnames, objs, args, scale)
print(data['Bukin2'][1][2])
#representfunc("TestFunctions/Bukin6.py")

2
SourceCode/SampleAlgorithms/SimmulatedAnnealing.py
View File

@ -72,7 +72,7 @@ def main(func, obj, S, args):
route.append(Best[:])
print(route)
if t < 0 or Quality(Best,y,func) > 50:
if t < 0 or Quality(Best,y,func) > 200:
break
#print('the Best Quality obtained was:{}'.format(Quality(Best,y)))
print("Final Quality is: {}".format(Quality(Best,y,func)))