Merge branch 'release-3.3.10'

CHANGELOG.md

@@ -6,6 +6,39 @@ Change Log
 * ...
 
 
+[3.3.10] - 2017-01-18
+--------------------
+##### Enhancements
+* Input/output signal replacement declarations ([#1810](../../pull/1810))
+
+##### Bugfixes
+* MDS Widget: Handle NaN values for plot point styling ([#1931](../../pull/1931))
+* OWPCA: Fix crash for dataset with no rows or no attributes ([#1915](../../pull/1915))
+* OWMosaic: Discretize metas as well ([#1912](../../pull/1912))
+* owfeaturecontructor: Fix an IndexError accessing exception's args ([#1905](../../pull/1905))
+* owrank: Remove `super()` call from `migrate_settings` ([#1902](../../pull/1902))
+* OWBoxPlot: Fix ordering of boxes ([#1900](../../pull/1900))
+* canvas/readwrite: Fix byte literal serialization ([#1898](../../pull/1898))
+* owpca: Handle the case of 0 total variance in the PCA solution ([#1897](../../pull/1897))
+* Copy data attributes for annotated data set ([#1895](../../pull/1895))
+* colorpalette: Fix AttributeError ([#1889](../../pull/1889))
+* OWDistributions: Reset combos when data is removed ([#1887](../../pull/1887))
+* Concatenate bugfix ([#1886](../../pull/1886))
+* OWPredictions: Fix crash when opening report ([#1884](../../pull/1884))
+* owsilhouetteplot: Fix TypeError when cluster column is an object array ([#1876](../../pull/1876))
+* OWSave: Safer Check if Writer Support Sparse ([#1864](../../pull/1864))
+* OWImageViewer: Fix selection with missing values ([#1861](../../pull/1861))
+* owselectcolumns: Fix auto commit on any change ([#1859](../../pull/1859))
+* Table.transpose: Keep metas array two dimensional when no attributes in domain ([#1855](../../pull/1855))
+* Select Rows filter enum ([#1854](../../pull/1854))
+* Scatter plot: don't crash on report without data ([#1840](../../pull/1840))
+* Crash on ctrl-c/cmd-c in widgets without graphs ([#1827](../../pull/1827))
+* Fix crash in listview if labels are changed before calling __setitem__ ([#1825](../../pull/1825))
+* Scatterplot: Allow labelling by string attributes ([#1812](../../pull/1812))
+* Fix copy to clipboard in "Data Table" widget ([#1808](../../pull/1808))
+* TreeGraph: Compatibility with old schemas ([#1804](../../pull/1804))
+
+
 [3.3.9] - 2016-12-02
 --------------------
 ##### Enhancements
@@ -314,7 +347,8 @@ Change Log
 * Initial version based on Python 1.5.2 and Qt 2.3
 
 
-[next]: https://github.com/biolab/orange3/compare/3.3.9...HEAD
+[next]: https://github.com/biolab/orange3/compare/3.3.10...HEAD
+[3.3.10]: https://github.com/biolab/orange3/compare/3.3.9...3.3.10
 [3.3.9]: https://github.com/biolab/orange3/compare/3.3.8...3.3.9
 [3.3.8]: https://github.com/biolab/orange3/compare/3.3.7...3.3.8
 [3.3.7]: https://github.com/biolab/orange3/compare/3.3.6...3.3.7

Orange/data/util.py

@@ -18,11 +18,15 @@ def one_hot(values, dtype=float):
     result
         2d array with ones in respective indicator columns.
     """
+    if not len(values):
+       return np.zeros((0, 0), dtype=dtype)
     return np.eye(int(np.max(values) + 1), dtype=dtype)[np.asanyarray(values, dtype=int)]
 
 
 def scale(values, min=0, max=1):
     """Return values scaled to [min, max]"""
+    if not len(values):
+        return np.array([])
     minval = np.float_(bn.nanmin(values))
     ptp = bn.nanmax(values) - minval
     if ptp == 0:

