import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# 生成示例数据
np.random.seed(42)
data = pd.DataFrame({
    'X': np.random.normal(0, 1, 100),
    'Y': np.random.normal(0, 1, 100) + 0.7 * np.random.normal(0, 1, 100)
})

# 绘制散点图
plt.figure(figsize=(8, 6))
plt.scatter(data['X'], data['Y'], alpha=0.6)
plt.title('相关性散点图示例')
plt.xlabel('变量X')
plt.ylabel('变量Y')
plt.grid(True)
plt.show()

// 使用Chart.js实现相关性热力图
const ctx = document.getElementById('heatmapChart').getContext('2d');
const data = {
  datasets: [{
    label: '相关性热力图',
    data: [
      {x: 'A', y: 'X', v: 0.8},
      {x: 'A', y: 'Y', v: 0.2},
      {x: 'B', y: 'X', v: 0.3},
      {x: 'B', y: 'Y', v: 0.7}
    ],
    backgroundColor: function(context) {
      const value = context.dataset.data[context.dataIndex].v;
      const alpha = Math.abs(value);
      return `rgba(53, 162, 235, ${alpha})`;
    },
    borderWidth: 1
  }]
};

new Chart(ctx, {
  type: 'matrix',
  data: data,
  options: {
    plugins: {
      legend: { display: false },
      tooltip: {
        callbacks: {
          label: function(context) {
            return `相关性: ${context.raw.v.toFixed(2)}`;
          }
        }
      }
    },
    scales: {
      x: { type: 'category' },
      y: { type: 'category' }
    }
  }
});