mirror of
https://github.com/Rushilwiz/AI.git
synced 2025-04-09 22:10:17 -04:00
461 lines
31 KiB
Python
461 lines
31 KiB
Python
# Name: Rushil Umaretiya
|
|
# Data: 10/22/2020
|
|
import random, pickle, math, time
|
|
from math import pi, acos, sin, cos
|
|
from tkinter import *
|
|
|
|
class HeapPriorityQueue():
|
|
def __init__(self):
|
|
self.queue = ["dummy"] # we do not use index 0 for easy index calulation
|
|
self.current = 1 # to make this object iterable
|
|
|
|
def next(self): # define what __next__ does
|
|
if self.current >=len(self.queue):
|
|
self.current = 1 # to restart iteration later
|
|
raise StopIteration
|
|
|
|
out = self.queue[self.current]
|
|
self.current += 1
|
|
|
|
return out
|
|
|
|
def __iter__(self):
|
|
return self
|
|
|
|
__next__ = next
|
|
|
|
def isEmpty(self):
|
|
return len(self.queue) <= 1 # b/c index 0 is dummy
|
|
|
|
def swap(self, a, b):
|
|
self.queue[a], self.queue[b] = self.queue[b], self.queue[a]
|
|
|
|
# Add a value to the heap_pq
|
|
def push(self, value):
|
|
self.queue.append(value)
|
|
# write more code here to keep the min-heap property
|
|
self.heapUp(len(self.queue)-1)
|
|
|
|
# helper method for push
|
|
def heapUp(self, k):
|
|
if k <= 1:
|
|
return
|
|
|
|
if len(self.queue) % 2 == 1 and k == len(self.queue) - 1: # no sibling
|
|
if sum(self.queue[k//2][1:3]) > sum(self.queue[k][1:3]):
|
|
self.swap(k, k//2)
|
|
self.heapUp(k//2)
|
|
return
|
|
|
|
if k % 2 == 0:
|
|
parent, sibling = k//2, k+1
|
|
else:
|
|
parent, sibling = k//2, k-1
|
|
|
|
if sum(self.queue[k][1:3]) > sum(self.queue[sibling][1:3]):
|
|
child = sibling
|
|
else:
|
|
child = k
|
|
|
|
if sum(self.queue[parent][1:3]) > sum(self.queue[child][1:3]):
|
|
self.swap(child, parent)
|
|
self.heapUp(parent)
|
|
|
|
|
|
# helper method for reheap and pop
|
|
def heapDown(self, k, size):
|
|
left, right = 2*k, 2*k+1
|
|
|
|
if left == size and sum(self.queue[k][1:3]) > sum(self.queue[size][1:3]): # One child
|
|
self.swap(k, left)
|
|
|
|
elif right <= size:
|
|
child = (left if sum(self.queue[left][1:3]) < sum(self.queue[right][1:3]) else right)
|
|
|
|
if sum(self.queue[k][1:3]) > sum(self.queue[child][1:3]):
|
|
self.swap(k, child)
|
|
self.heapDown(child, size)
|
|
|
|
# make the queue as a min-heap
|
|
def reheap(self):
|
|
if self.isEmpty():
|
|
return -1
|
|
|
|
for k in range((len(self.queue)-1)//2, 0, -1):
|
|
self.heapUp(k)
|
|
|
|
# remove the min value (root of the heap)
|
|
# return the removed value
|
|
def pop(self):
|
|
if self.isEmpty():
|
|
return -1
|
|
self.swap (1, len(self.queue) - 1)
|
|
val = self.queue.pop()
|
|
self.heapDown(1, len(self.queue) - 1)
|
|
return val
|
|
|
|
# remove a value at the given index (assume index 0 is the root)
|
|
# return the removed value
|
|
def remove(self, index):
|
|
|
|
if self.isEmpty():
|
|
return -1
|
|
|
|
if len (self.queue) == 2:
|
|
val = self.queue.pop()
|
|
self.queue = []
|
|
return val
|
|
|
|
self.swap (index + 1, len(self.queue) - 1)
|
|
val = self.queue.pop()
|
|
self.heapDown(index + 1, len(self.queue) - 1)
|
|
|
|
return val
|
|
|
|
def calc_edge_cost(y1, x1, y2, x2):
|
|
#
|
|
# y1 = lat1, x1 = long1
|
|
# y2 = lat2, x2 = long2
|
|
