kedm.eval_smap¶
- kedm.eval_smap(lib: numpy.ndarray[numpy.float32], pred: numpy.ndarray[numpy.float32], *, target: numpy.ndarray[numpy.float32] = None, E: int = 1, tau: int = 1, Tp: int = 1, theta: float = 1.0) float ¶
Predict a time series from another using S-Map and quantify its predictive skill.
- Parameters:
lib – Library time series
pred – Prediction time series
target – Target time series (defaults to
lib
if None)E – Embedding dimension
tau – Time delay
Tp – Prediction interval
theta – Neighbor localization exponent
- Returns:
Pearson’s correlation coefficient between observation and prediction