def edges_to_graph(edges):
"""Construct an `open_cp.network` style graph from an "edges" input.
Merges very close vertices (<0.1 meters). From "edges" data there should
not be repeated edges.
:param roads: Iterable of `(name, geo)`
:return: `(graph, names)` where `names` is a dictionary from the edge
index to an instance of `EdgeNoLine`.
"""
edges = list(edges)
all_nodes = []
for edge in edges:
for pt in edge.line:
all_nodes.append(pt)
b = _network.PlanarGraphNodeOneShot(all_nodes)
name_lookup = _collections.defaultdict(set)
for edge in edges:
for e in b.add_path(edge.line):
name_lookup[e].add(_to_edge_noline(edge))
graph = b.build()
names = dict()
for e, ns in name_lookup.items():
index, _ = graph.find_edge(*e)
if index in names:
raise Exception("Repeated edge: {}".format(e))
if len(ns) > 1:
raise Exception("Edge {} has multiple data: {}".format(e, ns))
names[index] = list(ns)[0]
return graph, names
def roads_to_graph(roads):
"""Construct an `open_cp.network` style graph from a "roads" input.
Merges very close vertices (<0.1 meters) and repeated edges.
:param roads: Iterable of `(name, geo)`
:return: `(graph, names)` where `names` is a dictionary from the edge
index to the set of road names which make use of that edge (in
either direction).
"""
roads = list(roads)
all_nodes = []
for _, geo in roads:
for pt in geo:
all_nodes.append(pt)
b = _network.PlanarGraphNodeOneShot(all_nodes)
name_lookup = _collections.defaultdict(set)
for name, geo in roads:
for e in b.add_path(geo):
name_lookup[e].add(name)
b.remove_duplicate_edges()
graph = b.build()
names = _collections.defaultdict(set)
for e, ns in name_lookup.items():
index, _ = graph.find_edge(*e)
names[index].update(ns)
return graph, dict(names)
def test_PlanarGraphNodeOneShot():
nodes = [(0, 0), (1, 1), (5.1, 1.2), (0.1, 0.01), (2, 2)]
b = network.PlanarGraphNodeOneShot(nodes, 0.2)
r = b.add_path([(0, 0), (1, 1), (5.1, 1.2)])
assert r == [(0, 1), (1, 2)]
r = b.add_edge(0.1, 0.01, 2, 2)
assert r == (0, 3)
g = b.build()
assert set(g.vertices.values()) == {(0, 0), (1, 1), (5.1, 1.2), (2, 2)}
assert len(g.edges) == 3
assert [g.vertices[x] for x in g.edges[0]] == [(0, 0), (1, 1)]
assert [g.vertices[x] for x in g.edges[1]] == [(1, 1), (5.1, 1.2)]
assert [g.vertices[x] for x in g.edges[2]] == [(0, 0), (2, 2)]
def test_PlanarGraphNodeOneShot_remove_duplicates():
nodes = [(0, 0), (1, 1), (5.1, 1.2), (0.1, 0.01), (2, 2)]
b = network.PlanarGraphNodeOneShot(nodes, 0.2)
b.add_path([(0, 0), (1, 1), (5.1, 1.2)])
b.add_edge(0.1, 0.01, 2, 2)
b.add_edge(1, 1, 1, 1)
b.add_edge(0.1, 0.01, 2, 2)
with pytest.raises(ValueError):
b.build()
b.remove_duplicate_edges()
g = b.build()
assert set(g.vertices.values()) == {(0, 0), (1, 1), (5.1, 1.2), (2, 2)}
assert len(g.edges) == 3
assert [g.vertices[x] for x in g.edges[0]] == [(0, 0), (1, 1)]
assert [g.vertices[x] for x in g.edges[1]] == [(1, 1), (5.1, 1.2)]
assert [g.vertices[x] for x in g.edges[2]] == [(0, 0), (2, 2)]
def graph_from_streets(streets, to_projected_line):
"""Constructs a graph from a generic collection of "streets".
:param streets: Iterator of "street" objects
:param to_projected_line: Callable object which takes a "street" object
as from the iterable `streets`, and returns a "line" which is
suitable projected (if necessary). A "line" is an iterable of points,
where each point is a pair `(x,y)`.
:return: Pair `(graph, names)` where `graph` is a graph object, and
`names` is a dictionary from edge index (in graph) to a list of
"street" instances which are the street(s) associated with that
edge.
"""
all_streets, projected_lines = [], []
for street in streets:
all_streets.append(street)
projected_lines.append(to_projected_line(street))
all_nodes = []
for line in projected_lines:
for pt in line:
all_nodes.append(pt)
b = _network.PlanarGraphNodeOneShot(all_nodes)
name_lookup = _collections.defaultdict(list)
for street, line in zip(all_streets, projected_lines):
for e in b.add_path(line):
name_lookup[e].append(street)
b.remove_duplicate_edges()
graph = b.build()
names = _collections.defaultdict(list)
for e, ns in name_lookup.items():
if e[0] == e[1]:
# These have been removed
continue
index, _ = graph.find_edge(*e)
names[index].extend(ns)
return graph, names