# all assumed to be in decimal degrees
|
|
|
|
# if (and only if) the input is strings
|
|
# use the following conversions
|
|
|
|
y1 = float(y1)
|
|
x1 = float(x1)
|
|
y2 = float(y2)
|
|
x2 = float(x2)
|
|
#
|
|
R = 3958.76 # miles = 6371 km
|
|
#
|
|
y1 *= pi/180.0
|
|
x1 *= pi/180.0
|
|
y2 *= pi/180.0
|
|
x2 *= pi/180.0
|
|
#
|
|
# approximate great circle distance with law of cosines
|
|
#
|
|
return acos( sin(y1)*sin(y2) + cos(y1)*cos(y2)*cos(x2-x1) ) * R
|
|
#
|
|
|
|
|
|
# NodeLocations, NodeToCity, CityToNode, Neighbors, EdgeCost
|
|
# Node: (lat, long) or (y, x), node: city, city: node, node: neighbors, (n1, n2): cost
|
|
def make_graph(nodes = "rrNodes.txt", node_city = "rrNodeCity.txt", edges = "rrEdges.txt"):
|
|
nodeLoc, nodeToCity, cityToNode, neighbors, edgeCost = {}, {}, {}, {}, {}
|
|
map = {} # have screen coordinate for each node location
|
|
|
|
nodes = open(nodes, "r")
|
|
node_city = open(node_city, "r")
|
|
edges = open(edges, "r")
|
|
|
|
for line in node_city.readlines():
|
|
args = line.strip().split(" ", 1)
|
|
nodeToCity[args[0]] = args[1]
|
|
cityToNode[args[1]] = args[0]
|
|
|
|
for line in nodes.readlines():
|
|
args = line.strip().split(" ")
|
|
nodeLoc[args[0]] = (float(args[1]), float(args[2]))
|
|
|
|
for line in edges.readlines():
|
|
args = line.strip().split(" ")
|
|
cost = calc_edge_cost(nodeLoc[args[0]][0], nodeLoc[args[0]][1], nodeLoc[args[1]][0], nodeLoc[args[1]][1])
|
|
edgeCost[(args[0],args[1])] = cost
|
|
edgeCost[(args[1],args[0])] = cost
|
|
|
|
if args[0] in neighbors:
|
|
neighbors[args[0]]+=[args[1]]
|
|
else:
|
|
neighbors[args[0]] = [args[1]]
|
|
|
|
if args[1] in neighbors:
|
|
neighbors[args[1]]+=[args[0]]
|
|
else:
|
|
neighbors[args[1]] = [args[0]]
|
|
|
|
|
|
for node in nodeLoc: #checks each
|
|
lat = float(nodeLoc[node][0]) #gets latitude
|
|
long = float(nodeLoc[node][1]) #gets long
|
|
modlat = (lat - 10)/60 #scales to 0-1
|
|
modlong = (long+130)/70 #scales to 0-1
|
|
map[node] = [modlat*800, modlong*1200] #scales to fit 800 1200
|
|
|
|
return [nodeLoc, nodeToCity, cityToNode, neighbors, edgeCost, map]
|
|
|
|
# Retuen the direct distance from node1 to node2
|
|
# Use calc_edge_cost function.
|
|
def dist_heuristic(n1, n2, graph):
|
|
return calc_edge_cost(graph[0][n1][0],graph[0][n1][1],graph[0][n2][0],graph[0][n2][1])
|
|
|
|
# Create a city path.
|
|
# Visit each node in the path. If the node has the city name, add the city name to the path.
|
|
# Example: ['Charlotte', 'Hermosillo', 'Mexicali', 'Los Angeles']
|
|
def display_path(path, graph):
|
|
print([graph[1][node] for node in path if node in graph[1]])
|
|
|
|
# Using the explored, make a path by climbing up to "s"
|
|
# This method may be used in your BFS and Bi-BFS algorithms.
|
|
def generate_path(state, explored, graph):
|
|
path = [state]
|
|
cost = 0
|
|
|
|
while explored[state] != "s": #"s" is initial's parent
|
|
cost += graph[4][(state,explored[state])]
|
|
state = explored[state]
|
|
path.append(state)
|
|
|
|
return path[::-1], cost
|
|
|
|
def drawLine(canvas, y1, x1, y2, x2, col):
|
|
x1, y1, x2, y2 = float(x1), float(y1), float(x2), float(y2)
|
|
canvas.create_line(x1, 800-y1, x2, 800-y2, fill=col)
