From 0cefc175f4e7facac38eba0bfd6b4c6ef1a29ddd Mon Sep 17 00:00:00 2001
From: janezd <janez.demsar@fri.uni-lj.si>
Date: Fri, 25 Feb 2022 08:35:31 +0100
Subject: [PATCH] Calibration plot: Fix crash for Results without folds

---
 Orange/widgets/evaluate/owcalibrationplot.py    |  2 +-
 .../evaluate/tests/test_owcalibrationplot.py    | 17 +++++++++++++++++
 2 files changed, 18 insertions(+), 1 deletion(-)

diff --git a/Orange/widgets/evaluate/owcalibrationplot.py b/Orange/widgets/evaluate/owcalibrationplot.py
index 72c2822d8c1..853c7ae3c42 100644
--- a/Orange/widgets/evaluate/owcalibrationplot.py
+++ b/Orange/widgets/evaluate/owcalibrationplot.py
@@ -487,7 +487,7 @@ def commit(self):
         if results is not None:
             problems = [
                 msg for condition, msg in (
-                    (len(results.folds) > 1,
+                    (results.folds is not None and len(results.folds) > 1,
                      "each training data sample produces a different model"),
                     (results.models is None,
                      "test results do not contain stored models - try testing "
diff --git a/Orange/widgets/evaluate/tests/test_owcalibrationplot.py b/Orange/widgets/evaluate/tests/test_owcalibrationplot.py
index 87f1fdc9e17..bfcb9cd9198 100644
--- a/Orange/widgets/evaluate/tests/test_owcalibrationplot.py
+++ b/Orange/widgets/evaluate/tests/test_owcalibrationplot.py
@@ -1,5 +1,6 @@
 import copy
 import warnings
+import unittest
 from unittest.mock import Mock, patch
 
 import numpy as np
@@ -637,3 +638,19 @@ def test_warn_nan_probabilities(self, *_):
         self.assertTrue(widget.Warning.omitted_nan_prob_points.is_shown())
         self._set_list_selection(widget.controls.selected_classifiers, [0, 2])
         self.assertFalse(widget.Warning.omitted_folds.is_shown())
+
+    @patch("Orange.widgets.evaluate.owcalibrationplot.ThresholdClassifier")
+    @patch("Orange.widgets.evaluate.owcalibrationplot.CalibratedLearner")
+    def test_no_folds(self, *_):
+        """Warn about omitted points with nan probabiities"""
+        widget = self.widget
+
+        self.results.folds = None
+        self.send_signal(widget.Inputs.evaluation_results, self.results)
+        widget.selected_classifiers = [0]
+        widget.commit.now()
+        self.assertIsNotNone(self.get_output(widget.Outputs.calibrated_model))
+
+
+if __name__ == "__main__":
+    unittest.main()