7f4f88e853
新增期货数据动态播放器功能，包括基础版和增强版实现，添加测试脚本和详细文档说明。主要变更包括： 1. 实现买卖盘深度可视化播放功能 2. 添加播放控制、速度调节和跳转功能 3. 提供统一价格轴显示优化版本 4. 添加测试脚本验证功能 5. 编写详细使用文档和README说明
202 lines
7.4 KiB
Python
202 lines
7.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Quick demo for Unified Futures Data Player
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快速演示统一价格轴版本的期货数据播放器
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"""
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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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def demo_unified_chart():
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"""演示统一价格轴图表效果"""
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print("=== Unified Market Depth Demo ===")
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print("Creating sample visualization...")
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# Load some sample data
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df = pd.read_parquet('data/au2512_20251013.parquet')
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# Column mapping
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columns_mapping = {
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'时间': 'time', '累积成交量': 'cumulative_volume', '成交价': 'price',
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'买1价': 'bid1_price', '卖1价': 'ask1_price',
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'买1量': 'bid1_volume', '卖1量': 'ask1_volume',
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'买2价': 'bid2_price', '卖2价': 'ask2_price',
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'买2量': 'bid2_volume', '卖2量': 'ask2_volume',
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'买3价': 'bid3_price', '卖3价': 'ask3_price',
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'买3量': 'bid3_volume', '卖3量': 'ask3_volume',
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'买4价': 'bid4_price', '卖4价': 'ask4_price',
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'买4量': 'bid4_volume', '卖4量': 'ask4_volume',
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'买5价': 'bid5_price', '卖5价': 'ask5_price',
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'买5量': 'bid5_volume', '卖5量': 'ask5_volume'
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}
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df = df.rename(columns=columns_mapping)
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# Get a sample row
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sample_row = df.iloc[1000] # Sample from middle of data
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current_price = sample_row['price']
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min_tick = 0.02
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# Create figure
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fig, ax = plt.subplots(figsize=(12, 8))
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fig.suptitle('Unified Market Depth Demo - AU2512', fontsize=16, fontweight='bold')
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# Collect market depth data
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bid_prices = []
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bid_volumes = []
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ask_prices = []
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ask_volumes = []
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for i in range(1, 6):
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bid_price = sample_row[f'bid{i}_price']
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bid_volume = sample_row[f'bid{i}_volume']
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ask_price = sample_row[f'ask{i}_price']
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ask_volume = sample_row[f'ask{i}_volume']
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if pd.notna(bid_price) and pd.notna(bid_volume) and bid_volume > 0:
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bid_prices.append(bid_price)
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bid_volumes.append(bid_volume)
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if pd.notna(ask_price) and pd.notna(ask_volume) and ask_volume > 0:
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ask_prices.append(ask_price)
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ask_volumes.append(ask_volume)
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print(f"Sample data at sequence 1000:")
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print(f"Current price: {current_price:.2f}")
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print(f"Bid prices: {[f'{p:.2f}' for p in bid_prices]}")
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print(f"Ask prices: {[f'{p:.2f}' for p in ask_prices]}")
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# Define volume scale points (equal spacing)
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volume_scale_points = [10, 30, 60, 150, 300]
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# Create unified visualization with horizontal bars
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all_prices = []
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all_volumes = []
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all_colors = []
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# Add bid data (green horizontal bars)
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for bp, bv in zip(bid_prices, bid_volumes):
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all_prices.append(bp)
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all_volumes.append(bv)
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all_colors.append('green')
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# Add ask data (red horizontal bars)
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for ap, av in zip(ask_prices, ask_volumes):
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all_prices.append(ap)
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all_volumes.append(av)
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all_colors.append('red')
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# Map volumes to scale positions
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def map_volume_to_scale(volume):
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"""Map actual volume to scale position"""
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if volume <= 10:
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return 10
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elif volume <= 30:
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return 30
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elif volume <= 60:
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return 60
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elif volume <= 150:
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return 150
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elif volume <= 300:
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return 300
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else:
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return 300 # Cap at 300 for display
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# Map volumes to display scale
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mapped_volumes = [map_volume_to_scale(v) for v in all_volumes]
