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GA.py
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GA.py
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'''
Copyright {2017} {siddhartha singh | [email protected]}
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
'''
import random,time
import math
from dna import *
class population:
def __init__(self):
self.dna = DNA()
self.fitness = 0 # fitness is how good the creature is in finding the goal into the simulation
self.objectType = ' '
self.objectId = -1
self.health = 100 # health is physical health of the creature
self.state = 'alive'
def randomize(self):
self.fitness = 0
self.health = 100
self.dna.randomDna(8)
class GA:
def __init__(self):
#======================================
self.Population = []
self.initialPopulation = 10
self.genration = 0
self.mutationRate = 10 # in percentage
self.crossOverRate = 2 # in percentage
#======================================
def createRandomPopulation(self,n):
for i in range(0,n):
p = population()
p.randomize()
self.Population.append(p)
def Genration(self):
self.genration += 1
def naturalSelection(self,task,**args):
# run the GA simulation in physical world
for i in range(0,len(self.Population)):
fit(self.Population[i],task,**args)# pass the fintness function into this
# by default fitness is depends on the time taken by the creature to perform the task
for i in range(0,len(self.Population)):
if self.Population[i].health < 20:
self.Population[i].state = 'dead'
def ShowFitness(self):
for i in range(0,self.initialPopulation):
self.Population[i].CalFitness()
def findBestFitesest(self):
parent1 = parent2 = self.Population[0]
for i in range(1,self.initialPopulation):
#print(parent1.fitness," | ",parent2.fitness," || ",Population[i].fitness)
if parent1.fitness < self.Population[i].fitness:
parent2 = parent1
parent1 = self.Population[i]
elif parent2.fitness < self.Population[i].fitness:
parent2 = self.Population[i]
def crossOverEngine(self):
pass
def mutation(self):
pass
def regenration(self):
pass
def main():
print 'Starting genetic sequence'
createRandomPopulation(5)
Genration()
if __name__ == '__main__':
main()