Orange/tests/test_data_util.py

@@ -11,13 +11,15 @@ def test_scale(self):
         np.testing.assert_equal(scale([0, 1, 2], -1, 1), [-1, 0, 1])
         np.testing.assert_equal(scale([3, 3, 3]), [1, 1, 1])
         np.testing.assert_equal(scale([.1, .5, np.nan]), [0, 1, np.nan])
+        np.testing.assert_equal(scale(np.array([])), np.array([]))
 
     def test_one_hot(self):
         np.testing.assert_equal(
             one_hot([0, 1, 2, 1], int), [[1, 0, 0],
                                          [0, 1, 0],
                                          [0, 0, 1],
                                          [0, 1, 0]])
+        np.testing.assert_equal(one_hot([], int), np.zeros((0, 0), dtype=int))
 
 
 class DummyPlus(SharedComputeValue):

Orange/widgets/data/owcontinuize.py

@@ -120,12 +120,12 @@ def constructContinuizer(self):
 
     def commit(self):
         continuizer = self.constructContinuizer()
-        if self.data is not None:
+        if self.data is not None and len(self.data):
             domain = continuizer(self.data)
             data = Table.from_table(domain, self.data)
             self.send("Data", data)
         else:
-            self.send("Data", None)
+            self.send("Data", self.data)  # None or empty data
 
     def send_report(self):
         self.report_items(

Orange/widgets/data/owdatasampler.py

@@ -50,6 +50,7 @@ class Error(OWWidget.Error):
         too_many_folds = Msg("Number of folds exceeds data size")
         sample_larger_than_data = Msg("Sample must be smaller than data")
         not_enough_to_stratify = Msg("Data is too small to stratify")
+        no_data = Msg("Data set is empty")
 
     def __init__(self):
         super().__init__()
@@ -228,7 +229,9 @@ def updateindices(self):
             if self.data.domain.has_discrete_class else 0
 
         size = None
-        if self.sampling_type == self.FixedSize:
+        if not data_length:
+            self.Error.no_data()
+        elif self.sampling_type == self.FixedSize:
             size = self.sampleSizeNumber
             repl = self.replacement
         elif self.sampling_type == self.FixedProportion:

Orange/widgets/data/owdiscretize.py

@@ -309,6 +309,9 @@ def _update_points(self):
         """
         Update the induced cut points.
         """
+        if self.data is None or not len(self.data):
+            return
+
         def induce_cuts(method, data, var):
             dvar = _dispatch[type(method)](method, data, var)
             if dvar is None:
@@ -327,7 +330,6 @@ def induce_cuts(method, data, var):
                 points, dvar = induce_cuts(state.method, self.data, var)
                 new_state = state._replace(points=points, disc_var=dvar)
                 self._set_var_state(i, new_state)
-        self.commit()
 
     def _method_index(self, method):
         return METHODS.index((type(method), ))
@@ -389,6 +391,7 @@ def _default_disc_changed(self):
             if isinstance(self.var_state[i].method, Default):
                 self._set_var_state(i, state)
         self._update_points()
+        self.commit()
 
     def _disc_method_changed(self):
         self._update_spin_positions()
@@ -398,6 +401,7 @@ def _disc_method_changed(self):
         for idx in indices:
             self._set_var_state(idx, state)
         self._update_points()
+        self.commit()
 
     def _var_selection_changed(self, *args):
         indices = self.selected_indices()
@@ -461,7 +465,7 @@ def disc_var(source):
 
     def commit(self):
         output = None
-        if self.data is not None:
+        if self.data is not None and len(self.data):
             domain = self.discretized_domain()
             output = self.data.from_table(domain, self.data)
         self.send("Data", output)

Orange/widgets/data/owimpute.py

@@ -240,6 +240,11 @@ def commit(self):
         data = self.data
 
         if self.data is not None:
+            if not len(self.data):
+                self.send("Data", self.data)
+                self.modified = False
+                return
+
             drop_mask = np.zeros(len(self.data), bool)
 
             attributes = []