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# Create horizontal bars (volume on x-axis, price on y-axis)
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bars = ax.barh(all_prices, mapped_volumes, height=min_tick * 0.8,
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color=all_colors, alpha=0.7,
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edgecolor='darkgreen' if 'green' in all_colors else 'darkred',
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linewidth=1)
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# Add volume labels on bars
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for price, volume, mapped_vol in zip(all_prices, all_volumes, mapped_volumes):
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if volume > 0:
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ax.text(mapped_vol + 5, price, f'{int(volume):,}',
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ha='left', va='center', fontsize=10, fontweight='bold')
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# Set up price axis with true tick spacing
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price_range = 1.0
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min_price = current_price - price_range/2
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max_price = current_price + price_range/2
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tick_prices = np.arange(np.floor(min_price / min_tick) * min_tick,
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np.ceil(max_price / min_tick) * min_tick + min_tick,
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min_tick)
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ax.set_xticks(tick_prices[::3]) # Show every 3rd tick
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ax.set_xticklabels([f'{p:.2f}' for p in tick_prices[::3]], rotation=45)
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ax.set_xlim(min_price, max_price)
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# Add current price line
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ax.axvline(x=current_price, color='blue', linestyle='--', alpha=0.8, linewidth=2,
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label=f'Last Price: {current_price:.2f}')
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# Highlight spread
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if bid_prices and ask_prices:
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best_bid = max(bid_prices)
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best_ask = min(ask_prices)
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spread = best_ask - best_bid
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ax.axvspan(best_bid, best_ask, alpha=0.3, color='yellow',
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label=f'Spread: {spread:.2f}')
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print(f"Best bid: {best_bid:.2f}, Best ask: {best_ask:.2f}")
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print(f"Bid-ask spread: {spread:.2f}")
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# Set y-axis with true tick spacing (price)
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ax.set_yticks(tick_prices[::3]) # Show every 3rd tick to avoid crowding
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ax.set_yticklabels([f'{p:.2f}' for p in tick_prices[::3]])
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ax.set_ylim(min_price, max_price)
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# Set x-axis with defined volume scale points
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ax.set_xticks(volume_scale_points)
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ax.set_xticklabels([f'{v}' for v in volume_scale_points])
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ax.set_xlim(0, max(volume_scale_points) * 1.2)
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# Labels and formatting
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ax.set_xlabel('Volume', fontsize=12)
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ax.set_ylabel('Price (¥)', fontsize=12)
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ax.set_title('Unified Market Depth View', fontsize=14)
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ax.grid(True, alpha=0.3, axis='x')
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# Legend
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import matplotlib.patches as mpatches
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bid_patch = mpatches.Patch(color='green', alpha=0.7, label='Bid Volume')
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ask_patch = mpatches.Patch(color='red', alpha=0.7, label='Ask Volume')
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ax.legend(handles=[bid_patch, ask_patch], loc='upper right')
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# Add annotations
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ax.text(0.02, 0.98, f"Time: {sample_row['time']}",
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transform=ax.transAxes, fontsize=10,
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verticalalignment='top',
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bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.8))
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ax.text(0.02, 0.92, f"Tick Size: {min_tick}",
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transform=ax.transAxes, fontsize=10,
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verticalalignment='top',
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bbox=dict(boxstyle='round', facecolor='lightblue', alpha=0.8))
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plt.tight_layout()
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# Save the demo chart
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output_file = 'unified_market_depth_demo.png'
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plt.savefig(output_file, dpi=150, bbox_inches='tight')
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print(f"\nDemo chart saved as: {output_file}")
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plt.show()
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print("\nThis demo shows the unified market depth visualization where:")
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print("- Green horizontal bars: Bid volumes at different price levels")
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print("- Red horizontal bars: Ask volumes at different price levels")
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print("- Blue dashed line: Current last price (horizontal)")
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print("- Yellow shaded area: Bid-ask spread (horizontal)")
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print("- Price axis (vertical) shows true minimum tick spacing (0.02)")
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print("- Volume axis (horizontal) uses simplified scale: 10, 30, 60, 150, 300 (equal spacing)")
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print("- Volume bars extend rightward with sizes matching the scale points")
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print("- Volumes larger than 300 are capped at 300 for display consistency")
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if __name__ == "__main__":
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demo_unified_chart() |