edges = [(0, 1), (0, 2), (1, 2), (2, 3)]

def edges_to_adjacency_matrix(edges):
    # 找到圖中節(jié)點(diǎn)的數(shù)量
    max_node = max(max(edge) for edge in edges) + 1
    
    # 創(chuàng)建零矩陣
    adjacency_matrix = [[0] * max_node for _ in range(max_node)]
    
    # 遍歷原始邊列表，更新鄰接矩陣
    for edge in edges:
        adjacency_matrix[edge[0]][edge[1]] = 1
        adjacency_matrix[edge[1]][edge[0]] = 1  # 如果是無(wú)向圖，邊是雙向的
    
    return adjacency_matrix

# 測(cè)試
edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
adjacency_matrix = edges_to_adjacency_matrix(edges)
for row in adjacency_matrix:
    print(row)

import numpy as np

def edges_to_adjacency_matrix(edges, directed=False):
    max_node = max(max(edge) for edge in edges) + 1
    adjacency_matrix = np.zeros((max_node, max_node))
    for edge in edges:
        if directed:
            adjacency_matrix[edge[0]][edge[1]] = 1
        else:
            adjacency_matrix[edge[0]][edge[1]] = 1
            adjacency_matrix[edge[1]][edge[0]] = 1
    return adjacency_matrix

# 測(cè)試
edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
adjacency_matrix = edges_to_adjacency_matrix(edges)
print("無(wú)向圖的鄰接矩陣：")
print(adjacency_matrix)

directed_edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
directed_adjacency_matrix = edges_to_adjacency_matrix(directed_edges, directed=True)
print("\n有向圖的鄰接矩陣：")
print(directed_adjacency_matrix)

import numpy as np
from scipy.sparse import lil_matrix

def edges_to_adjacency_matrix(edges, directed=False):
    max_node = max(max(edge) for edge in edges) + 1
    adjacency_matrix = lil_matrix((max_node, max_node), dtype=np.int8)
    for edge in edges:
        if directed:
            adjacency_matrix[edge[0], edge[1]] = 1
        else:
            adjacency_matrix[edge[0], edge[1]] = 1
            adjacency_matrix[edge[1], edge[0]] = 1
    return adjacency_matrix

# 測(cè)試
edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
adjacency_matrix = edges_to_adjacency_matrix(edges)
print("無(wú)向圖的鄰接矩陣：")
print(adjacency_matrix.toarray())

directed_edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
directed_adjacency_matrix = edges_to_adjacency_matrix(directed_edges, directed=True)
print("\n有向圖的鄰接矩陣：")
print(directed_adjacency_matrix.toarray())

import numpy as np
from scipy.sparse import lil_matrix

def edges_to_adjacency_matrix(edges, directed=False, weighted=False):
    max_node = max(max(edge[0], edge[1]) for edge in edges) + 1
    adjacency_matrix = lil_matrix((max_node, max_node), dtype=np.float32)
    for edge in edges:
        if directed:
            if weighted:
                adjacency_matrix[edge[0], edge[1]] = edge[2]
            else:
                adjacency_matrix[edge[0], edge[1]] = 1
        else:
            if weighted:
                adjacency_matrix[edge[0], edge[1]] = edge[2]
                adjacency_matrix[edge[1], edge[0]] = edge[2]
            else:
                adjacency_matrix[edge[0], edge[1]] = 1
                adjacency_matrix[edge[1], edge[0]] = 1
    return adjacency_matrix

# 測(cè)試
weighted_edges = [(0, 1, 5), (0, 2, 3), (1, 2, 2), (2, 3, 7)]
weighted_adjacency_matrix = edges_to_adjacency_matrix(weighted_edges, weighted=True)
print("帶權(quán)重的鄰接矩陣：")
print(weighted_adjacency_matrix.toarray())

import networkx as nx
import matplotlib.pyplot as plt

def visualize_adjacency_matrix(adjacency_matrix):
    G = nx.from_numpy_matrix(adjacency_matrix)
    pos = nx.spring_layout(G)  # 定義節(jié)點(diǎn)位置
    nx.draw(G, pos, with_labels=True, node_color='skyblue', node_size=500, font_size=10)  # 繪制圖
    edge_labels = {(i, j): w['weight'] for i, j, w in G.edges(data=True)}  # 獲取邊權(quán)重
    nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, font_size=10)  # 繪制邊權(quán)重
    plt.title("Graph Visualization")
    plt.show()

# 測(cè)試
weighted_edges = [(0, 1, 5), (0, 2, 3), (1, 2, 2), (2, 3, 7)]
weighted_adjacency_matrix = edges_to_adjacency_matrix(weighted_edges, weighted=True)
print("帶權(quán)重的鄰接矩陣：")
print(weighted_adjacency_matrix.toarray())

visualize_adjacency_matrix(weighted_adjacency_matrix.toarray())

import numpy as np

def adjacency_matrix_to_edges(adjacency_matrix):
    edges = []
    for i in range(adjacency_matrix.shape[0]):
        for j in range(adjacency_matrix.shape[1]):
            if adjacency_matrix[i, j] != 0:
                edges.append((i, j, adjacency_matrix[i, j]))
    return edges

# 測(cè)試
adjacency_matrix = np.array([[0, 1, 0, 0],
                              [1, 0, 1, 0],
                              [0, 1, 0, 1],
                              [0, 0, 1, 0]], dtype=np.float32)
print("原始鄰接矩陣：")
print(adjacency_matrix)

edges = adjacency_matrix_to_edges(adjacency_matrix)
print("\n轉(zhuǎn)換后的邊列表：")
print(edges)