def doTests(self):
sc2 = open(DATA_PREFIX + SUMMARY_RESULTS + DATA_SUFFIX, 'w')
# Main control loop
representatives = [] # List of resulting final generations (stat boxe datatype)
for problem in self.tests.problems:
print "# " * 30
for algorithm in self.tests.algorithms:
# Initialize Data file for recording summary information [for just this problem + algorithm]
backend = problem.name + "_" + algorithm.name + ".txt"
# Decision Data
# filename = problem.name + "-p" + str(self.configurations["Universal"]["Population_Size"]) + "-d" + str(len(problem.decisions)) + "-o" + str(len(problem.objectives))+"_"+algorithm.name+DATA_SUFFIX
filename = problem.name + "-p" + str(100) + "-d" + str(len(problem.decisions)) + "-o" + str(len(problem.objectives))+"_"+algorithm.name+DATA_SUFFIX
dbt = open(DATA_PREFIX + DECISION_BIN_TABLE + "_" + filename, 'w')
sr = open(DATA_PREFIX + SUMMARY_RESULTS + filename, 'w')
rrs = open(DATA_PREFIX + RRS_TABLE + "_" + filename, 'w')
# Results Record:
# # # Every generation
# # # Decisions + Objectives
# Summary Record
# - Best Generation Only
# - Number of Evaluations + Aggregated Objective Score
# -
fa = open("Data/results_"+filename, 'w')
strings = ["NumEval"] \
+ [obj.name + "_median,(%chg),"
+ obj.name + "_spread" for obj in problem.objectives]\
+ ["IBD,(%chg), IBS"] + ["IGD,(%chg)"]
for s in strings: fa.write(s + ",")
fa.write("\n")
fa.close()
print "+ " * 30
# Repeat Core
for repeat in range(self.configurations["Universal"]["Repeats"]):
print "#<-------|" + problem.name + " + " + algorithm.name + " + " + str(repeat) + "|------->#"
# Run
start = time.time()
statBox = jmoo_evo(problem, algorithm, self.configurations)
end = time.time()
# Find best generation
representative = statBox.box[0]
for r,rep in enumerate(statBox.box):
# for indi in rep.population:
# print indi
if rep.IBD < representative.IBD:
representative = statBox.box[r]
representatives.append(representative)
# Decision Bin Data
s = ""
for row in representative.population:
for dec in row.decisionValues:
s += str("%10.2f" % dec) + ","
if row.valid:
for obj in row.fitness.fitness:
s += str("%10.2f" % obj) + ","
else:
for obj in problem.objectives:
s += "?" + ","
s += str(representative.numEval) + ","
s += "\n"
dbt.write(s)
baseline = problem.referencePoint
s = ""
for row in representative.population:
#if not row.valid:
# row.evaluate()
if row.valid:
for o,base,obj in zip(row.fitness.fitness, baseline, problem.objectives ):
c = percentChange(o, base, obj.lismore, obj.low, obj.up)
s += c + ","
s += str(representative.numEval) + ","
for o,base,obj in zip(row.fitness.fitness, baseline, problem.objectives ):
c = str("%12.2f" % o)
s += c + ","
s += "\n"
rrs.write(s)
#output every generation
for box in [representative]:
s_out = ""
s_out += str(self.configurations["Universal"]["Population_Size"]) + ","
s_out += problem.name + "-p" + str(self.configurations["Universal"]["Population_Size"]) + "-d" + str(len(problem.decisions)) + "-o" + str(len(problem.objectives)) + ","
s_out += algorithm.name + ","
s_out += str(box.numEval) + ","
for low in representative.fitnessMedians:
s_out += str("%10.2f" % low) + ","
s_out += str("%10.2f" % box.IBD) + "," + str("%10.2f" % box.IBS) + "," + str((end-start))
sr.write(s_out + "\n")
sc2.write(s_out + "\n")
# Finish
print " # Finished: Celebrate! # " #+ " Time taken: " + str("%10.5f" % (end-start)) + " seconds."
