Remove IES

equinor · Jan 22, 2025 · b7f37e7 · b7f37e7
1 parent 2839ae7
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diff --git a/docs/ert/reference/running_ert.rst b/docs/ert/reference/running_ert.rst
@@ -43,15 +43,6 @@ Ensemble Smoother
    :prog: ert
    :path: ensemble_smoother
 
-Iterative Ensemble Smoother
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-.. argparse::
-   :module: ert.__main__
-   :func: get_ert_parser
-   :prog: ert
-   :path: iterative_ensemble_smoother
-
 ES MDA
 ~~~~~~
 

diff --git a/docs/ert/theory/ensemble_based_methods.rst b/docs/ert/theory/ensemble_based_methods.rst
@@ -384,11 +384,6 @@ In plain English, the ES MDA consists of several consecutive smoother updates wi
 error bars. The ES MDA with one iteration is identical to the Ensemble smoother.
 
 
-Iterative ensemble smoother - Ensemble subspace version
--------------------------------------------------------
-
-The algorithm implemented is described in the article `Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching <https://www.frontiersin.org/articles/10.3389/fams.2019.00047/full>`_.
-
 Kalman posterior properties
 ---------------------------
 

diff --git a/src/ert/__main__.py b/src/ert/__main__.py
@@ -28,7 +28,6 @@
     ENSEMBLE_EXPERIMENT_MODE,
     ENSEMBLE_SMOOTHER_MODE,
     ES_MDA_MODE,
-    ITERATIVE_ENSEMBLE_SMOOTHER_MODE,
     TEST_RUN_MODE,
     WORKFLOW_MODE,
 )
@@ -421,73 +420,6 @@ def get_ert_parser(parser: ArgumentParser | None = None) -> ArgumentParser:
         help="Name of the experiment",
     )
 
-    # iterative_ensemble_smoother_parser
-    iterative_ensemble_smoother_description = (
-        "Run experiments in cli while performing updates"
-        " on the parameters using the iterative ensemble smoother algorithm."
-    )
-    iterative_ensemble_smoother_parser = subparsers.add_parser(
-        ITERATIVE_ENSEMBLE_SMOOTHER_MODE,
-        description=iterative_ensemble_smoother_description,
-        help=iterative_ensemble_smoother_description,
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--current-case",
-        type=valid_name,
-        default="default",
-        action=DeprecatedAction,
-        alternative_option="--current-ensemble",
-        dest="current_ensemble",
-        help="Deprecated: This argument is deprecated and will be "
-        "removed in future versions. Use --current-ensemble instead.",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--current-ensemble",
-        type=valid_name,
-        default="default",
-        help="Name of the ensemble where the results for the experiment "
-        "using the prior parameters will be stored.",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--target-case",
-        type=valid_name_format,
-        default="iter-%d",
-        action=DeprecatedAction,
-        dest="target_ensemble",
-        alternative_option="--target--ensemble",
-        help="Deprecated: This argument is deprecated and will be "
-        "removed in future versions. Use --target-ensemble instead.",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--target-ensemble",
-        type=valid_name_format,
-        default="iter-%d",
-        help="The iterative ensemble smoother creates multiple ensembles for the different "
-        "iterations. The ensemble names will follow the specified format. "
-        "For example, 'Target ensemble format: iter_%%d' will generate "
-        "ensembles with the names iter_0, iter_1, iter_2, iter_3, ....",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--realizations",
-        type=valid_realizations,
-        help="These are the realizations that will be used to perform experiments."
