def generate_independent_edges(graph, num_nodes, prob_edges, allow_loops=False):
"""
Generate an Erdos-Renyi random graph. Possible edges are added with
a fixed probability.
@type: graph: graph
@param: graph: Graph.
@type: num_nodes: number
@param: num_nodes: Number of nodes.
@type: prob_edges: number
@param: prob_edges: Probability for adding a possible edge.
@type: allow_loops: bool
@param: allow_loops: If set to True, loops can be added. Defaults to False.
"""
# Discover if graph is directed or not
directed = isinstance( graph, digraph )
# Nodes first
nodes = xrange(num_nodes)
graph.add_nodes(nodes)
# Build a list of all possible edges
edges = generate_possible_edges(nodes, directed, allow_loops)
# Now do a random experiment for every edge and add it in case of success
for each in edges:
if random() < prob_edges:
graph.add_edge(each[0], each[1])
def page_rank(self):
#将图中没有出链的节点改为对所有节点有出链
for node in self.graph.nodes():
if len(self.graph.neighbors(node))==0:
for node2 in self.graph.nodes():
graph.add_edge(self.graph,(node,node2))
nodes=self.graph.nodes()
graph_size=len(nodes)
if graph_size==0:
return{}
page_rank=dict.fromkeys(nodes,1.0/graph_size)#给每一个顶点赋予初始的PR值
damping_value=(1.0-self.damping_factor)/graph_size#公式中的(1-a)/N部分
flag=False
for i in range(self.max_iterations):
change=0
for node in nodes:
rank=0
for incident_page in self.graph.neighbors(node):
rank+=self.damping_factor*(page_rank[incident_page]/len(self.graph.neighbors(incident_page)))
rank+=damping_value
change+=abs(page_rank[node]-rank)#绝对值
page_rank[node]=rank
print("This is No.%s iteration"%(i+1))
print(page_rank)
if change<self.min_delta:
flag=True
break
if flag:
print("finished in %s iterations!"%node)
else:
print("finished out of 100 iterations!")
return page_rank
def render_graph_color(graph_object,filename_str):
import pydot
node_list, adjacency_matrix = graph_object.labels, graph_object.adjacency_matrix
if not (adjacency_matrix.shape[0] == adjacency_matrix.shape[1]):
raise Exception("adjacency matrix should be square")
if not (len(node_list) == adjacency_matrix.shape[0]):
raise Exception("number of nodes is inconsistent with the number of available node labels")
if is_directed(adjacency_matrix):
graph = pydot.Dot(graph_type='digraph')
else:
graph = pydot.Dot(graph_type='graph')
nodes_dot=[]
for n in node_list:
tmp = pydot.Node(n)
nodes_dot.append(tmp)
graph.add_node(tmp)
for (i,j) in get_indices(adjacency_matrix):
graph.add_edge(pydot.Edge(nodes_dot[i], nodes_dot[j], label=graph_object.property_str, labelfontcolor="#009933", fontsize="10.0", color=graph_object.edge_color))
name = "%s.png" % filename_str
graph.write_png(name)
def AddNodeAndEdge(graph, nodeLst):
for node in nodeLst:
if not graph.has_node(node):
graph.add_node(node)
i = 0
while i < len(nodeLst)-1:
if not graph.has_edge((nodeLst[i],nodeLst[i+1])):
graph.add_edge((nodeLst[i],nodeLst[i+1]))
i += 1
def co_occurence_edge(graph, window_size=2):
window_start = 0
window_end = window_size
while 1:
window_words = tagged[window_start:window_end]
if len(window_words) == 2:
print window_words
try:
graph.add_edge((window_words[0][0], window_words[1][0]))
except AdditionError, e:
print 'already added %s, %s' % ((window_words[0][0], window_words[1][0]))
else:
break
window_start += 1
window_end += 1
def render_multi_prop_graph(multi_prop_graph,filename_str):
node_list, adjacency_matrix = multi_prop_graph.labels, multi_prop_graph.adjacency_matrix
if not (adjacency_matrix.shape[0] == adjacency_matrix.shape[1]):
raise Exception("adjacency matrix should be square")
if not (len(node_list) == adjacency_matrix.shape[0]):
raise Exception("number of nodes is inconsistent with the number of available node labels")
if is_directed(adjacency_matrix):
graph = pydot.Dot(graph_type='digraph')
direction = 'forward'
else:
graph = pydot.Dot(graph_type='graph',compound='true',mindist='0',ranksep='0',nodesep='0')
direction = 'none'
nodes_dot=[]
for n in node_list:
tmp = pydot.Node(n)
nodes_dot.append(tmp)
graph.add_node(tmp)
y = deepcopy(adjacency_matrix)
for (i,j) in get_indices(y):
if y[i][j] == 1:
if y[j][i] ==1:
y[j][i] =0
direction = 'none'
graph.add_edge(pydot.Edge(nodes_dot[i], nodes_dot[j], label=multi_prop_graph.property_str, labelfontcolor="#009933", fontsize="10.0", dir=direction,color=multi_prop_graph.edge_colormap[node_list[i],node_list[j]]))
if is_directed(adjacency_matrix) :
direction = 'forward'
name = "%s.png" % filename_str
#graph = add_legend(graph, property_colormap)
graph.write_png(name)
def drawGraphFromSM2(SM, names, outFile, Cut):
graph = pydot.Dot(graph_type='graph')
# THRESHOLD SM:
nonZeroMean = np.mean(SM[SM.nonzero()])
if Cut:
T = 5.0 * nonZeroMean
else:
T = 0.0;
for i in range(SM.shape[0]):
for j in range(SM.shape[0]):
if SM[i,j] <= T:
SM[i,j] = 0.0
else:
SM[i,j] = 1.0
numOfConnections = sum(SM, axis = 0)
#fig = plt.figure(1)
#plot1 = plt.imshow(SM, origin='upper', cmap=cm.gray, interpolation='nearest')
#plt.show()
numOfConnections = 9*numOfConnections / max(numOfConnections)
for i,f in enumerate(names):
if sum(SM[i,:])>0:
fillColorCurrent = "{0:d}".format(int(ceil(numOfConnections[i])))
# NOTE: SEE http://www.graphviz.org/doc/info/colors.html for color schemes
node = pydot.Node(f, style="filled", fontsize="8", shape="egg", fillcolor=fillColorCurrent, colorscheme = "reds9")
graph.add_node(node)
for i in range(len(names)):
for j in range(len(names)):
if i<j:
if SM[i][j] > 0:
#gr.add_edge((names[i], names[j]))
edge = pydot.Edge(names[i], names[j])
graph.add_edge(edge)
graph.write_png(outFile)