def doTests(self):
sc2 = open(DATA_PREFIX + SUMMARY_RESULTS + DATA_SUFFIX, 'w')
# Main control loop
representatives = [
] # List of resulting final generations (stat boxe datatype)
record_string = "<Experiment>\n"
for problem in self.tests.problems:
record_string += "<Problem name = '" + problem.name + "'>\n"
for algorithm in self.tests.algorithms:
record_string += "<Algorithm name = '" + algorithm.name + "'>\n"
print "#<------- " + problem.name + " + " + algorithm.name + " ------->#"
# Initialize Data file for recording summary information [for just this problem + algorithm]
backend = problem.name + "_" + algorithm.name + ".txt"
# Decision Data
filename = problem.name + "-p" + str(
self.configurations["Universal"]["Population_Size"]
) + "-d" + str(len(problem.decisions)) + "-o" + str(
len(problem.objectives)
) + "_" + algorithm.name + DATA_SUFFIX
dbt = open(DATA_PREFIX + DECISION_BIN_TABLE + "_" + filename,
'w')
sr = open(DATA_PREFIX + SUMMARY_RESULTS + filename, 'w')
rrs = open(DATA_PREFIX + RRS_TABLE + "_" + filename, 'w')
# Results Record:
# # # Every generation
# # # Decisions + Objectives
# Summary Record
# - Best Generation Only
# - Number of Evaluations + Aggregated Objective Score
# -
fa = open("Data/results_" + filename, 'w')
strings = ["NumEval"] \
+ [obj.name + "_median,(%chg),"
+ obj.name + "_spread" for obj in problem.objectives] \
+ ["IBD,(%chg), IBS"] + ["IGD,(%chg)"]
for s in strings:
fa.write(s + ",")
fa.write("\n")
fa.close()
IGD_Values = []
# Repeat Core
for repeat in range(
self.configurations["Universal"]["Repeats"]):
foldername = "./RawData/PopulationArchives/" + algorithm.name + "_" + problem.name + "/" + str(
repeat)
import os
if not os.path.exists(foldername):
os.makedirs(foldername)
# Run
record_string += "<Run id = '" + str(repeat + 1) + "'>\n"
start = time.time()
statBox = jmoo_evo(problem, algorithm, self.configurations)
end = time.time()
# Find best generation
representative = statBox.box[0]
for r, rep in enumerate(statBox.box):
# for indi in rep.population:
# print indi
if rep.IBD < representative.IBD:
representative = statBox.box[r]
representatives.append(representative)
# Decision Bin Data
s = ""
for row in representative.population:
for dec in row.decisionValues:
s += str("%10.2f" % dec) + ","
if row.valid:
for obj in row.fitness.fitness:
s += str("%10.2f" % obj) + ","
else:
for obj in problem.objectives:
s += "?" + ","
s += str(representative.numEval) + ","
s += "\n"
dbt.write(s)
baseline = problem.referencePoint
s = ""
for row in representative.population:
# if not row.valid:
# row.evaluate()
if row.valid:
for o, base, obj in zip(row.fitness.fitness,
baseline,
problem.objectives):
c = percentChange(o, base, obj.lismore,
obj.low, obj.up)
s += c + ","
s += str(representative.numEval) + ","
for o, base, obj in zip(row.fitness.fitness,
baseline,
problem.objectives):
c = str("%12.2f" % o)
s += c + ","
s += "\n"
rrs.write(s)
# output every generation
for box in [representative]:
s_out = ""
s_out += str(self.configurations["Universal"]
["Population_Size"]) + ","
s_out += problem.name + "-p" + str(
self.configurations["Universal"]["Population_Size"]
) + "-d" + str(len(problem.decisions)) + "-o" + str(
len(problem.objectives)) + ","
s_out += algorithm.name + ","
s_out += str(box.numEval) + ","
for low in representative.fitnessMedians:
s_out += str("%10.2f" % low) + ","
s_out += str("%10.2f" % box.IBD) + "," + str(
"%10.2f" % box.IBS) + "," + str((end - start))
sr.write(s_out + "\n")
sc2.write(s_out + "\n")
record_string += "<Summary>\n"
record_string += "<NumEvals>" + str(
representative.numEval) + "</NumEvals>\n"
record_string += "<RunTime>" + str(
(end - start)) + "</RunTime>\n"
record_string += "<IBD>" + str(box.IBD) + "</IBD>\n"
record_string += "<IBS>" + str(box.IBS) + "</IBS>\n"
for i in range(len(problem.objectives)):
record_string += "<" + problem.objectives[
i].name + ">" + str(
representative.fitnessMedians[i]
) + "</" + problem.objectives[i].name + ">\n"
record_string += "</Summary>"
# Finish
record_string += "</Run>\n"
print " # Finished: Celebrate! # " + " Time taken: " + str(
"%10.5f" % (end - start)) + " seconds."
