import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime, timedelta

# 创建示例订单簿数据
times = [datetime.now() - timedelta(seconds=i) for i in range(10)]
prices = np.linspace(10000, 10100, 10)
bid_qtys = np.random.rand(10, 10) * 100  # 随机生成挂单数量

# 创建一个DataFrame来表示订单簿数据
order_book_df = pd.DataFrame(
    {
        'time': np.repeat(times, 10),
        'price': np.tile(prices, 10),
        'bid_qty': bid_qtys.flatten()
    }
)

# 设置索引为时间和价格
order_book_df.set_index(['time', 'price'], inplace=True)

# 选择 bid_qty 列来绘制热力图
heatmap_data = order_book_df['bid_qty'].unstack().T

# 创建热力图
plt.figure(figsize=(12, 8))
sns.heatmap(heatmap_data, cmap="Blues", cbar=True, cbar_kws={'label': 'Order Quantity'})
plt.title('Order Book Heatmap')
plt.xlabel('Time')
plt.ylabel('Price')
plt.xticks(rotation=45)
plt.tight_layout()
plt.show()