自定义节点图标

使用自定义图标以matplotlib表示节点的示例。

节点图标的图片来自www.materialui.co

import matplotlib.pyplot as plt
import networkx as nx
import PIL

# 图节点的图像URL
icons = {
    "router": "icons/router_black_144x144.png",
    "switch": "icons/switch_black_144x144.png",
    "PC": "icons/computer_black_144x144.png",
}

# 加载图像
images = {k: PIL.Image.open(fname) for k, fname in icons.items()}

# 生成计算机网络图
G = nx.Graph()

G.add_node("router", image=images["router"])
for i in range(1, 4):
    G.add_node(f"switch_{i}", image=images["switch"])
    for j in range(1, 4):
        G.add_node("PC_" + str(i) + "_" + str(j), image=images["PC"])

G.add_edge("router", "switch_1")
G.add_edge("router", "switch_2")
G.add_edge("router", "switch_3")
for u in range(1, 4):
    for v in range(1, 4):
        G.add_edge("switch_" + str(u), "PC_" + str(u) + "_" + str(v))

# 获取可重复的布局并创建图形
pos = nx.spring_layout(G, seed=1734289230)
fig, ax = plt.subplots()

# 注意：min_source/target_margin 关键字参数仅适用于 FancyArrowPatch 对象。
# 通过设置 `arrows=True` 强制使用 FancyArrowPatch 进行边绘制
# 但通过 `arrowstyle="-"` 来隐藏箭头
nx.draw_networkx_edges(
    G,
    pos=pos,
    ax=ax,
    arrows=True,
    arrowstyle="-",
    min_source_margin=15,
    min_target_margin=15,
)

# 将数据坐标（在xlim和ylim之间缩放）转换为显示坐标
tr_figure = ax.transData.transform
# 从显示坐标转换为图形坐标
tr_axes = fig.transFigure.inverted().transform

# 选择图像的大小（相对于X轴）
icon_size = (ax.get_xlim()[1] - ax.get_xlim()[0]) * 0.025
icon_center = icon_size / 2.0

# 为每个节点添加相应的图像
for n in G.nodes:
    xf, yf = tr_figure(pos[n])
    xa, ya = tr_axes((xf, yf))
    # 获取重叠的轴并绘制图标
    a = plt.axes([xa - icon_center, ya - icon_center, icon_size, icon_size])
    a.imshow(G.nodes[n]["image"])
    a.axis("off")
plt.show()