OWPythagorasTree: Add test for determinism, update tests to use models

Author: pavlin-policar

Orange/widgets/visualize/tests/test_owpythagorastree.py

@@ -2,9 +2,10 @@
 import math
 import unittest
 
-from Orange.classification import TreeLearner as TreeClassificationLearner
+from os import path
+
 from Orange.data import Table
-from Orange.regression import TreeLearner as TreeRegressionLearner
+from Orange.modelling import TreeLearner
 from Orange.widgets.tests.base import WidgetTest, WidgetOutputsTestMixin
 from Orange.widgets.visualize.owpythagorastree import OWPythagorasTree
 from Orange.widgets.visualize.pythagorastreeviewer import (
@@ -93,7 +94,7 @@ def setUpClass(cls):
         WidgetOutputsTestMixin.init(cls)
 
         # Set up for output tests
-        tree = TreeClassificationLearner()
+        tree = TreeLearner()
         cls.model = tree(cls.data)
         cls.model.instances = cls.data
 
@@ -102,11 +103,11 @@ def setUpClass(cls):
 
         # Set up for widget tests
         titanic_data = Table('titanic')[::50]
-        cls.titanic = TreeClassificationLearner(max_depth=1)(titanic_data)
+        cls.titanic = TreeLearner(max_depth=1)(titanic_data)
         cls.titanic.instances = titanic_data
 
         housing_data = Table('housing')[:10]
-        cls.housing = TreeRegressionLearner(max_depth=1)(housing_data)
+        cls.housing = TreeLearner(max_depth=1)(housing_data)
         cls.housing.instances = housing_data
 
     def setUp(self):
@@ -283,3 +284,46 @@ def test_label_on_tree_connect_and_disconnect(self):
         self.assertNotRegex(
             self.widget.info.text(), regex,
             'Initial info should not contain node or depth info')
+
+    def test_tree_determinism(self):
+        """Check that the tree is drawn identically upon receiving the same
+        dataset with no parameter changes."""
+        n_tries = 10
+
+        def _check_all_same(data):
+            """Check that all the elements within an iterable are identical."""
+            iterator = iter(data)
+            try:
+                first = next(iterator)
+            except StopIteration:
+                return True
+            return all(first == rest for rest in iterator)
+
+        # Make sure the tree are deterministic for iris
+        scene_nodes = []
+        for i in range(n_tries):
+            self.send_signal(self.signal_name, self.signal_data)
+            scene_nodes.append([n.pos() for n in self.get_visible_squares()])
+        for node_row in zip(*scene_nodes):
+            self.assertTrue(
+                _check_all_same(node_row),
+                "The tree was not drawn identically in the %d times it was "
+                "sent to widget after receiving the iris dataset." % n_tries
+            )
+
+        # Make sure trees are deterministic with data where some variables have
+        # the same entropy
+        data_same_entropy = Table(path.join(
+            path.dirname(__file__), "../../tests/datasets/same_entropy.tab"))
+        data_same_entropy = TreeLearner()(data_same_entropy)
+        scene_nodes = []
+        for i in range(n_tries):
+            self.send_signal(self.signal_name, data_same_entropy)
+            scene_nodes.append([n.pos() for n in self.get_visible_squares()])
+        for node_row in zip(*scene_nodes):
+            self.assertTrue(
+                _check_all_same(node_row),
+                "The tree was not drawn identically in the %d times it was "
+                "sent to widget after receiving a dataset with variables with "
+                "same entropy." % n_tries
+            )