subspace⚓︎
Stochastic iterative ensemble smoother (IES) with subspace implementation.
subspace_update
⚓︎
Bases: AnalysisBase
Ensemble subspace update (weight-space IES).
The update is formulated in the ensemble weight space W (shape ne × ne)
rather than model space, making it efficient when ne ≪ nx. The caller
checks self.w_step (not self.step) to apply the update.
References
Raanes, P. N., Stordal, A. S., & Evensen, G. (2019). Revising the stochastic iterative ensemble smoother. Nonlinear Processes in Geophysics, 26(3), 325-338. https://doi.org/10.5194/npg-26-325-2019
Evensen, G., Raanes, P. N., Stordal, A. S., & Hove, J. (2019). Efficient implementation of an iterative ensemble smoother for data assimilation and reservoir history matching. Frontiers in Applied Mathematics and Statistics, 5, 47. https://doi.org/10.3389/fams.2019.00047
update(enX, enY, enE, **kwargs)
⚓︎
Perform the subspace (weight-space) LM update.
Sets self.scheme.w_step (shape ne × ne) and returns None --
the caller applies the weight update, not a state-space step.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
enX
|
(ndarray, shape(nx, ne))
|
State ensemble matrix (unused directly; included for interface parity). |
required |
enY
|
(ndarray, shape(nd, ne))
|
Predicted data ensemble matrix. |
required |
enE
|
(ndarray, shape(nd, ne))
|
Perturbed observations ensemble. |
required |
Returns:
| Type | Description |
|---|---|
AnalysisResult
|
The weight-space step |