Merge pull request #2678 from janezd/scatterplot-selection-groups

[ENH] Add Groups column to Selected Data in Scatter plot output

Author: jerneju

Orange/widgets/utils/annotated_data.py

@@ -1,4 +1,5 @@
 import re
+from itertools import chain
 
 import numpy as np
 from Orange.data import Domain, DiscreteVariable
@@ -52,6 +53,11 @@ def get_next_name(names, name):
     :param name: str
     :return: str
     """
+    if isinstance(names, Domain):
+        names = [
+            var.name
+            for var in chain(names.attributes, names.class_vars, names.metas)
+        ]
     indexes = get_indices(names, name)
     if name not in names and not indexes:
         return name
@@ -74,6 +80,19 @@ def get_unique_names(names, proposed):
     return proposed
 
 
+def _table_with_annotation_column(data, values, column_data, var_name):
+    var = DiscreteVariable(get_next_name(data.domain, var_name), values)
+    class_vars, metas = data.domain.class_vars, data.domain.metas
+    if not data.domain.class_vars:
+        class_vars += (var, )
+    else:
+        metas += (var, )
+    domain = Domain(data.domain.attributes, class_vars, metas)
+    table = data.transform(domain)
+    table[:, var] = column_data.reshape((len(data), 1))
+    return table
+
+
 def create_annotated_table(data, selected_indices):
     """
     Returns data with concatenated flag column. Flag column represents
@@ -86,30 +105,23 @@ def create_annotated_table(data, selected_indices):
     """
     if data is None:
         return None
-    names = [var.name for var in data.domain.variables + data.domain.metas]
-    name = get_next_name(names, ANNOTATED_DATA_FEATURE_NAME)
-    domain = add_columns(data.domain, metas=[DiscreteVariable(name, ("No", "Yes"))])
     annotated = np.zeros((len(data), 1))
     if selected_indices is not None:
         annotated[selected_indices] = 1
-    table = data.transform(domain)
-    table[:, name] = annotated
-    return table
+    return _table_with_annotation_column(
+        data, ("No", "Yes"), annotated, ANNOTATED_DATA_FEATURE_NAME)
 
 
-def create_groups_table(data, selection):
+def create_groups_table(data, selection,
+                        include_unselected=True,
+                        var_name=ANNOTATED_DATA_FEATURE_NAME):
     if data is None:
         return None
-    names = [var.name for var in data.domain.variables + data.domain.metas]
-    name = get_next_name(names, ANNOTATED_DATA_FEATURE_NAME)
-    metas = data.domain.metas + (
-        DiscreteVariable(
-            name,
-            ["Unselected"] + ["G{}".format(i + 1)
-                              for i in range(np.max(selection))]),
-    )
-    domain = Domain(data.domain.attributes, data.domain.class_vars, metas)
-    table = data.transform(domain)
-    table.metas[:, len(data.domain.metas):] = \
-        selection.reshape(len(data), 1)
-    return table
+    values = ["G{}".format(i + 1) for i in range(np.max(selection))]
+    if include_unselected:
+        values.insert(0, "Unselected")
+    else:
+        mask = np.flatnonzero(selection)
+        data = data[mask]
+        selection = selection[mask] - 1
+    return _table_with_annotation_column(data, values, selection, var_name)

Orange/widgets/visualize/owscatterplot.py

@@ -20,9 +20,8 @@
 from Orange.widgets.visualize.owscatterplotgraph import OWScatterPlotGraph
 from Orange.widgets.visualize.utils import VizRankDialogAttrPair
 from Orange.widgets.widget import OWWidget, AttributeList, Msg, Input, Output
-from Orange.widgets.utils.annotated_data import (create_annotated_table,
-                                                 ANNOTATED_DATA_SIGNAL_NAME,
-                                                 create_groups_table)
+from Orange.widgets.utils.annotated_data import (
+    create_annotated_table, create_groups_table, ANNOTATED_DATA_SIGNAL_NAME)
 
 
 class ScatterPlotVizRank(VizRankDialogAttrPair):
@@ -427,25 +426,26 @@ def selection_changed(self):
         self.commit()
 
     def send_data(self):
-        selected = None
-        selection = None
         # TODO: Implement selection for sql data
+        def _get_selected():
+            if not len(selection):
+                return None
+            return create_groups_table(data, graph.selection, False, "Group")
+
+        def _get_annotated():
+            if graph.selection is not None and np.max(graph.selection) > 1:
+                return create_groups_table(data, graph.selection)
+            else:
+                return create_annotated_table(data, selection)
+
         graph = self.graph
-        if isinstance(self.data, SqlTable):
-            selected = self.data
-        elif self.data is not None:
-            selection = graph.get_selection()
-            if len(selection) > 0:
-                selected = self.data[selection]
-        if graph.selection is not None and np.max(graph.selection) > 1:
-            annotated = create_groups_table(self.data, graph.selection)
-        else:
-            annotated = create_annotated_table(self.data, selection)
-        self.Outputs.selected_data.send(selected)
-        self.Outputs.annotated_data.send(annotated)
+        data = self.data
+        selection = graph.get_selection()
+        self.Outputs.annotated_data.send(_get_annotated())
+        self.Outputs.selected_data.send(_get_selected())
 
