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ernado/main.py

Created June 29, 2011 11:24
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Profiler for GeneticAlgorythm
Raw
main.py
# -*- coding: utf-8 -*-
import cProfile
from random import randint
from copy import deepcopy
from math import floor
import random
class Organism:
#initiate
def __init__(self, alleles, fitness, likelihood):
self.alleles = alleles
self.fitness = fitness
self.likelihood = likelihood
self.result = 0
def __unicode__(self):
return '%s [%s - %s]' % (self.alleles, self.fitness, self.likelihood)
class CDiophantine:
def __init__(self, coefficients, result):
self.coefficients = coefficients
self.result = result
maxPopulation = 60
organisms = []
def GetGene (self,i):
return self.organisms[i]
def OrganismFitness (self,gene):
gene.result = 0
for i in range (0, len(self.coefficients)):
gene.result += self.coefficients[i]*gene.alleles[i]
gene.fitness = abs(gene.result - self.result)
return gene.fitness
def Fitness (self):
for organism in self.organisms:
organism.fitness = self.OrganismFitness(organism)
if organism.fitness == 0:
return organism
return None
def MultiplyFitness (self):
coefficientSum = 0
for organism in self.organisms:
coefficientSum += 1/float(organism.fitness)
return coefficientSum
def GenerateLikelihoods (self):
last = 0
multiplyFitness = self.MultiplyFitness()
for organism in self.organisms:
last = ((1/float(organism.fitness)/multiplyFitness)*100)
#print '1/%s/%s*100 - %s' % (organism.fitness, multiplyFitness, last)
organism.likelihood = last
def Breed (self, parentOne, parentTwo):
crossover = randint (1,len(self.coefficients)-1)
child = deepcopy(parentOne)
initial = 0
final = len(parentOne.alleles) - 1
if randint (1,100) < 50:
father = parentOne
mother = parentTwo
else:
father = parentTwo
mother = parentOne
child.alleles = mother.alleles[:crossover] + father.alleles[crossover:]
if randint (1,100) < 5:
child.alleles[randint(0,len(child.alleles)-1)] = randint (0,self.result)
return child
def CreateNewOrganisms (self):
#generating new population
tempPopulation = []
for _ in self.organisms:
iterations = 0
father = deepcopy(self.organisms[0])
mother = deepcopy(self.organisms[1])
while father.alleles == mother.alleles:
father = self.WeightedChoice()
mother = self.WeightedChoice()
iterations+=1
if iterations > 35:
break
kid = self.Breed(father,mother)
tempPopulation.append(kid)
self.organisms = tempPopulation
def WeightedChoice (self):
list = []
for organism in self.organisms:
list.append((organism.likelihood,organism))
list = sorted((random.random() * x[0], x[1]) for x in list)
return list[-1][1]
def AverageFitness (self):
sum = 0
for organism in self.organisms:
sum += organism.fitness
return float(sum)/len(self.organisms)
def AverageLikelihoods (self):
sum = 0
for organism in self.organisms:
sum += organism.likelihood
return sum/len(self.organisms)
def Solve (self):
solution = None
for i in range(0,self.maxPopulation):
alleles = []
#
for j in range(0, len(self.coefficients)):
alleles.append(randint(0, self.result))
self.organisms.append(Organism(alleles,0,0))
solution = self.Fitness()
if solution:
return solution.alleles
iterations = 0
while not solution and iterations <3000:
self.GenerateLikelihoods()
self.CreateNewOrganisms()
solution = self.Fitness()
if solution:
print 'SOLUTION FOUND IN %s ITERATIONS' % iterations
return solution.alleles
iterations += 1
return -1
if __name__ == "__main__":
diophantine = CDiophantine ([1,2,3,4],141)
cProfile.run('diophantine.Solve()')
#print diophantine.Solve()
Raw
profiler
#Profiler for Solve
#maxPopulation = 60
#diophantine = CDiophantine ([1,2,3,4],141)
D:\Python27\python.exe C:/Users/Ernado/PycharmProjects/GeneticAlgorythm/main.py
