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+import sys
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+import copy
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+import math
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+from heapq import heappush, heappop
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+from random import randint
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+import matplotlib.pyplot as plt
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+
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+distances = []
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+n = 0
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+
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+# returns hueristic value
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+def heuristic(source, target, dist):
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+ #return 0
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+ for i in range(0, min(n * 2, n ** 2)):
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+ if (dist <= distances[i]):
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+ return 0
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+ return dist
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+
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+
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+# returns weight(distance) between 2 vertices
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+def weight(city1, city2):
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+ return math.sqrt((city1[1] - city2[1]) ** 2 + (city1[2] - city2[2]) ** 2)
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+
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+
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+# returns if going to city i from curnode is okay
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+def valid(curnode, cities, i):
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+ # can't revisit a city
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+ if (i in curnode[2]):
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+ return False
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+ # if curnode hasn't visited everything else and we are going to the gaol
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+ elif (len(curnode[2]) != (len(cities) - 1) and i == (len(cities) - 1)):
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+ return False
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+ else:
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+ return True
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+
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+
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+# returns the count of child states. updates frontier
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+def explore(curnode, frontier, cities):
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+ children = 0
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+
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+ for i in range(1, len(cities)):
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+ # can we go here?
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+ if (valid(curnode, cities, i)):
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+ children += 1
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+ # add to frontier
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+ dist = weight(curnode[1], cities[i])
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+ metric = dist + heuristic(curnode[1], cities[i], dist)
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+ heappush(frontier, [curnode[0] + metric, cities[i], copy.deepcopy(curnode[2])])
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+
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+ return children
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+
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+
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+# A* solver for TSP
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+def solve(frontier, cities):
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+ # number of child states
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+ newnodes = 0
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+ curnode = heappop(frontier)
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+
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+ # while we are not on the goal node
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+ while (curnode[1] != cities[-1]):
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+ newnodes += explore(curnode, frontier, cities)
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+ curnode = heappop(frontier)
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+ curnode[2].append(cities.index(curnode[1]))
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+
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+ return newnodes + 1
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+
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+
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+def tsp(filename):
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+ # import map
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+ #prob = "instance_10.txt"
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+ prob = filename
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+ with open(prob) as file:
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+ prob = file.read().splitlines()
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+
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+ global n
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+ n = int(prob[0])
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+ cities = prob[1:]
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+ counter = 0
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+ # convert to list of list of ints
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+ for l in cities:
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+ temp = l.split()
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+ temp[1] = int(temp[1])
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+ temp[2] = int(temp[2])
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+ temp.append(counter)
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+ counter += 1
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+ cities[cities.index(l)] = temp
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+
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+ global distances
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+ distances = []
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+
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+ for i in range(0, len(cities) - 1):
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+ for j in range(i, len(cities)):
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+ dist = weight(cities[i], cities[j])
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+ distances.append(dist)
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+
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+ distances.sort()
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+
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+ # add in goal state
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+ cities.append(copy.deepcopy(cities[0]))
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+ cities[-1][0] = "Goal"
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+
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+ # create frontier
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+ frontier = []
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+ # add start state, list of visited, and distancesofar to frontier
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+ heappush(frontier, [0, cities[0], [0]])
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+
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+ print(solve(frontier, cities))
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+
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+
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+def main():
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+ plt.ioff()
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+ plt.switch_backend('agg')
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+ averages = []
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+
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+ for i in range(1, 13):
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+ average = 0
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+ for j in range(1, 11):
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+ filepath = "tsp_problems/" + str(i) + "/instance_" + str(j) + ".txt"
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+ average += tsp(filepath)
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+
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+ averages.append(average / 10.0)
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+
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+ figure, axes = plt.subplots(1, 1, True)
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+ axes.plot(range(1, 13), averages, label='TSP Solver (Heuristic)')
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+ axes.legend()
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+ plt.xlabel("Number of Cities")
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+ plt.ylabel("Average Number of Nodes Generated in 10 Runs")
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+ plt.savefig("graph.pdf")
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+
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+main()
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