OWKMeans: pylint

Author: janezd

Orange/widgets/unsupervised/owkmeans.py

@@ -34,7 +34,8 @@ def __init__(self, parent=None):
     def rowCount(self, index=QModelIndex()):
         return 0 if index.isValid() else len(self.scores)
 
-    def columnCount(self, index=QModelIndex()):
+    @staticmethod
+    def columnCount(_index=QModelIndex()):
         return 1
 
     def flags(self, index):
@@ -65,10 +66,12 @@ def data(self, index, role=Qt.DisplayRole):
             return score
         elif role == gui.BarRatioRole and valid:
             return score
+        return None
 
-    def headerData(self, row, orientation, role=Qt.DisplayRole):
+    def headerData(self, row, _orientation, role=Qt.DisplayRole):
         if role == Qt.DisplayRole:
             return str(row + self.start_k)
+        return None
 
 
 class Task:
@@ -444,8 +447,9 @@ def update_results(self):
 
     def selected_row(self):
         indices = self.table_view.selectedIndexes()
-        if indices:
-            return indices[0].row()
+        if not indices:
+            return None
+        return indices[0].row()
 
     def select_row(self):
         self.send_data()

Orange/widgets/unsupervised/tests/test_owkmeans.py

@@ -241,12 +241,12 @@ def test_centroids_domain_on_output(self):
     class KMeansFail(Orange.clustering.KMeans):
         fail_on = set()
 
-        def fit(self, *args):
+        def fit(self, X, Y=None):
             # when not optimizing, params is empty?!
             k = self.params.get("n_clusters", 3)
             if k in self.fail_on:
                 raise ValueError("k={} fails".format(k))
-            return super().fit(*args)
+            return super().fit(X, Y)
 
     @patch("Orange.widgets.unsupervised.owkmeans.KMeans", new=KMeansFail)
     def test_optimization_fails(self):
@@ -387,7 +387,8 @@ def test_silhouette_column(self):
         widget.k = 4
         widget.optimize_k = False
 
-        random = np.random.RandomState(0)  # Avoid randomness in the test
+        # Avoid randomness in the test
+        random = np.random.RandomState(0)  # pylint: disable=no-member
         table = Table(random.rand(110, 2))
         with patch("Orange.clustering.kmeans.SILHOUETTE_MAX_SAMPLES", 100):
             self.send_signal(self.widget.Inputs.data, table)