feat: Add SunnyBands indicator implementation with ATR and signal generation

src/indicators/__init__.py

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+# Initialize indicators package

src/indicators/sunny_bands.py

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+import numpy as np
+import pandas as pd
+
+class SunnyBands:
+    def __init__(self, length: int = 50, atr_multiplier: float = 1.5, smooth_factor: int = 2):
+        """
+        Initialize SunnyBands indicator
+        
+        Args:
+            length (int): DMA Length (default: 50)
+            atr_multiplier (float): ATR Multiplier (default: 1.5)
+            smooth_factor (int): Smoothing Factor (default: 2)
+        """
+        self.length = length
+        self.atr_multiplier = atr_multiplier
+        self.smooth_factor = smooth_factor
+
+    def calculate_atr(self, high: pd.Series, low: pd.Series, close: pd.Series) -> pd.Series:
+        """Calculate Average True Range"""
+        tr1 = high - low
+        tr2 = abs(high - close.shift(1))
+        tr3 = abs(low - close.shift(1))
+        tr = pd.concat([tr1, tr2, tr3], axis=1).max(axis=1)
+        return tr.rolling(window=self.length).mean()
+
+    def calculate(self, df: pd.DataFrame) -> pd.DataFrame:
+        """
+        Calculate SunnyBands indicator
+        
+        Args:
+            df (pd.DataFrame): DataFrame with 'high', 'low', 'close' columns
+            
+        Returns:
+            pd.DataFrame: DataFrame with added columns for DMA and bands
+        """
+        # Calculate DMA (Double EMA)
+        ema1 = df['close'].ewm(span=self.length, adjust=False).mean()
+        dma = ema1.ewm(span=self.smooth_factor, adjust=False).mean()
+        
+        # Calculate ATR
+        atr = self.calculate_atr(df['high'], df['low'], df['close'])
+        
+        # Calculate Bands
+        upper_band = dma + (atr * self.atr_multiplier)
+        lower_band = dma - (atr * self.atr_multiplier)
+        
+        # Generate signals
+        bullish = (df['close'] > lower_band) & (df['close'].shift(1) <= lower_band)
+        bearish = (df['close'] < upper_band) & (df['close'].shift(1) >= upper_band)
+        
+        # Add results to DataFrame
+        results = pd.DataFrame({
+            'dma': dma,
+            'upper_band': upper_band,
+            'lower_band': lower_band,
+            'bullish_signal': bullish,
+            'bearish_signal': bearish
+        })
+        
+        return results
+
+    def get_signals(self, df: pd.DataFrame) -> dict:
+        """
+        Get the current trading signals based on SunnyBands
+        
+        Args:
+            df (pd.DataFrame): DataFrame with price data
+            
+        Returns:
+            dict: Dictionary containing current signals and band values
+        """
+        results = self.calculate(df)
+        
+        # Get latest values
+        current = results.iloc[-1]
+        
+        return {
+            'dma': current['dma'],
+            'upper_band': current['upper_band'],
+            'lower_band': current['lower_band'],
+            'is_bullish': current['bullish_signal'],
+            'is_bearish': current['bearish_signal']
+        }