def test_example_clustering_on(self, data):
constructors = [Euclidean, Manhattan]
for distance_constructor in constructors:
clust = clustering(data, distance_constructor, HierarchicalClustering.Single)
clust = clustering(data, distance_constructor, HierarchicalClustering.Average)
clust = clustering(data, distance_constructor, HierarchicalClustering.Complete)
clust = clustering(data, distance_constructor, HierarchicalClustering.Ward)
top_clust = top_clusters(clust, 5)
cluster_list = cluster_to_list(clust, 5)
def test_example_clustering_on(self, data):
constructors = [Euclidean, Manhattan]
for distance_constructor in constructors:
clust = clustering(data, distance_constructor,
HierarchicalClustering.Single)
clust = clustering(data, distance_constructor,
HierarchicalClustering.Average)
clust = clustering(data, distance_constructor,
HierarchicalClustering.Complete)
clust = clustering(data, distance_constructor,
HierarchicalClustering.Ward)
top_clust = top_clusters(clust, 5)
cluster_list = cluster_to_list(clust, 5)
def test():
app = QApplication([])
scene = QGraphicsScene()
view = QGraphicsView()
view.setScene(scene)
view.show()
import Orange
data = Orange.data.Table("../doc/datasets/iris.tab")
root = hierarchical.clustering(data)
# print hierarchical.cophenetic_correlation(root, hierarchical.instance_distance_matrix(data))
# widget = DendrogramWidget(hierarchical.pruned(root, level=4))#, orientation=Qt.Horizontal)
widget = DendrogramWidget(root)
scene.addItem(widget)
line = CutoffLine(widget)
# widget.layout().setMaximumHeight(400)
app.exec_()
def test():
app = QApplication([])
scene = QGraphicsScene()
view = QGraphicsView()
view.setScene(scene)
view.show()
import Orange
data = Orange.data.Table("../doc/datasets/iris.tab")
root = hierarchical.clustering(data)
# print hierarchical.cophenetic_correlation(root, hierarchical.instance_distance_matrix(data))
# widget = DendrogramWidget(hierarchical.pruned(root, level=4))#, orientation=Qt.Horizontal)
widget = DendrogramWidget(root)
scene.addItem(widget)
line = CutoffLine(widget)
# widget.layout().setMaximumHeight(400)
app.exec_()
def test_pickling_on(self, data):
cluster = clustering(data, Euclidean, HierarchicalClustering.Single)
s = pickle.dumps(cluster)
cluster_clone = pickle.loads(s)
self.assertEqual(len(cluster), len(cluster_clone))
self.assertEqual(cluster.mapping, cluster_clone.mapping)
def test_pickling_on(self, data):
cluster = clustering(data, Euclidean, HierarchicalClustering.Single)
s = pickle.dumps(cluster)
cluster_clone = pickle.loads(s)
self.assertEqual(len(cluster), len(cluster_clone))
self.assertEqual(cluster.mapping, cluster_clone.mapping)
