TCPDashboard/data/common/indicators/implementations/rsi.py

"""
Relative Strength Index (RSI) indicator implementation.
"""

from typing import List
import pandas as pd
import numpy as np

from ..base import BaseIndicator
from ..result import IndicatorResult


class RSIIndicator(BaseIndicator):
    """
    Relative Strength Index (RSI) technical indicator.
    
    Measures momentum by comparing the magnitude of recent gains to recent losses.
    Handles sparse data appropriately without interpolation.
    """
    
    def calculate(self, df: pd.DataFrame, period: int = 14,
                 price_column: str = 'close') -> pd.DataFrame:
        """
        Calculate Relative Strength Index (RSI).
        
        Args:
            df: DataFrame with OHLCV data
            period: Number of periods for RSI calculation (default: 14)
            price_column: Price column to use ('open', 'high', 'low', 'close')
            
        Returns:
            DataFrame with RSI values and metadata, indexed by timestamp
        """
        # Validate input data
        if not self.validate_dataframe(df, period):
            return pd.DataFrame()
        try:
            df = df.copy()
            delta = df[price_column].diff()
            gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
            loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
            rs = gain / loss
            rs = rs.replace([np.inf, -np.inf], np.nan)
            df['rsi'] = 100 - (100 / (1 + rs))
            # Only keep rows with valid RSI, and only 'timestamp' and 'rsi' columns
            result_df = df.loc[df['rsi'].notna(), ['timestamp', 'rsi']].copy()
            result_df = result_df.iloc[period-1:]
            result_df.set_index('timestamp', inplace=True)
            return result_df
        except Exception:
            return pd.DataFrame()