【邻接矩阵生成有向图（带权重）】

效果图

代码

import networkx as nx
import matplotlib.pyplot as plt
#二维数组生成有向图/无向图
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):