         # Store current selection in a setting that is stored in workflow
-        if selection is not None and len(selection):
+        if len(selection):
             self.selection_group = list(zip(selection, graph.selection[selection]))
         else:
             self.selection_group = None

Orange/widgets/visualize/tests/test_owscatterplot.py

@@ -18,13 +18,19 @@ class TestOWScatterPlot(WidgetTest, WidgetOutputsTestMixin):
     def setUpClass(cls):
         super().setUpClass()
         WidgetOutputsTestMixin.init(cls)
+        cls.same_input_output_domain = False
 
         cls.signal_name = "Data"
         cls.signal_data = cls.data
 
     def setUp(self):
         self.widget = self.create_widget(OWScatterPlot)
 
+    def _compare_selected_annotated_domains(self, selected, annotated):
+        # Base class tests that selected.domain is a subset of annotated.domain
+        # In scatter plot, the two domains are unrelated, so we disable the test
+        pass
+
     def test_set_data(self):
         # Connect iris to scatter plot
         self.send_signal(self.widget.Inputs.data, self.data)
@@ -154,6 +160,9 @@ def test_group_selections(self):
         def selectedx():
             return self.get_output(self.widget.Outputs.selected_data).X
 
+        def selected_groups():
+            return self.get_output(self.widget.Outputs.selected_data).metas[:, 0]
+
         def annotated():
             return self.get_output(self.widget.Outputs.annotated_data).metas
 
@@ -163,6 +172,7 @@ def annotations():
         # Select 0:5
         graph.select(points[:5])
         np.testing.assert_equal(selectedx(), x[:5])
+        np.testing.assert_equal(selected_groups(), np.zeros(5))
         sel_column[:5] = 1
         np.testing.assert_equal(annotated(), sel_column)
         self.assertEqual(annotations(), ["No", "Yes"])
@@ -171,6 +181,7 @@ def annotations():
         with self.modifiers(Qt.ShiftModifier):
             graph.select(points[5:10])
         np.testing.assert_equal(selectedx(), x[:10])
+        np.testing.assert_equal(selected_groups(), np.array([0] * 5 + [1] * 5))
         sel_column[5:10] = 2
         np.testing.assert_equal(annotated(), sel_column)
         self.assertEqual(len(annotations()), 3)
@@ -180,12 +191,14 @@ def annotations():
         sel_column = np.zeros((len(self.data), 1))
         sel_column[15:20] = 1
         np.testing.assert_equal(selectedx(), x[15:20])
+        np.testing.assert_equal(selected_groups(), np.zeros(5))
         self.assertEqual(annotations(), ["No", "Yes"])
 
         # Alt-select (remove) 10:17; we have 17:20
         with self.modifiers(Qt.AltModifier):
             graph.select(points[10:17])
         np.testing.assert_equal(selectedx(), x[17:20])
+        np.testing.assert_equal(selected_groups(), np.zeros(3))
         sel_column[15:17] = 0
         np.testing.assert_equal(annotated(), sel_column)
         self.assertEqual(annotations(), ["No", "Yes"])
@@ -194,6 +207,7 @@ def annotations():
         with self.modifiers(Qt.ShiftModifier | Qt.ControlModifier):
             graph.select(points[20:25])
         np.testing.assert_equal(selectedx(), x[17:25])
+        np.testing.assert_equal(selected_groups(), np.zeros(8))
         sel_column[20:25] = 1
         np.testing.assert_equal(annotated(), sel_column)
         self.assertEqual(annotations(), ["No", "Yes"])
@@ -205,6 +219,7 @@ def annotations():
         with self.modifiers(Qt.ShiftModifier | Qt.ControlModifier):
             graph.select(points[35:40])
         sel_column[30:40] = 2
+        np.testing.assert_equal(selected_groups(), np.array([0] * 8 + [1] * 10))
         np.testing.assert_equal(annotated(), sel_column)
         self.assertEqual(len(annotations()), 3)