record_string += "</Algorithm>\n"
record_string += "</Problem>\n"
record_string += "</Experiment>\n"
from time import strftime
date_folder_prefix = strftime("%m-%d-%Y")
if not os.path.isdir('./RawData/ExperimentalRecords/' +
date_folder_prefix):
os.makedirs('./RawData/ExperimentalRecords/' + date_folder_prefix)
record_number = len([
name for name in os.listdir('./RawData/ExperimentalRecords/' +
date_folder_prefix)
]) + 1
filename = './RawData/ExperimentalRecords/' + date_folder_prefix + '/Record' + "_" + str(
"%02d" % record_number) + "_" + 'ExperimentRecords.xml'
zOutFile = open(filename, 'w')
zOutFile.write(record_string)
def doSingleTest(self, problem, algorithm, repeat_index):
"""
import os
filename = problem.name + "-p" + str(self.configurations["Universal"]["Population_Size"]) + "-d" + str(
len(problem.decisions)) + "-o" + str(
len(problem.objectives)) + "_" + algorithm.name + DATA_SUFFIX
results_file = "Data/results_" + filename
if not os.path.isfile(results_file):
fa = open("Data/results_" + filename, 'w')
strings = ["NumEval"] \
+ [obj.name + "_median,(%chg),"
+ obj.name + "_spread" for obj in problem.objectives] \
+ ["IBD,(%chg), IBS"] + ["IGD,(%chg)"]
for s in strings: fa.write(s + ",")
fa.write("\n")
fa.close()
"""
print "#<-- " + problem.name + " + " + algorithm.name + " ---repeat: " + str(repeat_index) + "---->#"
foldername = "./RawData/PopulationArchives/" + algorithm.name + "_" + problem.name + "/" + str(repeat_index)
import os
if not os.path.exists(foldername):
os.makedirs(foldername)
representatives = [] # List of resulting final generations (stat box datatype)
record_string = "<Run id = '" + str(repeat_index + 1) + "'>\n"
start = time.time()
statBox = jmoo_evo(problem, algorithm, self.configurations, repeat=repeat_index)
end = time.time()
# Find best generation
representative = statBox.box[0]
for r, rep in enumerate(statBox.box):
# for indi in rep.population:
# print indi
if rep.IBD < representative.IBD:
representative = statBox.box[r]
representatives.append(representative)
# Decision Bin Data
s = ""
sr = ""
sc2 = ""
for row in representative.population:
for dec in row.decisionValues:
s += str("%10.2f" % dec) + ","
if row.valid:
for obj in row.fitness.fitness:
s += str("%10.2f" % obj) + ","
else:
for obj in problem.objectives:
s += "?" + ","
s += str(representative.numEval) + ","
s += "\n"
DBT = s
baseline = problem.referencePoint
s = ""
for row in representative.population:
# if not row.valid:
# row.evaluate()
if row.valid:
for o, base, obj in zip(row.fitness.fitness, baseline, problem.objectives):
c = percentChange(o, base, obj.lismore, obj.low, obj.up)
s += c + ","
s += str(representative.numEval) + ","
for o, base, obj in zip(row.fitness.fitness, baseline, problem.objectives):
c = str("%12.2f" % o)
s += c + ","
s += "\n"
RRS = s
# output every generation
for box in [representative]:
s_out = ""
s_out += str(self.configurations["Universal"]["Population_Size"]) + ","
s_out += problem.name + "-p" + str(
self.configurations["Universal"]["Population_Size"]) + "-d" + str(
len(problem.decisions)) + "-o" + str(len(problem.objectives)) + ","
