def main():
# greeting
print("Welcome to Alice's Restaurant")
print("Open everyday except Thanksgiving.")
# display command list
print('Enter "a" to add a guest to the waiting list.')
print(
'Enter "s" to remove the next guest from the waiting list once they have been seated.'
)
print('Enter "q" to quit.')
# initialize reservation list & guest tracking number
reservationList = BinHeap()
guestnumber = 0
# get user imput
command = input("Command: ")
while command.lower() != "q":
# add guest
if command.lower() == "a":
name = input("Guest name: ")
priority = input("Guest priority: ")
guestnumber += 1
newguest = Guest(name, priority, guestnumber)
reservationList.insert(newguest)
print("A reservation for", newguest.name, "has been made.")
print("They have been assigned a priority of",
newguest.priority + ".")
print("They are currently", reservationList._heap.index(newguest),
"in line for a table.")
command = input("Command: ")
# get next guest from list
elif command.lower() == "s":
serving = reservationList.pop()
# check if there are guests on list
if serving:
print("Now serving", serving.name)
command = input("Command: ")
# warn if no guests on list
else:
print("There are no customers on the waiting list")
command = input("Command: ")
# control for invalid commands
elif command.lower() != "a" or "s":
print("Unrecognised command! Please try again.")
command = input("Command: ")
# exit program
else:
print("Goodbye!")
exit()
class PriorityQueue():
"""优先级队列"""
def __init__(self, maxNode):
self.priorityQueue = BinHeap(maxNode)
self.dataDict = dict()
def enqueue(self, priority, data):
"""入队"""
self.priorityQueue.insert(priority)
self.dataDict[priority] = data
def dequeue(self):
"""出队"""
pri = self.priorityQueue.delMin()
return self.dataDict[pri]
class PriorityQueue:
def __init__(self):
self._heap = BinHeap()
def isEmpty(self):
return self._heap.isEmpty()
def enqueue(self, item):
self._heap.insert(item)
def dequeue(self):
return self._heap.delMin()
def size(self):
return self._heap.size()
def __str__(self):
return str(self._heap)
def find_split(segments):
"""Finds an appropriate pair of segments that differ enough in timbre but
also don't lie two near the beginning or the end."""
#initiate minimum binary heap instance
deltas = BinHeap()
#compares delta for each pair of segments (1,2), (2,3), etc... and save the values in deltas
for i in range(len(segments)-2):
deltas.insert((find_delta_segment(segments[i], segments[i+1]), i))
#take the largest difference
a = deltas.delMin()
#makes sure that a is not too near the beginning (before 1/6 of song) or
#the end (after 5/6 of song)
while a[1] < len(segments)//4 or a[1] > (3*len(segments))//4:
a = deltas.delMin()
return a
def dijkstra(vertice_list,src,num_ver):
import CPUtimer
timer = CPUtimer.CPUTimer()
timer.reset()
cond = False
parent = []
#marca todos os vertices como nao visitados
for i in range(num_ver):
parent.append(-1)
#vertice inicial tem distancia 0. Na 1 iteracao todos os demais estao setados com 'infinidade'
vertice_list[src].dist=0
from binheap import BinHeap
f = BinHeap()
f.insert(vertice_list[src].dist,src)
#print("Nodes:",f.total_nodes)
#pelo numero de vertices, escolha o vertice de menor distancia atualmente no grafo.
#Na primeira iteracao sera o source.
i = 0
while(f.currentSize!=0):
#while(i<10):
i+=1
v_min_node = f.delMin() # 1.1
#print('key:',v_min_node.key)
#print("Nodes:",f.total_nodes)
v_min = vertice_list[v_min_node[1]]
if(v_min==None):
continue
v_min.visited=1#marque vertice minimo como ja visitado. Desse modo o 1.2 sera feito, pois nao sera mais contado
#para cada vertice adjacente ao vertice minimo
for key in v_min.adjs:# 1.3
adj_ver = vertice_list[v_min.adjs[key].id]#pega o vertice adjacente
#Se a distancia atual do vertice minimo, mais o seu peso, for menor que a distancia do vert adjacente
if(adj_ver.visited==0 and v_min.dist + v_min.weights[key] < adj_ver.dist ):
adj_ver.dist = v_min.dist + v_min.weights[key] #a distancia do vertice adjacente tera esse novo valor
parent[adj_ver.id] = v_min.id # a pos que era do vertice adjacente, sera do menor v agora
f.insert(adj_ver.dist,adj_ver.id)
