(Everest) Use one experiment per optimization

src/ert/simulator/batch_simulator.py

@@ -9,7 +9,7 @@
 from .batch_simulator_context import BatchContext
 
 if TYPE_CHECKING:
-    from ert.storage import Ensemble, Storage
+    from ert.storage import Ensemble, Experiment
 
 
 class BatchSimulator:
@@ -181,7 +181,7 @@ def start(
         self,
         case_name: str,
         case_data: List[Tuple[int, Dict[str, Dict[str, Any]]]],
-        storage: Storage,
+        experiment: Experiment,
     ) -> BatchContext:
         """Start batch simulation, return a simulation context
 
@@ -240,13 +240,7 @@ def start(
         time, so when you have called the 'start' method you need to let that
         batch complete before you start a new batch.
         """
-        experiment = storage.create_experiment(
-            parameters=self.ert_config.ensemble_config.parameter_configuration,
-            responses=self.ert_config.ensemble_config.response_configuration,
-            name=f"experiment_{case_name}",
-        )
-        ensemble = storage.create_ensemble(
-            experiment.id,
+        ensemble = experiment.create_ensemble(
             name=case_name,
             ensemble_size=self.ert_config.model_config.num_realizations,
         )

src/everest/detached/__init__.py

@@ -93,8 +93,14 @@ def start_server(config: EverestConfig, ert_config: ErtConfig, storage):
             "Failed to save optimization config: {}".format(e)
         )
 
+    experiment = storage.create_experiment(
+        name=f"DetachedEverest@{datetime.now().strftime('%Y-%m-%d@%H:%M:%S')}",
+        parameters=[],
+        responses=[],
+    )
+
     _server = BatchSimulator(ert_config, {}, [])
-    _context = _server.start("dispatch_server", [(0, {})], storage)
+    _context = _server.start("dispatch_server", [(0, {})], experiment)
 
     return _context
 

src/everest/export.py

@@ -162,7 +162,10 @@ def get_internalized_keys(config: EverestConfig, batch_ids: Optional[Set[int]] =
     with open_storage(config.storage_dir, "r") as storage:
         for batch_id in batch_ids:
             case_name = f"batch_{batch_id}"
-            experiment = storage.get_experiment_by_name(f"experiment_{case_name}")
+            experiments = [*storage.experiments]
+            assert len(experiments) == 1
+            experiment = experiments[0]
+
             ensemble = experiment.get_ensemble_by_name(case_name)
             if not internal_keys:
                 internal_keys = set(ensemble.get_summary_keyset())
@@ -313,7 +316,12 @@ def _load_simulation_data(
         # pylint: disable=unnecessary-lambda-assignment
         def load_batch_by_id():
             case_name = f"batch_{batch}"
-            experiment = storage.get_experiment_by_name(f"experiment_{case_name}")
+            experiments = [*storage.experiments]
+
+            # Always assume 1 experiment per simulation/enspath, never multiple
+            assert len(experiments) == 1
+            experiment = experiments[0]
+
             ensemble = experiment.get_ensemble_by_name(case_name)
             return ensemble.load_all_summary_data()
 

src/everest/simulator/simulator.py

@@ -1,5 +1,6 @@
 import time
 from collections import defaultdict
+from datetime import datetime
 from itertools import count
 from typing import Any, DefaultDict, Dict, List, Mapping, Optional, Tuple, Union
 
@@ -35,6 +36,7 @@ def __init__(self, ever_config: EverestConfig, callback=None):
             self._ert_config, controls_def, results_def, callback=callback
         )
 
+        self._experiment_id = None
         self._batch = 0
         self._cache: Optional[_SimulatorCache] = None
         if ever_config.simulator is not None and ever_config.simulator.enable_cache:
@@ -132,7 +134,19 @@ def __call__(
                 case_data.append((real_id, controls))
 
         with open_storage(self._ert_config.ens_path, "w") as storage:
-            sim_context = self.start(f"batch_{self._batch}", case_data, storage)
+            if self._experiment_id is None:
+                experiment = storage.create_experiment(
+                    name=f"EnOpt@{datetime.now().strftime('%Y-%m-%d@%H:%M:%S')}",
+                    parameters=self.ert_config.ensemble_config.parameter_configuration,
+                    responses=self.ert_config.ensemble_config.response_configuration,
+                )
+
+                self._experiment_id = experiment.id
+            else:
+                experiment = storage.get_experiment(self._experiment_id)
+
+            sim_context = self.start(f"batch_{self._batch}", case_data, experiment)
+
             while sim_context.running():
                 time.sleep(0.2)
             results = sim_context.results()

tests/ert/unit_tests/simulator/test_batch_sim.py

@@ -142,8 +142,14 @@ def batch_simulator(batch_sim_example):
 def test_that_starting_with_invalid_key_raises_key_error(
     batch_simulator, _input, match, storage
 ):
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=batch_simulator.ert_config.ensemble_config.parameter_configuration,
+        responses=batch_simulator.ert_config.ensemble_config.response_configuration,
+    )
+
     with pytest.raises(KeyError, match=match):
-        batch_simulator.start("case", _input, storage)
+        batch_simulator.start("case", _input, experiment)
 
