import logging import seaborn as sns import matplotlib.pyplot as plt import pandas as pd from cycles.utils.storage import Storage from cycles.Analysis.strategies import Strategy logging.basicConfig( level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s", handlers=[ logging.FileHandler("backtest.log"), logging.StreamHandler() ] ) config = { "start_date": "2023-01-01", "stop_date": "2024-01-01", "data_file": "btcusd_1-min_data.csv" } config_strategy = { "bb_width": 0.05, "bb_period": 20, "rsi_period": 14, "trending": { "rsi_threshold": [30, 70], "bb_std_dev_multiplier": 2.5, }, "sideways": { "rsi_threshold": [40, 60], "bb_std_dev_multiplier": 1.8, }, "strategy_name": "MarketRegimeStrategy", "SqueezeStrategy": True } IS_DAY = False if __name__ == "__main__": # Load data storage = Storage(logging=logging) data = storage.load_data(config["data_file"], config["start_date"], config["stop_date"]) # Run strategy strategy = Strategy(config=config_strategy, logging=logging) processed_data = strategy.run(data.copy(), config_strategy["strategy_name"]) # Get buy and sell signals buy_condition = processed_data.get('BuySignal', pd.Series(False, index=processed_data.index)).astype(bool) sell_condition = processed_data.get('SellSignal', pd.Series(False, index=processed_data.index)).astype(bool) buy_signals = processed_data[buy_condition] sell_signals = processed_data[sell_condition] # Plot the data with seaborn library if processed_data is not None and not processed_data.empty: # Create a figure with two subplots, sharing the x-axis fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(16, 8), sharex=True) strategy_name = config_strategy["strategy_name"] # Plot 1: Close Price and Strategy-Specific Bands/Levels sns.lineplot(x=processed_data.index, y='close', data=processed_data, label='Close Price', ax=ax1) if strategy_name == "MarketRegimeStrategy": if 'UpperBand' in processed_data.columns and 'LowerBand' in processed_data.columns: sns.lineplot(x=processed_data.index, y='UpperBand', data=processed_data, label='Upper Band (BB)', ax=ax1) sns.lineplot(x=processed_data.index, y='LowerBand', data=processed_data, label='Lower Band (BB)', ax=ax1) else: logging.warning("MarketRegimeStrategy: UpperBand or LowerBand not found for plotting.") elif strategy_name == "CryptoTradingStrategy": if 'UpperBand_15m' in processed_data.columns and 'LowerBand_15m' in processed_data.columns: sns.lineplot(x=processed_data.index, y='UpperBand_15m', data=processed_data, label='Upper Band (15m)', ax=ax1) sns.lineplot(x=processed_data.index, y='LowerBand_15m', data=processed_data, label='Lower Band (15m)', ax=ax1) else: logging.warning("CryptoTradingStrategy: UpperBand_15m or LowerBand_15m not found for plotting.") if 'StopLoss' in processed_data.columns: sns.lineplot(x=processed_data.index, y='StopLoss', data=processed_data, label='Stop Loss', ax=ax1, linestyle='--', color='orange') if 'TakeProfit' in processed_data.columns: sns.lineplot(x=processed_data.index, y='TakeProfit', data=processed_data, label='Take Profit', ax=ax1, linestyle='--', color='purple') # Plot Buy/Sell signals on Price chart if not buy_signals.empty: ax1.scatter(buy_signals.index, buy_signals['close'], color='green', marker='o', s=10, label='Buy Signal', zorder=5) if not sell_signals.empty: ax1.scatter(sell_signals.index, sell_signals['close'], color='red', marker='o', s=10, label='Sell Signal', zorder=5) ax1.set_title(f'Price and Signals ({strategy_name})') ax1.set_ylabel('Price') ax1.legend() ax1.grid(True) # Plot 2: RSI and Strategy-Specific Thresholds rsi_col_name = 'RSI' if strategy_name == "MarketRegimeStrategy" else 'RSI_15m' if rsi_col_name in processed_data.columns: sns.lineplot(x=processed_data.index, y=rsi_col_name, data=processed_data, label=f'{rsi_col_name} (' + str(config_strategy.get("rsi_period", 14)) + ')', ax=ax2, color='purple') if strategy_name == "MarketRegimeStrategy": # Assuming trending thresholds are what we want to show generally ax2.axhline(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1], color='red', linestyle='--', linewidth=0.8, label=f'Overbought (' + str(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1]) + ')') ax2.axhline(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0], color='green', linestyle='--', linewidth=0.8, label=f'Oversold (' + str(config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0]) + ')') elif strategy_name == "CryptoTradingStrategy": ax2.axhline(65, color='red', linestyle='--', linewidth=0.8, label='Overbought (65)') # As per Crypto strategy logic ax2.axhline(35, color='green', linestyle='--', linewidth=0.8, label='Oversold (35)') # As per Crypto strategy logic # Plot Buy/Sell signals on RSI chart if not buy_signals.empty and rsi_col_name in buy_signals.columns: ax2.scatter(buy_signals.index, buy_signals[rsi_col_name], color='green', marker='o', s=20, label=f'Buy Signal ({rsi_col_name})', zorder=5) if not sell_signals.empty and rsi_col_name in sell_signals.columns: ax2.scatter(sell_signals.index, sell_signals[rsi_col_name], color='red', marker='o', s=20, label=f'Sell Signal ({rsi_col_name})', zorder=5) ax2.set_title(f'Relative Strength Index ({rsi_col_name}) with Signals') ax2.set_ylabel(f'{rsi_col_name} Value') ax2.set_ylim(0, 100) ax2.legend() ax2.grid(True) else: logging.info(f"{rsi_col_name} data not available for plotting.") # Plot 3: Strategy-Specific Indicators ax3.clear() # Clear previous plot content if any if strategy_name == "MarketRegimeStrategy": if 'BBWidth' in processed_data.columns: sns.lineplot(x=processed_data.index, y='BBWidth', data=processed_data, label='BB Width', ax=ax3) if 'MarketRegime' in processed_data.columns: sns.lineplot(x=processed_data.index, y='MarketRegime', data=processed_data, label='Market Regime (Sideways: 1, Trending: 0)', ax=ax3) ax3.set_title('Bollinger Bands Width & Market Regime') ax3.set_ylabel('Value') elif strategy_name == "CryptoTradingStrategy": if 'VolumeMA_15m' in processed_data.columns: sns.lineplot(x=processed_data.index, y='VolumeMA_15m', data=processed_data, label='Volume MA (15m)', ax=ax3) if 'volume' in processed_data.columns: # Plot original volume for comparison sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume (15m)', ax=ax3, alpha=0.5) ax3.set_title('Volume Analysis (15m)') ax3.set_ylabel('Volume') ax3.legend() ax3.grid(True) plt.xlabel('Date') fig.tight_layout() plt.show() else: logging.info("No data to plot.")