|
|
|
|
|
|
# Draw the final shortest path.
|
|
# Use drawLine function.
|
|
def draw_final_path(ROOT, canvas, path, graph, col='red'):
|
|
|
|
for i in range(len(path[1:])):
|
|
drawLine(canvas, *graph[5][path[i]], *graph[5][path[i+1]], col)
|
|
|
|
ROOT.update()
|
|
pass
|
|
|
|
|
|
def draw_all_edges(ROOT, canvas, graph):
|
|
ROOT.geometry("1200x800") #sets geometry
|
|
canvas.pack(fill=BOTH, expand=1) #sets fill expand
|
|
for n1, n2 in graph[4]: #graph[4] keys are edge set
|
|
drawLine(canvas, *graph[5][n1], *graph[5][n2], 'white') #graph[5] is map dict
|
|
ROOT.update()
|
|
|
|
|
|
def bfs(start, goal, graph, col):
|
|
ROOT = Tk() #creates new tkinter
|
|
ROOT.title("BFS")
|
|
canvas = Canvas(ROOT, background='black') #sets background
|
|
draw_all_edges(ROOT, canvas, graph)
|
|
|
|
counter = 0
|
|
frontier, explored = [], {start: "s"}
|
|
frontier.append(start)
|
|
while frontier:
|
|
s = frontier.pop(0)
|
|
if s == goal:
|
|
path, cost = generate_path(s, explored, graph)
|
|
print(f'The number of explored nodes of BFS: {len(explored)}')
|
|
print(f'The whole path: {path}')
|
|
print(f'The length of the whole path {len(path)}')
|
|
draw_final_path(ROOT, canvas, path, graph)
|
|
return path, cost
|
|
for a in graph[3][s]: #graph[3] is neighbors
|
|
if a not in explored:
|
|
explored[a] = s
|
|
frontier.append(a)
|
|
drawLine(canvas, *graph[5][s], *graph[5][a], col)
|
|
counter += 1
|
|
if counter % 1000 == 0: ROOT.update()
|
|
return None
|
|
|
|
def bi_bfs(start, goal, graph, col):
|
|
|
|
ROOT = Tk() #creates new tkinter
|
|
ROOT.title("Bi-BFS")
|
|
canvas = Canvas(ROOT, background='black') #sets background
|
|
draw_all_edges(ROOT, canvas, graph)
|
|
|
|
Q = [[start],[goal]]
|
|
explored = [{start:"s"},{goal:"s"}]
|
|
flag = 0
|
|
counter = 0
|
|
|
|
while Q[0] or Q[1]:
|
|
flag = 1 - flag
|
|
for i in range(len(Q[flag])):
|
|
state = Q[flag].pop(0)
|
|
adj_list = graph[3][state]
|
|
|
|
for adj in adj_list:
|
|
if adj in explored[1 - flag]:
|
|
explored[flag][adj] = state
|
|
start_path, start_cost = generate_path(adj, explored[0], graph)
|
|
goal_path, goal_cost = generate_path(adj, explored[1], graph)
|
|
path = start_path[:-1] + goal_path[::-1]
|
|
|
|
draw_final_path(ROOT, canvas, path, graph)
|
|
|
|
print(f'The number of explored nodes of Bi-BFS: {len(explored[0]) + len(explored[1])}')
|
|
print(f'The whole path: {path}')
|
|
print(f'The length of the whole path {len(path)}')
|
|
|
|
return path, start_cost + goal_cost
|
|
|
|
for neighbor in adj_list:
|
|
if neighbor not in explored[flag]:
|
|
explored[flag][neighbor] = state
|
|
Q[flag].append(neighbor)
|
|
drawLine(canvas, *graph[5][state], *graph[5][neighbor], col)
|
|
|
|
counter += 1
|
|
if counter % 1000 == 0: ROOT.update()
|
|
return None
|
|
|
|
def a_star(start, goal, graph, col, heuristic=dist_heuristic):
|
|
|
|
ROOT = Tk() #creates new tkinter
|
|
ROOT.title("A*")
|
|
canvas = Canvas(ROOT, background='black') #sets background
|
|
draw_all_edges(ROOT, canvas, graph)
|
|
|
|
frontier = HeapPriorityQueue()
|
|
explored = {}
|
|
if start == goal: return []
|
|
|
|
# We are pushing tuples of the (current_node, heuristic, path_cost, path))
|
|
frontier.push((start, heuristic(start, goal, graph), 0, [start]))
|
|
explored[start] = heuristic(start, goal, graph)
|
|
|
|
counter = 0
|
|
|
|
|
|
while not frontier.isEmpty():
|
|
state = frontier.pop()
|
|
|
|
# Goal test
|
|
if state[0] == goal:
|
|
path = state[3]
|
|
print(f'The number of explored nodes of A star: {len(explored)}')
|
|
print(f'The whole path: {path}')
|
|
print(f'The length of the whole path {len(path)}')
|
|
|
|
draw_final_path(ROOT, canvas, state[3], graph)
|
|
|
|
return path, state[2]
|
|
|
|
|
|
# Push children on heapq
|
|
#print(state[1] + state[2])
|
|
for neighbor in graph[3][state[0]]:
|
|
h = heuristic(neighbor, goal, graph)
|
|
path_cost = graph[4][(neighbor, state[0])] + state[2]
|
|
cost = h + path_cost
|
|
if neighbor not in explored or explored[neighbor] > cost:
|
|
explored[neighbor] = cost
|
|
frontier.push((neighbor, h, path_cost, state[3] + [neighbor]))
|
|
drawLine(canvas, *graph[5][state[0]], *graph[5][neighbor], col)
|
|
|
|
counter += 1
|
|
if counter % 1000 == 0: ROOT.update()
|
|
|
|
return None
|
|
|
|
|
|
def bi_a_star(start, goal, graph, col, heuristic=dist_heuristic):
|
|
|
|
# Your code goes here
|
|
|
|
return None
|
|
|
|
def tri_directional(city1, city2, city3, graph, col, heuristic=dist_heuristic):
|
|
|
|
# Your code goes here
|
|
|
|
return None
|
|
|
|
def main():
|
|
start, goal = input("Start city: "), input("Goal city: ")
|
|
#third = input("Third city for tri-directional: ")
|
|
graph = make_graph("rrNodes.txt", "rrNodeCity.txt", "rrEdges.txt") # Task 1
|
|
|
|
cur_time = time.time()
|
|
path, cost = bfs(graph[2][start], graph[2][goal], graph, 'yellow') #graph[2] is city to node
|
|
if path != None: display_path(path, graph)
|
|
else: print ("No Path Found.")
