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.inscode

-run = "pip install -r requirements.txt;python main.py"
+run = "python main.py"
 language = "python"
 
 [packager]

main.py

-print('欢迎来到 InsCode')
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+import matplotlib.pyplot as plt
+import numpy as np
+
+# 设置图片清晰度
+plt.rcParams['figure.dpi'] = 300
+
+# 绘制简单神经网络
+# 定义每层神经元的位置
+input_layer = np.array([(0, i) for i in range(3)])
+hidden_layer = np.array([(1, i) for i in range(4)])
+output_layer = np.array([(2, i) for i in range(1)])
+
+# 绘制神经元
+plt.scatter(input_layer[:, 0], input_layer[:, 1], s=200, label='输入层')
+plt.scatter(hidden_layer[:, 0], hidden_layer[:, 1], s=200, label='隐藏层')
+plt.scatter(output_layer[:, 0], output_layer[:, 1], s=200, label='输出层')
+
+# 绘制连接
+for i in input_layer:
+    for h in hidden_layer:
+        plt.plot([i[0], h[0]], [i[1], h[1]], 'k-')
+for h in hidden_layer:
+    for o in output_layer:
+        plt.plot([h[0], o[0]], [h[1], o[1]], 'k-')
+
+# 添加权重标注（简单示意）
+for i in input_layer:
+    for h in hidden_layer:
+        mid_x = (i[0] + h[0]) / 2
+        mid_y = (i[1] + h[1]) / 2
+        plt.text(mid_x, mid_y, 'w', ha='center', va='center')
+
+# 添加标签和标题
+plt.legend()
+plt.title('简单神经网络示例')
+plt.axis('off')
+plt.show()
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