OwLouvain: Widget changed to match new clustering interface.

Orange/widgets/unsupervised/owlouvainclustering.py

@@ -15,6 +15,7 @@
 from AnyQt.QtWidgets import QSlider, QCheckBox, QWidget, QLabel
 
 from Orange.clustering.louvain import table_to_knn_graph, Louvain
+from Orange.clustering.clustering import preprocess_data
 from Orange.data import Table, DiscreteVariable
 from Orange.data.util import get_unique_names, array_equal
 from Orange import preprocess
@@ -612,7 +613,7 @@ def run_on_data(data, normalize, pca_components, k_neighbors, metric, resolution
 
     # Apply Louvain preprocessing before converting the table into a graph
     louvain = Louvain(resolution=resolution, random_state=0)
-    data = louvain.preprocess(data)
+    data = preprocess_data(louvain.preprocessors, data)
 
     if state.is_interuption_requested():
         return res
@@ -625,8 +626,7 @@ def pcallback(val):
     try:
         res.graph = graph = table_to_knn_graph(
             data, k_neighbors=k_neighbors, metric=metric,
-            progress_callback=pcallback
-        )
+            progress_callback=pcallback)
     except InteruptRequested:
         return res
 
@@ -638,7 +638,7 @@ def pcallback(val):
     if state.is_interuption_requested():
         return res
 
-    res.partition = louvain.fit_predict(graph)
+    res.partition = louvain(graph)
     state.set_partial_results(("partition", res.partition))
     return res
 
@@ -654,7 +654,7 @@ def run_on_graph(graph, resolution, state):
     state.set_status("Detecting communities...")
     if state.is_interuption_requested():
         return res
-    partition = louvain.fit_predict(graph)
+    partition = louvain(graph)
     res.partition = partition
     state.set_partial_results(("partition", res.partition))
     return res