|
|
print ('BFS Path Cost:', cost)
|
|
print ('BFS duration:', (time.time() - cur_time))
|
|
print ()
|
|
|
|
cur_time = time.time()
|
|
path, cost = bi_bfs(graph[2][start], graph[2][goal], graph, 'green')
|
|
if path != None: display_path(path, graph)
|
|
else: print ("No Path Found.")
|
|
print ('Bi-BFS Path Cost:', cost)
|
|
print ('Bi-BFS duration:', (time.time() - cur_time))
|
|
print ()
|
|
|
|
|
|
cur_time = time.time()
|
|
path, cost = a_star(graph[2][start], graph[2][goal], graph, 'blue')
|
|
if path != None: display_path(path, graph)
|
|
else: print ("No Path Found.")
|
|
print ('A star Path Cost:', cost)
|
|
print ('A star duration:', (time.time() - cur_time))
|
|
print ()
|
|
|
|
"""
|
|
cur_time = time.time()
|
|
path, cost = bi_a_star(graph[2][start], graph[2][goal], graph, 'orange', ROOT, canvas)
|
|
if path != None: display_path(path, graph)
|
|
else: print ("No Path Found.")
|
|
print ('Bi-A star Path Cost:', cost)
|
|
print ("Bi-A star duration: ", (time.time() - cur_time))
|
|
print ()
|
|
|
|
print ("Tri-Search of ({}, {}, {})".format(start, goal, third))
|
|
cur_time = time.time()
|
|
path, cost = tri_directional(graph[2][start], graph[2][goal], graph[2][third], graph, 'pink', ROOT, canvas)
|
|
if path != None: display_path(path, graph)
|
|
else: print ("No Path Found.")
|
|
print ('Tri-A star Path Cost:', cost)
|
|
print ("Tri-directional search duration:", (time.time() - cur_time))
|
|
"""
|
|
mainloop() # Let TK windows stay still
|
|
|
|
if __name__ == '__main__':
|
|
main()
|
|
|
|
|
|
''' Sample output
|
|
----jGRASP exec: python Lab10_railroad_Kim_2019_2020.py
|
|
Start city: Charlotte
|
|
Goal city: Los Angeles
|
|
Third city for tri-directional: Chicago
|
|
The number of explored nodes of BFS: 19735
|
|
The whole path: ['3700421', '3700258', '3700256', '3700004', '3700076', '3700075', '0000530', '4500272', '4500042', '4500270', '4500231', '4500069', '4500023', '4500233', '4500094', '4500095', '4500096', '4500097', '4500234', '4500225', '4500104', '4500082', '4500164', '4500015', '4500181', '4500167', '0000533', '1300133', '1300197', '1300132', '1300146', '1300198', '1300204', '1300208', '1300087', '1300279', '1300088', '1300369', '1300459', '1300458', '1300090', '1300460', '1300107', '1300210', '1300398', '1300099', '0000031', '0100343', '0100342', '0100341', '0100084', '0100506', '0100012', '0100325', '0100345', '0100331', '0100520', '0100354', '0100355', '0100042', '0100566', '0100356', '0100357', '0100456', '0100103', '0100515', '0100264', '0100032', '0100263', '0100102', '0100033', '0100062', '0100129', '0100513', '0100061', '0000461', '2800154', '2800153', '2800032', '2800150', '2800031', '2800108', '2800247', '2800191', '2800156', '2800169', '2800001', '2800162', '2800163', '2800164', '2800125', '2800030', '2800028', '0000419', '2200078', '2200143', '2200039', '2200274', '2200379', '2200080', '2200273', '2200205', '2200112', '2200037', '2200076', '2200311', '0000411', '0500250', '0500019', '0500248', '0500005', '0500020', '0500134', '0000573', '4800439', '4800085', '4800410', '4801165', '4800956', '4801086', '4800081', '4800584', '4800082', '4800084', '4800309', '4800898', '4801101', '4800271', '4800578', '4800274', '4800881', '4800882', '4800167', '4800483', '4800464', '4800168', '4801228', '4800170', '4801230', '4800172', '4800462', '4800461', '4800230', '4800199', '4800832', '4800831', '4800198', '4801190', '4800830', '4800197', '4800200', '4800302', '4800648', '4800763', '4800286', '4800759', '4800758', '4800649', '4800675', '4801214', '4800285', '4800674', '4800757', '4800673', '4800672', '4800535', '4800280', '4800279', '4801134', '4800896', '4800357', '0009483', '9100020', '9100502', '9100501', '9100505', '9100507', '9100504', '9100503', '9100515', '9100153', '9100122', '9100478', '9100448', '9100442', '9100477', '9100476', '9100479', '9100436', '9100124', '9100150', '9100427', '9100012', '9100485', '9100484', '9100081', '9100486', '9100007', '9100117', '9100006', '9100116', '9100080', '9100438', '9100001', '0009063', '0600129', '0600577', '0600041', '0600579', '0600117', '0600039', '0600646', '0600797', '0600747', '0600516', '0600750', '0600584', '0600746', '0600585', '0600586', '0600042', '0600770', '0600434', '0600689', '0600464', '0600688', '0600384', '0600588', '0600460', '0600408', '0600799', '0600402', '0600766', '0600686', '0600079', '0600080', '0600086', '0600684', '0600425', '0600088', '0600759', '0600427', '0600316']
