Merge pull request #4067 from VesnaT/owcorrelations_cont_target

[ENH] Correlations: Include continuous class and meta variables

Orange/widgets/data/owcorrelations.py

@@ -262,8 +262,8 @@ class Warning(OWWidget.Warning):
 
     def __init__(self):
         super().__init__()
-        self.data = None
-        self.cont_data = None
+        self.data = None  # type: Table
+        self.cont_data = None  # type: Table
 
         # GUI
         box = gui.vBox(self.mainArea)
@@ -347,9 +347,9 @@ def set_data(self, data):
                 self.Warning.not_enough_inst()
             else:
                 domain = data.domain
-                cont_attrs = [a for a in domain.attributes if a.is_continuous]
-                cont_dom = Domain(cont_attrs, domain.class_vars, domain.metas)
-                cont_data = Table.from_table(cont_dom, data)
+                cont_vars = [a for a in domain.class_vars + domain.metas +
+                             domain.attributes if a.is_continuous]
+                cont_data = Table.from_table(Domain(cont_vars), data)
                 remover = Remove(Remove.RemoveConstant)
                 cont_data = remover(cont_data)
                 if remover.attr_results["removed"]:
@@ -365,7 +365,11 @@ def set_data(self, data):
 
     def set_feature_model(self):
         self.feature_model.set_domain(self.cont_data and self.cont_data.domain)
-        self.feature = None
+        data = self.data
+        if self.cont_data and data.domain.has_continuous_class:
+            self.feature = self.cont_data.domain[data.domain.class_var.name]
+        else:
+            self.feature = None
 
     def apply(self):
         self.vizrank.initialize()

Orange/widgets/data/tests/test_owcorrelations.py

@@ -28,6 +28,7 @@ def setUpClass(cls):
         cls.data_cont = Table("iris")
         cls.data_disc = Table("zoo")
         cls.data_mixed = Table("heart_disease")
+        cls.housing = Table("housing")
 
     def setUp(self):
         self.widget = self.create_widget(OWCorrelations)
@@ -86,7 +87,7 @@ def test_input_data_one_instance(self):
         self.assertFalse(self.widget.Warning.not_enough_inst.is_shown())
 
     def test_input_data_with_constant_features(self):
-        """Check correlation table for dataset with a constant columns"""
+        """Check correlation table for dataset with constant columns"""
         np.random.seed(0)
         # pylint: disable=no-member
         X = np.random.randint(3, size=(4, 3)).astype(float)
@@ -118,6 +119,20 @@ def test_input_data_with_constant_features(self):
         self.send_signal(self.widget.Inputs.data, None)
         self.assertFalse(self.widget.Information.removed_cons_feat.is_shown())
 
+    def test_input_data_cont_target(self):
+        """Check correlation table for dataset with continuous class variable"""
+        data = self.housing[:5, 11:]
+        self.send_signal(self.widget.Inputs.data, data)
+        time.sleep(0.1)
+        self.process_events()
+        self.assertEqual(self.widget.vizrank.rank_model.rowCount(), 2)
+        self.assertEqual(self.widget.controls.feature.count(), 4)
+        self.assertEqual(self.widget.controls.feature.currentText(), "MEDV")
+
+        data = self.housing[:5, 13:]
+        self.send_signal(self.widget.Inputs.data, data)
+        self.assertTrue(self.widget.Warning.not_enough_vars.is_shown())
+
     def test_output_data(self):
         """Check dataset on output"""
         self.send_signal(self.widget.Inputs.data, self.data_cont)
@@ -230,8 +245,8 @@ def test_feature_combo(self):
         self.assertEqual(len(feature_combo.model()), len(cont_attributes) + 1)
 
         self.wait_until_stop_blocking()
-        self.send_signal(self.widget.Inputs.data, Table("housing"))
-        self.assertEqual(len(feature_combo.model()), 14)
+        self.send_signal(self.widget.Inputs.data, self.housing)
+        self.assertEqual(len(feature_combo.model()), 15)
 
     def test_select_feature(self):
         """Test feature selection"""