def test_Genetic_SelectionVals(self):
'''
Testing that all the values are as expected, a percentage of their value vs the total value, and that they are in increasing order
'''
selectVals = RouteCalc.Wrap_CalcRelativeFitness(self.Population)
self.assertEqual(self.Pop_Size, len(selectVals))
selectMult = RouteCalc.GetSelectionMult()
lastVal = selectMult * self.Pop_Size
self.assertAlmostEqual(lastVal, selectVals[-1])
popSum = sum([route.Fitness for route in self.Population])
firstVal = self.Population[0].Fitness / popSum * lastVal
self.assertEqual(firstVal, selectVals[0])
for i in range(500):
with self.subTest(i=i):
index = random.randrange(1, self.Pop_Size - 1)
randSelectVal = selectVals[index]
randRoute = self.Population[index]
sumToIndex = sum(
[route.Fitness for route in self.Population[:index + 1]])
calcVal = (sumToIndex / popSum) * lastVal
self.assertAlmostEqual(calcVal, randSelectVal)
self.assertListEqual(selectVals, sorted(selectVals))
def test_Genetic_StartBadRoutelength(self):
#Assert passing a route length 3 or over 15 raises exception for fittype.EvenSplit
for routeLen in range(3):
with self.subTest(routeLen=routeLen):
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(self.Pop_Size,
self.All_Systems, routeLen,
True, FitnessType.EvenSplit)
for routeLen in range(16, 19):
with self.subTest(routeLen=routeLen):
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(self.Pop_Size,
self.All_Systems, routeLen,
True, FitnessType.EvenSplit)
#FirstOver should throw exception on routes under len 6 and over 35
for routeLen in range(6):
with self.subTest(routeLen=routeLen):
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(self.Pop_Size,
self.All_Systems, routeLen,
True, FitnessType.FirstOver)
for routeLen in range(36, 39):
with self.subTest(routeLen=routeLen):
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(self.Pop_Size,
self.All_Systems, routeLen,
True, FitnessType.FirstOver)
def test_Genetic_MutateSpecial(self):
'''
Test the special case where number of valid systems is equal to route length
'''
tempValidSystems = self.All_Systems[:self.Route_Length]
RouteCalc.SetValidSystems(tempValidSystems)
systemLists = routecalc.GenerateSystemLists(self.Pop_Size,
self.Route_Length,
tempValidSystems)
for systemList in systemLists:
with self.subTest(systemList=systemList):
mutatedList = RouteCalc.Wrap_Mutate(systemList)
self.failIfEqual(systemList, mutatedList)
def test_Genetic_Reproduce(self):
'''
Test that children generated by the reproduce function are not the same.
'''
#TODO: Will still fail sometimes if reproduce function shuffles the same way twice
selectVals = RouteCalc.Wrap_CalcRelativeFitness(self.Population)
for reproNum in range(self.Pop_Size):
with self.subTest(reproNum=reproNum):
children = RouteCalc.Wrap_Reproduce(self.Population,
selectVals)
self.assertEqual(len(children), 2,
"RouteCalc.Repro must create 2 children")
self.failIfEqual(children[0], children[1],
"Generated children must be different")
def CheckPerformance(cls, systemsList: list, fitType: FitnessType):
maxTests = 10
minPopSize = 300
maxPopSize = 300
popSizeStep = 50
popSizes = range(minPopSize, maxPopSize + 1, popSizeStep)
minLength = 8
maxLength = 8
lengths = range(minLength, maxLength + 1, 1)
print("\nFitness Type: {0}".format(fitType.name))
for routeLength in lengths:
for popSize in popSizes:
stats = PerformanceMetrics(routeLength, popSize)
for testNum in range(maxTests):
solved = False
startTime = time.time()
bestRoute, numGenerations = RouteCalc.StartGeneticSolver(
systemsList, routeLength, True, fitType)
endTime = time.time()
elapsed = endTime - startTime
if bestRoute.Fitness >= RouteCalc.Route_Cutoff:
stats.Types.append(bestRoute.Route_Type)
stats.Values.append(bestRoute.Fitness)
solved = True
stats.Times.append(elapsed)
stats.Solved.append(solved)
stats.Gens.append(numGenerations)
print(stats)
def __RunGenetic(systems: list, routeLength: int, fitType: FitnessType,
silent: bool, stopShort: bool):
exitTestLoop = False
runNum = 0
maxRuns = 5
geneticStart = time.time()
bestRoute = None
while not exitTestLoop and runNum < maxRuns:
runNum += 1
print("Run: {0}".format(runNum))
bestRoute, numGenerations = RouteCalc.StartGeneticSolver(
systems, routeLength, silent, fitType)
geneticEnd = time.time()
if bestRoute.Fitness >= RouteCalc.Route_Cutoff or stopShort:
exitTestLoop = True
if bestRoute.Fitness < RouteCalc.Route_Cutoff:
print("No good route found")
print(bestRoute)
bestRoute.DisplayInConsole()
print("Generations: {0}".format(numGenerations))
print("Time since start: {0:.5f}s".format((geneticEnd - geneticStart)))
bestRoute.DrawRoute()
#Eventually take this out once im satisfied with hold times
for k, v in bestRoute.Hold_Times.items():
print(k.System_Name, " -> ", v)
def test_Genetic_StartBadArgs(self):
#Assert empty system list raises exception
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(500, [], 20, True, self.Fit_Type)
#Assert passing a pop size under 3 raises exception
for popSize in range(3):
with self.subTest(popSize=popSize):
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(popSize, self.All_Systems, 6,
True, self.Fit_Type)
#Assert fail if there are more systems in the route than in the list of valid systems
with self.assertRaises(Exception):
RouteCalc.StartGeneticSolver(
200, self.All_Systems[:self.Route_Length - 1],
self.Route_Length, True, self.Fit_Type)
def test_Genetic_Mutate(self):
'''
General test to make sure mutate will never return the same system list that we pass to it
'''
systemLists = routecalc.GenerateSystemLists(self.Pop_Size,
self.Route_Length,
self.All_Systems)
for systemList in systemLists:
with self.subTest(systemList=systemList):
mutatedList = RouteCalc.Wrap_Mutate(systemList)
self.failIfEqual(systemList, mutatedList)
def setUp(self):
self.Pop_Size = 300
self.Route_Length = 8
self.Fit_Type = FitnessType.FirstOver
RouteCalc.SetValidSystems(self.All_Systems)
self.Population = [
EDRareRoute(systems, self.Fit_Type)
for systems in routecalc.GenerateSystemLists(
self.Pop_Size, self.Route_Length, self.All_Systems)
]
def test_Genetic_StartNoArgs(self):
RouteCalc.StartGeneticSolver()