|
|
The length of the whole path: 243
|
|
['Charlotte', 'Hermosillo', 'Mexicali', 'Los Angeles']
|
|
BFS Path Cost: 2965.7640233572088
|
|
BFS duration: 288.9429421424866
|
|
|
|
The number of explored nodes of Bi-BFS: 12714
|
|
The whole path: ['3700421', '3700258', '3700256', '3700004', '3700076', '3700075', '0000530', '4500272', '4500042', '4500270', '4500231', '4500069', '4500023', '4500233', '4500094', '4500095', '4500096', '4500097', '4500234', '4500225', '4500104', '4500082', '4500164', '4500015', '4500181', '4500167', '0000533', '1300133', '1300197', '1300132', '1300146', '1300198', '1300204', '1300208', '1300087', '1300279', '1300088', '1300369', '1300459', '1300458', '1300090', '1300460', '1300107', '1300210', '1300398', '1300099', '0000031', '0100343', '0100342', '0100341', '0100084', '0100506', '0100012', '0100325', '0100345', '0100331', '0100520', '0100354', '0100355', '0100042', '0100566', '0100356', '0100357', '0100456', '0100103', '0100515', '0100264', '0100032', '0100263', '0100102', '0100033', '0100062', '0100129', '0100513', '0100061', '0000461', '2800154', '2800153', '2800032', '2800150', '2800031', '2800108', '2800247', '2800191', '2800156', '2800169', '2800001', '2800162', '2800163', '2800164', '2800125', '2800030', '2800028', '0000419', '2200078', '2200143', '2200039', '2200274', '2200379', '2200080', '2200273', '2200205', '2200112', '2200037', '2200076', '2200311', '0000411', '0500250', '0500019', '0500248', '0500005', '0500020', '0500134', '0000573', '4800439', '4800085', '4800410', '4801165', '4800956', '4801086', '4800081', '4800584', '4800082', '4800084', '4800309', '4800898', '4801101', '4800271', '4800578', '4800274', '4800881', '4800882', '4800167', '4800483', '4800464', '4800168', '4801228', '4800170', '4801230', '4800172', '4800462', '4800461', '4800230', '4800199', '4800832', '4800831', '4800198', '4801190', '4800830', '4800197', '4800200', '4800302', '4800648', '4800763', '4800286', '4800759', '4800758', '4800649', '4800675', '4801214', '4800285', '4800674', '4800757', '4800673', '4800672', '4800535', '4800280', '4800279', '4801134', '4800896', '4800357', '0009483', '9100020', '9100502', '9100501', '9100505', '9100018', '9100508', '9100503', '9100515', '9100153', '9100122', '9100478', '9100448', '9100442', '9100477', '9100476', '9100479', '9100436', '9100124', '9100150', '9100427', '9100012', '9100485', '9100484', '9100081', '9100486', '9100007', '9100117', '9100006', '9100116', '9100080', '9100438', '9100001', '0009063', '0600129', '0600577', '0600041', '0600579', '0600117', '0600039', '0600646', '0600797', '0600747', '0600516', '0600750', '0600584', '0600746', '0600585', '0600586', '0600042', '0600770', '0600434', '0600690', '0600875', '0600691', '0600692', '0600082', '0600313', '0600383', '0600312', '0600404', '0600405', '0600403', '0600079', '0600080', '0600086', '0600684', '0600425', '0600088', '0600759', '0600427', '0600316']
|
|
The length of the whole path 243
|
|
['Charlotte', 'Hermosillo', 'Mexicali', 'Los Angeles']
|
|
Bi-BFS Path Cost: 2965.4128704488785
|
|
Bi-BFS duration: 115.2277946472168
|
|
|
|
The number of explored nodes of A star: 7692
|
|
