Merge pull request #3444 from VesnaT/fix_radviz

[FIX] Radviz: Enable projection for less than two selected variables

Orange/widgets/visualize/owradviz.py

@@ -275,16 +275,10 @@ class OWRadviz(OWAnchorProjectionWidget):
     graph = SettingProvider(OWRadvizGraph)
 
     class Warning(OWAnchorProjectionWidget.Warning):
-        no_features = widget.Msg("Radviz requires at least two features.")
         invalid_embedding = widget.Msg("No projection for selected features")
         removed_vars = widget.Msg("Categorical variables with more than"
                                   " two values are not shown.")
 
-    class Error(OWAnchorProjectionWidget.Error):
-        no_features = widget.Msg(
-            "At least three numeric or categorical variables are required"
-        )
-
     def __init__(self):
         self.model_selected = VariableListModel(enable_dnd=True)
         self.model_selected.removed.connect(self.__model_selected_changed)
@@ -331,12 +325,6 @@ def __vizrank_set_attrs(self, attrs):
     def __model_selected_changed(self):
         self.selected_vars = [(var.name, vartype(var)) for var
                               in self.model_selected]
-
-        self.Warning.no_features.clear()
-        if len(self.model_selected) < 2:
-            self.Warning.no_features()
-            return
-
         self.init_projection()
         self.setup_plot()
         self.commit()
@@ -347,6 +335,12 @@ def colors_changed(self):
 
     def set_data(self, data):
         super().set_data(data)
+        self._init_vizrank()
+        self.init_projection()
+
+    def use_context(self):
+        self.model_selected.clear()
+        self.model_other.clear()
         if self.data is not None and len(self.selected_vars):
             d, selected = self.data.domain, [v[0] for v in self.selected_vars]
             self.model_selected[:] = [d[name] for name in selected]
@@ -360,9 +354,6 @@ def set_data(self, data):
             self.model_selected[:] = variables[:5]
             self.model_other[:] = variables[5:] + class_var
 
-        self._init_vizrank()
-        self.init_projection()
-
     def _init_vizrank(self):
         is_enabled = self.data is not None and \
             len(self.primitive_variables) > 3 and \
@@ -376,20 +367,13 @@ def _init_vizrank(self):
             self.vizrank.initialize()
 
     def check_data(self):
-        def error(err):
-            err()
-            self.data = None
-
         super().check_data()
         if self.data is not None:
-            if len(self.primitive_variables) < 3:
-                error(self.Error.no_features)
-            else:
-                domain = self.data.domain
-                vars_ = chain(domain.variables, domain.metas)
-                n_vars = sum(v.is_primitive() for v in vars_)
-                if len(self.primitive_variables) < n_vars:
-                    self.Warning.removed_vars()
+            domain = self.data.domain
+            vars_ = chain(domain.variables, domain.metas)
+            n_vars = sum(v.is_primitive() for v in vars_)
+            if len(self.primitive_variables) < n_vars:
+                self.Warning.removed_vars()
 
     def init_attr_values(self):
         super().init_attr_values()
@@ -408,10 +392,6 @@ def _send_components_metas(self):
         return np.vstack((super()._send_components_metas(), ["angle"]))
 
     def clear(self):
-        if self.model_selected:
-            self.model_selected.clear()
-        if self.model_other:
-            self.model_other.clear()
         super().clear()
         self.projector = RadViz()
 

Orange/widgets/visualize/tests/test_owradviz.py

@@ -1,8 +1,9 @@
 # Test methods with long descriptive names can omit docstrings
 # pylint: disable=missing-docstring
+from unittest.mock import Mock
 import numpy as np
 
-from Orange.data import Table, Domain
+from Orange.data import Table
 from Orange.widgets.tests.base import (
     WidgetTest, WidgetOutputsTestMixin,
     AnchorProjectionWidgetTestMixin, datasets
@@ -43,14 +44,7 @@ def check_vizrank(data):
             check_vizrank(ds)
 
     def test_no_features(self):
-        w = self.widget
-        data2 = self.data.transform(Domain(self.data.domain.attributes[:1],
-                                           self.data.domain.class_vars))
-        self.assertFalse(w.Error.no_features.is_shown())
-        self.send_signal(w.Inputs.data, data2)
-        self.assertTrue(w.Error.no_features.is_shown())
-        self.send_signal(w.Inputs.data, None)
-        self.assertFalse(w.Error.no_features.is_shown())
+        self.send_signal(self.widget.Inputs.data, self.data[:, :0])
 
     def test_not_enough_instances(self):
         w = self.widget
@@ -101,3 +95,38 @@ def test_discrete_attributes(self):
         self.assertTrue(self.widget.Warning.removed_vars.is_shown())
         self.send_signal(self.widget.Inputs.data, None)
         self.assertFalse(self.widget.Warning.removed_vars.is_shown())
+
+    def test_saved_selected_vars(self):
+        self.send_signal(self.widget.Inputs.data, self.data)
+
+        self.widget.model_selected[:] = self.data.domain[:1]
+        self.widget.variables_selection.removed.emit()
+        self.send_signal(self.widget.Inputs.data, self.data)
+        self.assertEqual(len(self.widget.model_selected[:]), 1)
+
+        self.widget.model_selected[:] = self.data.domain[:0]
+        self.widget.variables_selection.removed.emit()
+        self.send_signal(self.widget.Inputs.data, self.data)
+        self.assertEqual(len(self.widget.model_selected[:]), 4)
+
+    def test_invalidated_model_selected(self):
+        self.widget.setup_plot = Mock()
+        self.send_signal(self.widget.Inputs.data, self.data)
+        self.widget.setup_plot.assert_called_once()
+
+        self.widget.setup_plot.reset_mock()
+        self.widget.model_selected[:] = self.data.domain[2:]
+        self.widget.variables_selection.removed.emit()
+        self.widget.setup_plot.assert_called_once()
+
+        self.widget.setup_plot.reset_mock()
+        self.send_signal(self.widget.Inputs.data, self.data[:, 2:])
+        self.widget.setup_plot.assert_not_called()
+
+        self.widget.model_selected[:] = self.data.domain[3:]
+        self.widget.variables_selection.removed.emit()
+        self.widget.setup_plot.assert_called_once()
+
+        self.widget.setup_plot.reset_mock()
+        self.send_signal(self.widget.Inputs.data, self.data)
+        self.widget.setup_plot.assert_called_once()

Orange/widgets/visualize/utils/widget.py

@@ -423,6 +423,7 @@ def set_data(self, data):
         if not same_domain:
             self.init_attr_values()
         self.openContext(self.data)
+        self.use_context()
         self.__invalidated = not (
             data_existed and self.data is not None and
             effective_data.X.shape == self.effective_data.X.shape and
@@ -436,6 +437,9 @@ def check_data(self):
         self.valid_data = None
         self.clear_messages()
 
+    def use_context(self):
+        pass
+
     @Inputs.data_subset
     @check_sql_input
     def set_subset_data(self, subset):