owpaintdata: Adjust color model to input dataset

Fix a IndexError when the input dataset's class variable has more then
17 values.

Author: ales-erjavec

Orange/widgets/data/owpaintdata.py

@@ -794,6 +794,7 @@ def __init__(self):
 
         self.input_data = None
         self.input_classes = []
+        self.input_colors = None
         self.input_has_attr2 = True
         self.current_tool = None
         self._selected_indices = None
@@ -1016,9 +1017,12 @@ def _check_and_set_data(data):
             if data.domain.class_vars:
                 self.Warning.continuous_target()
             self.input_classes = ["C1"]
+            self.input_colors = None
             y = np.zeros(len(data))
         else:
             self.input_classes = y.values
+            self.input_colors = y.colors
+
             y = data[:, y].Y
 
         self.input_has_attr2 = len(data.domain.attributes) >= 2
@@ -1036,7 +1040,16 @@ def reset_to_input(self):
         self.undo_stack.clear()
 
         index = self.selected_class_label()
+        if self.input_colors is not None:
+            colors = self.input_colors
+        else:
+            colors = colorpalette.DefaultRGBColors
+        palette = colorpalette.ColorPaletteGenerator(
+            number_of_colors=len(colors), rgb_colors=colors)
+        self.colors = palette
+        self.class_model.colors = palette
         self.class_model[:] = self.input_classes
+
         newindex = min(max(index, 0), len(self.class_model) - 1)
         itemmodels.select_row(self.classValuesView, newindex)
 

Orange/widgets/data/tests/test_owpaintdata.py

@@ -4,7 +4,7 @@
 import numpy as np
 from AnyQt.QtCore import QRectF, QPointF
 
-from Orange.data import Table
+from Orange.data import Table, DiscreteVariable, ContinuousVariable, Domain
 from Orange.widgets.data import owpaintdata
 from Orange.widgets.data.owpaintdata import OWPaintData
 from Orange.widgets.tests.base import WidgetTest
@@ -43,3 +43,12 @@ def test_output_shares_internal_buffer(self):
         np.testing.assert_equal(output1.Y, output1_copy.Y)
 
         self.assertTrue(np.any(output1.X != output2.X))
+
+    def test_20_values_class(self):
+        domain = Domain(
+            [ContinuousVariable("A"),
+             ContinuousVariable("B")],
+            DiscreteVariable("C", values=[chr(ord("a") + i) for i in range(20)])
+        )
+        data = Table(domain, [[0.1, 0.2, "a"], [0.4, 0.7, "t"]])
+        self.send_signal("Data", data)