Cycles/test_bbrsi.py

import logging
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import datetime

from cycles.utils.storage import Storage
from cycles.Analysis.bb_rsi import BollingerBandsStrategy

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(message)s",
    handlers=[
        logging.FileHandler("backtest.log"),
        logging.StreamHandler()
    ]
)

config = {
     "start_date": "2025-03-01",
    "stop_date": datetime.datetime.today().strftime('%Y-%m-%d'),
    "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", # CryptoTradingStrategy
    "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 = BollingerBandsStrategy(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)
        
        # Use standardized column names for bands
        if 'UpperBand' in processed_data.columns and 'LowerBand' in processed_data.columns:
            # Instead of lines, shade the area between upper and lower bands
            ax1.fill_between(processed_data.index, 
                           processed_data['LowerBand'],
                           processed_data['UpperBand'], 
                           alpha=0.1, color='blue', label='Bollinger Bands')
        else:
            logging.warning(f"{strategy_name}: UpperBand or LowerBand not found for plotting.")
            
        # Add strategy-specific extra indicators if available
        if strategy_name == "CryptoTradingStrategy":
            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=20, label='Buy Signal', zorder=5)
        if not sell_signals.empty:
            ax1.scatter(sell_signals.index, sell_signals['close'], color='red', marker='o', s=20, 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
        if 'RSI' in processed_data.columns: 
            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')
            if strategy_name == "MarketRegimeStrategy":
                # Get threshold values
                upper_threshold = config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[1]
                lower_threshold = config_strategy.get("trending", {}).get("rsi_threshold", [30,70])[0]
                
                # Shade overbought area (upper)
                ax2.fill_between(processed_data.index, upper_threshold, 100, 
                                alpha=0.1, color='red', label=f'Overbought (>{upper_threshold})')
                
                # Shade oversold area (lower)
                ax2.fill_between(processed_data.index, 0, lower_threshold, 
                                alpha=0.1, color='green', label=f'Oversold (<{lower_threshold})')
                
            elif strategy_name == "CryptoTradingStrategy":
                # Shade overbought area (upper)
                ax2.fill_between(processed_data.index, 65, 100, 
                                alpha=0.1, color='red', label='Overbought (>65)')
                
                # Shade oversold area (lower)
                ax2.fill_between(processed_data.index, 0, 35, 
                                alpha=0.1, color='green', label='Oversold (<35)')

            # Plot Buy/Sell signals on RSI chart
            if not buy_signals.empty and 'RSI' in buy_signals.columns:
                ax2.scatter(buy_signals.index, buy_signals['RSI'], color='green', marker='o', s=20, label='Buy Signal (RSI)', zorder=5)
            if not sell_signals.empty and 'RSI' in sell_signals.columns:
                ax2.scatter(sell_signals.index, sell_signals['RSI'], color='red', marker='o', s=20, label='Sell Signal (RSI)', zorder=5)
            ax2.set_title('Relative Strength Index (RSI) with Signals')
            ax2.set_ylabel('RSI Value')
            ax2.set_ylim(0, 100) 
            ax2.legend()
            ax2.grid(True)
        else:
            logging.info("RSI data not available for plotting.")

        # Plot 3: Strategy-Specific Indicators
        ax3.clear() # Clear previous plot content if any
        if 'BBWidth' in processed_data.columns:
            sns.lineplot(x=processed_data.index, y='BBWidth', data=processed_data, label='BB Width', ax=ax3)
            
        if strategy_name == "MarketRegimeStrategy":
            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' in processed_data.columns:
                sns.lineplot(x=processed_data.index, y='VolumeMA', data=processed_data, label='Volume MA', ax=ax3)
            if 'volume' in processed_data.columns:
                sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume', ax=ax3, alpha=0.5)
            ax3.set_title('Volume Analysis')
            ax3.set_ylabel('Volume')
        
        ax3.legend()
        ax3.grid(True)

        plt.xlabel('Date') 
        fig.tight_layout() 
        plt.show()
    else:
        logging.info("No data to plot.")