Make design_matrix parameter_configuration a single GenKw element

The dictionary introduced in parameter configuration in design matrix config seems to be not necessary and thus removing it.
equinor · Jan 22, 2025 · 3442885 · 3442885
1 parent 2839ae7
commit 3442885
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Showing 3 changed files with 8 additions and 9 deletions.
diff --git a/src/ert/config/design_matrix.py b/src/ert/config/design_matrix.py
@@ -100,8 +100,8 @@ def merge_with_other(self, dm_other: DesignMatrix) -> None:
         except ValueError as exc:
             errors.append(ErrorInfo(f"Error when merging design matrices {exc}!"))
 
-        pc_other = dm_other.parameter_configuration[DESIGN_MATRIX_GROUP]
-        pc_self = self.parameter_configuration[DESIGN_MATRIX_GROUP]
+        pc_other = dm_other.parameter_configuration
+        pc_self = self.parameter_configuration
         assert isinstance(pc_other, GenKwConfig)
         assert isinstance(pc_self, GenKwConfig)
         for tfd in pc_other.transform_function_definitions:
@@ -131,7 +131,7 @@ def merge_with_existing_parameters(
 
         new_param_config: list[ParameterConfig] = []
 
-        design_parameter_group = self.parameter_configuration[DESIGN_MATRIX_GROUP]
+        design_parameter_group = self.parameter_configuration
         design_keys = []
         if isinstance(design_parameter_group, GenKwConfig):
             design_keys = [e.name for e in design_parameter_group.transform_functions]
@@ -163,7 +163,7 @@ def merge_with_existing_parameters(
 
     def read_design_matrix(
         self,
-    ) -> tuple[list[bool], pd.DataFrame, dict[str, ParameterConfig]]:
+    ) -> tuple[list[bool], pd.DataFrame, 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.
@@ -204,7 +204,6 @@ def read_design_matrix(
         )
         design_matrix_df = design_matrix_df.assign(**defaults_to_use)
 
-        parameter_configuration: dict[str, ParameterConfig] = {}
         transform_function_definitions: list[TransformFunctionDefinition] = []
         for parameter in design_matrix_df.columns:
             transform_function_definitions.append(
@@ -214,7 +213,7 @@ def read_design_matrix(
                     values=[],
                 )
             )
-        parameter_configuration[DESIGN_MATRIX_GROUP] = GenKwConfig(
+        parameter_configuration = GenKwConfig(
             name=DESIGN_MATRIX_GROUP,
             forward_init=False,
             template_file=None,

diff --git a/tests/ert/unit_tests/sensitivity_analysis/test_design_matrix.py b/tests/ert/unit_tests/sensitivity_analysis/test_design_matrix.py
@@ -77,7 +77,7 @@ def test_merge_multiple_occurrences(
             design_matrix_1.merge_with_other(design_matrix_2)
     else:
         design_matrix_1.merge_with_other(design_matrix_2)
-        design_params = design_matrix_1.parameter_configuration.get("DESIGN_MATRIX", [])
+        design_params = design_matrix_1.parameter_configuration
         assert all(param in design_params for param in ("a", "b", "c", "d"))
         assert design_matrix_1.active_realizations == [True, True, True]
         df = design_matrix_1.design_matrix_df
@@ -181,7 +181,7 @@ def test_reading_design_matrix(tmp_path):
             xl_write, index=False, sheet_name="DefaultValues", header=False
         )
     design_matrix = DesignMatrix(design_path, "DesignSheet01", "DefaultValues")
-    design_params = design_matrix.parameter_configuration.get(DESIGN_MATRIX_GROUP, [])
+    design_params = design_matrix.parameter_configuration
     assert all(param in design_params for param in ("a", "b", "c", "one", "d"))
     assert design_matrix.active_realizations == [True, True, False, False, True]
 

diff --git a/tests/ert/unit_tests/test_libres_facade.py b/tests/ert/unit_tests/test_libres_facade.py
@@ -284,7 +284,7 @@ def test_save_parameters_to_storage_from_design_dataframe(
     design_matrix = DesignMatrix(design_path, "DesignSheet01", "DefaultValues")
     with open_storage(tmp_path / "storage", mode="w") as storage:
         experiment_id = storage.create_experiment(
-            parameters=[design_matrix.parameter_configuration[DESIGN_MATRIX_GROUP]]
+            parameters=[design_matrix.parameter_configuration]
         )
         ensemble = storage.create_ensemble(
             experiment_id, name="default", ensemble_size=ensemble_size