"""Double Exponential Moving Average (DEMA) adapter using TA-Lib."""
from typing import Dict, Any
import numpy as np
import talib as ta
from .base import BaseIndicator
from ..models.market_data import MarketData
from ..models.indicator_result import IndicatorResult
class DEMAIndicator(BaseIndicator):
def __init__(self):
super().__init__(name="dema", description="Double Exponential Moving Average (DEMA)")
@property
def input_schema(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"close_prices": {"type": "array", "items": {"type": "number"}},
"timeperiod": {"type": "integer", "default": 30},
},
"required": ["close_prices"],
}
async def calculate(self, market_data: MarketData, options: Dict[str, Any] = None) -> IndicatorResult:
if options is None:
options = {}
timeperiod = options.get("timeperiod", 30)
close = np.asarray(market_data.close, dtype=float)
try:
out = ta.DEMA(close, timeperiod=timeperiod)
return IndicatorResult(
indicator_name=self.name,
success=True,
values={"dema": out.tolist()},
metadata={"timeperiod": timeperiod, "input_points": len(close), "output_points": len(out)},
)
except Exception as e:
return IndicatorResult(indicator_name=self.name, success=False, values={}, error_message=str(e))