owtestlearners: Add tests

Author: ales-erjavec

Orange/widgets/evaluate/tests/test_owtestlearners.py

@@ -0,0 +1,62 @@
+# pylint: disable=missing-docstring
+import numpy as np
+
+import unittest
+
+from Orange.data import Table
+from Orange.classification import MajorityLearner
+from Orange.regression import MeanLearner
+
+from Orange.evaluation import Results, TestOnTestData
+from Orange.widgets.tests.base import WidgetTest
+from Orange.widgets.evaluate.owtestlearners import OWTestLearners
+from Orange.widgets.evaluate import owtestlearners
+
+
+class TestOWTestLearners(WidgetTest):
+    def setUp(self):
+        super().setUp()
+        self.widget = self.create_widget(OWTestLearners)  # type: OWTestLearners
+
+    def test_basic(self):
+        data = Table("iris")[::3]
+        self.send_signal("Data", data)
+        self.send_signal("Learner", MajorityLearner(), 0)
+        res = self.get_output("Evaluation Results")
+        self.assertIsInstance(res, Results)
+        self.assertIsNotNone(res.domain)
+        self.assertIsNotNone(res.data)
+        self.assertIsNotNone(res.probabilities)
+
+        self.send_signal("Learner", None, 0)
+
+        data = Table("housing")[::10]
+        self.send_signal("Data", data)
+        self.send_signal("Learner", MeanLearner(), 0)
+        res = self.get_output("Evaluation Results")
+        self.assertIsInstance(res, Results)
+        self.assertIsNotNone(res.domain)
+        self.assertIsNotNone(res.data)
+
+
+class TestHelpers(unittest.TestCase):
+    def test_results_one_vs_rest(self):
+        data = Table("lenses")
+        learners = [MajorityLearner()]
+        res = TestOnTestData(data[1::2], data[::2], learners=learners)
+        r1 = owtestlearners.results_one_vs_rest(res, pos_index=0)
+        r2 = owtestlearners.results_one_vs_rest(res, pos_index=1)
+        r3 = owtestlearners.results_one_vs_rest(res, pos_index=2)
+
+        np.testing.assert_almost_equal(np.sum(r1.probabilities, axis=2), 1.0)
+        np.testing.assert_almost_equal(np.sum(r2.probabilities, axis=2), 1.0)
+        np.testing.assert_almost_equal(np.sum(r3.probabilities, axis=2), 1.0)
+
+        np.testing.assert_almost_equal(
+            r1.probabilities[:, :, 1] +
+            r2.probabilities[:, :, 1] +
+            r3.probabilities[:, :, 1],
+            1.0
+        )
+
+