Predictions: Add models and folds to output Results

biolab · Feb 25, 2022 · cadc612 · cadc612
1 parent 4631d8c
commit cadc612
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Showing 2 changed files with 6 additions and 1 deletion.
diff --git a/Orange/widgets/evaluate/owpredictions.py b/Orange/widgets/evaluate/owpredictions.py
@@ -570,7 +570,8 @@ def _commit_evaluation_results(self):
         nanmask = numpy.isnan(self.data.get_column_view(self.class_var)[0])
         data = self.data[~nanmask]
         results = Results(data, store_data=True)
-        results.folds = None
+        results.folds = [...]
+        results.models = numpy.array([[p.predictor for p in self.predictors]])
         results.row_indices = numpy.arange(len(data))
         results.actual = data.Y.ravel()
         results.predicted = numpy.vstack(

diff --git a/Orange/widgets/evaluate/tests/test_owpredictions.py b/Orange/widgets/evaluate/tests/test_owpredictions.py
@@ -10,6 +10,7 @@
 
 from Orange.base import Model
 from Orange.classification import LogisticRegressionLearner
+from Orange.classification.majority import ConstantModel
 from Orange.data.io import TabReader
 from Orange.regression import LinearRegressionLearner
 from Orange.widgets.tests.base import WidgetTest
@@ -505,6 +506,9 @@ def test_multi_inputs(self):
         def check_evres(expected):
             out = self.get_output(w.Outputs.evaluation_results)
             self.assertSequenceEqual(out.learner_names, expected)
+            self.assertEqual(out.folds, [...])
+            self.assertEqual(out.models.shape, (1, len(out.learner_names)))
+            self.assertIsInstance(out.models[0, 0], ConstantModel)
 
         check_evres(["P1", "P2", "P3"])