Orange/widgets/data/owpaintdata.py

@@ -990,15 +990,15 @@ def set_data(self, data):
         """Set the input_data and call reset_to_input"""
         def _check_and_set_data(data):
             self.clear_messages()
-            if data is not None:
+            if data is not None and len(data):
                 if not data.domain.attributes:
                     self.Warning.no_input_variables()
                     data = None
                 elif len(data.domain.attributes) > 2:
                     self.Information.use_first_two()
             self.input_data = data
             self.btResetToInput.setDisabled(data is None)
-            return data is not None
+            return data is not None and len(data)
 
         if not _check_and_set_data(data):
             return

Orange/widgets/data/tests/test_owcontinuize.py

@@ -0,0 +1,35 @@
+# Test methods with long descriptive names can omit docstrings
+# pylint: disable=missing-docstring
+import numpy as np
+
+from Orange.data import Table
+from Orange.widgets.data.owcontinuize import OWContinuize
+from Orange.widgets.tests.base import WidgetTest
+
+
+class TestOWContinuize(WidgetTest):
+    def setUp(self):
+        self.widget = self.create_widget(OWContinuize)
+
+    def test_empty_data(self):
+        """No crash on empty data"""
+        data = Table("iris")
+        widget = self.widget
+        widget.multinomial_treatment = 1
+
+        self.send_signal("Data", data)
+        widget.unconditional_commit()
+        imp_data = self.get_output("Data")
+        np.testing.assert_equal(imp_data.X, data.X)
+        np.testing.assert_equal(imp_data.Y, data.Y)
+
+        widget.continuous_treatment = 1
+        self.send_signal("Data", Table(data.domain))
+        widget.unconditional_commit()
+        imp_data = self.get_output("Data")
+        self.assertEqual(len(imp_data), 0)
+
+        self.send_signal("Data", None)
+        widget.unconditional_commit()
+        imp_data = self.get_output("Data")
+        self.assertIsNone(imp_data)

Orange/widgets/data/tests/test_owdatasampler.py

@@ -24,3 +24,5 @@ def test_error_message(self):
         self.assertTrue(self.widget.Error.too_many_folds.is_shown())
         self.send_signal("Data", None)
         self.assertFalse(self.widget.Error.too_many_folds.is_shown())
+        self.send_signal("Data", Table(self.iris.domain))
+        self.assertTrue(self.widget.Error.no_data.is_shown())

Orange/widgets/data/tests/test_owdiscretize.py

@@ -0,0 +1,18 @@
+# Test methods with long descriptive names can omit docstrings
+# pylint: disable=missing-docstring
+from Orange.data import Table
+from Orange.widgets.data.owdiscretize import OWDiscretize
+from Orange.widgets.tests.base import WidgetTest
+
+
+class TestOWDiscretize(WidgetTest):
+    def setUp(self):
+        self.widget = self.create_widget(OWDiscretize)
+
+    def test_empty_data(self):
+        """No crash on empty data"""
+        data = Table("iris")
+        widget = self.widget
+        widget.default_method = 3
+        self.send_signal("Data", Table(data.domain))
+        widget.unconditional_commit()

Orange/widgets/data/tests/test_owimpute.py

@@ -0,0 +1,30 @@
+# Test methods with long descriptive names can omit docstrings
+# pylint: disable=missing-docstring
+import numpy as np
+
+from Orange.data import Table
+from Orange.widgets.data.owimpute import OWImpute
+from Orange.widgets.tests.base import WidgetTest
+
+
+class TestOWImpute(WidgetTest):
+    def setUp(self):
+        self.widget = self.create_widget(OWImpute)
+
+    def test_empty_data(self):
+        """No crash on empty data"""
+        data = Table("iris")
+        widget = self.widget
+        widget.default_method_index = widget.MODEL_BASED_IMPUTER
+        widget.default_method = widget.METHODS[widget.default_method_index]
+
+        self.send_signal("Data", data)
+        widget.unconditional_commit()
+        imp_data = self.get_output("Data")
+        np.testing.assert_equal(imp_data.X, data.X)
+        np.testing.assert_equal(imp_data.Y, data.Y)
+
+        self.send_signal("Data", Table(data.domain))
+        widget.unconditional_commit()
+        imp_data = self.get_output("Data")
+        self.assertEqual(len(imp_data), 0)

Orange/widgets/data/tests/test_owpaintdata.py

@@ -0,0 +1,16 @@
+# Test methods with long descriptive names can omit docstrings
+# pylint: disable=missing-docstring
+from Orange.data import Table
+from Orange.widgets.data.owpaintdata import OWPaintData
+from Orange.widgets.tests.base import WidgetTest
+
+
+class TestOWPaintData(WidgetTest):
+    def setUp(self):
+        self.widget = self.create_widget(OWPaintData)
+
+    def test_empty_data(self):
+        """No crash on empty data"""
+        data = Table("iris")
+        self.send_signal("Data", data)
+        self.send_signal("Data", Table(data.domain))

