CDE

Task/Evolutionary-algorithm/Python/evolutionary-algorithm-1.py

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+from string import ascii_uppercase
+from random import choice, random
+
+target  = list("METHINKS IT IS LIKE A WEASEL")
+charset = ascii_uppercase + ' '
+parent  = [choice(charset) for _ in range(len(target))]
+minmutaterate  = .09
+C = range(100)
+
+perfectfitness = float(len(target))
+def fitness(trial):
+    'Sum of matching chars by position'
+    return sum(t==h for t,h in zip(trial, target))
+
+def mutaterate():
+    'Less mutation the closer the fit of the parent'
+    return 1-((perfectfitness - fitness(parent)) / perfectfitness * (1 - minmutaterate))
+
+def mutate(parent, rate):
+    return [(ch if random() <= rate else choice(charset)) for ch in parent]
+
+def que():
+    '(from the favourite saying of Manuel in Fawlty Towers)'
+    print ("#%-4i, fitness: %4.1f%%, '%s'" %
+           (iterations, fitness(parent)*100./perfectfitness, ''.join(parent)))
+
+iterations = 0
+while parent != target:
+    rate =  mutaterate()
+    iterations += 1
+    if iterations % 100 == 0: que()
+    copies = [ mutate(parent, rate) for _ in C ]  + [parent]
+    parent = max(copies, key=fitness)
+print ()
+que()