def huffman(str):
freqdict = frequency(str)
pq = PriorityQueue()
for char in freqdict: # NOT for char in STRING!!
t = BinaryTree(char)
key = freqdict[char]
pq.add((key, t))
while pq.getSize() > 1:
u = pq.delMin()
v = pq.delMin()
t = BinaryTree(u[0] + v[0])
t.insertLeft(u[1]) # inserts left subtree T1
t.insertRight(v[1]) # inserts right subtree T2
pq.add((u[0] + v[0],
t)) # inserts T into PQ with key f1 + f2 (from u and v tuples)
result = pq.delMin() # tuple of (freq, T)
return result[1] # returns the final tree, T
def dijkstra(aGraph,start): pq = PriorityQueue() start.setDistance(0) pq.buildHeap([(v.getDistance(),v) for v in aGraph]) while not pq.isEmpty(): currentVert = pq.delMin() for nextVert in currentVert.getConnections(): newDist = currentVert.getDistance() + currentVert.getWeight(nextVert) if newDist < nextVert.getDistance(): nextVert.getDistance( newDist ) nextVert.setPred(currentVert) pq.decreaseKey(nextVert,newdist)
def dijkstra(aGraph, start):
pq = PriorityQueue()
start.setDistance(0)
pq.buildHeap([(v.getDistance(), v)
for v in aGraph]) # builds heap from list
while not pq.isEmpty():
currentVert = pq.delMin() # start with the lowest distance item first
for nextVert in currentVert.getConnections(
): # for each connected node...
newDist = currentVert.getDistance() + currentVert.getWeight(
nextVert)
if newDist < nextVert.getDistance():
nextVert.setDistance(newDist)
nextVert.setPred(currentVert)
pq.decreaseKey(
nextVert,
newDist) # is this like bubbling up the priority?