s_out += algorithm.name + ","
s_out += str(box.numEval) + ","
for low in representative.fitnessMedians:
s_out += str("%10.2f" % low) + ","
s_out += str("%10.2f" % box.IBD) + "," + str("%10.2f" % box.IBS) + "," + str((end - start))
sr += (s_out + "\n")
sc2 += (s_out + "\n")
record_string += "<Summary>\n"
record_string += "<NumEvals>" + str(representative.numEval) + "</NumEvals>\n"
record_string += "<RunTime>" + str((end - start)) + "</RunTime>\n"
record_string += "<IBD>" + str(box.IBD) + "</IBD>\n"
record_string += "<IBS>" + str(box.IBS) + "</IBS>\n"
for i in range(len(problem.objectives)):
record_string += "<" + problem.objectives[i].name + ">" + str(
representative.fitnessMedians[i]) + "</" + problem.objectives[i].name + ">\n"
record_string += "</Summary>"
# Finish
record_string += "</Run>\n"
print " # Finished: Celebrate! # " + " Time taken: " + str("%10.5f" % (end - start)) + " seconds."
runs = "./HpcData/" + algorithm.name + "_" + problem.name + "_" + str(repeat_index) + ".rundata"
import pickle
with open(runs, 'w+') as f:
pickle.dump([DBT, RRS, sr, sc2, record_string], f)
def doTests(self):
sc2 = open(DATA_PREFIX + SUMMARY_RESULTS + DATA_SUFFIX, 'w')
# Main control loop
representatives = [
] # List of resulting final generations (stat boxe datatype)
for problem in self.tests.problems:
print "# " * 30
for algorithm in self.tests.algorithms:
# Initialize Data file for recording summary information [for just this problem + algorithm]
backend = problem.name + "_" + algorithm.name + ".txt"
# Decision Data
# filename = problem.name + "-p" + str(self.configurations["Universal"]["Population_Size"]) + "-d" + str(len(problem.decisions)) + "-o" + str(len(problem.objectives))+"_"+algorithm.name+DATA_SUFFIX
filename = problem.name + "-p" + str(100) + "-d" + str(
len(problem.decisions)) + "-o" + str(
len(problem.objectives)
) + "_" + algorithm.name + DATA_SUFFIX
dbt = open(DATA_PREFIX + DECISION_BIN_TABLE + "_" + filename,
'w')
sr = open(DATA_PREFIX + SUMMARY_RESULTS + filename, 'w')
rrs = open(DATA_PREFIX + RRS_TABLE + "_" + filename, 'w')
# Results Record:
# # # Every generation
# # # Decisions + Objectives
# Summary Record
# - Best Generation Only
# - Number of Evaluations + Aggregated Objective Score
# -
fa = open("Data/results_" + filename, 'w')
strings = ["NumEval"] \
+ [obj.name + "_median,(%chg),"
+ obj.name + "_spread" for obj in problem.objectives]\
+ ["IBD,(%chg), IBS"] + ["IGD,(%chg)"]
for s in strings:
fa.write(s + ",")
fa.write("\n")
fa.close()
print "+ " * 30
# Repeat Core
for repeat in range(
self.configurations["Universal"]["Repeats"]):
print "#<-------|" + problem.name + " + " + algorithm.name + " + " + str(
repeat) + "|------->#"
# Run
start = time.time()
statBox = jmoo_evo(problem, algorithm, self.configurations)
end = time.time()
# Find best generation
representative = statBox.box[0]
for r, rep in enumerate(statBox.box):
# for indi in rep.population:
# print indi
if rep.IBD < representative.IBD:
representative = statBox.box[r]
representatives.append(representative)
# Decision Bin Data
s = ""
