Enhance strategy output standardization and improve plotting logic

- Introduced a new method to standardize output column names across different strategies, ensuring consistency in data handling and plotting.
- Updated plotting logic in test_bbrsi.py to utilize standardized column names, improving clarity and maintainability.
- Enhanced error handling for missing data in plots and adjusted visual elements for better representation of trading signals.
- Improved the overall structure of strategy implementations to support additional indicators and metadata for better analysis.

cycles/Analysis/strategies.py

@@ -16,14 +16,66 @@ class Strategy:
 
     def run(self, data, strategy_name):
         if strategy_name == "MarketRegimeStrategy":
-            return self.MarketRegimeStrategy(data)
+            result = self.MarketRegimeStrategy(data)
+            return self.standardize_output(result, strategy_name)
         elif strategy_name == "CryptoTradingStrategy":
-            return self.CryptoTradingStrategy(data)
+            result = self.CryptoTradingStrategy(data)
+            return self.standardize_output(result, strategy_name)
         else:
             if self.logging is not None:
                 self.logging.warning(f"Strategy {strategy_name} not found. Using no_strategy instead.")
             return self.no_strategy(data)
 
+    def standardize_output(self, data, strategy_name):
+        """
+        Standardize column names across different strategies to ensure consistent plotting and analysis
+        
+        Args:
+            data (DataFrame): Strategy output DataFrame
+            strategy_name (str): Name of the strategy that generated this data
+            
+        Returns:
+            DataFrame: Data with standardized column names
+        """
+        if data.empty:
+            return data
+            
+        # Create a copy to avoid modifying the original
+        standardized = data.copy()
+        
+        # Standardize column names based on strategy
+        if strategy_name == "MarketRegimeStrategy":
+            # MarketRegimeStrategy already has standard column names for most fields
+            # Just ensure all standard columns exist
+            pass
+        elif strategy_name == "CryptoTradingStrategy":
+            # Map strategy-specific column names to standard names
+            column_mapping = {
+                'UpperBand_15m': 'UpperBand',
+                'LowerBand_15m': 'LowerBand',
+                'SMA_15m': 'SMA',
+                'RSI_15m': 'RSI',
+                'VolumeMA_15m': 'VolumeMA',
+                # Keep StopLoss and TakeProfit as they are
+            }
+            
+            # Add standard columns from mapped columns
+            for old_col, new_col in column_mapping.items():
+                if old_col in standardized.columns and new_col not in standardized.columns:
+                    standardized[new_col] = standardized[old_col]
+                    
+            # Add additional strategy-specific data as metadata columns
+            if 'UpperBand_1h' in standardized.columns:
+                standardized['UpperBand_1h_meta'] = standardized['UpperBand_1h']
+            if 'LowerBand_1h' in standardized.columns:
+                standardized['LowerBand_1h_meta'] = standardized['LowerBand_1h']
+        
+        # Ensure all strategies have BBWidth if possible
+        if 'BBWidth' not in standardized.columns and 'UpperBand' in standardized.columns and 'LowerBand' in standardized.columns:
+            standardized['BBWidth'] = (standardized['UpperBand'] - standardized['LowerBand']) / standardized['SMA'] if 'SMA' in standardized.columns else np.nan
+            
+        return standardized
+
     def no_strategy(self, data):
         """No strategy: returns False for both buy and sell conditions"""
         buy_condition = pd.Series([False] * len(data), index=data.index)
@@ -74,6 +126,7 @@ class Strategy:
             DataFrame: A unified DataFrame containing original data, BB, RSI, and signals.
         """
 
+        # data = aggregate_to_hourly(data, 4)
         data = aggregate_to_daily(data)
         
         # Calculate Bollinger Bands

test_bbrsi.py

@@ -33,7 +33,7 @@ config_strategy = {
         "rsi_threshold": [40, 60],
         "bb_std_dev_multiplier": 1.8,
     },
-    "strategy_name": "MarketRegimeStrategy",
+    "strategy_name": "MarketRegimeStrategy", # CryptoTradingStrategy
     "SqueezeStrategy": True
 }
 
@@ -65,18 +65,19 @@ if __name__ == "__main__":
 
         # 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":
+        
+        # Use standardized column names for bands
         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)
+            # Instead of lines, shade the area between upper and lower bands
-                sns.lineplot(x=processed_data.index, y='LowerBand', data=processed_data, label='Lower Band (BB)', ax=ax1)
+            ax1.fill_between(processed_data.index, 
+                           processed_data['LowerBand'],
+                           processed_data['UpperBand'], 
+                           alpha=0.1, color='blue', label='Bollinger Bands')
         else:
-                logging.warning("MarketRegimeStrategy: UpperBand or LowerBand not found for plotting.")
+            logging.warning(f"{strategy_name}: 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:
+        # Add strategy-specific extra indicators if available
-                sns.lineplot(x=processed_data.index, y='UpperBand_15m', data=processed_data, label='Upper Band (15m)', ax=ax1)
+        if strategy_name == "CryptoTradingStrategy":
-                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:
@@ -84,54 +85,68 @@ if __name__ == "__main__":
         
         # 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)
+            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=10, label='Sell Signal', zorder=5)
+            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
-        rsi_col_name = 'RSI' if strategy_name == "MarketRegimeStrategy" else 'RSI_15m'
+        if 'RSI' in processed_data.columns: 
-        if rsi_col_name 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')
-            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
+                # Get threshold values
-                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]) + ')')
+                upper_threshold = 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]) + ')')
+                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":
-                ax2.axhline(65, color='red', linestyle='--', linewidth=0.8, label='Overbought (65)') # As per Crypto strategy logic
+                # Shade overbought area (upper)
-                ax2.axhline(35, color='green', linestyle='--', linewidth=0.8, label='Oversold (35)') # As per Crypto strategy logic
+                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_col_name in buy_signals.columns:
+            if not buy_signals.empty and 'RSI' 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)
+                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_col_name in sell_signals.columns:
+            if not sell_signals.empty and 'RSI' 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.scatter(sell_signals.index, sell_signals['RSI'], color='red', marker='o', s=20, label='Sell Signal (RSI)', zorder=5)
-            ax2.set_title(f'Relative Strength Index ({rsi_col_name}) with Signals')
+            ax2.set_title('Relative Strength Index (RSI) with Signals')
-            ax2.set_ylabel(f'{rsi_col_name} Value')
+            ax2.set_ylabel('RSI Value')
             ax2.set_ylim(0, 100) 
             ax2.legend()
             ax2.grid(True)
         else:
-            logging.info(f"{rsi_col_name} data not available for plotting.")
+            logging.info("RSI 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 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_15m' in processed_data.columns:
+            if 'VolumeMA' in processed_data.columns:
-                sns.lineplot(x=processed_data.index, y='VolumeMA_15m', data=processed_data, label='Volume MA (15m)', ax=ax3)
+                sns.lineplot(x=processed_data.index, y='VolumeMA', data=processed_data, label='Volume MA', ax=ax3)
-            if 'volume' in processed_data.columns: # Plot original volume for comparison
+            if 'volume' in processed_data.columns:
-                sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume (15m)', ax=ax3, alpha=0.5)
+                sns.lineplot(x=processed_data.index, y='volume', data=processed_data, label='Volume', ax=ax3, alpha=0.5)
-            ax3.set_title('Volume Analysis (15m)')
+            ax3.set_title('Volume Analysis')
             ax3.set_ylabel('Volume')
         
         ax3.legend()