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
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)
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)]
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
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()
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
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)
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())