for row in representative.population:
for dec in row.decisionValues:
s += str("%10.2f" % dec) + ","
if row.valid:
for obj in row.fitness.fitness:
s += str("%10.2f" % obj) + ","
else:
for obj in problem.objectives:
s += "?" + ","
s += str(representative.numEval) + ","
s += "\n"
dbt.write(s)
baseline = problem.referencePoint
s = ""
for row in representative.population:
#if not row.valid:
# row.evaluate()
if row.valid:
for o, base, obj in zip(row.fitness.fitness,
baseline,
problem.objectives):
c = percentChange(o, base, obj.lismore,
obj.low, obj.up)
s += c + ","
s += str(representative.numEval) + ","
for o, base, obj in zip(row.fitness.fitness,
baseline,
problem.objectives):
c = str("%12.2f" % o)
s += c + ","
s += "\n"
rrs.write(s)
#output every generation
for box in [representative]:
s_out = ""
s_out += str(self.configurations["Universal"]
["Population_Size"]) + ","
s_out += problem.name + "-p" + str(
self.configurations["Universal"]["Population_Size"]
) + "-d" + str(len(problem.decisions)) + "-o" + str(
len(problem.objectives)) + ","
s_out += algorithm.name + ","
s_out += str(box.numEval) + ","
for low in representative.fitnessMedians:
s_out += str("%10.2f" % low) + ","
s_out += str("%10.2f" % box.IBD) + "," + str(
"%10.2f" % box.IBS) + "," + str((end - start))
sr.write(s_out + "\n")
sc2.write(s_out + "\n")
# Finish
print " # Finished: Celebrate! # " #+ " Time taken: " + str("%10.5f" % (end-start)) + " seconds."
def doTests(self):
sc2 = open(DATA_PREFIX + SUMMARY_RESULTS + DATA_SUFFIX, 'w')
# Main control loop
representatives = [] # List of resulting final generations (stat box datatype)
record_string = "<Experiment>\n"
for problem in self.tests.problems:
record_string += "<Problem name = '" + problem.name + "'>\n"
for algorithm in self.tests.algorithms:
record_string += "<Algorithm name = '" + algorithm.name + "'>\n"
print "#<------- " + problem.name + " + " + algorithm.name + " ------->#"
# Initialize Data file for recording summary information [for just this problem + algorithm]
backend = problem.name + "_" + algorithm.name + ".txt"
# Decision Data
filename = problem.name + "-p" + str(self.configurations["Universal"]["Population_Size"]) + "-d" + str(
len(problem.decisions)) + "-o" + str(
len(problem.objectives)) + "_" + algorithm.name + DATA_SUFFIX
dbt = open(DATA_PREFIX + DECISION_BIN_TABLE + "_" + filename, 'w')
sr = open(DATA_PREFIX + SUMMARY_RESULTS + filename, 'w')
rrs = open(DATA_PREFIX + RRS_TABLE + "_" + filename, 'w')
# Results Record:
# # # Every generation
# # # Decisions + Objectives
# Summary Record
# - Best Generation Only
# - Number of Evaluations + Aggregated Objective Score
# -
fa = open("Data/results_" + filename, 'w')
strings = ["NumEval"] \
+ [obj.name + "_median,(%chg),"
+ obj.name + "_spread" for obj in problem.objectives] \
+ ["IBD,(%chg), IBS"] + ["IGD,(%chg)"]
for s in strings: fa.write(s + ",")
fa.write("\n")
fa.close()
IGD_Values = []
# Repeat Core
for repeat in range(self.configurations["Universal"]["Repeats"]):
foldername = "./RawData/PopulationArchives/" + algorithm.name + "_" + problem.name + "/" + str(
