神经网络的可视化，如何根据权值改变线宽？

import matplotlib.pyplot as plt
import numpy as np

# 假设我们有一个简单的神经网络连接权重矩阵
weights = np.array([[0.1, 0.5, 0.3],
                    [0.2, 0.8, 0.4],
                    [0.3, 0.6, 0.7]])

# 创建一个图形
fig, ax = plt.subplots()

# 绘制节点
nodes = ['A', 'B', 'C']
pos = {node: (i, 0) for i, node in enumerate(nodes)}

# 绘制边
for i in range(len(nodes)):
    for j in range(len(nodes)):
        if i != j:
            weight = weights[i, j]
            ax.plot([pos[nodes[i]][0], pos[nodes[j]][0]], [pos[nodes[i]][1], pos[nodes[j]][1]],
                    linewidth=weight * 10, label=f'{nodes[i]}-{nodes[j]} ({weight:.2f})')

# 设置节点位置
for node, (x, y) in pos.items():
    ax.scatter(x, y)
    ax.text(x, y, node)

# 添加图例
ax.legend()

# 显示图形
plt.show()