如何用数组控制3D图边透明度？解决Axes3DSubplot报错并求库推荐

错误原因 #

draw_networkx_nodes是NetworkX的专属绘图函数，不能通过Matplotlib的3D轴对象（Axes3DSubplot）调用，且NetworkX原生绘图API仅针对2D场景设计，无直接支持3D节点/边绘制的方法。

方案一：基于现有依赖（Matplotlib+NetworkX）手动实现 #

无需额外安装库，直接用Matplotlib的3D绘图API手动绘制节点和边，支持数组控制透明度：

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import networkx as nx
import numpy as np

def draw_graph(edges):
    G = nx.Graph()
    G.add_edges_from(edges)
    pos = nx.spring_layout(G, dim=3)
    pos_ary = np.array([pos[n] for n in G.nodes()])
    node_count = len(G.nodes())
    edge_count = len(G.edges())

    # 生成节点、边的透明度数组（长度匹配节点/边数量）
    node_alphas = np.linspace(0.1, 1, node_count)
    edge_alphas = np.linspace(0.1, 1, edge_count)

    fig = plt.figure(figsize=(20,10), facecolor="w")
    ax = fig.add_subplot(111, projection="3d")

    # 绘制节点，传入透明度数组
    ax.scatter(
        pos_ary[:, 0],
        pos_ary[:, 1],
        pos_ary[:, 2],
        s=200,
        c="b",
        alpha=node_alphas
    )
    
    # 遍历边，逐个绘制并设置对应透明度
    for idx, e in enumerate(G.edges()):
        node0_pos = pos[e[0]]
        node1_pos = pos[e[1]]
        xx = [node0_pos[0], node1_pos[0]]
        yy = [node0_pos[1], node1_pos[1]]
        zz = [node0_pos[2], node1_pos[2]]
        ax.plot3D(xx, yy, zz, color="b", alpha=edge_alphas[idx])
    
    plt.show()

edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0), (0, 5), (1, 6), (2, 7), (3, 8), (4, 9)]
draw_graph(edges)

方案二：使用Plotly库（交互式3D网络图） #

Plotly对3D网络图支持更友好，原生支持节点/边的独立透明度设置，且生成交互式可拖拽的图：

先安装Plotly：

pip install plotly

示例代码：

import plotly.graph_objects as go
import networkx as nx
import numpy as np

def draw_3d_graph(edges):
    G = nx.Graph()
    G.add_edges_from(edges)
    pos = nx.spring_layout(G, dim=3)
    
    # 提取节点坐标
    x_nodes = [pos[n][0] for n in G.nodes()]
    y_nodes = [pos[n][1] for n in G.nodes()]
    z_nodes = [pos[n][2] for n in G.nodes()]
    
    # 生成透明度数组
    node_alphas = np.linspace(0.1, 1, len(G.nodes()))
    edge_alphas = np.linspace(0.1, 1, len(G.edges()))
    
    # 整理边的坐标数据（用None分隔不同边）
    x_edges = []
    y_edges = []
    z_edges = []
    for e in G.edges():
        x_edges.extend([pos[e[0]][0], pos[e[1]][0], None])
        y_edges.extend([pos[e[0]][1], pos[e[1]][1], None])
        z_edges.extend([pos[e[0]][2], pos[e[1]][2], None])
    
    # 创建节点轨迹
    node_trace = go.Scatter3d(
        x=x_nodes, y=y_nodes, z=z_nodes,
        mode='markers',
        marker=dict(
            size=10,
            color='blue',
            opacity=node_alphas
        )
    )
    
    # 创建每条边的轨迹，单独设置透明度
    edge_traces = []
    for idx in range(len(G.edges())):
        start_idx = idx * 3
        edge_trace = go.Scatter3d(
            x=x_edges[start_idx:start_idx+2], 
            y=y_edges[start_idx:start_idx+2], 
            z=z_edges[start_idx:start_idx+2],
            mode='lines',
            line=dict(color='blue', width=2),
            opacity=edge_alphas[idx]
        )
        edge_traces.append(edge_trace)
    
    # 组合所有轨迹并展示
    fig = go.Figure(data=[node_trace] + edge_traces)
    fig.show()

edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0), (0, 5), (1, 6), (2, 7), (3, 8), (4, 9)]
draw_3d_graph(edges)

内容的提问来源于stack exchange，提问作者networkxxxx