starting over

1 files changed, 39 insertions, 39 deletions

diff --git a/lib/selection.py b/lib/selection.py
index 22a0ea9..48947cc 100644
--- a/lib/selection.py
+++ b/lib/selection.py
@@ -1,6 +1,6 @@
 # DAWKINS' BLIND WATCHMAKER -- "METHINKS IT IS LIKE A WEASEL" EXAMPLE
 #
-# Start with a random phrase. Successively:
+# Start with a random phrase.  Successively:
 # Breed a next generation by copying with small mutations.
 # Choose the member of the next generation that most closely resembles
 # the target phrase to start breeding the next generation.
@@ -16,57 +16,57 @@ Alphabet = ' abcdefghijklmnopqrstuvwxyz'
 GenerationSize = 100
 MutationChance = 1.0/28.0
 
-IndexSet = range(len(Target)) # Used to speed up loops
+IndexSet = range(len(Target))	# Used to speed up loops
 
 def choice(sequence):
- n = len(sequence)
- i = int(random() * float(n)) % n
- return sequence[i]
+	n = len(sequence)
+	i = int(random() * float(n)) % n
+	return sequence[i]
 
 def random_phrase():
- phrase = ''
- for i in IndexSet:
- phrase = phrase + choice(Alphabet)
- return phrase
+	phrase = ''
+	for i in IndexSet:
+		phrase = phrase + choice(Alphabet)
+	return phrase
 
 def mutate_phrase(phrase):
- mutant = phrase
- for i in range(int(0.5 + MutationChance*float(len(phrase)))):
- i = choice(IndexSet)
- c = choice(Alphabet)
- mutant = mutant[:i] + c + mutant[i+1:]
- #print `mutant`
- return mutant
+	mutant = phrase
+	for i in range(int(0.5 + MutationChance*float(len(phrase)))):
+		i = choice(IndexSet)
+		c = choice(Alphabet)
+		mutant = mutant[:i] + c + mutant[i+1:]
+	#print `mutant`
+	return mutant
 
 def matching_factor(phrase):
- factor = 0
- for i in IndexSet:
- if phrase[i] = Target[i]: factor = factor + 1
- return factor
+	factor = 0
+	for i in IndexSet:
+		if phrase[i] = Target[i]: factor = factor + 1
+	return factor
 
 def breed_generation(phrase):
- generation = [phrase]
- while len(generation) < GenerationSize:
- generation.append(mutate_phrase(phrase))
- return generation
+	generation = [phrase]
+	while len(generation) < GenerationSize:
+		generation.append(mutate_phrase(phrase))
+	return generation
 
 def select_best(generation):
- factor, selected = -1, ''
- for phrase in generation:
- f = matching_factor(phrase)
- if f > factor:
- factor, selected = f, phrase
- return selected
+	factor, selected = -1, ''
+	for phrase in generation:
+		f = matching_factor(phrase)
+		if f > factor:
+			factor, selected = f, phrase
+	return selected
 
 def main():
- gen = 0
- phrase = random_phrase()
- print gen, `phrase`
- while phrase <> Target:
- next_generation = breed_generation(phrase)
- #print next_generation
- phrase = select_best(next_generation)
- gen = gen+1
- print gen, `phrase`
+	gen = 0
+	phrase = random_phrase()
+	print gen, `phrase`
+	while phrase <> Target:
+		next_generation = breed_generation(phrase)
+		#print next_generation
+		phrase = select_best(next_generation)
+		gen = gen+1
+		print gen, `phrase`
 
 main()