2025-06-07 14:01:20 +08:00
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"""
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Simple Moving Average (SMA) indicator implementation.
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"""
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import pandas as pd
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from ..base import BaseIndicator
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class SMAIndicator(BaseIndicator):
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"""
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Simple Moving Average (SMA) technical indicator.
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Calculates the unweighted mean of previous n periods.
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Handles sparse data appropriately without interpolation.
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"""
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def calculate(self, df: pd.DataFrame, period: int = 20,
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price_column: str = 'close') -> pd.DataFrame:
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2025-06-07 14:01:20 +08:00
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"""
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Calculate Simple Moving Average (SMA).
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Args:
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df: DataFrame with OHLCV data
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period: Number of periods for moving average (default: 20)
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price_column: Price column to use ('open', 'high', 'low', 'close')
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Returns:
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DataFrame with SMA values and metadata, indexed by timestamp
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"""
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# Validate input data
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if not self.validate_dataframe(df, period):
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return pd.DataFrame()
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try:
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df = df.copy()
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df['sma'] = df[price_column].rolling(window=period, min_periods=period).mean()
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# Only keep rows with valid SMA, and only 'timestamp' and 'sma' columns
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result_df = df.loc[df['sma'].notna(), ['timestamp', 'sma']].copy()
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result_df = result_df.iloc[period-1:]
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result_df.set_index('timestamp', inplace=True)
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return result_df
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except Exception:
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return pd.DataFrame()
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