OWBoxPlot: Fix crash when continuous attributes appear only in metas

Author: VesnaT

Orange/data/domain.py

@@ -283,25 +283,35 @@ def index(self, var):
         except KeyError:
             raise ValueError("'%s' is not in domain" % var)
 
-    def has_discrete_attributes(self, include_class=False):
+    def has_discrete_attributes(self, include_class=False, include_metas=False):
         """
-        Return `True` if domain has any discrete attributes. If `include_class`
-                is set, the check includes the class attribute(s).
+        Return `True` if domain has any discrete attributes. If
+        `include_class` is set, the check includes the class attribute(s). If
+        `include_metas` is set, the check includes the meta attributes.
         """
         if not include_class:
-            return any(var.is_discrete for var in self.attributes)
+            attributes = list(self.attributes) if not include_metas \
+                else list(self.attributes) + list(self.metas)
+            return any(var.is_discrete for var in attributes)
         else:
-            return any(var.is_discrete for var in self.variables)
+            variables = list(self.variables) if not include_metas \
+                else list(self.variables) + list(self.metas)
+            return any(var.is_discrete for var in variables)
 
-    def has_continuous_attributes(self, include_class=False):
+    def has_continuous_attributes(self, include_class=False, include_metas=False):
         """
         Return `True` if domain has any continuous attributes. If
-        `include_class` is set, the check includes the class attribute(s).
+        `include_class` is set, the check includes the class attribute(s). If
+        `include_metas` is set, the check includes the meta attributes.
         """
         if not include_class:
-            return any(var.is_continuous for var in self.attributes)
+            attributes = list(self.attributes) if not include_metas \
+                else list(self.attributes) + list(self.metas)
+            return any(var.is_continuous for var in attributes)
         else:
-            return any(var.is_continuous for var in self.variables)
+            variables = list(self.variables) if not include_metas \
+                else list(self.variables) + list(self.metas)
+            return any(var.is_continuous for var in variables)
 
     @property
     def has_continuous_class(self):

Orange/tests/test_domain.py

@@ -310,6 +310,15 @@ def test_has_discrete(self):
         self.assertTrue(Domain([race], age).has_discrete_attributes(True))
         self.assertTrue(Domain([], [race, age]).has_discrete_attributes(True))
 
+        d = Domain([], None, [gender])
+        self.assertTrue(d.has_discrete_attributes(False, True))
+        d = Domain([], None, [age])
+        self.assertFalse(d.has_discrete_attributes(False, True))
+        d = Domain([], [age], [gender])
+        self.assertTrue(d.has_discrete_attributes(True, True))
+        d = Domain([], [incomeA], [age])
+        self.assertFalse(d.has_discrete_attributes(True, True))
+
     def test_has_continuous(self):
         self.assertFalse(Domain([]).has_continuous_attributes())
         self.assertFalse(Domain([], [age]).has_continuous_attributes())
@@ -328,6 +337,15 @@ def test_has_continuous(self):
         self.assertTrue(Domain([race], age).has_continuous_attributes(True))
         self.assertTrue(Domain([], [race, age]).has_continuous_attributes(True))
 
+        d = Domain([], None, [age])
+        self.assertTrue(d.has_continuous_attributes(False, True))
+        d = Domain([], None, [gender])
+        self.assertFalse(d.has_continuous_attributes(False, True))
+        d = Domain([], [gender], [age])
+        self.assertTrue(d.has_continuous_attributes(True, True))
+        d = Domain([], [race], [gender])
+        self.assertFalse(d.has_continuous_attributes(True, True))
+
     def test_get_conversion(self):
         compute_value = lambda: 42
         new_income = income.copy(compute_value=compute_value)

Orange/widgets/visualize/owboxplot.py

@@ -289,7 +289,7 @@ def compute_score(attr):
                 return 3
             if attr.is_continuous:
                 # One-way ANOVA
-                col = data.get_column_view(attr)[0]
+                col = data.get_column_view(attr)[0].astype(float)
                 groups = (col[group_col == i] for i in range(n_groups))
                 groups = (col[~np.isnan(col)] for col in groups)
                 groups = [group for group in groups if len(group)]
@@ -320,9 +320,9 @@ def compute_score(attr):
         group_var = self.group_var
         if self.order_by_importance and group_var is not None:
             n_groups = len(group_var.values)
-            group_col = data.get_column_view(group_var)[0] \
-                if domain.has_continuous_attributes(include_class=True) \
-                else None
+            group_col = data.get_column_view(group_var)[0] if \
+                domain.has_continuous_attributes(
+                    include_class=True, include_metas=True) else None
             self.attrs.sort(key=compute_score)
         else:
             self.attrs[:] = chain(

Orange/widgets/visualize/tests/test_owboxplot.py

@@ -3,7 +3,7 @@
 
 import numpy as np
 
-from Orange.data import Table, ContinuousVariable
+from Orange.data import Table, ContinuousVariable, StringVariable, Domain
 from Orange.widgets.visualize.owboxplot import OWBoxPlot, FilterGraphicsRectItem
 from Orange.widgets.tests.base import WidgetTest, WidgetOutputsTestMixin
 
@@ -113,3 +113,11 @@ def _select_data(self):
         return [100, 103, 104, 108, 110, 111, 112, 115, 116,
                 120, 123, 124, 126, 128, 132, 133, 136, 137,
                 139, 140, 141, 143, 144, 145, 146, 147, 148]
+
+    def test_continuous_metas(self):
+        domain = self.iris.domain
+        metas = domain.attributes[:-1] + (StringVariable("str"),)
+        domain = Domain([], domain.class_var, metas)
+        data = Table.from_table(domain, self.iris)
+        self.send_signal("Data", data)
+        self.widget.controls.order_by_importance.setChecked(True)