Beispiel #1
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def test_same_set():
    """A set should be clustered with itself"""
    s = lshhdc.utils.randset()
    cluster = lshhdc.cluster.Cluster()
    cluster.add_set(s)
    cluster.add_set(s)
    assert len(cluster.get_sets()) == 1
Beispiel #2
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def test_dissimilar_sets():
    """Two non-similar sets should not be clustered"""
    cluster = lshhdc.cluster.Cluster()
    cluster.add_set("12345abcdef")
    cluster.add_set("1234567890z")
    print cluster.get_sets()
    assert len(cluster.get_sets()) == 2
def test_names():
    data_dir = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'data')
    names = open('{}/{}'.format(data_dir, 'sample-data.txt'), 'r').readlines()
    names = [name.strip().lower().replace('\n', '') for name in names if name]
    cluster = lshhdc.cluster.Cluster(threshold=0.5)
    for name in set(names):
        cluster.add_set(lshhdc.utils.shingle(name, 5), name)
    assert len(cluster.get_sets()) == 6
def test_names():
    data_dir = os.path.join(os.path.abspath(os.path.dirname(__file__)), "data")
    names = open("{}/{}".format(data_dir, "sample-data.txt"), "r").readlines()
    names = [name.strip().lower().replace("\n", "") for name in names if name]
    cluster = lshhdc.cluster.Cluster(threshold=0.5)
    for name in set(names):
        cluster.add_set(lshhdc.utils.shingle(name, 5), name)
    assert len(cluster.get_sets()) == 6
Beispiel #5
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def test_cluster_threshold():
    """Expected error for threshold to similarity should be reasonable"""
    n_tests = 50
    dim = 15
    expected_error = 0.20

    tot_err = 0
    for test in range(n_tests):
        # Get some sets and their similarities
        sets = (lshhdc.utils.randset(), lshhdc.utils.randset())
        jsim = lshhdc.utils.jaccard_sim(*sets)

        # Find the threshold at which they cluster together
        for threshold in range(1, 100, 5):
            threshold = float(threshold) / 100
            cluster = lshhdc.cluster.Cluster(dim, threshold)
            cluster.add_set(sets[0])
            cluster.add_set(sets[1])
            if len(cluster.get_sets()) == 2:
                tot_err += abs(jsim - threshold)
                break
    avg_err = float(tot_err) / n_tests
    assert avg_err <= expected_error
Beispiel #6
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def test_similar_sets():
    """Two similar sets should be clustered"""
    cluster = lshhdc.cluster.Cluster()
    cluster.add_set("abcdefg")
    cluster.add_set("abcdefghi")
    assert len(cluster.get_sets()) == 1