Exemplo n.º 1
0
def test_induced_subgraph():
    num_nodes = 6

    graph = Graph()
    for i in range(num_nodes - 1):
        graph.add_edge(i, i + 1)
    graph.add_edge(1, 0)
    g = graph.compressed()

    # First test select array,
    select = np.array([True, True, True, False, False, True])
    g2 = induced_subgraph(g, select)
    assert g2.num_nodes == 4
    assert g2.num_edges == 3
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)

    # then test select function.
    g2 = induced_subgraph(g, lambda i: select[i])
    assert g2.num_nodes == 4
    assert g2.num_edges == 3
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)

    # Now the same with edge weights.
    edge_w = np.arange(g.num_edges, dtype=gint_dtype)
    g2, edge_w2 = induced_subgraph(g, select, edge_w)
    assert g2.num_nodes == 4
    assert g2.num_edges == 3
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)
    assert edge_w[g.first_edge_id(0,1)] == edge_w2[g2.first_edge_id(0,1)]
    assert edge_w[g.first_edge_id(1,0)] == edge_w2[g2.first_edge_id(1,0)]
    assert edge_w[g.first_edge_id(1,2)] == edge_w2[g2.first_edge_id(1,2)]

    g2, edge_w2 = induced_subgraph(g, lambda i: select[i], edge_w)
    assert g2.num_nodes == 4
    assert g2.num_edges == 3
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)
    assert edge_w[g.first_edge_id(0,1)] == edge_w2[g2.first_edge_id(0,1)]
    assert edge_w[g.first_edge_id(1,0)] == edge_w2[g2.first_edge_id(1,0)]
    assert edge_w[g.first_edge_id(1,2)] == edge_w2[g2.first_edge_id(1,2)]
Exemplo n.º 2
0
def _DISABLED_test_bisect():
    # REMARK: This test is somewhat limited in the sense that it can only test
    #         for the general sanity of the output, not if the bisection is
    #         really good (balanced, etc.).
    size = 5
    graph = Graph()

    for i in xrange(size-1):
        offset = i * size
        for j in xrange(size-1):
            graph.add_edge(offset + j, offset + j + 1)
            graph.add_edge(offset + j + 1, offset + j)
        if i > 0:
            for j in xrange(size):
                graph.add_edge(offset + j, offset + j - size)
                graph.add_edge(offset + j - size, offset + j)
    g = graph.compressed()

    parts = bisect(g)
    for i in xrange(g.num_nodes):
        assert_true(parts[i] == 0 or parts[i] == 1)
Exemplo n.º 3
0
def _DISABLED_test_bisect():
    # REMARK: This test is somewhat limited in the sense that it can only test
    #         for the general sanity of the output, not if the bisection is
    #         really good (balanced, etc.).
    size = 5
    graph = Graph()

    for i in range(size - 1):
        offset = i * size
        for j in range(size - 1):
            graph.add_edge(offset + j, offset + j + 1)
            graph.add_edge(offset + j + 1, offset + j)
        if i > 0:
            for j in range(size):
                graph.add_edge(offset + j, offset + j - size)
                graph.add_edge(offset + j - size, offset + j)
    g = graph.compressed()

    parts = bisect(g)
    for i in range(g.num_nodes):
        assert parts[i] == 0 or parts[i] == 1
Exemplo n.º 4
0
def _DISABLED_test_reset():
    size = 5
    graph = Graph()

    for i in xrange(size-1):
        offset = i * size
        for j in xrange(size-1):
            graph.add_edge(offset + j, offset + j + 1)
            graph.add_edge(offset + j + 1, offset + j)
        if i > 0:
            for j in xrange(size):
                graph.add_edge(offset + j, offset + j - size)
                graph.add_edge(offset + j - size, offset + j)
    g = graph.compressed()

    # After calling reset, SCOTCH returns identical results.
    reset()
    parts1 = bisect(g)
    reset()
    parts2 = bisect(g)

    assert_true((parts1 == parts2).all())
Exemplo n.º 5
0
def _DISABLED_test_reset():
    size = 5
    graph = Graph()

    for i in range(size - 1):
        offset = i * size
        for j in range(size - 1):
            graph.add_edge(offset + j, offset + j + 1)
            graph.add_edge(offset + j + 1, offset + j)
        if i > 0:
            for j in range(size):
                graph.add_edge(offset + j, offset + j - size)
                graph.add_edge(offset + j - size, offset + j)
    g = graph.compressed()

