pyesmda.compute_normalized_objective_function¶
- pyesmda.compute_normalized_objective_function(pred: ndarray[Any, dtype[float64]], obs: ndarray[Any, dtype[float64]], cov_obs: ndarray[Any, dtype[float64]]) float[source]¶
Compute the normalized objective function for a given member \(j\).
\[O_{N_{d}, j} = \frac{1}{2N_{d}} \sum_{j=1}^{N_{e}}\left(d^{l}_{j} - {d_{obs}} \right)^{T}C_{D}^{-1}\left(d^{l}_{j} - {d_{obs}} \right)\]- Parameters
pred (npt.NDArray[np.float64]) – Vector of predicted values.
obs (npt.NDArray[np.float64]) – Vector of observed values.
cov_obs (npt.NDArray[np.float64]) – Covariance matrix of observed data measurement errors with dimensions (\(N_{obs}\), \(N_{obs}\)). Also denoted \(R\).
- Returns
The objective function.
- Return type