Source Code for Module Bio.GA.Crossover.Uniform

 1  """Perform uniform crossovers between the genomes of two organisms. 
 2   
 3   
 4  genome 1 --       A B C D E F G 
 5                    .   . .   . 
 6  genome 2 --       a b c d e f g 
 7   
 8  After crossover: 
 9   
10  new genome 1 --  a B c d E f G 
11  new genome 2 --  A b C D e F g 
12   
13  Uniform Crossover is a standard crossover technique for 
14  rapid mutation-behavior. 
15  """ 
16  # standard modules 
17  import random 
18   
19   
20 -class UniformCrossover(object): 
21      """Perform single point crossover between genomes at some defined rates. 
22   
23      This performs a single crossover between two genomes at some 
24      defined frequency. The location of the crossover is chosen randomly 
25      if the crossover meets the probability to occur. 
26      """ 
27 -    def __init__(self, crossover_prob = .1, uniform_prob = 0.7): 
28          """Initialize to do uniform crossover at the specified probability and frequency. 
29          """ 
30          self._crossover_prob = crossover_prob 
31          self._uniform_prob = uniform_prob 
32          return 
33   
34 -    def do_crossover(self, org_1, org_2): 
35          """Potentially do a crossover between the two organisms. 
36          """ 
37          new_org_1 = org_1.copy() 
38          new_org_2 = org_2.copy() 
39   
40          # determine if we have a crossover 
41          crossover_chance = random.random() 
42          if crossover_chance <= self._crossover_prob: 
43              minlen = min(len(new_org_1.genome),len(new_org_2.genome)) 
44              for i in range( minlen ): 
45                  uniform_chance = random.random() 
46                  if uniform_chance <= self._uniform_prob: 
47                      # cycle element 
48                      temp = new_org_1.genome[i] 
49                      new_org_1.genome[i] = new_org_2.genome[i] 
50                      new_org_2.genome[i] = temp 
51   
52          return new_org_1, new_org_2 
53