SOLUTION FOUND IN 43 ITERATIONS
12292081 function calls (12189121 primitive calls) in 7.381 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 7.381 7.381 <string>:1(<module>)
110880/7920 0.262 0.000 0.613 0.000 copy.py:145(deepcopy)
87120 0.014 0.000 0.014 0.000 copy.py:198(_deepcopy_atomic)
7920 0.031 0.000 0.190 0.000 copy.py:226(_deepcopy_list)
7920 0.040 0.000 0.479 0.000 copy.py:253(_deepcopy_dict)
110880 0.103 0.000 0.136 0.000 copy.py:267(_keep_alive)
7920 0.029 0.000 0.578 0.000 copy.py:283(_deepcopy_inst)
60 0.000 0.000 0.000 0.000 main.py:10(__init__)
1 0.001 0.001 7.381 7.381 main.py:110(Solve)
2686 0.008 0.000 0.010 0.000 main.py:28(OrganismFitness)
45 0.002 0.000 0.011 0.000 main.py:35(Fitness)
44 0.001 0.000 0.001 0.000 main.py:43(MultiplyFitness)
44 0.001 0.000 0.003 0.000 main.py:49(GenerateLikelihoods)
2640 0.016 0.000 0.257 0.000 main.py:57(Breed)
44 0.168 0.004 7.366 0.167 main.py:73(CreateNewOrganisms)
61502 1.403 0.000 6.541 0.000 main.py:90(WeightedChoice)
3751622 1.913 0.000 2.371 0.000 main.py:94(<genexpr>)
8380 0.019 0.000 0.020 0.000 random.py:173(randrange)
8380 0.007 0.000 0.027 0.000 random.py:237(randint)
2686 0.000 0.000 0.000 0.000 {abs}
31680 0.034 0.000 0.034 0.000 {hasattr}
253440 0.031 0.000 0.031 0.000 {id}
8136 0.001 0.000 0.001 0.000 {len}
3827700 0.488 0.000 0.488 0.000 {method 'append' of 'list' objects}
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
221760 0.039 0.000 0.039 0.000 {method 'get' of 'dict' objects}
7920 0.002 0.000 0.002 0.000 {method 'iteritems' of 'dict' objects}
3698500 0.459 0.000 0.459 0.000 {method 'random' of '_random.Random' objects}
7920 0.005 0.000 0.005 0.000 {method 'update' of 'dict' objects}
2747 0.001 0.000 0.001 0.000 {range}
61502 2.302 0.000 4.674 0.000 {sorted}
Raw
profiler2
#maxPopulation = 120
SOLUTION FOUND IN 105 ITERATIONS
198845337 function calls (198349257 primitive calls) in 123.613 seconds
Ordered by: standard name
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 123.613 123.613 <string>:1(<module>)
534240/38160 1.295 0.000 3.085 0.000 copy.py:145(deepcopy)
419040 0.066 0.000 0.066 0.000 copy.py:198(_deepcopy_atomic)
38160 0.156 0.000 0.964 0.000 copy.py:226(_deepcopy_list)
38160 0.204 0.000 2.392 0.000 copy.py:253(_deepcopy_dict)
533520 0.524 0.000 0.689 0.000 copy.py:267(_keep_alive)
38160 0.155 0.000 2.905 0.000 copy.py:283(_deepcopy_inst)
120 0.000 0.000 0.000 0.000 main.py:10(__init__)
1 0.001 0.001 123.613 123.613 main.py:110(Solve)
12797 0.037 0.000 0.045 0.000 main.py:28(OrganismFitness)
107 0.007 0.000 0.053 0.000 main.py:35(Fitness)
106 0.006 0.000 0.006 0.000 main.py:43(MultiplyFitness)
106 0.007 0.000 0.013 0.000 main.py:49(GenerateLikelihoods)
12720 0.092 0.000 1.370 0.000 main.py:57(Breed)
106 2.533 0.024 123.545 1.166 main.py:73(CreateNewOrganisms)
534038 24.098 0.000 117.678 0.000 main.py:90(WeightedChoice)
64618598 33.775 0.000 41.681 0.000 main.py:94(<genexpr>)
39716 0.103 0.000 0.109 0.000 random.py:173(randrange)
39716 0.040 0.000 0.149 0.000 random.py:237(randint)
12797 0.002 0.000 0.002 0.000 {abs}
152640 0.173 0.000 0.173 0.000 {hasattr}
1220400 0.160 0.000 0.160 0.000 {id}
38895 0.007 0.000 0.007 0.000 {len}
64745880 7.668 0.000 7.668 0.000 {method 'append' of 'list' objects}
1 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1067760 0.200 0.000 0.200 0.000 {method 'get' of 'dict' objects}
38160 0.010 0.000 0.010 0.000 {method 'iteritems' of 'dict' objects}
64124276 7.913 0.000 7.913 0.000 {method 'random' of '_random.Random' objects}
38160 0.026 0.000 0.026 0.000 {method 'update' of 'dict' objects}
12918 0.005 0.000 0.005 0.000 {range}
534038 44.350 0.000 86.031 0.000 {sorted}
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