Use get_ensemble in csv-export

Add experiment name to output.

src/ert/gui/tools/export/export_panel.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import json
 from typing import TYPE_CHECKING, Optional
 
 from qtpy.QtWidgets import QCheckBox, QWidget
@@ -25,33 +26,38 @@ def __init__(
     ) -> None:
         description = "The CSV export requires some information before it starts:"
         super().__init__("export", description, parent)
-
+        self.storage = storage  # Store the storage reference
         subs_list = ert_config.substitution_list
         default_csv_output_path = subs_list.get("<CSV_OUTPUT_PATH>", "output.csv")
         self.output_path_model = PathModel(default_csv_output_path)
         output_path_chooser = PathChooser(self.output_path_model)
-
         design_matrix_default = subs_list.get("<DESIGN_MATRIX_PATH>", "")
         self.design_matrix_path_model = PathModel(
             design_matrix_default, is_required=False, must_exist=True
         )
         design_matrix_path_chooser = PathChooser(self.design_matrix_path_model)
 
-        self.list_edit = ListEditBox(
-            [ensemble.name for ensemble in storage.ensembles if ensemble.has_data()]
-        )
+        # Create a dictionary of ensemble names to their IDs and experiment names
+        self.ensemble_dict = {
+            ensemble.name: {
+                "ensemble_id": str(ensemble.id),
+                "experiment_name": ensemble.experiment.name,
+            }
+            for ensemble in storage.ensembles
+            if ensemble.has_data()
+        }
+
+        self.list_edit = ListEditBox(list(self.ensemble_dict.keys()))
 
         self.drop_const_columns_check = QCheckBox()
         self.drop_const_columns_check.setChecked(False)
         self.drop_const_columns_check.setToolTip(
             "If checked, exclude columns whose value is the same for every entry"
         )
-
         self.addLabeledOption("Output file path", output_path_chooser)
         self.addLabeledOption("Design matrix path", design_matrix_path_chooser)
         self.addLabeledOption("List of ensembles to export", self.list_edit)
         self.addLabeledOption("Drop constant columns", self.drop_const_columns_check)
-
         self.addButtons()
 
     @property
@@ -60,7 +66,16 @@ def output_path(self) -> Optional[str]:
 
     @property
     def ensemble_list(self) -> str:
-        return ",".join(self.list_edit.getItems())
+        selected_ensembles = self.list_edit.getItems()
+        selected_dict = {
+            self.ensemble_dict[name]["ensemble_id"]: {
+                "name": name,
+                "experiment_name": self.ensemble_dict[name]["experiment_name"],
+            }
+            for name in selected_ensembles
+            if name in self.ensemble_dict
+        }
+        return json.dumps(selected_dict)
 
     @property
     def design_matrix_path(self) -> Optional[str]:

src/ert/resources/workflows/jobs/internal-gui/scripts/csv_export.py

@@ -1,4 +1,6 @@
+import json
 import os
+from uuid import UUID
 
 import pandas
 
@@ -22,9 +24,9 @@ class CSVExportJob(ErtScript):
 
     Optional arguments:
 
-    ensemble_list: a comma separated list of ensembles to export (no spaces allowed)
-               if no list is provided the current ensemble is exported
-               a single * can be used to export all ensembles
+    ensemble_dict: a string representation of a dictionary mapping ensemble IDs to names
+               if no dictionary is provided, the current ensemble is exported
+               a single "*" can be used to export all ensembles
 
     design_matrix: a path to a file containing the design matrix
 
@@ -53,37 +55,34 @@ def run(
         workflow_args,
     ):
         output_file = workflow_args[0]
-        ensemble_list = None if len(workflow_args) < 2 else workflow_args[1]
+        ensemble_dict_str = None if len(workflow_args) < 2 else workflow_args[1]
         design_matrix_path = None if len(workflow_args) < 3 else workflow_args[2]
         _ = True if len(workflow_args) < 4 else workflow_args[3]
         drop_const_cols = False if len(workflow_args) < 5 else workflow_args[4]
-        ensembles = []
         facade = LibresFacade(ert_config)
 
-        ensembles = ensemble_list.split(",")
-
-        if ensemble_list is None or len(ensembles) == 0:
-            ensembles = "default"
+        ensemble_dict = json.loads(ensemble_dict_str)
 
         if design_matrix_path is not None:
             if not os.path.exists(design_matrix_path):
-                raise UserWarning("The design matrix file does not exists!")
-
+                raise UserWarning("The design matrix file does not exist!")
             if not os.path.isfile(design_matrix_path):
                 raise UserWarning("The design matrix is not a file!")
 
         data = pandas.DataFrame()
 
-        for ensemble in ensembles:
-            ensemble = ensemble.strip()
-
+        for ensemble_id, ensemble_info in ensemble_dict.items():
             try:
-                ensemble = self.storage.get_ensemble_by_name(ensemble)
+                ensemble = storage.get_ensemble(UUID(ensemble_id))
             except KeyError as exc:
-                raise UserWarning(f"The ensemble '{ensemble}' does not exist!") from exc
+                raise UserWarning(
+                    f"The ensemble with ID '{ensemble_id}' does not exist!"
+                ) from exc
 
             if not ensemble.has_data():
-                raise UserWarning(f"The ensemble '{ensemble}' does not have any data!")
+                raise UserWarning(
+                    f"The ensemble '{ensemble.name}' does not have any data!"
+                )
 
             ensemble_data = ensemble.load_all_gen_kw_data()
 
@@ -105,13 +104,16 @@ def run(
 
             ensemble_data["Iteration"] = ensemble.iteration
             ensemble_data["Ensemble"] = ensemble.name
+            ensemble_data["Experiment"] = ensemble_info["experiment_name"]
             ensemble_data.set_index(
-                ["Ensemble", "Iteration"], append=True, inplace=True
+                ["Ensemble", "Experiment", "Iteration"], append=True, inplace=True
             )
 
             data = pandas.concat([data, ensemble_data])
 
-        data = data.reorder_levels(["Realization", "Iteration", "Date", "Ensemble"])
+        data = data.reorder_levels(
+            ["Realization", "Iteration", "Date", "Experiment", "Ensemble"]
+        )
         if drop_const_cols:
             data = data.loc[:, (data != data.iloc[0]).any()]