def areItemsSwitchable(self, chromosome, periodGene, altPeriod,
periodGeneLowerLimit, periodGeneUpperLimit):
"""
"""
if chromosome.stringIdentifier[altPeriod] > 0:
altPeriodGene = chromosome.genesByPeriod[altPeriod]
altPeriodGeneLowerLimit, altPeriodGeneUpperLimit = Chromosome.geneLowerUpperLimit(
chromosome, altPeriodGene)
if (periodGeneLowerLimit <= altPeriod
and altPeriod < periodGeneUpperLimit) and (
altPeriodGeneLowerLimit <= periodGene.period
and periodGene.period < altPeriodGeneUpperLimit):
return True
else:
if (periodGeneLowerLimit <= altPeriod
and altPeriod < periodGeneUpperLimit):
return True
return False
def searchIndividu(self, chromosome, strategy):
"""
"""
results = []
if strategy == "absolute_mutation":
if self._visitedNodes[chromosome.stringIdentifier] is not None:
return None
print("chrom : ", chromosome, self.searchDepth)
# shuffledPeriods = [(period, item) for period, item in enumerate(chromosome.stringIdentifier)]
# print("shuffledPeriods : ", shuffledPeriods, chromosome.stringIdentifier)
# random.shuffle(shuffledPeriods)
orderedGenes = [
gene for itemGenes in chromosome.dnaArray for gene in itemGenes
if gene.cost > 0
]
# orderedGenes.sort(key=lambda gene: gene.cost, reverse= True)
random.shuffle(orderedGenes)
# print("ordered : ", orderedGenes)
for periodGene in orderedGenes:
print("gene : ", periodGene)
periodGeneLowerLimit, periodGeneUpperLimit = Chromosome.geneLowerUpperLimit(
chromosome, periodGene)
i = 1
backwardPeriod, forwardPeriod = periodGene.period, periodGene.period
while True:
if forwardPeriod is not None:
forwardPeriod = periodGene.period + i
if backwardPeriod is not None:
backwardPeriod = periodGene.period - i
if backwardPeriod is not None and backwardPeriod < 0:
backwardPeriod = None
if forwardPeriod is not None and forwardPeriod > InputDataInstance.instance.nPeriods - 1:
forwardPeriod = None
# print(backwardPeriod, forwardPeriod)
if backwardPeriod is not None:
if self.areItemsSwitchable(chromosome, periodGene,
backwardPeriod,
periodGeneLowerLimit,
periodGeneUpperLimit):
evaluationData = self.evaluateItemsSwitch(
chromosome, periodGene, backwardPeriod)
if strategy == "random_mutation":
self.result = self.switchItems(
chromosome, periodGene, backwardPeriod,
evaluationData)
return None
if strategy == "population":
results.append(
self.switchItems(chromosome, periodGene,
backwardPeriod,
evaluationData))
if strategy == "positive_mutation":
if evaluationData["variance"] > 0:
self.result = self.switchItems(
chromosome, periodGene, backwardPeriod,
evaluationData)
return None
if strategy == "simple_mutation":
if evaluationData["variance"] > 0:
self.result = self.switchItems(
chromosome, periodGene, backwardPeriod,
evaluationData)
return None
results.append(evaluationData)
if strategy == "absolute_mutation":
if evaluationData["variance"] > 0:
results.append(evaluationData)
else:
backwardPeriod = None
if forwardPeriod is not None:
if self.areItemsSwitchable(chromosome, periodGene,
forwardPeriod,
periodGeneLowerLimit,
periodGeneUpperLimit):
evaluationData = self.evaluateItemsSwitch(
chromosome, periodGene, forwardPeriod)
if strategy == "random_mutation":
self.result = self.switchItems(
chromosome, periodGene, forwardPeriod,
evaluationData)
return None
if strategy == "population":
results.append(
self.switchItems(chromosome, periodGene,
forwardPeriod,
evaluationData))
if strategy == "positive_mutation":
if evaluationData["variance"] > 0:
self.result = self.switchItems(
chromosome, periodGene, forwardPeriod,
evaluationData)
return None
if strategy == "simple_mutation":
if evaluationData["variance"] > 0:
self.result = self.switchItems(
chromosome, periodGene, forwardPeriod,
evaluationData)
return None
results.append(evaluationData)
if strategy == "absolute_mutation":
if evaluationData["variance"] > 0:
results.append(evaluationData)
else:
forwardPeriod = None
if backwardPeriod is None and forwardPeriod is None:
break
i += 1
if strategy == "absolute_mutation":
if len(results) > 0:
self.searchDepth += 1
self._visitedNodes[chromosome.stringIdentifier] = 1
self.searchIndividu(results[-1], strategy)
if self._stopSearchEvent.is_set():
return None
if strategy == "absolute_mutation":
if len(results) == 0:
self.result = chromosome
self._stopSearchEvent.set()
return None
elif strategy == "simple_mutation":
# self.result = np.random.choice(results)
return None
elif strategy == "population":
self.result = results
return None