-        "For example, if 'Number of realizations:50 and active realizations are 0-9', "
-        "then only realizations 0,1,2,3,...,9 will be used to perform experiments "
-        "while realizations 10,11, 12,...,49 will be excluded.",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--num-iterations",
-        type=valid_num_iterations,
-        required=False,
-        help="The number of iterations to run.",
-    )
-    iterative_ensemble_smoother_parser.add_argument(
-        "--experiment-name",
-        type=str,
-        default="ies",
-        help="Name of the experiment",
-    )
-
     # es_mda_parser
     es_mda_description = f"Run '{ES_MDA_MODE}' in cli"
     es_mda_parser = subparsers.add_parser(
@@ -574,7 +506,6 @@ def get_ert_parser(parser: ArgumentParser | None = None) -> ArgumentParser:
         test_run_parser,
         ensemble_experiment_parser,
         ensemble_smoother_parser,
-        iterative_ensemble_smoother_parser,
         es_mda_parser,
         workflow_parser,
     ]:

diff --git a/src/ert/analysis/__init__.py b/src/ert/analysis/__init__.py
@@ -1,6 +1,5 @@
 from ._es_update import (
     ErtAnalysisError,
-    iterative_smoother_update,
     smoother_update,
 )
 from .event import (
@@ -26,6 +25,5 @@
     "ObservationAndResponseSnapshot",
     "ObservationStatus",
     "SmootherSnapshot",
-    "iterative_smoother_update",
     "smoother_update",
 ]
diff --git a/src/ert/analysis/_es_update.py b/src/ert/analysis/_es_update.py
@@ -22,7 +22,7 @@
 from ert.config import GenKwConfig
 
 from ..config.analysis_config import ObservationGroups, UpdateSettings
-from ..config.analysis_module import BaseSettings, ESSettings, IESSettings
+from ..config.analysis_module import BaseSettings, ESSettings
 from . import misfit_preprocessor
 from .event import (
     AnalysisCompleteEvent,
@@ -629,123 +629,6 @@ def correlation_callback(
         )
 
 
-def analysis_IES(
-    parameters: Iterable[str],
-    observations: Iterable[str],
-    rng: np.random.Generator,
-    analysis_config: IESSettings,
-    alpha: float,
-    std_cutoff: float,
-    smoother_snapshot: SmootherSnapshot,
-    ens_mask: npt.NDArray[np.bool_],
-    source_ensemble: Ensemble,
-    target_ensemble: Ensemble,
-    sies_smoother: ies.SIES | None,
-    progress_callback: Callable[[AnalysisEvent], None],
-    auto_scale_observations: list[ObservationGroups],
-    sies_step_length: Callable[[int], float],
-    initial_mask: npt.NDArray[np.bool_],
-) -> ies.SIES:
-    iens_active_index = np.flatnonzero(ens_mask)
-    # Pick out realizations that were among the initials that are still living
-    # Example: initial_mask=[1,1,1,0,1], ens_mask=[0,1,1,0,1]
-    # Then the result is [0,1,1,1]
-    # This is needed for the SIES library
-    masking_of_initial_parameters = ens_mask[initial_mask]
-
-    progress_callback(AnalysisStatusEvent(msg="Loading observations and responses.."))
-
-    (
-        S,
-        (
-            observation_values,
-            observation_errors,
-            update_snapshot,
-        ),
-    ) = _load_observations_and_responses(
-        source_ensemble,
-        alpha,
-        std_cutoff,
-        1.0,
-        iens_active_index,
-        observations,
-        auto_scale_observations,
-        progress_callback,
-    )
-
-    smoother_snapshot.update_step_snapshots = update_snapshot
-    if len(observation_values) == 0:
-        msg = "No active observations for update step"
-        progress_callback(
-            AnalysisErrorEvent(
-                error_msg=msg,
-                data=DataSection(
-                    header=smoother_snapshot.header,
-                    data=smoother_snapshot.csv,
-                    extra=smoother_snapshot.extra,
-                ),
-            )
-        )
-        raise ErtAnalysisError(msg)
-
-    # if the algorithm object is not passed, initialize it
-    if sies_smoother is None:
-        # The sies smoother must be initialized with the full parameter ensemble
-        # Get relevant active realizations
-        parameter_ensemble_active = _all_parameters(source_ensemble, iens_active_index)
-        sies_smoother = ies.SIES(
-            parameters=parameter_ensemble_active,
-            covariance=observation_errors**2,
-            observations=observation_values,
-            seed=rng,
-            inversion=analysis_config.inversion,
-            truncation=analysis_config.enkf_truncation,
-        )
-
-        # Keep track of iterations to calculate step-lengths
-        sies_smoother.iteration = 1
-
-    # Calculate step-lengths to scale SIES iteration
-    step_length = sies_step_length(sies_smoother.iteration)
-
-    # Propose a transition matrix using only active realizations
-    proposed_W = sies_smoother.propose_W_masked(
-        S, ensemble_mask=masking_of_initial_parameters, step_length=step_length
-    )
-
-    # Store transition matrix for later use on sies object
-    sies_smoother.W[:, masking_of_initial_parameters] = proposed_W
-
-    for param_group in parameters:
-        param_ensemble_array = _load_param_ensemble_array(
-            source_ensemble, param_group, iens_active_index
-        )
-        param_ensemble_array += (
-            param_ensemble_array @ sies_smoother.W / np.sqrt(len(iens_active_index) - 1)
-        )
-
-        progress_callback(AnalysisStatusEvent(msg=f"Storing data for {param_group}.."))
