added makefile

python/gen/Makefile

@@ -0,0 +1,9 @@
+TSP_FILE_PATH=../../data/a280.tsp 
+NUM_OF_GENERATIONS=10
+OUTPUT_EVERY_X_GEN=2
+MUTATION_RATE=0.1
+POPULATION_SIZE=100
+TOURNEY_SIZE=25
+
+run:
+	python main.py $(TSP_FILE_PATH) $(NUM_OF_GENERATIONS) $(OUTPUT_EVERY_X_GEN) $(MUTATION_RATE) $(POPULATION_SIZE) $(TOURNEY_SIZE)

python/gen/README.md

@@ -1 +1,13 @@
 siddkumar sk35435
+
+
+edit Makefile to set 
+ input file path, 
+ number of generations, 
+ how often you want to print output,
+ the mutation rate,
+ the population size,
+ and the tournament size.
+
+special thanks to http://www.theprojectspot.com/tutorial-post/applying-a-genetic-algorithm-to-the-travelling-salesman-problem/5
+

python/gen/main.py

@@ -203,44 +203,16 @@ def cross(self,tourA, tourB):
 		return childtour
 
 def distance(posa, posb):
-	return ((posb[1] - posa[1]) ** 2 + (posb[0] - posa[0]) ** 2) ** 0.5
+	return ( (posb[1] - posa[1]) ** 2 + (posb[0] - posa[0]) ** 2 ) ** 0.5
 
 def main():
-
-	places = [0,1,2]
-
-
-	a = vertex(0)
-	b = vertex(1)
-	c = vertex(2)
-
-
-	a.addEdge(b,2)
-	a.addEdge(c,5)
-	b.addEdge(c,10)
-
-	cities = [a,b,c]
-
-	mypop = pop(4, True, cities)
-	best =  mypop.max_fit()
-
-	#  mutation rate, popsize, tourneysize, eliteflag, cities
-	ga = gen(.10, 100, 5, False, cities)
-
-	ga.evolve()
-
-	macks =  ga.pool.max_fit()
-	# print macks[0].tostr(),macks[1], macks[0].getdist()
-
-	# 
-	# 
-	# 
 
 	path =  sys.argv[1]
 
-	with gzip.open(path,'rb') as f:
-		file = f.readlines()
+	# with gzip.open(path,'rb') as f:
+	# 	file = f.readlines()
 
+	file = open(path, 'r')
 
 	counter = 0
 	curr_cities = []
@@ -259,14 +231,23 @@ def main():
 		curr_cities.append(city)
 		counter += 1
 
-
+
+	r = int(sys.argv[2])
+	p = int(sys.argv[3])
+
+
 	#  mutation rate, popsize, tourneysize, eliteflag, cities
-	ga = gen(.10, 100, 25, True, curr_cities)
+	mr = float(sys.argv[4])
+	ps = int(sys.argv[5])
+	ts = int(sys.argv[6])
+
+
+	ga = gen(mr, ps, ts, True, curr_cities)
 
 
-	for i in range(1000):
+	for i in range(r):
 		ga.evolve()
-		if i % 250 == 1:
+		if i % p == 0:
 			print "Best route at Generation", i
 			macks =  ga.pool.max_fit()	
 			print macks[0].tostr(),macks[1], macks[0].getdist()