Updated tests and fix Avoid copy.deepcopy (restriction in FEniCS) #90

BAMresearch · Aug 28, 2024 · 18221f9 · 18221f9
1 parent f267172
commit 18221f9
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Showing 5 changed files with 4 additions and 13 deletions.
diff --git a/probeye/inference/solver.py b/probeye/inference/solver.py
@@ -31,7 +31,7 @@ def __init__(
     ):
 
         # attributes from arguments
-        self.problem = problem
+        self.problem = cp.deepcopy(problem)
         self.show_progress = show_progress
         self.seed = seed
 

diff --git a/probeye/subroutines.py b/probeye/subroutines.py
@@ -1345,7 +1345,7 @@ def synchronize_objects(
         if attr_is_valid:
             if hasattr(new_obj, attribute):
                 try:
-                    setattr(new_obj, attribute, getattr(ref_obj, attribute))
+                    setattr(new_obj, attribute, copy(getattr(ref_obj, attribute)))
                 except AttributeError:  # pragma: no cover
                     raise AttributeError(
                         f"can't set attribute '{attribute}'"

diff --git a/tests/unit_tests/inference/bias/test_likelihood_models.py b/tests/unit_tests/inference/bias/test_likelihood_models.py
@@ -21,7 +21,7 @@
 
 
 class TestProblem(unittest.TestCase):
-    def test_embedded_pce_solver(self):
+    def test_embedded_likelihood_models(self):
 
         # define the forward model
         class LinRe(ForwardModelBase):
@@ -93,8 +93,6 @@ def response(self, inp: dict) -> dict:
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False
         )
 
-        problem.forward_models.pop("LinRe")
-        problem.add_forward_model(LinRe("LinRe"), experiments="Tests")
         problem.likelihood_models.pop("Tests")
         dummy_lmodel.gamma = 1.0
         likelihood_model = GlobalMomentMatchingModelError(dummy_lmodel)
@@ -104,8 +102,6 @@ def response(self, inp: dict) -> dict:
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False
         )
 
-        problem.forward_models.pop("LinRe")
-        problem.add_forward_model(LinRe("LinRe"), experiments="Tests")
         problem.likelihood_models.pop("Tests")
         likelihood_model = RelativeGlobalMomentMatchingModelError(dummy_lmodel)
         problem.add_likelihood_model(likelihood_model)
@@ -114,8 +110,6 @@ def response(self, inp: dict) -> dict:
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False
         )
 
-        problem.forward_models.pop("LinRe")
-        problem.add_forward_model(LinRe("LinRe"), experiments="Tests")
         problem.likelihood_models.pop("Tests")
         dummy_lmodel.tolerance = 1e-6
         likelihood_model = GlobalMomentMatchingModelError(dummy_lmodel)

diff --git a/tests/unit_tests/inference/bias/test_solver.py b/tests/unit_tests/inference/bias/test_solver.py
@@ -88,15 +88,11 @@ def response(self, inp: dict) -> dict:
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False
         )
 
-        problem.forward_models.pop("LinRe")
-        problem.add_forward_model(LinRe("LinRe"), experiments="Tests")
         solver_2 = EmbeddedPCESolver(problem, seed=42)
         inference_data_2 = solver_2.run(
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False
         )
 
-        problem.forward_models.pop("LinRe")
-        problem.add_forward_model(LinRe("LinRe"), experiments="Tests")
         solver_1b = EmbeddedPCESolver(problem, seed=123)
         inference_data_1b = solver_1b.run(
             n_walkers=n_walkers, n_steps=n_steps, vectorize=False

diff --git a/tests/unit_tests/inference/dynesty/test_solver.py b/tests/unit_tests/inference/dynesty/test_solver.py
@@ -65,6 +65,7 @@ def __call__(self, inp):
             "dynamic", nlive_init=nlive_init, nlive_batch=nlive_batch, maxbatch=maxbatch
         )
 
+
         dynesty_solver_2 = DynestySolver(problem, seed=42)
         inference_data_2 = dynesty_solver_2.run(
             "dynamic", nlive_init=nlive_init, nlive_batch=nlive_batch, maxbatch=maxbatch