The whole path: ['3700421', '3700258', '3700257', '3700142', '3700422', '3700001', '3700235', '3700234', '3700330', '3700329', '3700002', '3700356', '3700355', '3700357', '3700197', '3700198', '0000529', '4500042', '4500270', '4500231', '4500069', '4500023', '4500233', '4500094', '4500095', '4500096', '4500097', '4500234', '4500225', '4500104', '4500082', '4500164', '4500015', '4500181', '4500167', '0000533', '1300133', '1300197', '1300132', '1300146', '1300198', '1300204', '1300208', '1300087', '1300279', '1300088', '1300369', '1300459', '1300458', '1300090', '1300460', '1300107', '1300210', '1300398', '1300099', '0000031', '0100343', '0100342', '0100341', '0100084', '0100340', '0100276', '0100339', '0100338', '0100324', '0100344', '0100508', '0100273', '0100329', '0100272', '0100303', '0100090', '0100430', '0100429', '0100435', '0100240', '0100239', '0100018', '0100138', '0100139', '0100088', '0100289', '0100569', '0100222', '0100224', '0100227', '0100188', '0100256', '0100101', '0100134', '0100038', '0100317', '0100319', '0100157', '0100253', '0100316', '0100198', '0100030', '0100465', '0100472', '0100028', '0100200', '0100293', '0100104', '0000462', '2800033', '2800152', '2800032', '2800150', '2800031', '2800108', '2800247', '2800191', '2800156', '2800169', '2800001', '2800162', '2800163', '2800164', '2800125', '2800030', '2800028', '0000419', '2200078', '2200143', '2200039', '2200274', '2200379', '2200080', '2200273', '2200205', '2200112', '2200037', '2200076', '2200277', '2200074', '2200322', '2200320', '2200035', '2200212', '2200218', '2200248', '2200036', '2200211', '2200209', '2200208', '2200265', '2200073', '2200312', '2200314', '0000143', '4801029', '4801030', '4800307', '4801033', '4801031', '4801171', '4800227', '4800306', '4800901', '4801289', '4800309', '4800416', '4800531', '4801183', '4800786', '4801181', '4800365', '4801180', '4800530', '4801168', '4800785', '4800096', '4800478', '4800097', '4800107', '4800106', '4800100', '4800586', '4800099', '4801026', '4800058', '4800842', '4800843', '4800467', '4800646', '4800056', '4800645', '4800456', '4800048', '4800455', '4801124', '4800778', '4800046', '4800853', '4800852', '4800045', '4801244', '4800681', '4800738', '4800291', '4800362', '4800363', '4800539', '4800295', '4800288', '4800540', '4800634', '4800554', '4801293', '4801292', '4800549', '4801294', '4800292', '4801290', '4800283', '4800702', '4800754', '4800281', '4800755', '4800756', '4800294', '4800550', '4800552', '4800553', '4800624', '4800823', '4801012', '4800536', '4800751', '4801307', '4801295', '4800743', '4800300', '4800746', '4800749', '4800516', '4801299', '0000588', '3500100', '3500044', '3500086', '3500106', '3500137', '3500015', '3500143', '3500041', '3500024', '0000310', '0400107', '0400029', '0400098', '0400105', '0400097', '0400030', '0400031', '0400033', '0400034', '0400036', '0400111', '0400110', '0400118', '0400037', '0400108', '0400120', '0400119', '0400103', '0400026', '0400079', '0400134', '0400072', '0400099', '0400044', '0400045', '0400135', '0400080', '0400048', '0400112', '0400092', '0400053', '0400060', '0000146', '0600798', '0600648', '0600758', '0600796', '0600039', '0600646', '0600797', '0600747', '0600516', '0600750', '0600584', '0600746', '0600585', '0600586', '0600042', '0600770', '0600434', '0600689', '0600464', '0600688', '0600384', '0600588', '0600460', '0600408', '0600799', '0600402', '0600766', '0600686', '0600079', '0600080', '0600085', '0600685', '0600084', '0600751', '0600322', '0600427', '0600316']
|
|
The length of the whole path 319
|
|
['Charlotte', 'Dallas', 'Tucson', 'Los Angeles']
|
|
A star Path Cost: 2419.9700735372285
|
|
A star duration: 6.368658781051636
|
|
|
|
The number of explored nodes of Bi-A star: 7692
|
|
