Add run experiment with design matrix to ensemble experiment panel

- Catagorical data is not treated properly yet, wherein the design
matrix group that contains catagorical data will automatically store all
parameters inside this group to objects; ie, strings.
- Prefil active realization box with realizations from design matrix
- Use design_matrix parameters in ensemble experiment
- add test run cli with design matrix and poly example
- add test that save parameters internalize DataFrame parameters in the storage
- add merge function to merge design parameters with existing parameters
 -- Raise Validation error when having multiple overlapping groups
- Update writting to parameter.txt with categorical values

src/ert/config/design_matrix.py

@@ -14,9 +14,7 @@
 from .parsing import ConfigValidationError, ErrorInfo
 
 if TYPE_CHECKING:
-    from ert.config import (
-        ParameterConfig,
-    )
+    from ert.config import ParameterConfig
 
 DESIGN_MATRIX_GROUP = "DESIGN_MATRIX"
 
@@ -28,10 +26,17 @@ class DesignMatrix:
     default_sheet: str
 
     def __post_init__(self) -> None:
-        self.num_realizations: int | None = None
-        self.active_realizations: list[bool] | None = None
-        self.design_matrix_df: pd.DataFrame | None = None
-        self.parameter_configuration: dict[str, ParameterConfig] | None = None
+        try:
+            (
+                self.active_realizations,
+                self.design_matrix_df,
+                self.parameter_configuration,
+            ) = self.read_design_matrix()
+        except (ValueError, AttributeError) as exc:
+            raise ConfigValidationError.with_context(
+                f"Error reading design matrix {self.xls_filename}: {exc}",
+                str(self.xls_filename),
+            ) from exc
 
     @classmethod
     def from_config_list(cls, config_list: list[str]) -> DesignMatrix:
@@ -73,9 +78,60 @@ def from_config_list(cls, config_list: list[str]) -> DesignMatrix:
             default_sheet=default_sheet,
         )
 
+    def merge_with_existing_parameters(
+        self, existing_parameters: list[ParameterConfig]
+    ) -> tuple[list[ParameterConfig], ParameterConfig | None]:
+        """
+        This method merges the design matrix parameters with the existing parameters and
+        returns the new list of existing parameters, wherein we drop GEN_KW group having a full overlap with the design matrix group.
+        GEN_KW group that was dropped will acquire a new name from the design matrix group.
+        Additionally, the ParameterConfig which is the design matrix group is returned separately.
+
+        Args:
+            existing_parameters (List[ParameterConfig]): List of existing parameters
+
+        Raises:
+            ConfigValidationError: If there is a partial overlap between the design matrix group and any existing GEN_KW group
+
+        Returns:
+            tuple[List[ParameterConfig], ParameterConfig]: List of existing parameters and the dedicated design matrix group
+        """
+
+        new_param_config: list[ParameterConfig] = []
+
+        design_parameter_group = self.parameter_configuration[DESIGN_MATRIX_GROUP]
+        design_keys = []
+        if isinstance(design_parameter_group, GenKwConfig):
+            design_keys = [e.name for e in design_parameter_group.transform_functions]
+
+        design_group_added = False
+        for parameter_group in existing_parameters:
+            if not isinstance(parameter_group, GenKwConfig):
+                new_param_config += [parameter_group]
+                continue
+            existing_keys = [e.name for e in parameter_group.transform_functions]
+            if set(existing_keys) == set(design_keys):
+                if design_group_added:
+                    raise ConfigValidationError(
+                        "Multiple overlapping groups with design matrix found in existing parameters!\n"
+                        f"{design_parameter_group.name} and {parameter_group.name}"
+                    )
+
+                design_parameter_group.name = parameter_group.name
+                design_group_added = True
+            elif set(design_keys) & set(existing_keys):
+                raise ConfigValidationError(
+                    "Overlapping parameter names found in design matrix!\n"
+                    f"{DESIGN_MATRIX_GROUP}:{design_keys}\n{parameter_group.name}:{existing_keys}"
+                    "\nThey need to much exactly or not at all."
+                )
+            else:
+                new_param_config += [parameter_group]
+        return new_param_config, design_parameter_group
+
     def read_design_matrix(
         self,
-    ) -> None:
+    ) -> tuple[list[bool], pd.DataFrame, dict[str, ParameterConfig]]:
         # Read the parameter names (first row) as strings to prevent pandas from modifying them.
         # This ensures that duplicate or empty column names are preserved exactly as they appear in the Excel sheet.
         # By doing this, we can properly validate variable names, including detecting duplicates or missing names.
@@ -139,11 +195,11 @@ def read_design_matrix(
             [[DESIGN_MATRIX_GROUP], design_matrix_df.columns]
         )
         reals = design_matrix_df.index.tolist()
-        self.num_realizations = len(reals)
-        self.active_realizations = [x in reals for x in range(max(reals) + 1)]
-
-        self.design_matrix_df = design_matrix_df
-        self.parameter_configuration = parameter_configuration
+        return (
+            [x in reals for x in range(max(reals) + 1)],
+            design_matrix_df,
+            parameter_configuration,
+        )
 
