fix(metrics): name the wrapper mock correctly and document NaN r2 with one valid pair (SIENTIAPDE-2215)

model_manager/utils/repository/data_manager_repository.py

@@ -358,7 +358,7 @@ class DataManagerRepository(SientiaMonitoring):
         behavior, assuming that predictions (y_pred/y_train_pred) are already on the
         correct scale for metric calculation (any scaling is handled inside the
         model wrapper). Pairs with a NaN target or a NaN prediction are left out of
-        mse/mae/r2.
+        mse/mae/r2. With a single valid pair left, r2_val is NaN (R² needs 2 samples).
 
         Args:
             tmr: Training result containing:

tests/utils/repository/test_data_manager_repository.py

@@ -343,10 +343,10 @@ def test_compute_regression_metrics_all_nan_pairs_raises():
         val_data=pd.DataFrame({'t': [1.0, 2.0]}, index=idx),
         y_pred=pd.DataFrame({'p': [np.nan, np.nan]}, index=idx),
     )
-    metadata = MagicMock()
+    wrapper = MagicMock()
 
     with pytest.raises(ValueError, match='No validation rows with both target and prediction'):
-        repo.compute_regression_metrics(tmr, metadata)
+        repo.compute_regression_metrics(tmr, wrapper)
 
 
 def test_compute_regression_metrics_linear_equation():