tutorails and ok/not_ok assignment fixed

Author: TonyKatkov89

hypex/reporters/abstract.py

@@ -104,13 +104,22 @@ def _get_struct_dict(data: dict):
 
     @staticmethod
     def _convert_struct_dict_to_dataset(data: dict) -> Dataset:
+        def _is_truthy(v) -> bool:
+            """Return True iff v represents a truthy pass value.
+
+            Handles the case where transpose().to_records() stringifies booleans
+            (e.g. numpy.bool_(False) → "False"), so a plain bool() check would
+            incorrectly treat the non-empty string "False" as True.
+            """
+            if v is None:
+                return False
+            if isinstance(v, str):
+                return v.lower() == "true"
+            return bool(v)
+
         def rename_passed(data: dict[str, bool]):
             return {
-                c: (
-                    ("NOT OK" if (v is not None and bool(v)) else "OK")
-                    if "pass" in c
-                    else v
-                )
+                c: (("NOT OK" if _is_truthy(v) else "OK") if "pass" in c else v)
                 for c, v in data.items()
             }
 

tests/test_tutorials.py

@@ -81,13 +81,13 @@ def matching_data():
 
 def test_aatest(aa_data):
     mapping = {
-        "aa-casual": AATest(n_iterations=10),
+        "aa-casual": AATest(random_states=[56, 72, 2, 43]),
         "aa-rs": AATest(random_states=[56, 72, 2, 43]),
         "aa-strat": AATest(stratification=True, random_states=[56, 72, 2, 43]),
-        "aa-sample": AATest(n_iterations=10, sample_size=0.3),
-        "aa-cat_target": AATest(n_iterations=10),
-        "aa-equal_var": AATest(n_iterations=10, t_test_equal_var=False),
-        "aa-n": AATest(n_iterations=10, groups_sizes=[0.5, 0.2, 0.3]),
+        "aa-sample": AATest(sample_size=0.3, random_states=[56, 72, 2, 43]),
+        "aa-cat_target": AATest(random_states=[56, 72, 2, 43]),
+        "aa-equal_var": AATest(equal_variance=False, random_states=[56, 72, 2, 43]),
+        "aa-n": AATest(groups_sizes=[0.5, 0.2, 0.3], random_states=[56, 72, 2, 43]),
     }
 
     mapping_resume = {
@@ -122,7 +122,7 @@ def test_aatest(aa_data):
             {
                 "TTest aa test": {0: "OK", 1: "OK"},
                 "KSTest aa test": {0: "OK", 1: "OK"},
-                "TTest best split": {0: "NOT OK", 1: "NOT OK"},
+                "TTest best split": {0: "OK", 1: "OK"},
                 "KSTest best split": {0: "OK", 1: "OK"},
                 "result": {0: "OK", 1: "OK"},
             }
@@ -150,7 +150,7 @@ def test_aatest(aa_data):
         "aa-n": pd.DataFrame(
             {
                 "TTest aa test": {0: "OK", 1: "OK", 2: "OK", 3: "OK"},
-                "KSTest aa test": {0: "OK", 1: "OK", 2: "OK", 3: "OK"},
+                "KSTest aa test": {0: "NOT OK", 1: "NOT OK", 2: "OK", 3: "OK"},
                 "TTest best split": {0: "OK", 1: "OK", 2: "OK", 3: "OK"},
                 "KSTest best split": {0: "OK", 1: "OK", 2: "OK", 3: "OK"},
                 "result": {0: "OK", 1: "OK", 2: "OK", 3: "OK"},