Commitin

tests/ert/ui_tests/cli/test_field_parameter.py

@@ -8,7 +8,12 @@
 import resfo
 import xtgeo
 
+from ert.analysis import (
+    smoother_update,
+)
 from ert.config import ErtConfig
+from ert.config.analysis_config import UpdateSettings
+from ert.config.analysis_module import ESSettings
 from ert.mode_definitions import ENSEMBLE_SMOOTHER_MODE
 from ert.storage import open_storage
 
@@ -210,3 +215,61 @@ def test_parameter_update_with_inactive_cells_xtgeo_grdecl(tmpdir):
             assert "nan" not in Path(
                 "simulations/realization-0/iter-1/my_param.grdecl"
             ).read_text(encoding="utf-8")
+
+
+def test_field_param_update_using_heat_equation_and_zero_var_params(
+    heat_equation_storage,
+):
+    config = ErtConfig.from_file("config.ert")
+    with open_storage(config.ens_path, mode="w") as storage:
+        experiment = storage.get_experiment_by_name("es-mda")
+        prior = experiment.get_ensemble_by_name("default_0")
+        # posterior = experiment.get_ensemble_by_name("default_1")
+        cond = prior.load_parameters("COND")
+
+        new_experiment = storage.create_experiment(name="exp-zero-var")
+        new_prior = storage.create_ensemble(
+            new_experiment,
+            ensemble_size=prior.ensemble_size,
+            iteration=0,
+            name="prior-zero-var",
+        )
+        # TODO: Set half of the parameters in cond to a constant value.
+        new_prior.save_parameters("COND", range(prior.ensemble_size), cond)
+
+        new_posterior = storage.create_ensemble(
+            new_prior.experiment_id,
+            ensemble_size=config.model_config.num_realizations,
+            iteration=1,
+            name="new_ensemble",
+            prior_ensemble=new_prior,
+        )
+
+        smoother_update(
+            new_prior,
+            new_posterior,
+            experiment.observation_keys,
+            config.ensemble_config.parameters,
+            UpdateSettings(),
+            ESSettings(),
+        )
+
+        # param_config = config.ensemble_config.parameter_configs["COND"]
+        # assert len(prior_result.x) == param_config.nx
+        # assert len(prior_result.y) == param_config.ny
+        # assert len(prior_result.z) == param_config.nz
+
+        # posterior_result = posterior.load_parameters("COND")["values"]
+        # prior_covariance = np.cov(
+        #     prior_result.values.reshape(
+        #         prior.ensemble_size, param_config.nx * param_config.ny * param_config.nz
+        #     )
+        # )
+        # posterior_covariance = np.cov(
+        #     posterior_result.values.reshape(
+        #         posterior.ensemble_size,
+        #         param_config.nx * param_config.ny * param_config.nz,
+        #     )
+        # )
+        # # Check that generalized variance is reduced by update step.
+        # assert np.trace(prior_covariance) > np.trace(posterior_covariance)