def find_maxima_cluster()

in clustering.py [0:0]

• 28 lines of code
• 9 McCabe index (conditional complexity)

def find_maxima_cluster(W, v):
    n, m = W.shape
    assert (n == m)
    assign = np.zeros(n)
    # for each node
    pointers = list(range(n))
    for i in range(n):
        best_vi = 0
        l0 = W.indptr[i]
        l1 = W.indptr[i + 1]
        for l in range(l0, l1):
            j = W.indices[l]
            vi = W.data[l] * (v[j] - v[i])
            if vi > best_vi:
                best_vi = vi
                pointers[i] = j
    n_clus = 0
    cluster_ids = -1 * np.ones(n)
    for i in range(n):
        if pointers[i] == i:
            cluster_ids[i] = n_clus
            n_clus = n_clus + 1
    for i in range(n):
        # go from pointers to pointers starting from i until reached a local optim
        current_node = i
        while pointers[current_node] != current_node:
            current_node = pointers[current_node]

        assign[i] = cluster_ids[current_node]
        assert (assign[i] >= 0)
    return assign