[FIX] Linear regression: Fix Elastic net; Fix Auto-apply buttons

Orange/widgets/regression/owlinearregression.py

@@ -29,7 +29,7 @@ class OWLinearRegression(OWBaseLearner):
     ridge = settings.Setting(False)
     reg_type = settings.Setting(OLS)
     alpha_index = settings.Setting(0)
-    l1_ratio = settings.Setting(0.5)
+    l2_ratio = settings.Setting(0.5)
     autosend = settings.Setting(True)
 
     want_main_area = False
@@ -65,55 +65,44 @@ def add_main_layout(self):
         gui.widgetLabel(box4, "Elastic net mixing:")
         box5 = gui.hBox(box4)
         gui.widgetLabel(box5, "L1")
-        self.l1_ratio_slider = gui.hSlider(
-            box5, self, "l1_ratio", minValue=0.01, maxValue=0.99,
+        self.l2_ratio_slider = gui.hSlider(
+            box5, self, "l2_ratio", minValue=0.01, maxValue=0.99,
             intOnly=False, ticks=0.1, createLabel=False, width=120,
-            step=0.01, callback=self._l1_ratio_changed)
+            step=0.01, callback=self._l2_ratio_changed)
         gui.widgetLabel(box5, "L2")
-        self.l1_ratio_label = gui.widgetLabel(
+        self.l2_ratio_label = gui.widgetLabel(
             box4, "",
             sizePolicy=(QSizePolicy.MinimumExpanding, QSizePolicy.Fixed))
-        self.l1_ratio_label.setAlignment(Qt.AlignCenter)
+        self.l2_ratio_label.setAlignment(Qt.AlignCenter)
 
-    def add_bottom_buttons(self):
         box5 = gui.hBox(self.controlArea)
         box5.layout().setAlignment(Qt.AlignCenter)
-        self._set_l1_ratio_label()
-
-        auto_commit = gui.auto_commit(
-                self.controlArea, self, "autosend", "Apply")
-        auto_commit.layout().insertWidget(0, self.report_button)
-        auto_commit.layout().insertSpacing(1, 20)
-        self.report_button.setMinimumWidth(150)
-
+        self._set_l2_ratio_label()
         self.layout().setSizeConstraint(QLayout.SetFixedSize)
         self.alpha_slider.setEnabled(self.reg_type != self.OLS)
-        self.l1_ratio_slider.setEnabled(self.reg_type == self.Elastic)
+        self.l2_ratio_slider.setEnabled(self.reg_type == self.Elastic)
 
     def handleNewSignals(self):
-        self.commit()
+        self.apply()
 
     def _reg_type_changed(self):
         self.alpha_slider.setEnabled(self.reg_type != self.OLS)
-        self.l1_ratio_slider.setEnabled(self.reg_type == self.Elastic)
-        self.commit()
+        self.l2_ratio_slider.setEnabled(self.reg_type == self.Elastic)
+        self.apply()
 
     def _set_alpha_label(self):
         self.alpha_label.setText("Alpha: {}".format(self.alphas[self.alpha_index]))
 
     def _alpha_changed(self):
         self._set_alpha_label()
-        self.commit()
-
-    def _set_l1_ratio_label(self):
-        self.l1_ratio_label.setText(
-            "{:.{}f} : {:.{}f}".format(self.l1_ratio, 2, 1 - self.l1_ratio, 2))
+        self.apply()
 
-    def _l1_ratio_changed(self):
-        self._set_l1_ratio_label()
-        self.commit()
+    def _set_l2_ratio_label(self):
+        self.l2_ratio_label.setText(
+            "{:.{}f} : {:.{}f}".format(1 - self.l2_ratio, 2, self.l2_ratio, 2))
 
-    def commit(self):
+    def _l2_ratio_changed(self):
+        self._set_l2_ratio_label()
         self.apply()
 
     def create_learner(self):
@@ -128,7 +117,7 @@ def create_learner(self):
             learner = LassoRegressionLearner(alpha=alpha, **args)
         elif self.reg_type == OWLinearRegression.Elastic:
             learner = ElasticNetLearner(alpha=alpha,
-                                        l1_ratio=self.l1_ratio, **args)
+                                        l1_ratio=1 - self.l2_ratio, **args)
         return learner
 
     def update_model(self):
@@ -157,8 +146,8 @@ def get_learner_parameters(self):
             regularization = ("Elastic Net Regression with α={}"
                               " and L1:L2 ratio of {}:{}"
                               .format(self.alphas[self.alpha_index],
-                                      self.l1_ratio,
-                                      1 - self.l1_ratio))
+                                      self.l2_ratio,
+                                      1 - self.l2_ratio))
         return ("Regularization", regularization),
 
 

Orange/widgets/regression/tests/test_owlinearregression.py

@@ -0,0 +1,9 @@
+from Orange.widgets.regression.owlinearregression import OWLinearRegression
+from Orange.widgets.tests.base import WidgetTest, WidgetLearnerTestMixin
+
+
+class TestOWLinearRegression(WidgetTest, WidgetLearnerTestMixin):
+    def setUp(self):
+        self.widget = self.create_widget(OWLinearRegression,
+                                         stored_settings={"auto_apply": False})
+        self.init()

Orange/widgets/tests/base.py

@@ -331,6 +331,9 @@ def init(self):
             self.model_class = ModelRegression
         self.parameters = []
 
+    def test_has_unconditional_apply(self):
+        self.assertTrue(hasattr(self.widget, "unconditional_apply"))
+
     def test_input_data(self):
         """Check widget's data with data on the input"""
         self.assertEqual(self.widget.data, None)