162 lines
7.2 KiB
Python
162 lines
7.2 KiB
Python
import logging
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import seaborn as sns
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import matplotlib.pyplot as plt
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import pandas as pd
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import datetime
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from cycles.utils.storage import Storage
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from cycles.Analysis.strategies import Strategy
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(message)s",
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handlers=[
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logging.FileHandler("backtest.log"),
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logging.StreamHandler()
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]
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)
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config = {
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"start_date": "2025-03-01",
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"stop_date": datetime.datetime.today().strftime('%Y-%m-%d'),
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"data_file": "btcusd_1-min_data.csv"
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}
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config_strategy = {
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"bb_width": 0.05,
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"bb_period": 20,
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"rsi_period": 14,
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"trending": {
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"rsi_threshold": [30, 70],
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"bb_std_dev_multiplier": 2.5,
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},
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"sideways": {
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"rsi_threshold": [40, 60],
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"bb_std_dev_multiplier": 1.8,
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},
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"strategy_name": "MarketRegimeStrategy", # CryptoTradingStrategy
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"SqueezeStrategy": True
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}
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IS_DAY = False
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if __name__ == "__main__":
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# Load data
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storage = Storage(logging=logging)
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data = storage.load_data(config["data_file"], config["start_date"], config["stop_date"])
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# Run strategy
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strategy = Strategy(config=config_strategy, logging=logging)
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processed_data = strategy.run(data.copy(), config_strategy["strategy_name"])
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# Get buy and sell signals
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buy_condition = processed_data.get('BuySignal', pd.Series(False, index=processed_data.index)).astype(bool)
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sell_condition = processed_data.get('SellSignal', pd.Series(False, index=processed_data.index)).astype(bool)
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buy_signals = processed_data[buy_condition]
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sell_signals = processed_data[sell_condition]
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# Plot the data with seaborn library
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if processed_data is not None and not processed_data.empty:
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# Create a figure with two subplots, sharing the x-axis
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fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(16, 8), sharex=True)
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strategy_name = config_strategy["strategy_name"]
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# Plot 1: Close Price and Strategy-Specific Bands/Levels
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sns.lineplot(x=processed_data.index, y='close', data=processed_data, label='Close Price', ax=ax1)
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# Use standardized column names for bands
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if 'UpperBand' in processed_data.columns and 'LowerBand' in processed_data.columns:
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# Instead of lines, shade the area between upper and lower bands
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ax1.fill_between(processed_data.index,
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processed_data['LowerBand'],
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processed_data['UpperBand'],
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alpha=0.1, color='blue', label='Bollinger Bands')
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else:
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logging.warning(f"{strategy_name}: UpperBand or LowerBand not found for plotting.")
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# Add strategy-specific extra indicators if available
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if strategy_name == "CryptoTradingStrategy":
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if 'StopLoss' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='StopLoss', data=processed_data, label='Stop Loss', ax=ax1, linestyle='--', color='orange')
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if 'TakeProfit' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='TakeProfit', data=processed_data, label='Take Profit', ax=ax1, linestyle='--', color='purple')
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# Plot Buy/Sell signals on Price chart
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if not buy_signals.empty:
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ax1.scatter(buy_signals.index, buy_signals['close'], color='green', marker='o', s=20, label='Buy Signal', zorder=5)
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if not sell_signals.empty:
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ax1.scatter(sell_signals.index, sell_signals['close'], color='red', marker='o', s=20, label='Sell Signal', zorder=5)
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ax1.set_title(f'Price and Signals ({strategy_name})')
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ax1.set_ylabel('Price')
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ax1.legend()
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ax1.grid(True)
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# Plot 2: RSI and Strategy-Specific Thresholds
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if 'RSI' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='RSI', data=processed_data, label=f'RSI (' + str(config_strategy.get("rsi_period", 14)) + ')', ax=ax2, color='purple')
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if strategy_name == "MarketRegimeStrategy":
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# Get threshold values
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upper_threshold = config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1]
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lower_threshold = config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0]
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# Shade overbought area (upper)
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ax2.fill_between(processed_data.index, upper_threshold, 100,
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alpha=0.1, color='red', label=f'Overbought (>{upper_threshold})')
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# Shade oversold area (lower)
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ax2.fill_between(processed_data.index, 0, lower_threshold,
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alpha=0.1, color='green', label=f'Oversold (<{lower_threshold})')
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elif strategy_name == "CryptoTradingStrategy":
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# Shade overbought area (upper)
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ax2.fill_between(processed_data.index, 65, 100,
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alpha=0.1, color='red', label='Overbought (>65)')
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# Shade oversold area (lower)
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ax2.fill_between(processed_data.index, 0, 35,
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alpha=0.1, color='green', label='Oversold (<35)')
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# Plot Buy/Sell signals on RSI chart
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if not buy_signals.empty and 'RSI' in buy_signals.columns:
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ax2.scatter(buy_signals.index, buy_signals['RSI'], color='green', marker='o', s=20, label='Buy Signal (RSI)', zorder=5)
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if not sell_signals.empty and 'RSI' in sell_signals.columns:
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ax2.scatter(sell_signals.index, sell_signals['RSI'], color='red', marker='o', s=20, label='Sell Signal (RSI)', zorder=5)
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ax2.set_title('Relative Strength Index (RSI) with Signals')
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ax2.set_ylabel('RSI Value')
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ax2.set_ylim(0, 100)
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ax2.legend()
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ax2.grid(True)
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else:
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logging.info("RSI data not available for plotting.")
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# Plot 3: Strategy-Specific Indicators
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ax3.clear() # Clear previous plot content if any
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if 'BBWidth' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='BBWidth', data=processed_data, label='BB Width', ax=ax3)
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if strategy_name == "MarketRegimeStrategy":
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if 'MarketRegime' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='MarketRegime', data=processed_data, label='Market Regime (Sideways: 1, Trending: 0)', ax=ax3)
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ax3.set_title('Bollinger Bands Width & Market Regime')
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ax3.set_ylabel('Value')
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elif strategy_name == "CryptoTradingStrategy":
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if 'VolumeMA' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='VolumeMA', data=processed_data, label='Volume MA', ax=ax3)
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if 'volume' in processed_data.columns:
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sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume', ax=ax3, alpha=0.5)
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ax3.set_title('Volume Analysis')
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ax3.set_ylabel('Volume')
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ax3.legend()
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ax3.grid(True)
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plt.xlabel('Date')
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fig.tight_layout()
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plt.show()
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else:
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logging.info("No data to plot.")
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