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@@ -0,0 +1,35 @@
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+import pandas as pd
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+import numpy as np
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+import matplotlib.pyplot as plt
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+import seaborn as sns
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+from datetime import datetime, timedelta
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+
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+# 创建示例订单簿数据
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+times = [datetime.now() - timedelta(seconds=i) for i in range(10)]
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+prices = np.linspace(10000, 10100, 10)
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+bid_qtys = np.random.rand(10, 10) * 100 # 随机生成挂单数量
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+
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+# 创建一个DataFrame来表示订单簿数据
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+order_book_df = pd.DataFrame(
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+ {
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+ 'time': np.repeat(times, 10),
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+ 'price': np.tile(prices, 10),
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+ 'bid_qty': bid_qtys.flatten()
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+ }
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+)
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+
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+# 设置索引为时间和价格
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+order_book_df.set_index(['time', 'price'], inplace=True)
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+
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+# 选择 bid_qty 列来绘制热力图
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+heatmap_data = order_book_df['bid_qty'].unstack().T
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+
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+# 创建热力图
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+plt.figure(figsize=(12, 8))
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+sns.heatmap(heatmap_data, cmap="Blues", cbar=True, cbar_kws={'label': 'Order Quantity'})
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+plt.title('Order Book Heatmap')
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+plt.xlabel('Time')
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+plt.ylabel('Price')
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+plt.xticks(rotation=45)
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+plt.tight_layout()
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+plt.show()
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