DataSampler: Fix Bootstrap signature

Orange/widgets/data/owdatasampler.py

@@ -385,7 +385,14 @@ def __init__(self, size=0, random_state=None):
         self.size = size
         self.random_state = random_state
 
-    def __call__(self):
+    def __call__(self, table=None):
+        """Bootstrap indices
+
+        Args:
+            table: Not used (but part of the signature)
+        Returns:
+            tuple (out_of_sample, sample) indices
+        """
         rgen = np.random.RandomState(self.random_state)
         sample = rgen.randint(0, self.size, self.size)
         sample.sort()  # not needed for the code below, just for the user

Orange/widgets/data/tests/test_owdatasampler.py

@@ -12,7 +12,7 @@ def setUpClass(cls):
         cls.iris = Table("iris")
 
     def setUp(self):
-        self.widget = self.create_widget(OWDataSampler)
+        self.widget = self.create_widget(OWDataSampler)  # type: OWDataSampler
 
     def test_error_message(self):
         """ Check if error message appears and then disappears when
@@ -33,3 +33,23 @@ def test_stratified_on_unbalanced_data(self):
         self.widget.controls.stratify.setChecked(True)
         self.send_signal("Data", unbalanced_data)
         self.assertTrue(self.widget.Warning.could_not_stratify.is_shown())
+
+    def test_bootstrap(self):
+        self.select_sampling_type(self.widget.Bootstrap)
+
+        self.send_signal("Data", self.iris)
+
+        in_input = set(self.iris.ids)
+        in_sample = set(self.get_output("Data Sample").ids)
+        in_remaining = set(self.get_output("Remaining Data").ids)
+
+        self.assertEqual(len(in_sample | in_remaining), len(in_input))
+        self.assertEqual(len(in_sample & in_remaining), 0)
+        self.assertGreater(len(in_sample), 0)
+        # The following assert has a really high probability of being true:
+        # 1-(1/150*2/150*...*145/150) ~= 1-2e-64
+        self.assertGreater(len(in_remaining), 0)
+
+    def select_sampling_type(self, sampling_type):
+        buttons = self.widget.controls.sampling_type.group.buttons()
+        buttons[sampling_type].click()