在 networkx 中获取具有边标签、颜色和权重的复杂图形，并逐步重现它

我有一个有序概念类别的数据集，并按照它们出现的顺序绘制图形，并根据节点之间连接多次发生的时间来标记概念距离和厚度。

我在 networkx 中有一个由以下方式生成的图表：

1. 一次添加一条边；然后
2. 将字典中的所有边缘信息添加到标签中；然后
3. 根据位置词典将位置应用到所有事物上

我花了很长时间才弄清楚如何制作正确的图表，但现在我对它很满意。我的问题是我想采用完整的图表 G 并一次复制一条边，这样我就可以随时制作动画。

这是我所做的，但它非常容易出错，因为标签出现在边缘之前。有什么想法可以正确做到这一点吗？

   ###############################################
    # Doing the bit where we output the video of the graph being constructed

    # Create an empty directed graph for animation
    positions = pos_dic
    G_animated = nx.DiGraph()

    # Initialize figure and axis for animation
    fig, ax = plt.subplots(figsize=(20, 12))
    plt.title(f'Graph for {key} at {timestamp}',font)

    # Step 2: Extract the edges, colors, weights, and labels from the original graph
    edges = list(G.edges(data=True))
    edge_colors = [attr['color'] for u, v, attr in edges]
    edge_weights = [attr['weight'] for u, v, attr in edges]
    edge_labels = {(u, v): attr['label'] for u, v, attr in edges}

    # Step 3: Function to update the graph step by step
    def update_graph(num):
        ax.clear()  # Clear the plot for the next frame
        
        if num < len(edges):
            u, v, attr = edges[num]
            
            # Add the nodes if they don't exist yet in G_animated
            if u not in G_animated.nodes:
                G_animated.add_node(u)
            if v not in G_animated.nodes:
                G_animated.add_node(v)
            
            # Now, add the edge with the attributes
            G_animated.add_edge(u, v, **attr)
        
        # Draw the updated graph with custom positions
        edge_color_list = [edge_colors[i] for i in range(len(G_animated.edges))]
        nx.draw(G_animated, pos=positions, ax=ax, with_labels=False, node_color='lightblue', 
                edge_color=edge_color_list, width=edge_weights[:len(G_animated.edges)], 
                node_size=500, arrows=True)
        nx.draw_networkx_labels(G_animated, pos_dic, font_size=11, font_color='black', font_weight='bold', bbox=dict(facecolor='white', edgecolor='black', boxstyle='round,pad=0.3'))
        # Draw edge labels (showing the label attributes)
        nx.draw_networkx_edge_labels(G_animated, pos=positions, edge_labels=edge_labels)

    # Step 4: Create animation object
    ani = FuncAnimation(fig, update_graph, frames=len(edges), repeat=False, interval=3000)

    # Step 5: Save the animation as a video (e.g., .mp4)
    writer = FFMpegWriter(fps=1, metadata=dict(artist='Nick Kelly'), bitrate=1800)
    ani.save(f"graph_animation_{key}.mp4", writer=writer)

    # plt.show()
    plt.close()

    # End video here
    ##################################################

这会产生非常故障的动画，请参阅此文件作为示例：https ://1drv.ms/v/s!AuaSDysD-RqIhOsFSP6pYZCUmvDYvQ?e=iz2k8L