def fastBuildGraph(node, edge, r_flag, e_flag):
"""Costruisce un grafo tramite liste di incidenza
con i valori dei nodi , archi , passati dal Parsers,
funzione asintoticamente più veloce della precedente
"""
g = Graph()
n = []
for i in range(node):
n.append(g.insertNode(i))
for j in range(edge):
tail = random.randint(0, node - 1)
head = random.randint(0, node - 1)
if r_flag: # Flag a True creo pesi random da perturbare
weight = round(random.randint(0, 1000) + \
(random.random() * (10 ** -3)), 5)
elif e_flag: # Flag a True creo archi con pesi uguali
weight = random.choice(range(0, 10))
else:
weight = random.choice(range(0, 1000, 2))
if tail == head: # elimino gli archi A -> A
continue
g.insertEdge(n[tail].index, n[head].index, weight)
g.insertEdge(n[head].index, n[tail].index, weight)
GraphHelper.cleanGraph(g) # Utilizzo la funzione cleanGraph
return g
def buildGraph():
g = Graph()
ginfo = ((0, 1, 3.0), (0, 3, 1.0), (1, 3, 2.0), (1, 2, 4.0), (2, 3, 5.0))
n = []
for i in range(4):
n.append(g.insertNode(i))
for e in ginfo:
g.insertEdge(n[e[0]].index, n[e[1]].index, e[2])
g.insertEdge(n[e[1]].index, n[e[0]].index, e[2])
return g
def buildGraph():
"""Costruisce un grafo tramite liste di incidenza."""
g = Graph()
ginfo = ((0, 1, 3.0), (0, 3, 1.0), (1, 3, 2.0), (1, 2, 4.0)\
, (2, 3, 5.0))
n = []
for i in range(4):
n.append(g.insertNode(i))
for e in ginfo:
g.insertEdge(n[e[0]].index, n[e[1]].index, e[2])
g.insertEdge(n[e[1]].index, n[e[0]].index, e[2])
return g
def buildGraph(node, edge, r_flag, e_flag):
"""Costruisce un grafo tramite liste di incidenza
con i valori dei nodi , archi , passati dal Parsers.
"""
g = Graph()
tail = []
head = []
weight = []
listEdge = ()
n = []
for i in range(node):
n.append(g.insertNode(i))
for x in range(edge):
tail.append(random.randint(0, node - 1))
head.append(random.randint(0, node - 1))
weight = random.sample(range(1000000), edge) #Pesi random univoci
if not (e_flag or r_flag):
print('Pesi archi univoci=\n', weight, '\n')
if e_flag: #Flag a True creo archi con pesi uguali
i = 0
while i < len(weight) - 2:
weight[i] = weight[i + 2]
weight[i + 1] = weight[i + 2]
i += 3
print('pesi archi uguali= \n', weight, '\n')
if r_flag: #Flag a True creo pesi random da perturbare
weight.clear()
for i in range(edge): # sto perturbando l'arco
weight.append(random.uniform(1, 100))
val = weight.pop(i)
_val = round(val + (random.random() * 10**-3), 5)
weight.insert(i, _val)
print('pesi archi random perturbati=\n', weight, '\n')
for u in range(edge):
listEdge += ((tail[u], head[u], weight[u]), )
ginfo = listEdge
for e in ginfo:
if e[0] == e[1]: # elimino gli archi A -> A
continue
g.insertEdge(n[e[0]].index, n[e[1]].index, e[2])
g.insertEdge(n[e[1]].index, n[e[0]].index, e[2])
GraphHelper.cleanGraph(g) # Utilizzo la funzione cleanGraph
return g
def buildGraph(num_nodes):
"""
Build a sample complete graph.
:param num_nodes number of nodes.
:return: a sample complete graph.
"""
graph = Graph()
nodes = []
for i in range(num_nodes):
nodes.append(graph.addNode(i))
for src in nodes:
for dst in nodes:
if dst.id > src.id:
graph.insertEdge(src.id, dst.id, num_nodes - src.id)
return graph
currWeight = currentWeight[head]
# relaxation step
if currWeight == INFINITE:
currentWeight[head] = weight
elif weight < currWeight:
currentWeight[head] = weight
curr = curr.next
return mstWeight, tree
if __name__ == "__main__":
#graph = GraphHelper.buildGraph(5)
#graph.print()
graph = Graph()
graph.addNode('A')
graph.addNode('B')
graph.addNode('C')
graph.addNode('D')
graph.addNode('E')
graph.addNode('F')
graph.addNode('G')
graph.insertEdge(0, 1, 7)
graph.insertEdge(0, 2, 14)
graph.insertEdge(0, 3, 30)
graph.insertEdge(1, 2, 21)
graph.insertEdge(2, 3, 10)
graph.insertEdge(2, 4, 1)
graph.insertEdge(4, 5, 6)