The whole path: ['3700421', '3700258', '3700257', '3700142', '3700422', '3700001', '3700235', '3700234', '3700330', '3700329', '3700002', '3700356', '3700355', '3700357', '3700197', '3700198', '0000529', '4500042', '4500270', '4500231', '4500069', '4500023', '4500233', '4500094', '4500095', '4500096', '4500097', '4500234', '4500225', '4500104', '4500082', '4500164', '4500015', '4500181', '4500167', '0000533', '1300133', '1300197', '1300132', '1300146', '1300198', '1300204', '1300208', '1300087', '1300279', '1300088', '1300369', '1300459', '1300458', '1300090', '1300460', '1300107', '1300210', '1300398', '1300099', '0000031', '0100343', '0100342', '0100341', '0100084', '0100340', '0100276', '0100339', '0100338', '0100324', '0100344', '0100508', '0100273', '0100329', '0100272', '0100303', '0100090', '0100430', '0100429', '0100435', '0100240', '0100367', '0100368', '0100282', '0100093', '0100152', '0100375', '0100304', '0100180', '0100278', '0100268', '0100387', '0100544', '0100137', '0100525', '0100312', '0100166', '0100167', '0100026', '0100109', '0100361', '0000466', '2800215', '2800039', '2800143', '2800214', '2800213', '2800058', '2800221', '2800059', '2800057', '2800209', '0000410', '4700333', '4700249', '4700217', '4700216', '4700355', '4700352', '4700005', '4700219', '4700220', '0000407', '0500006', '0500054', '0500281', '0500055', '0500074', '0500292', '0500228', '0500073', '0500216', '0500204', '0500071', '0500040', '0500309', '0500144', '0500143', '0500315', '0500314', '0500313', '0500311', '0500312', '0500316', '0500017', '0500117', '0500104', '0500320', '0500018', '0500240', '0500251', '0500019', '0500248', '0500005', '0500020', '0500134', '0000573', '4800439', '4800085', '4800410', '4801165', '4800956', '4801086', '4800081', '4800583', '4800437', '4801087', '4800585', '4800080', '4800079', '4800076', '4800077', '4800075', '4800687', '4800088', '4800440', '4801172', '4800089', '4800112', '4801175', '4800482', '4800481', '4800784', '4800057', '4800054', '4800469', '4800470', '4800471', '4800644', '4800642', '4800641', '4800643', '4800645', '4800456', '4800048', '4800455', '4801124', '4800778', '4800046', '4800853', '4800852', '4800045', '4801244', '4800681', '4800738', '4800291', '4800362', '4800363', '4800539', '4800295', '4800288', '4800540', '4800634', '4800554', '4801293', '4801292', '4800549', '4801294', '4800292', '4801290', '4800283', '4800702', '4800754', '4800281', '4800755', '4800756', '4800294', '4800550', '4800552', '4800553', '4800624', '4800823', '4801012', '4800536', '4800751', '4801307', '4801295', '4800743', '4800300', '4800746', '4800749', '4800516', '4801299', '0000588', '3500100', '3500044', '3500086', '3500106', '3500137', '3500015', '3500143', '3500041', '3500024', '0000310', '0400107', '0400029', '0400098', '0400105', '0400097', '0400030', '0400031', '0400033', '0400034', '0400036', '0400111', '0400110', '0400118', '0400037', '0400108', '0400120', '0400119', '0400103', '0400026', '0400079', '0400134', '0400072', '0400099', '0400044', '0400045', '0400135', '0400080', '0400048', '0400112', '0400092', '0400053', '0400060', '0000146', '0600798', '0600648', '0600758', '0600796', '0600039', '0600646', '0600797', '0600747', '0600516', '0600750', '0600584', '0600746', '0600585', '0600586', '0600042', '0600770', '0600434', '0600689', '0600464', '0600688', '0600384', '0600588', '0600460', '0600408', '0600799', '0600402', '0600766', '0600686', '0600079', '0600080', '0600085', '0600685', '0600084', '0600751', '0600322', '0600427', '0600316']
|
|
The length of the whole path 319
|
|
['Charlotte', 'Dallas', 'Tucson', 'Los Angeles']
|
|
Bi-A star Path Cost: 2419.9700735372285
|
|
Bi-A star duration: 61.220252990722656
|
|
|
|
Tri-Search of (Charlotte, Los Angeles, Chicago)
|
|