repeat)
import os
if not os.path.exists(foldername):
os.makedirs(foldername)
# Run
record_string += "<Run id = '" + str(repeat + 1) + "'>\n"
start = time.time()
statBox = jmoo_evo(problem, algorithm, self.configurations)
end = time.time()
# Find best generation
representative = statBox.box[0]
for r, rep in enumerate(statBox.box):
# for indi in rep.population:
# print indi
if rep.IBD < representative.IBD:
representative = statBox.box[r]
representatives.append(representative)
# Decision Bin Data
s = ""
for row in representative.population:
for dec in row.decisionValues:
s += str("%10.2f" % dec) + ","
if row.valid:
for obj in row.fitness.fitness:
s += str("%10.2f" % obj) + ","
else:
for obj in problem.objectives:
s += "?" + ","
s += str(representative.numEval) + ","
s += "\n"
dbt.write(s)
baseline = problem.referencePoint
s = ""
for row in representative.population:
# if not row.valid:
# row.evaluate()
if row.valid:
for o, base, obj in zip(row.fitness.fitness, baseline, problem.objectives):
c = percentChange(o, base, obj.lismore, obj.low, obj.up)
s += c + ","
s += str(representative.numEval) + ","
for o, base, obj in zip(row.fitness.fitness, baseline, problem.objectives):
c = str("%12.2f" % o)
s += c + ","
s += "\n"
rrs.write(s)
# output every generation
for box in [representative]:
s_out = ""
s_out += str(self.configurations["Universal"]["Population_Size"]) + ","
s_out += problem.name + "-p" + str(
self.configurations["Universal"]["Population_Size"]) + "-d" + str(
len(problem.decisions)) + "-o" + str(len(problem.objectives)) + ","
s_out += algorithm.name + ","
s_out += str(box.numEval) + ","
for low in representative.fitnessMedians:
s_out += str("%10.2f" % low) + ","
s_out += str("%10.2f" % box.IBD) + "," + str("%10.2f" % box.IBS) + "," + str((end - start))
sr.write(s_out + "\n")
sc2.write(s_out + "\n")
record_string += "<Summary>\n"
record_string += "<NumEvals>" + str(representative.numEval) + "</NumEvals>\n"
record_string += "<RunTime>" + str((end - start)) + "</RunTime>\n"
record_string += "<IBD>" + str(box.IBD) + "</IBD>\n"
record_string += "<IBS>" + str(box.IBS) + "</IBS>\n"
for i in range(len(problem.objectives)):
record_string += "<" + problem.objectives[i].name + ">" + str(
representative.fitnessMedians[i]) + "</" + problem.objectives[i].name + ">\n"
record_string += "</Summary>"
# Finish
record_string += "</Run>\n"
print " # Finished: Celebrate! # " + " Time taken: " + str("%10.5f" % (end - start)) + " seconds."
record_string += "</Algorithm>\n"
record_string += "</Problem>\n"
record_string += "</Experiment>\n"
from time import strftime
date_folder_prefix = strftime("%m-%d-%Y")
if not os.path.isdir('./RawData/ExperimentalRecords/' + date_folder_prefix):
os.makedirs('./RawData/ExperimentalRecords/' + date_folder_prefix)
record_number = len([name for name in os.listdir('./RawData/ExperimentalRecords/' + date_folder_prefix)]) + 1
filename = './RawData/ExperimentalRecords/' + date_folder_prefix + '/Record' + "_" + str(
"%02d" % record_number) + "_" + 'ExperimentRecords.xml'
zOutFile = open(filename, 'w')
zOutFile.write(record_string)