def ad_ratio_np(prices: np.ndarray) -> np.ndarray:
"""
Advance/Decline Ratio (numpy)
:param prices: last dimension - time
:return:
"""
ch = change(prices, 1)
ch = np.nan_to_num(ch)
advance = np.where(ch > 0, 1, 0).sum(axis=0)
decline = np.where(ch < 0, 1, 0).sum(axis=0)
return advance / decline
def rsi(
series: nda.NdType,
ma: tp.Any = 14 # lambda series: wilder_ma(series, 14)
) -> nda.NdType:
if isinstance(ma, int):
ma_period = ma
ma = lambda series: wilder_ma(series, ma_period)
ch = change(series)
up = np.maximum(ch, 0) # positive changes
down = -np.minimum(ch, 0) # negative changes (inverted)
up = ma(up)
down = ma(down)
rs = up / down
rsi = 100 * (1 - 1 / (1 + rs))
return rsi