draw-pic.zip

import networkx as nx import matplotlib.pyplot as plt import xlrd import numpy as np class Graph_Matrix: """ Adjacency Matrix """ def __init__(self, vertices=[], matrix=[]): """ :param vertices:a dict with vertex id and index of matrix , such as {vertex:index} :param matrix: a matrix """ self.matrix = matrix self.edges_dict = {} # {(tail, head):weight} self.edges_array = [] # (tail, head, weight) self.vertices = vertices self.num_edges = 0 # if provide adjacency matrix then create the edges list if len(matrix) > 0: if len(vertices) != len(matrix): raise IndexError self.edges = self.getAllEdges() self.num_edges = len(self.edges) # if do not provide a adjacency matrix, but provide the vertices list, build a matrix with 0 elif len(vertices) > 0: self.matrix = [[0 for col in range(len(vertices))] for row in range(len(vertices))] self.num_vertices = len(self.matrix) def isOutRange(self, x): try: if x >= self.num_vertices or x <= 0: raise IndexError except IndexError: print("节点下标出界") def isEmpty(self): if self.num_vertices == 0: self.num_vertices = len(self.matrix) return self.num_vertices == 0 def add_vertex(self, key): if key not in self.vertices: self.vertices[key] = len(self.vertices) + 1 # add a vertex mean add a row and a column # add a column for every row for i in range(self.getVerticesNumbers()): self.matrix[i].append(0) self.num_vertices += 1 nRow = [0] * self.num_vertices self.matrix.append(nRow) def getVertex(self, key): pass def add_edges_from_list(self, edges_list): # edges_list : [(tail, head, weight),()] for i in range(len(edges_list)): self.add_edge(edges_list[i][0], edges_list[i][1], edges_list[i][2], ) def add_edge(self, tail, head, cost=0): # if self.vertices.index(tail) >= 0: # self.addVertex(tail) if tail not in self.vertices: self.add_vertex(tail) # if self.vertices.index(head) >= 0: # self.addVertex(head) if head not in self.vertices: self.add_vertex(head) # for directory matrix self.matrix[self.vertices.index(tail)][self.vertices.index(head)] = cost # for non-directory matrix # self.matrix[self.vertices.index(fromV)][self.vertices.index(toV)] = \ # self.matrix[self.vertices.index(toV)][self.vertices.index(fromV)] = cost self.edges_dict[(tail, head)] = cost self.edges_array.append((tail, head, cost)) self.num_edges = len(self.edges_dict) def getEdges(self, V): pass def getVerticesNumbers(self): if self.num_vertices == 0: self.num_vertices = len(self.matrix) return self.num_vertices def getAllVertices(self): return self.vertices def getAllEdges(self): for i in range(len(self.matrix)): for j in range(len(self.matrix)): if 0 < self.matrix[i][j] < float('inf'): self.edges_dict[self.vertices[i], self.vertices[j]] = self.matrix[i][j] self.edges_array.append([self.vertices[i], self.vertices[j], self.matrix[i][j]]) return self.edges_array def __repr__(self): return str(''.join(str(i) for i in self.matrix)) def to_do_vertex(self, i): print('vertex: %s' % (self.vertices[i])) def to_do_edge(self, w, k): print('edge tail: %s, edge head: %s, weight: %s' % (self.vertices[w], self.vertices[k], str(self.matrix[w][k]))) def create_undirected_matrix(my_graph,matrix): #nodes = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'] nodes = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60', '61', '62', '63', '64', '65', '66', '67', '68', '69', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', ] #matrix = [[0, 1, 1, 1, 1, 1, 0, 0], # a # [0, 0, 1, 0, 1, 0, 0, 0], # b # [0, 0, 0, 1, 0, 0, 0, 0], # c # [0, 0, 0, 0, 1, 0, 0, 0], # d # [0, 0, 0, 0, 0, 1, 0, 0], # e # [0, 0, 1, 0, 0, 0, 1, 1], # f # [0, 0, 0, 0, 0, 1, 0, 1], # g # [0, 0, 0, 0, 0, 1, 1, 0]] # h my_graph = Graph_Matrix(nodes, matrix) print(my_graph) return my_graph def matrix(path):#读取excel表格里的数据 table = xlrd.open_workbook(path).sheets()[6] # 获取第6个sheet表 row = table.nrows # 行数 col = table.ncols # 列数 datamatrix = np.zeros((row, col)) # 生成一个nrows行ncols列，且元素均为0的初始矩阵 for x in range(col): try: cols = np.matrix(table.col_values(x)) # 把list转换为矩阵进行矩阵操作 datamatrix[:, x] = cols # 按列把数据存进矩阵中 except: print(x) print(datamatrix.shape) return datamatrix def create_directed_matrix(my_graph):#二维数组生成有向图 nodes = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'] inf = float('inf') matrix = [[0, 2, 1, 3, 9, 4, inf, inf], # a [inf, 0, 4, inf, 3, inf, inf, inf], # b [inf, inf, 0, 8, inf, inf, inf, inf], # c [inf, inf, inf, 0, 7, inf, inf, inf], # d [inf, inf, inf, inf, 0, 5, inf, inf], # e [inf, inf, 2, inf, inf, 0, 2, 2], # f [inf, inf, inf, inf, inf, 1, 0, 6], # g [inf, inf, inf, inf, inf, 9, 8, 0]] # h my_graph = Graph_Matrix(nodes, matrix) print(my_graph) return my_graph def create_directed_graph_from_edges(my_graph):#用边生成有向图 nodes = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] edge_list = [('A', 'F', 9), ('A', 'B', 10), ('A', 'G', 15), ('B', 'F', 2), ('G', 'F', 3), ('G', 'E', 12), ('G', 'C', 10), ('C', 'E', 1), ('E', 'D', 7)] my_graph = Graph_Matrix(nodes) my_graph.add_edges_from_list(edge_list) print(my_graph) return my_graph def draw_undircted_graph(my_graph):#显示无向图 G = nx.Graph() # 建立一个空的无向图G for node in my_graph.vertices: G.add_node(str(node)) for edge in my_graph.edges: G.add_edge(str(edge[0]), str(edge[1])) print("nodes:", G.nodes()) # 输出全部的节点： [1, 2, 3] print("edges:", G.edges()) # 输出全部的边：[(2, 3)] print("number of edges:", G.number_of_edges()) # 输出边的数量：1 nx.draw(G, node_color = 'b',edge_color = 'r',with_labels=True) plt.savefig("undirected_graph.png") plt.show() def draw_directed_graph(my_graph):#显示有向图，带权 G = nx.DiGraph() # 建立一个空的无向图G for node in my_graph.vertices: G.add_node(str(node)) G.add_weighted_edges_from(my_graph.edges_array) print("nodes:", G.nodes()) # 输出全部的节点 print("edges:", G.edges()) # 输出全部的边 print("number of edges:", G.number_of_edges()) # 输出边的数量 nx.draw(