OWSieve: Fix crash for attribute with no values

Orange/widgets/visualize/owsieve.py

@@ -29,11 +29,29 @@ class ChiSqStats:
     pair of attributes. The class is also used for ranking.
     """
     def __init__(self, data, attr1, attr2):
-        self.observed = get_contingency(data, attr1, attr2)
-        self.n = np.sum(self.observed)
-        self.probs_x = self.observed.sum(axis=0) / self.n
-        self.probs_y = self.observed.sum(axis=1) / self.n
-        self.expected = np.outer(self.probs_y, self.probs_x) * self.n
+        attr1 = data.domain[attr1]
+        attr2 = data.domain[attr2]
+        if attr1.is_discrete and not attr1.values or \
+                attr2.is_discrete and not attr2.values:
+            self.observed, self.n = np.nan, len(data)
+            self.probs_x, self.probs_y = [], []
+            if attr1.values:
+                observed_x = np.unique(data.get_column_view(
+                    data.domain.index(attr1))[0], return_counts=True)[1]
+                self.probs_x = observed_x / self.n
+                self.observed = observed_x
+            elif attr2.values:
+                observed_y = np.unique(data.get_column_view(
+                    data.domain.index(attr2))[0], return_counts=True)[1]
+                self.probs_y = observed_y / self.n
+                self.observed = observed_y
+            self.expected = self.observed
+        else:
+            self.observed = get_contingency(data, attr1, attr2)
+            self.n = np.sum(self.observed)
+            self.probs_x = self.observed.sum(axis=0) / self.n
+            self.probs_y = self.observed.sum(axis=1) / self.n
+            self.expected = np.outer(self.probs_y, self.probs_x) * self.n
         self.residuals = \
             (self.observed - self.expected) / np.sqrt(self.expected)
         self.chisqs = self.residuals ** 2
@@ -447,6 +465,20 @@ def _oper(attr, txt):
             max_xlabel_h = max(int(xl.boundingRect().height()), max_xlabel_h)
             curr_x += width
 
+        if not disc_x.values and disc_y.values:
+            curr_y = y_off
+            for y in range(len(chi.probs_y) - 1, -1, -1):
+                py = chi.probs_y[y]
+                if py == 0:
+                    continue
+                text(disc_y.values[y], x_off, curr_y + square_size * py / 2,
+                     Qt.AlignRight | Qt.AlignVCenter)
+                curr_y += square_size * py
+
+        if not disc_x.values or not disc_y.values:
+            text("No data", square_size / 2 + x_off + 30,
+                 square_size / 2 + y_off, Qt.AlignRight | Qt.AlignVCenter)
+
         bottom = y_off + square_size + max_xlabel_h
         text(attr_y.name, 0, y_off + square_size / 2,
              Qt.AlignLeft | Qt.AlignVCenter, bold=True, vertical=True)

Orange/widgets/visualize/tests/test_owsieve.py

@@ -1,8 +1,11 @@
 # Test methods with long descriptive names can omit docstrings
 # pylint: disable=missing-docstring
+import numpy as np
+
 from AnyQt.QtCore import QEvent, QPoint, Qt
 from AnyQt.QtGui import QMouseEvent
 
+from Orange.data import DiscreteVariable, Domain, Table
 from Orange.widgets.tests.base import WidgetTest, WidgetOutputsTestMixin
 from Orange.widgets.visualize.owsieve import OWSieveDiagram
 
@@ -26,3 +29,11 @@ def _select_data(self):
             QEvent.MouseButtonPress, QPoint(), Qt.LeftButton,
             Qt.LeftButton, Qt.KeyboardModifiers()))
         return [0, 4, 6, 7, 11, 17, 19, 21, 22, 24, 26, 39, 40, 43, 44, 46]
+
+    def test_missing_values(self):
+        """Check widget for dataset with missing values"""
+        attrs = [DiscreteVariable("c1", ["a", "b", "c"])]
+        class_var = DiscreteVariable("cls", [])
+        X = np.array([1, 2, 0, 1, 0, 2])[:, None]
+        data = Table(Domain(attrs, class_var), X, np.array([np.nan] * 6))
+        self.send_signal("Data", data)