Update ensemble smoother

Author: xjules

src/ert/run_models/ensemble_smoother.py

@@ -7,9 +7,16 @@
 
 import numpy as np
 
-from ert.config import ErtConfig, ESSettings, HookRuntime, UpdateSettings
+from ert.config import (
+    ErtConfig,
+    ESSettings,
+    HookRuntime,
+    ParameterConfig,
+    ScalarParameters,
+    UpdateSettings,
+)
 from ert.config.parsing.config_errors import ConfigValidationError
-from ert.enkf_main import sample_prior, save_design_matrix_to_ensemble
+from ert.enkf_main import sample_prior
 from ert.ensemble_evaluator import EvaluatorServerConfig
 from ert.storage import Storage
 from ert.trace import tracer
@@ -77,16 +84,20 @@ def run_experiment(
     ) -> None:
         self.log_at_startup()
 
-        parameters_config = self._parameter_configuration
-        design_matrix = self._design_matrix
-        design_matrix_group = None
-        if design_matrix is not None:
-            try:
-                parameters_config, design_matrix_group = (
-                    design_matrix.merge_with_existing_parameters(parameters_config)
-                )
-            except ConfigValidationError as exc:
-                raise ErtRunError(str(exc)) from exc
+        if self._design_matrix is not None:
+            parameters_config: list[ParameterConfig] = []
+            for param in self._parameter_configuration:
+                if isinstance(param, ScalarParameters):
+                    try:
+                        new_scalar_config = (
+                            self._design_matrix.merge_with_existing_parameters(param)
+                        )
+                        parameters_config.append(new_scalar_config)
+                    except ConfigValidationError as exc:
+                        raise ErtRunError(str(exc)) from exc
+                else:
+                    parameters_config.append(param)
+            self._parameter_configuration = parameters_config
 
         self.restart = restart
         self.run_workflows(
@@ -95,8 +106,7 @@ def run_experiment(
         )
         ensemble_format = self.target_ensemble_format
         experiment = self._storage.create_experiment(
-            parameters=parameters_config
-            + ([design_matrix_group] if design_matrix_group else []),
+            parameters=self._parameter_configuration,
             observations=self._observations,
             responses=self._response_configuration,
             name=self.experiment_name,
@@ -119,15 +129,13 @@ def run_experiment(
             prior,
             np.where(self.active_realizations)[0],
             random_seed=self.random_seed,
+            design_matrix_df=(
+                self._design_matrix.design_matrix_df
+                if self._design_matrix is not None
+                else None
+            ),
         )
 
-        if design_matrix_group is not None and design_matrix is not None:
-            save_design_matrix_to_ensemble(
-                design_matrix.design_matrix_df,
-                prior,
-                np.where(self.active_realizations)[0],
-                design_matrix_group.name,
-            )
         self._evaluate_and_postprocess(
             prior_args,
             prior,

src/ert/run_models/multiple_data_assimilation.py

@@ -108,14 +108,13 @@ def run_experiment(
     ) -> None:
         self.log_at_startup()
 
-        design_matrix = self._design_matrix
-        if design_matrix is not None:
+        if self._design_matrix is not None:
             parameters_config: list[ParameterConfig] = []
             for param in self._parameter_configuration:
                 if isinstance(param, ScalarParameters):
                     try:
                         new_scalar_config = (
-                            design_matrix.merge_with_existing_parameters(param)
+                            self._design_matrix.merge_with_existing_parameters(param)
                         )
                         parameters_config.append(new_scalar_config)
                     except ConfigValidationError as exc:
@@ -175,8 +174,8 @@ def run_experiment(
                 np.where(self.active_realizations)[0],
                 random_seed=self.random_seed,
                 design_matrix_df=(
-                    design_matrix.design_matrix_df
-                    if design_matrix is not None
+                    self._design_matrix.design_matrix_df
+                    if self._design_matrix is not None
                     else None
                 ),
             )