-        _save_param_ensemble_array_to_disk(
-            target_ensemble, param_ensemble_array, param_group, iens_active_index
-        )
-
-    _copy_unupdated_parameters(
-        list(source_ensemble.experiment.parameter_configuration.keys()),
-        parameters,
-        iens_active_index,
-        source_ensemble,
-        target_ensemble,
-    )
-
-    assert sies_smoother is not None, "sies_smoother should be initialized"
-
-    # Increment the iteration number
-    sies_smoother.iteration += 1
-
-    # Return the sies smoother so it may be iterated over
-    return sies_smoother
-
-
 def _create_smoother_snapshot(
     prior_name: str,
     posterior_name: str,
@@ -827,73 +710,3 @@ def smoother_update(
         )
     )
     return smoother_snapshot
-
-
-def iterative_smoother_update(
-    prior_storage: Ensemble,
-    posterior_storage: Ensemble,
-    sies_smoother: ies.SIES | None,
-    parameters: Iterable[str],
-    observations: Iterable[str],
-    update_settings: UpdateSettings,
-    analysis_config: IESSettings,
-    sies_step_length: Callable[[int], float],
-    initial_mask: npt.NDArray[np.bool_],
-    rng: np.random.Generator | None = None,
-    progress_callback: Callable[[AnalysisEvent], None] | None = None,
-    global_scaling: float = 1.0,
-) -> tuple[SmootherSnapshot, ies.SIES]:
-    if not progress_callback:
-        progress_callback = noop_progress_callback
-    if rng is None:
-        rng = np.random.default_rng()
-
-    ens_mask = prior_storage.get_realization_mask_with_responses()
-
-    smoother_snapshot = _create_smoother_snapshot(
-        prior_storage.name,
-        posterior_storage.name,
-        update_settings,
-        global_scaling,
-    )
-
-    try:
-        sies_smoother = analysis_IES(
-            parameters=parameters,
-            observations=observations,
-            rng=rng,
-            analysis_config=analysis_config,
-            alpha=update_settings.alpha,
-            std_cutoff=update_settings.std_cutoff,
-            smoother_snapshot=smoother_snapshot,
-            ens_mask=ens_mask,
-            source_ensemble=prior_storage,
-            target_ensemble=posterior_storage,
-            sies_smoother=sies_smoother,
-            progress_callback=progress_callback,
-            auto_scale_observations=update_settings.auto_scale_observations,
-            sies_step_length=sies_step_length,
-            initial_mask=initial_mask,
-        )
-    except Exception as e:
-        progress_callback(
-            AnalysisErrorEvent(
-                error_msg=str(e),
-                data=DataSection(
-                    header=smoother_snapshot.header,
-                    data=smoother_snapshot.csv,
-                    extra=smoother_snapshot.extra,
-                ),
-            )
-        )
-        raise e
-    progress_callback(
-        AnalysisCompleteEvent(
-            data=DataSection(
-                header=smoother_snapshot.header,
-                data=smoother_snapshot.csv,
-                extra=smoother_snapshot.extra,
-            )
-        )
-    )
-    return smoother_snapshot, sies_smoother
diff --git a/src/ert/cli/main.py b/src/ert/cli/main.py
@@ -18,7 +18,6 @@
     ENSEMBLE_EXPERIMENT_MODE,
     ENSEMBLE_SMOOTHER_MODE,
     ES_MDA_MODE,
-    ITERATIVE_ENSEMBLE_SMOOTHER_MODE,
     TEST_RUN_MODE,
     WORKFLOW_MODE,
 )
@@ -68,7 +67,6 @@ def run_cli(args: Namespace, plugin_manager: ErtPluginManager | None = None) ->
     if args.mode in {
         ENSEMBLE_SMOOTHER_MODE,
         ES_MDA_MODE,
-        ITERATIVE_ENSEMBLE_SMOOTHER_MODE,
     }:
         if not ert_config.ensemble_config.parameter_configs:
             raise ErtCliError(

diff --git a/src/ert/config/parsing/analysis_mode.py b/src/ert/config/parsing/analysis_mode.py
@@ -2,5 +2,4 @@
 
 
 class AnalysisMode(StrEnum):
-    ITERATED_ENSEMBLE_SMOOTHER = "IES_ENKF"
     ENSEMBLE_SMOOTHER = "STD_ENKF"
diff --git a/src/ert/gui/simulation/experiment_panel.py b/src/ert/gui/simulation/experiment_panel.py
@@ -42,7 +42,6 @@
 from .ensemble_smoother_panel import EnsembleSmootherPanel
 from .evaluate_ensemble_panel import EvaluateEnsemblePanel
 from .experiment_config_panel import ExperimentConfigPanel
-from .iterated_ensemble_smoother_panel import IteratedEnsembleSmootherPanel
 from .manual_update_panel import ManualUpdatePanel
 from .multiple_data_assimilation_panel import MultipleDataAssimilationPanel
 from .run_dialog import RunDialog
@@ -168,12 +167,6 @@ def __init__(
             EnsembleSmootherPanel(analysis_config, run_path, notifier, ensemble_size),
             experiment_type_valid,
         )
-        self.addExperimentConfigPanel(
-            IteratedEnsembleSmootherPanel(
-                analysis_config, run_path, notifier, ensemble_size
-            ),
-            experiment_type_valid,
-        )
         self.addExperimentConfigPanel(
             ManualUpdatePanel(ensemble_size, run_path, notifier, analysis_config),
             experiment_type_valid,
Original file line number	Diff line number	Diff line change
Expand Up		@@ -2,5 +2,4 @@


		class AnalysisMode(StrEnum):
		ITERATED_ENSEMBLE_SMOOTHER = "IES_ENKF"
		ENSEMBLE_SMOOTHER = "STD_ENKF"