def test_graph_sparse_weighted():
edgelist = [
(0, 1, 5),
(0, 2, 2),
(0, 3, 3),
(1, 3, 1),
(2, 3, 7.7),
(2, 4, 3.3),
(2, 5, 13.0),
(0, 4, 9.999),
(2, 6, 3.0),
]
g = create_sparse_graph(edgelist, 7, directed=False)
assert not g.type.directed
assert g.type.weighted
assert g.vertices == set([0, 1, 2, 3, 4, 5, 6])
edgelist2 = []
for e in g.edges:
edgelist2.append(g.edge_tuple(e))
assert edgelist2 == edgelist
# sparse graphs cannot be modified
with pytest.raises(ValueError):
g.add_edge(0, 5)
def test_graph_sparse_lazy_incoming():
edgelist = [(0, 1), (0, 2), (0, 3), (1, 3), (2, 3), (2, 4), (2, 5), (0, 4),
(2, 6)]
g = create_sparse_graph(
edgelist,
7,
weighted=False,
incoming_edges_support=IncomingEdgesSupport.LAZY_INCOMING_EDGES)
assert g.type.directed
assert not g.type.weighted
assert g.vertices == set([0, 1, 2, 3, 4, 5, 6])
assert set(g.inedges_of(3)) == {2, 3, 4}
def test_graph_sparse_weighted():
edgelist = parse_edgelist_json(input1)
assert list(edgelist) == [
('0', '1', 1.0),
('0', '2', 1.0),
('0', '3', 1.0),
('0', '4', 1.0),
('0', '5', 1.0),
('0', '6', 1.0),
('0', '7', 1.0),
('0', '8', 1.0),
('0', '9', 1.0),
('1', '2', 1.0),
('2', '3', 1.0),
('3', '4', 1.0),
('4', '5', 1.0),
('5', '6', 1.0),
('6', '7', 1.0),
('7', '8', 1.0),
('8', '9', 1.0),
('9', '1', 1.0),
]
edgelist = [(int(s), int(t), w) for s, t, w in edgelist]
g = create_sparse_graph(edgelist, 10, directed=True)
print(g)
assert g.type.directed
assert g.type.weighted
assert g.vertices == set([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
edgelist2 = []
for e in g.edges:
edgelist2.append(g.edge_tuple(e))
assert edgelist2 == list(edgelist)
# sparse graphs cannot be modified
with pytest.raises(ValueError):
g.add_edge(0, 5)
def test_graph_sparse_no_vertex_count():
edgelist = [(0, 1), (0, 2), (0, 3), (1, 3), (2, 3), (2, 4), (2, 5), (0, 4), (2, 6)]
g = create_sparse_graph(edgelist, weighted=False)
assert g.type.directed
assert not g.type.weighted
assert g.vertices == set([0, 1, 2, 3, 4, 5, 6])
edgelist2 = []
for e in g.edges:
u, v, w = g.edge_tuple(e)
edgelist2.append((u, v))
assert edgelist2 == edgelist
# sparse graphs cannot be modified
with pytest.raises(ValueError):
g.add_edge(0, 5)
def test_graph_sparse_no_incoming():
edgelist = [(0, 1), (0, 2), (0, 3), (1, 3), (2, 3), (2, 4), (2, 5), (0, 4),
(2, 6)]
g = create_sparse_graph(
edgelist,
7,
weighted=False,
incoming_edges_support=IncomingEdgesSupport.NO_INCOMING_EDGES)
assert g.type.directed
assert not g.type.weighted
assert g.vertices == set([0, 1, 2, 3, 4, 5, 6])
# no incoming support
with pytest.raises(ValueError):
g.inedges_of(3)
m = re.match(r'v([0-9]+)', id)
vid = int(m.group(1))
return vid
edges = [(convert_id(s), convert_id(t), w) for s, t, w in edges]
print(edges)
# %%
# Now that we have all our edges, we need to figure out the number of vertices. Sparse graphs
# contain all vertices from :math:`[0, n)` where :math:`n` is the number of vertices.
# Then we call the :py:meth:`jgrapht.create_sparse_graph()` factory.
sparse = jgrapht.create_sparse_graph(edges,
num_of_vertices=5,
directed=True,
weighted=True)
print(sparse)
# %%
# Note that in the above call the graph must be weighted, as our edges also have a weight.
# Let us calculate a graph coloring using the greedy algorithm using saturation degree ordering.
import jgrapht.algorithms.coloring as coloring
num_colors, color_map = coloring.greedy_dsatur(sparse)
print('Total number of colors: {}'.format(num_colors))
print('Color map: {}'.format(color_map))