Orange/widgets/evaluate/owpredictions.py

@@ -202,6 +202,12 @@ def set_predictor(self, predictor=None, id=None):
 
     def handleNewSignals(self):
         self.clear_messages()
+        if self.data is not None and not len(self.data):
+            # The logic of this widget is complicated, so let us just pretend
+            # that we have not data. (Even issuing an error message here doesn't
+            # work since the next signal would clear it.). If the widget
+            # shows nothing, the user will check the data table anyway.
+            self.data = None
         if self.data is not None:
             for inputid, pred in list(self.predictors.items()):
                 if pred.results is None or numpy.isnan(pred.results[0]).all():

Orange/widgets/evaluate/owtestlearners.py

@@ -165,6 +165,8 @@ class OWTestLearners(OWWidget):
     class_selection = settings.ContextSetting(TARGET_AVERAGE)
 
     class Error(OWWidget.Error):
+        train_data_empty = Msg("Train data set is empty.")
+        test_data_empty = Msg("Test data set is empty.")
         class_required = Msg("Train data input requires a target variable.")
         too_many_classes = Msg("Too many target variables.")
         class_required_test = Msg("Test data input requires a target variable.")
@@ -274,6 +276,10 @@ def set_train_data(self, data):
         Set the input training dataset.
         """
         self.Information.data_sampled.clear()
+        self.Error.train_data_empty.clear()
+        if data is not None and not len(data):
+            self.Error.train_data_empty()
+            data = None
         if data and not data.domain.class_vars:
             self.Error.class_required()
             data = None
@@ -314,6 +320,10 @@ def set_test_data(self, data):
         Set the input separate testing dataset.
         """
         self.Information.test_data_sampled.clear()
+        self.Error.test_data_empty.clear()
+        if data is not None and not len(data):
+            self.Error.test_data_empty()
+            data = None
         if data and not data.domain.class_var:
             self.Error.class_required()
             data = None
@@ -388,7 +398,8 @@ def _update_results(self):
 
         if self.resampling == OWTestLearners.TestOnTest:
             if self.test_data is None:
-                self.Warning.test_data_missing()
+                if not self.Error.test_data_empty.is_shown():
+                    self.Warning.test_data_missing()
                 return
             elif self.test_data.domain.class_var != class_var:
                 self.Error.class_inconsistent()

Orange/widgets/unsupervised/owcorrespondence.py

@@ -56,6 +56,9 @@ class OWCorrespondenceAnalysis(widget.OWWidget):
 
     graph_name = "plot.plotItem"
 
+    class Error(widget.OWWidget.Error):
+        empty_data = widget.Msg("Empty data set")
+
     def __init__(self):
         super().__init__()
 
@@ -95,8 +98,14 @@ def __init__(self):
     def set_data(self, data):
         self.closeContext()
         self.clear()
-        self.data = data
 
+        if data is not None and not len(data):
+            self.Error.empty_data()
+            data = None
+        else:
+            self.Error.empty_data.clear()
+
+        self.data = data
         if data is not None:
             self.varlist[:] = [var for var in data.domain.variables
                                if var.is_discrete]

Orange/widgets/unsupervised/owdistances.py

@@ -41,7 +41,7 @@ class OWDistances(OWWidget):
     class Error(OWWidget.Error):
         no_continuous_features = Msg("No continuous features")
         dense_metric_sparse_data = Msg("Selected metric does not support sparse data")
-        empty_data = Msg("Empty data (shape = {})")
+        empty_data = Msg("Empty data set")
         too_few_observations = Msg("Too few observations for the number of dimensions")
 
     class Warning(OWWidget.Warning):
@@ -127,7 +127,7 @@ def compute_distances(self, metric, data):
             data = distance._preprocess(data)
 
         if not data.X.size:
-            self.Error.empty_data(data.X.shape)
+            self.Error.empty_data()
             return
 
         if isinstance(metric, distance.MahalanobisDistance):