def questionOne():
""" QUESTION ONE: Create a random graph with
N = 10000 and p = 0.0005 and analyze its properties.
"""
N = 10000 # number of nodes
p = 0.0005 #probability of linking
# building the Graph
G = nx.gnp_random_graph(N, p)
# compute de the number of connected componentes
cc = nx.connected_components(G) #connected components
ncc = nx.number_connected_components(G) #number of connected components
print("Number of connected components:", ncc)
# the size of the giant component
sortedComponents = sorted(
cc, key=len,
reverse=True) # sort components in descending order (length)
gc = G.subgraph(sortedComponents[0]) #the giant component
print("Size of the giant component:", gc.number_of_nodes())
# the average distance in the giant component
ad = nx.average_shortest_path_length(gc)
print("Average distance in the giant component:", ad)
def _compute_component_scores(self):
components = self._components.items()
# for each component, compute all necessary scores
for idx, _component in components:
component_graph = nx.subgraph(self._graph, _component)
component_score = {
'total_pop':
sum(self._graph.nodes[node]['pop'] for node in _component),
'components':
nx.number_connected_components(component_graph),
}
self._component_scores[idx] = component_score
if line.endswith("\\\n"): # continuation line, buffer, goto next
oldline = line.strip("\\\n")
continue
(headname, tails) = line.split(":")
# head
numfind = re.compile("^\d+") # re to find the number of this word
head = numfind.findall(headname)[0] # get the number
G.add_node(head)
for tail in tails.split():
if head == tail:
print("skipping self loop", head, tail, file=sys.stderr)
G.add_edge(head, tail)
return G
if __name__ == '__main__':
G = roget_graph()
print("Loaded roget_dat.txt containing 1022 categories.")
print("digraph has %d nodes with %d edges"
% (nx.number_of_nodes(G), nx.number_of_edges(G)))
UG = G.to_undirected()
print(nx.number_connected_components(UG), "connected components")
nx.draw_circular(UG)
plt.show()
numfind = re.compile(r"^\d+") # re to find the number of this word
head = numfind.findall(headname)[0] # get the number
G.add_node(head)
for tail in tails.split():
if head == tail:
print("skipping self loop", head, tail, file=sys.stderr)
G.add_edge(head, tail)
return G
G = roget_graph()
print("Loaded roget_dat.txt containing 1022 categories.")
print(
f"digraph has {nx.number_of_nodes(G)} nodes with {nx.number_of_edges(G)} edges"
)
UG = G.to_undirected()
print(nx.number_connected_components(UG), "connected components")
options = {
"node_color": "black",
"node_size": 1,
"edge_color": "gray",
"linewidths": 0,
"width": 0.1,
}
nx.draw_circular(UG, **options)
plt.show()
import gowalla from networkx import nx network = gowalla.get_spatial_friendship_network() locations = gowalla.get_users_locations() edges = set() for user, friends in network.items(): l_user = locations[user] for friend in friends: l_friend = locations[friend] dist = gowalla.calc_spatial_dist(l_user, l_friend) if dist < 160: if (user, friend) not in edges and (friend, user) not in edges: edges.add((user, friend)) G = nx.Graph() for a, b in edges: G.add_edge(a, b) print nx.number_connected_components(G)
#codigo em python 3
#pacote para fazer graficos
import matplotlib.pyplot as plt
#pacote para caracterizacao de redes
from networkx import nx
M = 100 # numero de vertices
p = 0.01 # probabilidade de conexao em um par aleatorio
#geracao da rede de Erdos Renyi, tambem chamada de binomial
grafo = nx.binomial_graph(M, p)
#escreve na tela informacoes gerais do grafo
print(nx.info(grafo))
#cria uma visualizacao do grafo
nx.draw(grafo,nodesize = 0.5)
#salva a visualizacao em um arquivo
plt.savefig('fig_erdos_renyi_v1a.png',dpi = 300, bbox_inches='tight')
#calcula o numero de componentes
nc = nx.number_connected_components(grafo)
print(nc) #escreve na tela
#calcula o tamanho (numero de vertices) da maior componente
largest_cc = max(nx.connected_components(grafo), key=len)
sc = len(largest_cc)
print(sc) #escreve na tela
