我们从Python开源项目中，提取了以下5个代码示例，用于说明如何使用networkx.edges()。
def scan_statistic(mygs, i): """ Computes scan statistic-i on a set of graphs Required Parameters: mygs: - Dictionary of graphs i: - which scan statistic to compute """ ss = OrderedDict() for key in mygs.keys(): g = mygs[key] tmp = np.array(()) for n in g.nodes(): sg = nx.ego_graph(g, n, radius=i) tmp = np.append(tmp, np.sum([sg.get_edge_data(e[0], e[1])['weight'] for e in sg.edges()])) ss[key] = tmp return ss
def create_directed_graphs(self): ''' :return: ''' self.directed_graphs = np.empty( (self.no_of_atoms, self.no_of_atoms - 1, 3), dtype=int) # parse all the atoms one by one and get directed graph to that atom # as the sink node for idx in range(self.no_of_atoms): # get shortest path from the root to all the other atoms and then reverse the edges. path = nx.single_source_dijkstra_path(self.graph, idx) G = nx.DiGraph() for i in range(self.no_of_atoms): temp = path[i] temp.reverse() G.add_path(temp) # do a topological sort to get a order of atoms with all edges pointing to the root topological_order = nx.topological_sort(G) sorted_path = np.empty((self.no_of_atoms - 1, 3)) no_of_incoming_edges = {} for i in range(self.no_of_atoms - 1): node = topological_order[i] edge = (nx.edges(G, node))[0] if edge[1] in no_of_incoming_edges: index = no_of_incoming_edges[edge[1]] no_of_incoming_edges[edge[1]] += 1 else: index = 0 no_of_incoming_edges[edge[1]] = 1 sorted_path[i, :] = [node, edge[1], index] self.directed_graphs[idx, :, :] = sorted_path
def get_production_rule(G, child, itx): rhs = nx.Graph() for n in G.subgraph(child).nodes(): rhs.add_node(n) for e in G.subgraph(child).edges(): rhs.add_edge(e[0], e[1]) # remove links between external nodes (edges in itx) for x in itertools.combinations(itx, 2): if rhs.has_edge(x[0], x[1]): rhs.remove_edge(x[0], x[1]) return rhs
def plot(cov, fig_name): G=nx.Graph() # add node edgewidth = [] edgecolor = [] for i in xrange(cov.shape[0]): G.add_node(i) # add edge for i in xrange(0,cov.shape[0]-1): for j in xrange(i+1,cov.shape[0]): #print i,j,"%.3f " %cov[i][j],', ', G.add_edge(i,j) edgewidth.append(cov[i][j]) edgecolor.append(cov[i][j]) #print #print len(edgewidth), len(edgecolor), len(nx.edges(G)) max_color = 5 mc = max(edgecolor) max_width = 5 mw = max(edgewidth) for i in xrange(len(edgecolor)): edgecolor[i] = (edgecolor[i])*max_color/mc edgewidth[i] = (edgewidth[i])*max_width/mw #print 'width', min(edgewidth), max(edgewidth), 'color', min(edgecolor), max(edgecolor) # set plt.clf() #plt.figure(1, size=(4,4)) pos=nx.spring_layout(G) # draw nx.draw_networkx_nodes(G, pos, node_size=500, node_color='w', labels=True) nx.draw_networkx_labels(G, pos, labels=None, font_size=12, font_color='k', font_family='sans-serif', font_weight='normal', alpha=1.0) nx.draw_networkx_edges(G, pos, edge_cmap = plt.cm.Blues, edge_color = edgecolor, alpha = 1, width = edgewidth) frame1 = plt.gca() frame1.axes.get_xaxis().set_visible(False) frame1.axes.get_yaxis().set_visible(False) plt.savefig(fig_name+".pdf", format='pdf')
