Chore/replace xfails

tests/decisiontree/test_estimators.py

@@ -30,16 +30,12 @@ def test_growth_params_(self):
         )
 
     def test_fit(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.fit(None, None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("DecisionTreeTemplate.fit expectedly refused call")
 
     def test_predict(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.predict(None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("DecisionTreeTemplate.predict expectedly refused call")
 
     def test_select_samples_and_features_no_sampling(self):
         self.model.frac_features = 1.0

tests/decisiontree/test_node.py

@@ -64,7 +64,7 @@ def test_Node(int_val, float_val, node_val, str_val, bool_val):
         if is_okay:
             raise ex
         else:
-            pytest.xfail("SplitScore validation failed as expected")
+            pass  # SplitScore validation failed as expected
     else:
         for att in [
             "array_column",

tests/decisiontree/test_split.py

@@ -77,7 +77,7 @@ def test_BestSplit(score, column, threshold, target_groups, default_is_left):
         if is_okay:
             raise ex
         else:
-            pytest.xfail("BestSplit validation failed as expected")
+            pass  # BestSplit validation failed as expected
     else:
         if is_bad:
             pytest.fail(
@@ -472,7 +472,7 @@ def test_1d(
             )
         except ValueError as ex:
             if is_homogenous:
-                pytest.xfail("Splitting a homogneous y failed as expected")
+                pass  # Splitting a homogneous y failed as expected
             else:
                 raise ex
         else:
@@ -524,7 +524,7 @@ def test_1d_missing(
             )
         except ValueError as ex:
             if is_homogenous:
-                pytest.xfail("Splitting a homogneous y failed as expected")
+                pass  # Splitting a homogneous y failed as expected
             else:
                 raise ex
         else:
@@ -576,7 +576,7 @@ def test_2d(
             )
         except ValueError as ex:
             if is_homogenous:
-                pytest.xfail("Splitting a homogneous y failed as expected")
+                pass  # Splitting a homogneous y failed as expected
             else:
                 raise ex
         else:
@@ -629,7 +629,7 @@ def test_2d_missing(
             )
         except ValueError as ex:
             if is_homogenous:
-                pytest.xfail("Splitting a homogneous y failed as expected")
+                pass  # Splitting a homogneous y failed as expected
             else:
                 raise ex
         else:

tests/decisiontree/test_split_objects.py

@@ -26,7 +26,7 @@ def test_SplitScore(name, value):
         if is_okay:
             raise ValueError(f"whoops {name=} {value=} failed with {ex}")
         else:
-            pytest.xfail("SplitScore validation failed as expected")
+            pass  # SplitScore validation failed as expected
     else:
         if is_bad:
             pytest.fail(

tests/test_extratrees.py

@@ -15,16 +15,12 @@ def test_tree_(self):
         assert not hasattr(self.model, "trees_")
 
     def test_fit(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.fit(None, None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("ExtraTreesTemplate.fit expectedly refused call")
 
     def test_predict(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.predict(None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("ExtraTreesTemplate.predict expectedly refused call")
 
 
 class TestExtraTreesRegressor:

tests/test_gradientboostedtrees.py

@@ -14,16 +14,12 @@ def test_tree_(self):
         assert not hasattr(self.model, "trees_")
 
     def test_fit(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.fit(None, None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("DecisionTreeTemplate.fit expectedly refused call")
 
     def test_predict(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.predict(None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("DecisionTreeTemplate.predict expectedly refused call")
 
 
 class TestGradientBoostedTreesRegressor:
@@ -112,7 +108,7 @@ def test_bool_to_float(x, exp, is_bad: bool):
         res = gbt.bool_to_float(x)
     except ValueError as ex:
         if is_bad:
-            pytest.xfail("Failed expectedly to convert non-bool values")
+            pass  # Failed expectedly to convert non-bool values
     else:
         if is_bad:
             pytest.fail(f"Passed unexpectedly for non-bool value {x} returning {res}")

tests/test_randomforest.py

@@ -14,16 +14,12 @@ def test_tree_(self):
         assert not hasattr(self.model, "trees_")
 
     def test_fit(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.fit(None, None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("RandomForestTemplate.fit expectedly refused call")
 
     def test_predict(self):
-        try:
+        with pytest.raises(NotImplementedError):
             self.model.predict(None)  # type: ignore
-        except NotImplementedError as ex:
-            pytest.xfail("RandomForestTemplate.predict expectedly refused call")
 
 
 class TestRandomForestRegressor:

