def adxr(adx: NdType, periods: int) -> NdType:
prev_adx = shift(adx, periods)
return (adx + prev_adx) / 2
def m(high: NdType, low: NdType) -> tp.Tuple[NdType, NdType]:
plus_m = high - shift(high, 1)
minus_m = shift(low, 1) - low
return plus_m, minus_m
def roc(series: nda.NdType, periods: int = 7) -> nda.NdType:
"""
Rate of change
"""
shifted = shift(series, periods)
return 100 * (series / shifted - 1)
def change(series: np.ndarray, periods: int = 1) -> np.ndarray:
shifted = shift(series, periods)
return series - shifted
def tr(high: NdType, low: NdType, close: NdType) -> NdType:
prev_close = shift(close, 1)
return np.maximum(high, prev_close) - np.minimum(low, prev_close)
