def prim(agraph, start):
"""
Prim's algorithm for minimum spanning tree
Using min-heap data structure
return a minimum spanning tree
"""
# vertex of minimun spanning tree
mst_vertex = []
pq = PriorityQueue()
for v in agraph:
v.setDistance(sys.maxsize)
v.setPred(None)
start.setDistance(0)
pq.buildHeap([(v.getDistance(), v) for v in agraph])
while not pq.isEmpty():
u = pq.delMin()
mst_vertex.append(u)
for adjacent in u.getConnections():
newcost = u.getWeight(adjacent)
if adjacent in pq and newcost < adjacent.getDistance():
adjacent.setPred(u)
adjacent.setDistance(newcost)
pq.decreaseKey(adjacent, newcost)
# edges of minimum spanning tree
mst = []
for i in range(1, len(mst_vertex)):
# u, v, cost
mst.append(
(mst_vertex[i - 1], mst_vertex[i], mst_vertex[i].getDistance()))
return mst
def dijkstra_pyds3(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.setDistance(newDist)
nextVert.setPred(currentVert)
pq.decreaseKey(nextVert, newDist)
def prim(agraph, start):
pq = PriorityQueue()
for v in agraph:
v.setDistance(sys.maxsize)
v.setPred(None)
start.setDistance(0)
pq.buildHeap([(v.getDistance(), v) for v in G])
while not pq.isEmpty():
u = pq.delMin()
for adjacent in u.getConnections():
newCost = u.getWeight(adjacent)
if adjacent in pq and newCost < adjacent.getDistance():
adjacent.setPred(u)
adjacent.setDistance(newCost)
pq.decreaseKey(adjacent, newCost)
def dijkstra(self, label: str):
index: int = self.findIndexByLabel(label)
self.vertices[index].weight = 0
pq = PriorityQueue()
pq.buildHeap(self.vertices)
current: Vertex
while not pq.isEmpty():
current = pq.deleteMin()
for neighbour in self.adjacencyList[current.label]:
if current.weight + neighbour.weight < self.vertices[
neighbour.index].weight:
self.prev[self.vertices[
neighbour.index].label] = current.label
self.vertices[
neighbour.
index].weight = current.weight + neighbour.weight
pq.decreaseKey(self.vertices[neighbour.index].key)
def prim(self, start):
# Ejecutamos el algoritmo in-place
pq = PriorityQueue()
for v in self:
v.set_distance(sys.maxsize)
v.set_pred(None)
start.set_distance(0)
pq.buildHeap([(v.get_distance(), v) for v in self])
while not pq.isEmpty():
currentVert = pq.delMin()
for nextVert in currentVert.get_connections():
newCost = currentVert.get_weight(nextVert)
if nextVert in pq and newCost < nextVert.get_distance():
nextVert.set_pred(currentVert)
nextVert.set_distance(newCost)
pq.decreaseKey(nextVert, newCost)
def dijkstra(G, start):
pq = PriorityQueue()
for v in G:
v.setDistance(sys.maxsize)
v.setPred(None)
start.setDistance(0)
pq.buildHeap([(v.getDistance(),v) for v in G])
print(pq)
while not pq.isEmpty():
currentVert = pq.delMin()
for nextVert in currentVert.getConnections():
newDist = currentVert.getDistance() + currentVert.getWeight(nextVert)
if newDist < nextVert.getDistance():
nextVert.setDistance(newDist)
nextVert.setPred(currentVert)
pq.decreaseKey(nextVert, newDist)
print(pq)
def dijkstra(aGraph, start):
"""
Find Single-Source shortest-paths on a weighted, directed graph
Return shortest path
aGraph: class Graph
start: class Vertex
"""
pq = PriorityQueue()
start.setDistance(0)
pq.buildHeap([(v.getDistance(), v) for v in aGraph])
while not pq.isEmpty():
u = pq.delMin()
for adjacent in u.getConnections():
newDist = u.dist + u.getWeight(adjacent)
if adjacent.dist > newDist:
adjacent.setDistance(newDist)
adjacent.setPred(u)
pq.decreaseKey(adjacent, newDist)
def prims(self, label: str):
result: str = ""
index: int = self.findIndexByLabel(label)
self.vertices[index].weight = 0
pq = PriorityQueue()
pq.buildHeap(self.vertices)
current: Vertex
while not pq.isEmpty():
current = pq.deleteMin()
print(current.label)
if self.prev[current.label] is not None:
result += self.prev[
current.label] + " -> " + current.label + ", "
for neighbour in self.adjacencyList[current.label]:
if neighbour.weight < self.vertices[neighbour.index].weight:
self.prev[self.vertices[
neighbour.index].label] = current.label
self.vertices[neighbour.index].weight = neighbour.weight
pq.decreaseKey(self.vertices[neighbour.index].key)
print(result)