OWDistributions: support for Dask Tables

Orange/widgets/visualize/owdistributions.py

@@ -2,6 +2,7 @@
 from itertools import count, groupby, repeat
 from xml.sax.saxutils import escape
 
+import dask
 import numpy as np
 from scipy.stats import norm, rayleigh, beta, gamma, pareto, expon
 
@@ -13,6 +14,7 @@
 import pyqtgraph as pg
 
 from Orange.data import Table, DiscreteVariable, ContinuousVariable, Domain
+from Orange.data.dask import DaskTable
 from Orange.preprocess.discretize import decimal_binnings, time_binnings, \
     short_time_units
 from Orange.statistics import distribution, contingency
@@ -29,6 +31,7 @@
     LegendItem as SPGLegendItem
 
 
+
 class ScatterPlotItem(pg.ScatterPlotItem):
     Symbols = pg.graphicsItems.ScatterPlotItem.Symbols
 
@@ -444,6 +447,7 @@ def set_data(self, data):
             self.var = varmodel[min(len(domain.class_vars), len(varmodel) - 1)]
         if domain is not None and domain.has_discrete_class:
             self.cvar = domain.class_var
+
         self.reset_select()
         self._user_var_bins.clear()
         self.openContext(domain)
@@ -539,12 +543,17 @@ def set_valid_data(self):
             return
 
         column = self.data.get_column(self.var)
+        if isinstance(self.data, DaskTable):
+            column = dask.compute(column)[0]
+
         valid_mask = np.isfinite(column)
         if not np.any(valid_mask):
             self.Error.no_defined_values_var(self.var.name)
             return
         if self.cvar:
             ccolumn = self.data.get_column(self.cvar)
+            if isinstance(self.data, DaskTable):
+                ccolumn = dask.compute(ccolumn)[0]
             valid_mask *= np.isfinite(ccolumn)
             if not np.any(valid_mask):
                 self.Error.no_defined_values_pair(self.var.name, self.cvar.name)
@@ -882,6 +891,9 @@ def recompute_binnings(self):
         if self.is_valid and self.var.is_continuous:
             # binning is computed on valid var data, ignoring any cvar nans
             column = self.data.get_column(self.var)
+            if isinstance(self.data, DaskTable):
+                column = dask.compute(column)[0]
+
             if np.any(np.isfinite(column)):
                 if self.var.is_time:
                     self.binnings = time_binnings(column, min_unique=5)

Orange/widgets/visualize/tests/test_owdistributions.py

@@ -11,6 +11,7 @@
 from orangewidget.utils.combobox import qcombobox_emit_activated
 
 from Orange.data import Table, Domain, DiscreteVariable
+from Orange.tests.test_dasktable import temp_dasktable
 from Orange.widgets.tests.base import WidgetTest
 from Orange.widgets.utils.annotated_data import ANNOTATED_DATA_FEATURE_NAME
 from Orange.widgets.utils.itemmodels import DomainModel
@@ -21,6 +22,7 @@ class TestOWDistributions(WidgetTest):
     def setUp(self):
         self.widget = self.create_widget(OWDistributions)  #: OWDistributions
         self.iris = Table("iris")
+        self.heart_disease = Table("heart_disease")
 
     def _set_cvar(self, cvar):
         combo = self.widget.controls.cvar
@@ -526,7 +528,7 @@ def test_report(self):
         widget.send_report()
 
     def test_sort_by_freq_no_split(self):
-        data = Table("heart_disease")
+        data = self.heart_disease
         domain = data.domain
         sort_by_freq = self.widget.controls.sort_by_freq
 
@@ -549,7 +551,7 @@ def test_sort_by_freq_no_split(self):
         self.assertEqual(out[1][1], 97)
 
     def test_sort_by_freq_split(self):
-        data = Table("heart_disease")
+        data = self.heart_disease
         domain = data.domain
         sort_by_freq = self.widget.controls.sort_by_freq
 
@@ -576,5 +578,13 @@ def test_sort_by_freq_split(self):
         self.assertEqual(out[4][2], 45)
 
 
+class TestOWDistributionsWithDask(TestOWDistributions):
+
+    def setUp(self):
+        self.widget = self.create_widget(OWDistributions)
+        self.iris = temp_dasktable("iris")
+        self.heart_disease = temp_dasktable("heart_disease")
+
+
 if __name__ == "__main__":
     unittest.main()