tests/test_scoring.py

@@ -24,7 +24,7 @@ def test_check_y_and_target_groups(y, target_groups, is_bad):
         scoring.check_y_and_target_groups(y, target_groups=target_groups)
     except ValueError as ex:
         if is_bad:
-            pytest.xfail("y and target_groups properly failed")
+            pass  # y and target_groups properly failed
         else:
             raise ex
     else:
@@ -51,7 +51,7 @@ def test_calc_variance(y: np.ndarray, target_groups: np.ndarray, variance_exp: f
         variance = scoring.calc_variance(y, target_groups)
     except ValueError as ex:
         if variance_exp is None:
-            pytest.xfail("Properly raised error calculating the variance")
+            pass  # "Properly raised error calculating the variance"
         else:
             raise ex
     else:
@@ -74,7 +74,7 @@ def test_entropy(y: np.ndarray):
         h = scoring.entropy(y)
     except ValueError as ex:
         if len(y) == 0:
-            pytest.xfail("entropy properly failed because of empty y")
+            pass  # entropy properly failed because of empty y
         else:
             raise ex
     else:
@@ -98,7 +98,7 @@ def test_entropy_rs(y: np.ndarray):
         h = rs_entropy(y.tolist())
     except ValueError as ex:
         if len(y) == 0:
-            pytest.xfail("entropy properly failed because of empty y")
+            pass  # entropy properly failed because of empty y
         else:
             raise ex
     else:
@@ -127,7 +127,7 @@ def test_calc_entropy(y: np.ndarray, target_groups: np.ndarray, h_exp: float):
         h = scoring.calc_entropy(y, target_groups)
     except ValueError as ex:
         if h_exp is None:
-            pytest.xfail("Properly raised error calculating the entropy")
+            pass  # Properly raised error calculating the entropy
         else:
             raise ex
     else:
@@ -155,7 +155,7 @@ def test_calc_entropy_rs(y: np.ndarray, target_groups: np.ndarray, h_exp: float)
         h = scoring.calc_entropy_rs(y, target_groups)
     except ValueError as ex:
         if h_exp is None:
-            pytest.xfail("Properly raised error calculating the entropy")
+            pass  # Properly raised error calculating the entropy
         else:
             raise ex
     else:
@@ -178,7 +178,7 @@ def test_gini_impurity(y: np.ndarray):
         g = scoring.gini_impurity(y)
     except ValueError as ex:
         if len(y) == 0:
-            pytest.xfail("gini_impurity properly failed because of empty y")
+            pass  # gini_impurity properly failed because of empty y
         else:
             raise ex
     else:
@@ -202,7 +202,7 @@ def test_gini_impurity_rs(y: np.ndarray):
         g = rs_gini_impurity(y.tolist())
     except ValueError as ex:
         if len(y) == 0:
-            pytest.xfail("gini_impurity properly failed because of empty y")
+            pass  # gini_impurity properly failed because of empty y
         else:
             raise ex
     else:
@@ -245,7 +245,7 @@ def test_calc_gini_impurity(y: np.ndarray, target_groups: np.ndarray, g_exp: flo
         g = scoring.calc_gini_impurity(y, target_groups)
     except ValueError as ex:
         if g_exp is None:
-            pytest.xfail("Properly raised error calculating the gini impurity")
+            pass  # Properly raised error calculating the gini impurity
         else:
             raise ex
     else:
@@ -273,7 +273,7 @@ def test_calc_gini_impurity_rs(y: np.ndarray, target_groups: np.ndarray, g_exp:
         g = scoring.calc_gini_impurity_rs(y, target_groups)
     except ValueError as ex:
         if g_exp is None:
-            pytest.xfail("Properly raised error calculating the gini impurity")
+            pass  # Properly raised error calculating the gini impurity
         else:
             raise ex
     else:
@@ -299,7 +299,7 @@ def test_xgboost_split_score(g: np.ndarray, h: np.ndarray, is_bad: bool):
         score = scoring.xgboost_split_score(g, h, growth_params)
     except ValueError as ex:
         if is_bad:
-            pytest.xfail("xgboost_split_score properly failed because of empty g or h")
+            pass  # xgboost_split_score properly failed because of empty g or h
         else:
             raise ex
     else:
@@ -355,7 +355,7 @@ def test_calc_xgboost_split_score(
         score = scoring.calc_xgboost_split_score(target_groups, g, h, growth_params)
     except ValueError as ex:
         if score_exp is None:
-            pytest.xfail("Properly raised error calculating the xgboost score")
+            pass  # Properly raised error calculating the xgboost score
         else:
             raise ex
     else: