finish tests on init

MESMER-group · Oct 3, 2024 · fb8d7c9 · fb8d7c9
1 parent 55d71d3
commit fb8d7c9
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Showing 2 changed files with 93 additions and 10 deletions.
diff --git a/mesmer/mesmer_x/train_l_distrib_mesmerx.py b/mesmer/mesmer_x/train_l_distrib_mesmerx.py
@@ -544,21 +544,19 @@ def __init__(
         elif isinstance(options_solver, dict):
             default_options_solver.update(options_solver)
         else:
-            raise ValueError("options_solver must be a dictionary")
+            raise ValueError("`options_solver` must be a dictionary")
         self.xtol_req = default_options_solver["xtol_req"]
         self.ftol_req = default_options_solver["ftol_req"]
         self.maxiter = default_options_solver["maxiter"]
         self.maxfev = default_options_solver["maxfev"]
         self.method_fit = default_options_solver["method_fit"]
-        if self.method_fit in [
-            "dogleg",
-            "trust-ncg",
-            "trust-krylov",
-            "trust-exact",
-            "COBYLA",
-            "SLSQP",
-            "CG",
-            "Newton-CG",
+        if self.method_fit not in [
+            "BFGS",
+            "L-BFGS-B",
+            "Nelder-Mead",
+            "Powell",
+            "TNC",
+            "trust-constr",
         ]:
             raise ValueError("method for this fit not prepared, to avoid")
         else:

diff --git a/tests/unit/test_mesmer_x_distrib_cov.py b/tests/unit/test_mesmer_x_distrib_cov.py
@@ -147,3 +147,88 @@ def test_distrib_cov_init_errors():
             {"tas": np.array([1, 2, np.inf]), "tas2": np.array([1, 2, np.nan])},
             expression,
         )
+
+    with pytest.raises(ValueError, match="Only one of "):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            data_targ_addtest=np.array([1, 2, 3]),
+        )
+
+    with pytest.raises(ValueError, match="Only one of "):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            data_preds_addtest={"tas": np.array([1, 2, 3])},
+        )
+
+    with pytest.raises(ValueError, match="`threshold_min_proba` must be in"):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            threshold_min_proba=-1,
+        )
+    with pytest.raises(ValueError, match="`threshold_min_proba` must be in"):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            threshold_min_proba=2,
+        )
+
+    with pytest.raises(
+        ValueError, match="The provided first guess does not have the correct shape:"
+    ):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            first_guess=np.array([1, 2, 3]),
+        )
+
+    with pytest.raises(ValueError, match="`options_solver` must be a dictionary"):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            options_solver="this is not a dictionary",
+        )
+
+    with pytest.raises(ValueError, match="`options_optim` must be a dictionary"):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            options_optim="this is not a dictionary",
+        )
+
+    with pytest.raises(ValueError, match="method for this fit not prepared, to avoid"):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            options_solver={"method_fit": "this is not a method"},
+        )
+
+    with pytest.raises(
+        ValueError, match="Lack of consistency on the options 'type_fun_optim'"
+    ):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            options_optim={"type_fun_optim": "NLL", "threshold_stopping_rule": 0.1},
+        )
+
+    with pytest.raises(
+        ValueError, match="Lack of consistency on the options 'type_fun_optim'"
+    ):
+        distrib_cov(
+            np.array([1, 2, 3]),
+            {"tas": np.array([1, 2, 3])},
+            expression,
+            options_optim={"type_fun_optim": "fcNLL", "threshold_stopping_rule": None},
+        )