def aStarSearch(graph, start, goal, heuristic):
# initialize Priority Queue
frontier = PriorityQueue()
frontier.put(start, 0)
previous = {}
currentCost = {}
previous[start] = None
currentCost[start] = 0
counter = 1
space = 0
# while frontier is not empty
while not frontier.empty():
current = frontier.get()
if current == goal:
break
for next in graph.neighbors(current):
# determine A* cost
new_cost = currentCost[current] + graph.distanceToDistination(graph.getWeight(current), graph.getWeight(next))
# check if the cost has gone down since last time we visited to determine if location has already been visited
if next not in currentCost or new_cost < currentCost[next]:
currentCost[next] = new_cost
# determine which heuristic to use
if heuristic == 1:
heuristicValue = heuristicEuclidean(graph.getWeight(current), graph.getWeight(goal))
else:
heuristicValue = heuristicChebyshev(graph.getWeight(current), graph.getWeight(goal))
# add heuristic cose to A* cost
priority = new_cost + heuristicValue
# add path with it's priority
frontier.put(next, priority)
previous[next] = current
counter = counter + 1
space = max(space, frontier.size())
return previous, currentCost, counter, space
def greedyFirstSearch(graph, start, goal, heuristic):
# initialize priority queue
frontier = PriorityQueue()
frontier.put(start, 0)
previous = {}
previous[start] = None
counter = 1
space = 0
# if frontier isn't empty
while not frontier.empty():
current = frontier.get()
# check if current is the goal
if current == goal:
break
for next in graph.neighbors(current):
if next not in previous:
# Greedy Best First Search will only use the heuristic to determine the path to choose
if heuristic == 1:
heuristicValue = heuristicEuclidean(graph.getWeight(current), graph.getWeight(goal))
else:
heuristicValue = heuristicChebyshev(graph.getWeight(current), graph.getWeight(goal))
priority = heuristicValue
frontier.put(next, priority)
counter = counter + 1
previous[next] = current
space = max(space, frontier.size())
return previous, counter, space
class PQueueTestCase(unittest.TestCase):
'''Test creation and use of a priority queue.'''
def setUp(self):
self.pq = PriorityQueue()
self.r1 = Rectangle(0, 150, 200, 50, media.forestgreen, 1)
self.o1= Oval(120, 160, 60, 60, media.white, 4)
self.o2 = Oval(120, 115, 45, 45, media.yellow, 3)
self.o3 = Oval(120, 80, 30, 30, media.orange, 2)
def tearDown(self):
self.pq = None
self.r1 = None
self.o1 = None
self.o2 = None
self.o3 = None
def testSize(self):
assert self.pq.size() == 0, 'mismatch in predicted pqueue size'
def testEnqueueSize(self):
self.pq.enqueue(self.r1)
assert self.pq.size() == 1, \
'mismatch in pqueue size after enqueue'
def testDequeue(self):
self.pq.enqueue(self.r1)
result = self.pq.dequeue()
assert result is self.r1, \
'mismatch in dequeued value'
def testMultipleEnqueueSize(self):
self.pq.enqueue(self.o1)
self.pq.enqueue(self.o2)
self.pq.enqueue(self.o3)
assert self.pq.size() == 3, \
'mismatch in pqueue size after enqueues'
def testMultipleDequeue(self):
self.pq.enqueue(self.o1)
self.pq.enqueue(self.o2)
self.pq.enqueue(self.o3)
result = self.pq.dequeue()
assert result is self.o3, 'mismatch in dequeuing correct value'
def main():
maze = Maze("maze2.png")
paths = PriorityQueue()
start = maze.getStart()
end = maze.getEnd()
paths.insert(PathHead(start[0], start[1], calcDistance(start, end)))
current = paths.minimum()
while paths.size() > 0 and current.getDistance() != 0.0:
current = paths.extractMin()
maze.setNodeVisited(current.getCords())
surroundings = maze.checkSurroundings(current.getCords())
insertSurroundings(paths, surroundings, current, end)
solved = maze.getMaze()
solved = numpy.array(solved)
img = Image.fromarray(solved.astype('uint8'), 'RGB')
img.save('solved.png')
import priorityqueue
from priorityqueue import PriorityQueue
import numpy as np
pq = PriorityQueue(0, 20)
ints = np.random.randint(1, 100, size=20)
print("Inserting 20 integers into pq: {0}".format(ints))
[pq.insert(i) for i in ints]
print("pq is full: {0}".format(pq.isFull()))
print("pq size: {0}".format(pq.size()))
print("Deleting 20 integers from pq: {0}".format(
[pq.delMin() for i in range(20)], sep=','))
print("pq is empty: {0}".format(pq.isEmpty()))
print("pq size: {0}".format(pq.size()))
import priorityqueue
from priorityqueue import PriorityQueue
import numpy as np
pq = PriorityQueue(0,20)
ints = np.random.randint(1,100, size=20)
print("Inserting 20 integers into pq: {0}".format(ints))
[pq.insert(i) for i in ints]
print("pq is full: {0}".format(pq.isFull()))
print("pq size: {0}".format(pq.size()))
print("Deleting 20 integers from pq: {0}".format([pq.delMin() for i in range(20)], sep=','))
print("pq is empty: {0}".format(pq.isEmpty()))
print("pq size: {0}".format(pq.size()))