     @staticmethod
     def _read_excel(

src/ert/enkf_main.py

@@ -10,20 +10,17 @@
 from typing import TYPE_CHECKING, Any
 
 import orjson
+import pandas as pd
+import xarray as xr
 from numpy.random import SeedSequence
 
 from ert.config.ert_config import forward_model_data_to_json
 from ert.config.forward_model_step import ForwardModelStep
 from ert.config.model_config import ModelConfig
 from ert.substitutions import Substitutions, substitute_runpath_name
 
-from .config import (
-    ExtParamConfig,
-    Field,
-    GenKwConfig,
-    ParameterConfig,
-    SurfaceConfig,
-)
+from .config import ExtParamConfig, Field, GenKwConfig, ParameterConfig, SurfaceConfig
+from .config.design_matrix import DESIGN_MATRIX_GROUP
 from .run_arg import RunArg
 from .runpaths import Runpaths
 
@@ -53,7 +50,10 @@ def _value_export_txt(
     with path.open("w") as f:
         for key, param_map in values.items():
             for param, value in param_map.items():
-                print(f"{key}:{param} {value:g}", file=f)
+                if isinstance(value, (int | float)):
+                    print(f"{key}:{param} {value:g}", file=f)
+                else:
+                    print(f"{key}:{param} {value}", file=f)
 
 
 def _value_export_json(
@@ -156,6 +156,29 @@ def _seed_sequence(seed: int | None) -> int:
     return int_seed
 
 
+def save_design_matrix_to_ensemble(
+    design_matrix_df: pd.DataFrame,
+    ensemble: Ensemble,
+    active_realizations: Iterable[int],
+    design_group_name: str = DESIGN_MATRIX_GROUP,
+) -> None:
+    assert not design_matrix_df.empty
+    for realization_nr in active_realizations:
+        row = design_matrix_df.loc[realization_nr][DESIGN_MATRIX_GROUP]
+        ds = xr.Dataset(
+            {
+                "values": ("names", list(row.values)),
+                "transformed_values": ("names", list(row.values)),
+                "names": list(row.keys()),
+            }
+        )
+        ensemble.save_parameters(
+            design_group_name,
+            realization_nr,
+            ds,
+        )
+
+
 def sample_prior(
     ensemble: Ensemble,
     active_realizations: Iterable[int],

src/ert/gui/simulation/ensemble_experiment_panel.py

@@ -15,7 +15,7 @@
 from ert.gui.tools.design_matrix.design_matrix_panel import DesignMatrixPanel
 from ert.mode_definitions import ENSEMBLE_EXPERIMENT_MODE
 from ert.run_models import EnsembleExperiment
-from ert.validation import RangeStringArgument
+from ert.validation import ActiveRange, RangeStringArgument
 from ert.validation.proper_name_argument import ExperimentValidation, ProperNameArgument
 
 from .experiment_config_panel import ExperimentConfigPanel
@@ -85,6 +85,9 @@ def __init__(
 
         design_matrix = analysis_config.design_matrix
         if design_matrix is not None:
+            self._active_realizations_field.setText(
+                ActiveRange(design_matrix.active_realizations).rangestring
+            )
             show_dm_param_button = QPushButton("Show parameters")
             show_dm_param_button.setObjectName("show-dm-parameters")
             show_dm_param_button.setMinimumWidth(50)
@@ -113,23 +116,14 @@ def __init__(
         self.notifier.ertChanged.connect(self._update_experiment_name_placeholder)
 
     def on_show_dm_params_clicked(self, design_matrix: DesignMatrix) -> None:
-        assert design_matrix is not None
-
-        if design_matrix.design_matrix_df is None:
-            design_matrix.read_design_matrix()
-
-        if (
-            design_matrix.design_matrix_df is not None
-            and not design_matrix.design_matrix_df.empty
-        ):
-            viewer = DesignMatrixPanel(
-                design_matrix.design_matrix_df,
-                design_matrix.xls_filename.name,
-            )
-            viewer.setMinimumHeight(500)
-            viewer.setMinimumWidth(1000)
-            viewer.adjustSize()
-            viewer.exec_()
+        viewer = DesignMatrixPanel(
+            design_matrix.design_matrix_df,
+            design_matrix.xls_filename.name,
+        )
+        viewer.setMinimumHeight(500)
+        viewer.setMinimumWidth(1000)
+        viewer.adjustSize()
+        viewer.exec_()
 
