def test_sample_doc_clustering_with_online(self):
oc = OnlineClusterer(N=2, window=3)
samples = get_orange_clustering_test_data()
for document in samples:
index = oc.add_document(document)
oc.cluster(document)
expected = [0, 0, 0, 1, 1, 1]
for cluster in oc.clusters:
print cluster.document_dict
def test_cluster_term_document_matrix(self):
oc = OnlineClusterer(N=2, window=3)
for document in samples:
index = oc.add_document(document)
oc.cluster(document)
calculated = oc.td_matrix
expected = numpy.array(
[[0.31388923, 0.11584717, 0, 0, 0, 0, 0.47083384],
[0, 0.13515504, 0.3662041, 0, 0.3662041, 0, 0],
[0, 0, 0, 0.54930614, 0, 0.549306140, 0]])
self.assertEqual(expected.all(), calculated.all())
def test_online_clustering_with_tweets(self):
from_date = datetime.datetime(2011, 1, 25, 0, 0, 0)
to_date = datetime.datetime(2011, 1, 26, 0, 00, 0)
items = ws.get_top_documents_by_date(from_date,
to_date,
threshold=1000)
window = 300
oc = OnlineClusterer(N=50, window=window)
for item in items:
oc.cluster(item)
clusters = oc.trimclusters()
oc.dump_clusters_to_file("online_with_tweets")
oc.plot_scatter()
oc.plot_growth_timeline(cumulative=True)
for cluster in oc.clusters:
print cluster.id
print cluster.get_size()
print '-----------------'