The whole path: ['0600316', '0600427', '0600322', '0600751', '0600084', '0600685', '0600085', '0600080', '0600079', '0600686', '0600766', '0600402', '0600799', '0600408', '0600460', '0600588', '0600384', '0600688', '0600463', '0600435', '0600107', '0600775', '0600769', '0600436', '0600032', '0600414', '0600867', '0600866', '0600031', '0600033', '0600795', '0600602', '0600603', '0600036', '0600604', '0600871', '0600870', '0600872', '0600495', '0000144', '0400113', '0400114', '0400009', '0400010', '0400116', '0400117', '0400148', '0400074', '0400146', '0400147', '0400064', '0400005', '0400006', '0400063', '0400100', '0400075', '0400071', '0400070', '0400002', '0400050', '0000312', '3500036', '3500062', '3500063', '3500068', '3500069', '3500101', '3500111', '3500061', '3500109', '3500084', '3500089', '3500102', '3500065', '3500066', '3500032', '3500027', '3500119', '3500071', '3500070', '3500090', '3500107', '3500072', '3500013', '3500047', '3500039', '3500141', '3500025', '3500099', '0000257', '4801203', '4800003', '4801200', '4800002', '0000248', '4000264', '4000138', '4000231', '0000246', '2000206', '2000503', '2000360', '2000427', '2000500', '2000452', '2000207', '2000419', '2000501', '2000502', '2000073', '2000074', '2000075', '2000473', '2000519', '2000506', '2000294', '2000295', '2000296', '2000514', '2000523', '2000077', '2000292', '2000504', '2000293', '2000092', '2000311', '2000472', '2000470', '2000094', '2000095', '2000404', '2000097', '2000277', '2000102', '2000414', '2000103', '2000104', '2000106', '2000356', '2000114', '2000372', '2000117', '2000465', '2000466', '2000467', '2000270', '2000258', '2000257', '2000256', '2000260', '0000232', '2900371', '2900374', '2900378', '2900238', '2900184', '2900358', '2900288', '2900289', '2900098', '2900366', '2900341', '2900367', '2900108', '2900287', '2900241', '2900103', '2900482', '2900102', '2900545', '2900556', '2900111', '2900120', '2900122', '2900494', '2900355', '2900121', '2900162', '2900165', '2900566', '2900468', '2900164', '0000395', '1900057', '1900382', '1900070', '0000393', '1701225', '1700286', '1701010', '1701170', '1700285', '1701321', '1701325', '1701326', '1701323', '1700750', '1701328', '1701327', '1700292', '1700281', '1700280', '1701120', '1700301', '1700922', '1701121', '1700487', '1700480', '1700479', '1700478', '1700477', '1700430', '1700431', '1701157', '1700449', '1700419', '1700465', '1700418', '1701034', '1701194', '1700417', '1700629', '1701394', '1700653', '1700631', '1700415', '1701267', '1701265', '1701291', '1700899', '1700919', '1701607', '1700411', '1700792', '1700624', '1700635', '1700434', '1701056', '1701063', '1701062', '1700651', '1700803', '0000580', '1800373', '1800287', '1800698', '1800697', '1800699', '1800700', '1800377', '1800404', '1800710', '1800709', '1800708', '1800705', '1800706', '1800396', '1800237', '1800228', '1800227', '1800226', '1800474', '1800475', '1800280', '1800416', '1800185', '1800195', '1800200', '1800317', '1800201', '1800145', '1800144', '1800146', '1800167', '1800461', '1800162', '1800460', '1800653', '1800651', '1800652', '1800513', '1800512', '1800511', '1800328', '1800100', '1800577', '1800095', '1800560', '1800096', '1800492', '1800746', '1800744', '1800070', '1800743', '1800069', '0000013', '3901034', '3900294', '3900813', '3900814', '3900526', '3900527', '3900290', '3900293', '3900896', '3900528', '0000183', '2100102', '2100259', '2100101', '2100296', '2100328', '2100321', '2100094', '2100093', '2100092', '2100088', '2100291', '2100398', '2100162', '2100322', '2100246', '2100184', '2100051', '2100186', '2100385', '2100384', '2100383', '2100381', '2100382', '2100053', '2100055', '2100160', '2100059', '2100216', '2100060', '2100158', '2100065', '2100064', '2100152', '2100156', '0000025', '5100179', '5100126', '5100128', '5100122', '5100121', '5100269', '5100384', '5100061', '5100385', '5100062', '5100436', '0000568', '4700230', '4700231', '4700101', '4700302', '4700143', '4700410', '4700141', '4700144', '0000200', '3700359', '3700082', '3700375', '3700126', '3700376', '3700127', '3700224', '3700091', '3700225', '3700125', '3700144', '3700077', '3700075', '3700076', '3700004', '3700256', '3700258', '3700421']
|
|
The length of the whole path 381
|
|
['Los Angeles', 'Chicago', 'Charlotte']
|
|
Tri-A star Path Cost: 2760.516003492685
|
|
Tri-directional search duration: 22.166738271713257
|
|
|
|
----jGRASP: operation complete.
|
|
''' |