def dijkstra(source, graph):
pQueue = PriorityQueue()
graph[source]['dist'] = 0
for v in graph:
pQueue.enqueue((graph[v]['dist'], v))
while not pQueue.isEmpty():
u = pQueue.dequeue()
baseDist = graph[u]['dist']
print('Visiting',u, 'at distance', baseDist)
print('Edges from this vertex', graph[u]['edgeTo'])
for w in graph[u]['edgeTo']:
edgeLen = graph[u]['edgeTo'][w]
newDist = baseDist + edgeLen
currentDist = graph[w]['dist']
if newDist < currentDist:
graph[w]['dist'] = newDist
print('Distance to', w, 'set to', baseDist, '+', edgeLen, '=', newDist)
pQueue.changePriority(w, newDist)
print()
# Print the results
print('Final result: distances of all vertices from ' + source)
distancesList = []
for v in graph:
distancesList.append((v, graph[v]['dist']))
print(distancesList)
def bestFirstSearch(aTree):
pQueue = PriorityQueue()
pQueue.enqueue((aTree.getRoot().getPayload(), aTree.getRoot()))
while not pQueue.isEmpty():
printPriorityQueue(pQueue)
nextNode = pQueue.dequeue()
print('Visiting: ',
nextNode.getKey(),
'(',
nextNode.getPayload(),
')',
sep='')
children = nextNode.getChildren()
for child in children:
pQueue.enqueue((child.getPayload(), child))
printPriorityQueue(pQueue)
def prim(first, graph):
pQueue = PriorityQueue()
graph[first]['dist'] = 0
for i in graph:
pQueue.enqueue((graph[i]['dist'], i))
mst = []
# dictionary to record for each vertex in the queue its nearest vertex in the tree
nearestInTreeTo = {}
print('Removing front item', first, 'from priority queue')
while not pQueue.isEmpty():
u = pQueue.dequeue()
print('Inspecting neighbours of vertex', u)
for w in graph[u]['edgeTo']:
edgeLen = graph[u]['edgeTo'][w]
print(u, 'to', w,':', edgeLen)
currentDist = graph[w]['dist']
if w in pQueue and edgeLen < currentDist:
graph[w]['dist'] = edgeLen
pQueue.changePriority(w, edgeLen)
nearestInTreeTo[w] = u
if not pQueue.isEmpty():
print('PriorityQueue is now :', pQueue.getEntries())
print()
nextVertex = pQueue.peek()
print('Next vertex is:', nextVertex)
weight = graph[nextVertex]['dist']
newEdge = [[(nearestInTreeTo[nextVertex], nextVertex), weight]]
print('Nearest in tree to', nextVertex,'is', nearestInTreeTo[nextVertex])
print('Adding', newEdge, 'to the tree')
mst = mst + [[(nearestInTreeTo[nextVertex], nextVertex), weight]]
print('Tree is now :', mst)
print()
print('Removing front item', nextVertex, 'from priority queue')
print('MST completed')
return mst
bestFirstSearchRecursive(pQueue)
#Helper function for bestFirstSearch() and bestFirstSearchRecursive()
def printPriorityQueue(aPQueue):
aList = aPQueue.getEntries()
print('pQueue: [', end='')
if not aPQueue.isEmpty():
for item in aList[:-1]:
print(item[1].getKey(), '(', item[0], '), ', sep='', end='')
lastItem = aList[len(aList) - 1]
print(lastItem[1].getKey(), '(', lastItem[0], ')', sep='', end='')
print(']')
print()
#Test the functions
print('------Testing breadthFirstSearch()------')
breadthFirstSearch(gameTree)
print()
print('------Testing bestFirstSearch()------')
bestFirstSearch(gameTree)
print()
print('------Testing bestFirstSearchRecursive()------')
thePQueue = PriorityQueue()
thePQueue.enqueue((gameTree.getRoot().getPayload(), gameTree.getRoot()))
bestFirstSearchRecursive(thePQueue)
