Use context for expected failures

tests/insights/test_shap.py

@@ -1,6 +1,7 @@
 """Tests for insights subpackage."""
 
 import inspect
+from contextlib import nullcontext
 from unittest import mock
 
 import numpy as np
@@ -80,26 +81,35 @@ def test_non_shap_signature(explainer_name):
 
 def _test_shap_insight(campaign, explainer_cls, use_comp_rep, is_shap):
     """Helper function for general SHAP explainer tests."""
-    try:
+    context = nullcontext()
+    if (
+        (not use_comp_rep)
+        and (explainer_cls != "KernelExplainer")
+        and any(not p.is_numerical for p in campaign.parameters)
+    ):
+        # We expect a validation error in case an explanation with an unsupported
+        # explainer type is attempted on a search space representation with
+        # non-numerical entries
+        context = pytest.raises(IncompatibleExplainerError)
+
+    with context:
         shap_insight = SHAPInsight.from_campaign(
             campaign,
             explainer_cls=explainer_cls,
             use_comp_rep=use_comp_rep,
         )
-    except IncompatibleExplainerError:
-        pytest.skip("Unsupported model/explainer combination.")
-
-    # Sanity check explainer
-    assert isinstance(shap_insight, insights.SHAPInsight)
-    assert isinstance(shap_insight.explainer, _get_explainer_cls(explainer_cls))
-    assert shap_insight.uses_shap_explainer == is_shap
 
-    # Sanity check explanation
-    df = campaign.measurements[[p.name for p in campaign.parameters]]
-    if use_comp_rep:
-        df = campaign.searchspace.transform(df)
-    shap_explanation = shap_insight.explain(df)
-    assert isinstance(shap_explanation, shap.Explanation)
+        # Sanity check explainer
+        assert isinstance(shap_insight, insights.SHAPInsight)
+        assert isinstance(shap_insight.explainer, _get_explainer_cls(explainer_cls))
+        assert shap_insight.uses_shap_explainer == is_shap
+
+        # Sanity check explanation
+        df = campaign.measurements[[p.name for p in campaign.parameters]]
+        if use_comp_rep:
+            df = campaign.searchspace.transform(df)
+        shap_explanation = shap_insight.explain(df)
+        assert isinstance(shap_explanation, shap.Explanation)
 
 
 @mark.slow