 
 @pytest.mark.integration_test
@@ -166,7 +172,13 @@ def test_batch_simulation(batch_simulator, storage):
         ),
     ]
 
-    ctx = batch_simulator.start("case", case_data, storage=storage)
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=batch_simulator.ert_config.ensemble_config.parameter_configuration,
+        responses=batch_simulator.ert_config.ensemble_config.response_configuration,
+    )
+
+    ctx = batch_simulator.start("case", case_data, experiment)
     assert len(case_data) == len(ctx.mask)
 
     # Asking for results before it is complete.
@@ -280,8 +292,15 @@ def test_that_batch_simulator_handles_invalid_suffixes_at_start(
         },
         ["ORDER"],
     )
+
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=batch_sim_example.ensemble_config.parameter_configuration,
+        responses=batch_sim_example.ensemble_config.response_configuration,
+    )
+
     with pytest.raises(KeyError, match=match):
-        rsim.start("case", inp, storage)
+        rsim.start("case", inp, experiment)
 
 
 @pytest.mark.integration_test
@@ -328,7 +347,13 @@ def test_batch_simulation_suffixes(batch_sim_example, storage):
         ),
     ]
 
-    ctx = rsim.start("case", case_data, storage=storage)
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=ert_config.ensemble_config.parameter_configuration,
+        responses=ert_config.ensemble_config.response_configuration,
+    )
+
+    ctx = rsim.start("case", case_data, experiment)
     assert len(case_data) == len(ctx)
     _wait_for_completion(ctx)
 
@@ -395,8 +420,14 @@ def test_stop_sim(copy_case, storage):
         ),
     ]
 
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=ert_config.ensemble_config.parameter_configuration,
+        responses=ert_config.ensemble_config.response_configuration,
+    )
+
     # Starting a simulation which should actually run through.
-    ctx = rsim.start(case_name, case_data, storage=storage)
+    ctx = rsim.start(case_name, case_data, experiment)
 
     ctx.stop()
     status = ctx.status
@@ -459,7 +490,13 @@ def test_batch_ctx_status_failing_jobs(setup_case, storage):
         for idx in range(10)
     ]
 
-    batch_ctx = rsim.start("case_name", ensembles, storage=storage)
+    experiment = storage.create_experiment(
+        name="EnOptCase",
+        parameters=ert_config.ensemble_config.parameter_configuration,
+        responses=ert_config.ensemble_config.response_configuration,
+    )
+
+    batch_ctx = rsim.start("case_name", ensembles, experiment)
     while batch_ctx.running():
         assertContextStatusOddFailures(batch_ctx)
         time.sleep(1)

tests/everest/test_everest_output.py

@@ -9,6 +9,7 @@
 from ert.storage import open_storage
 from everest.config import EverestConfig
 from everest.detached import generate_everserver_ert_config, start_server
+from everest.simulator.everest_to_ert import everest_to_ert_config
 from everest.strings import (
     DEFAULT_OUTPUT_DIR,
     DETACHED_NODE_DIR,
@@ -19,6 +20,27 @@
 from tests.everest.utils import relpath, tmpdir
 
 
+@tmpdir(relpath("..", "..", "test-data", "everest", "math_func"))
+def test_that_one_experiment_creates_one_ensemble_per_batch():
+    config = EverestConfig.load_file("config_minimal.yml")
+    workflow = _EverestWorkflow(config)
+    assert workflow is not None
+
+    workflow.start_optimization()
+
+    batches = os.listdir(config.simulation_dir)
+    ert_config = ErtConfig.with_plugins().from_dict(everest_to_ert_config(config))
+    enspath = ert_config.ens_path
+
+    with open_storage(enspath, mode="r") as storage:
+        experiments = [*storage.experiments]
+        assert len(experiments) == 1
+        experiment = experiments[0]
+
+        ensemble_names = {ens.name for ens in experiment.ensembles}
+        assert ensemble_names == set(batches)
+
+
 @pytest.mark.integration_test
 @patch("ert.simulator.BatchSimulator.start", return_value=None)
 @tmpdir(relpath("test_data", "mocked_test_case"))