     @Slot(ExperimentConfigPanel)
     def experimentTypeChanged(self, w: ExperimentConfigPanel) -> None:

src/ert/run_models/ensemble_experiment.py

@@ -6,13 +6,14 @@
 
 import numpy as np
 
-from ert.enkf_main import sample_prior
+from ert.config import ConfigValidationError
+from ert.enkf_main import sample_prior, save_design_matrix_to_ensemble
 from ert.ensemble_evaluator import EvaluatorServerConfig
 from ert.storage import Ensemble, Experiment, Storage
 from ert.trace import tracer
 
 from ..run_arg import create_run_arguments
-from .base_run_model import BaseRunModel, StatusEvents
+from .base_run_model import BaseRunModel, ErtRunError, StatusEvents
 
 if TYPE_CHECKING:
     from ert.config import ErtConfig, QueueConfig
@@ -64,10 +65,27 @@ def run_experiment(
     ) -> None:
         self.log_at_startup()
         self.restart = restart
+        # If design matrix is present, we try to merge design matrix parameters
+        # to the experiment parameters and set new active realizations
+        parameters_config = self.ert_config.ensemble_config.parameter_configuration
+        design_matrix = self.ert_config.analysis_config.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 not restart:
             self.experiment = self._storage.create_experiment(
                 name=self.experiment_name,
-                parameters=self.ert_config.ensemble_config.parameter_configuration,
+                parameters=(
+                    [*parameters_config, design_matrix_group]
+                    if design_matrix_group is not None
+                    else parameters_config
+                ),
                 observations=self.ert_config.observations,
                 responses=self.ert_config.ensemble_config.response_configuration,
             )
@@ -90,12 +108,21 @@ def run_experiment(
             np.array(self.active_realizations, dtype=bool),
             ensemble=self.ensemble,
         )
+
         sample_prior(
             self.ensemble,
             np.where(self.active_realizations)[0],
             random_seed=self.random_seed,
         )
 
+        if design_matrix_group is not None and design_matrix is not None:
+            save_design_matrix_to_ensemble(
+                design_matrix.design_matrix_df,
+                self.ensemble,
+                np.where(self.active_realizations)[0],
+                design_matrix_group.name,
+            )
+
         self._evaluate_and_postprocess(
             run_args,
             self.ensemble,

src/ert/run_models/model_factory.py

@@ -117,13 +117,20 @@ def _setup_ensemble_experiment(
     args: Namespace,
     status_queue: SimpleQueue[StatusEvents],
 ) -> EnsembleExperiment:
-    active_realizations = _realizations(args, config.model_config.num_realizations)
+    active_realizations = _realizations(
+        args, config.model_config.num_realizations
+    ).tolist()
+    if (
+        config.analysis_config.design_matrix is not None
+        and config.analysis_config.design_matrix.active_realizations is not None
+    ):
+        active_realizations = config.analysis_config.design_matrix.active_realizations
     experiment_name = args.experiment_name
     assert experiment_name is not None
 
     return EnsembleExperiment(
         random_seed=config.random_seed,
-        active_realizations=active_realizations.tolist(),
+        active_realizations=active_realizations,
         ensemble_name=args.current_ensemble,
         minimum_required_realizations=config.analysis_config.minimum_required_realizations,
         experiment_name=experiment_name,
@@ -271,9 +278,9 @@ def _setup_iterative_ensemble_smoother(
         random_seed=config.random_seed,
         active_realizations=active_realizations.tolist(),
         target_ensemble=_iterative_ensemble_format(args),
-        number_of_iterations=int(args.num_iterations)
-        if args.num_iterations is not None
-        else 4,
+        number_of_iterations=(
+            int(args.num_iterations) if args.num_iterations is not None else 4
+        ),
         minimum_required_realizations=config.analysis_config.minimum_required_realizations,
         num_retries_per_iter=4,
         experiment_name=experiment_name,