    # After calling reset, SCOTCH returns identical results.
    reset()
    parts1 = bisect(g)
    reset()
    parts2 = bisect(g)

    assert (parts1 == parts2).all()
Exemplo n.º 6
0
def test_remove_duplicates():
    graph = Graph()
    graph.add_edge(0, 1)
    graph.add_edge(0, 1)
    graph.add_edge(1, 2)

    # First test without edge weights,
    g = graph.compressed()
    remove_duplicates(g)
    assert g.num_edges == 2
    assert g.has_edge(0, 1)
    assert g.has_edge(1, 2)

    # then with edge weights.
    g = graph.compressed()
    edge_w = np.array([1,1,1], dtype=gint_dtype)
    remove_duplicates(g, edge_w)
    assert g.num_edges == 2
    assert g.has_edge(0, 1)
    assert g.has_edge(1, 2)
    assert edge_w[g.first_edge_id(0,1)] == 2
    assert edge_w[g.first_edge_id(1,2)] == 1
Exemplo n.º 7
0
def test_make_undirected():
    graph = Graph(True)
    graph.add_edge(0, 1)
    graph.add_edge(1, 0)
    graph.add_edge(1, 2)
    graph.add_edge(2, -1)
    g = graph.compressed()

    # First, test with no duplicates removed,
    g2 = make_undirected(g, remove_dups=False)

    assert g2.num_nodes == g.num_nodes
    assert g2.num_edges == 6
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)
    assert g2.has_edge(2, 1)

    # then with duplicates removed,
    g2 = make_undirected(g, remove_dups=True)

    assert g2.num_nodes == g.num_nodes
    assert g2.num_edges == 4
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)
    assert g2.has_edge(2, 1)

    # and finally with weights.
    g2, edge_w2 = make_undirected(g, remove_dups=True, calc_weights=True)

    assert g2.num_nodes == g.num_nodes
    assert g2.num_edges == 4
    assert g2.has_edge(0, 1)
    assert g2.has_edge(1, 0)
    assert g2.has_edge(1, 2)
    assert g2.has_edge(2, 1)
    assert edge_w2[g2.first_edge_id(0,1)] == 2
    assert edge_w2[g2.first_edge_id(1,0)] == 2
    assert edge_w2[g2.first_edge_id(1,2)] == 1
    assert edge_w2[g2.first_edge_id(2,1)] == 1
Exemplo n.º 8
0
def test_make_undirected():
    graph = Graph(True)
    graph.add_edge(0, 1)
    graph.add_edge(1, 0)
    graph.add_edge(1, 2)
    graph.add_edge(2, -1)
    g = graph.compressed()

    # First, test with no duplicates removed,
    g2 = make_undirected(g, remove_dups=False)

    assert_equal(g2.num_nodes, g.num_nodes)
    assert_equal(g2.num_edges, 6)
    assert_true(g2.has_edge(0, 1))
    assert_true(g2.has_edge(1, 0))
    assert_true(g2.has_edge(1, 2))
    assert_true(g2.has_edge(2, 1))

    # then with duplicates removed,
    g2 = make_undirected(g, remove_dups=True)

    assert_equal(g2.num_nodes, g.num_nodes)
    assert_equal(g2.num_edges, 4)
    assert_true(g2.has_edge(0, 1))
    assert_true(g2.has_edge(1, 0))
    assert_true(g2.has_edge(1, 2))
    assert_true(g2.has_edge(2, 1))

    # and finally with weights.
    g2, edge_w2 = make_undirected(g, remove_dups=True, calc_weights=True)

    assert_equal(g2.num_nodes, g.num_nodes)
    assert_equal(g2.num_edges, 4)
    assert_true(g2.has_edge(0, 1))
    assert_true(g2.has_edge(1, 0))
    assert_true(g2.has_edge(1, 2))
    assert_true(g2.has_edge(2, 1))
    assert_equal(edge_w2[g2.first_edge_id(0, 1)], 2)
    assert_equal(edge_w2[g2.first_edge_id(1, 0)], 2)
    assert_equal(edge_w2[g2.first_edge_id(1, 2)], 1)
    assert_equal(edge_w2[g2.first_edge_id(2, 1)], 1)