def test_network_skimming(self):
# graph
g = Graph()
g.load_from_disk(test_graph)
g.set_graph(cost_field="distance")
g.set_skimming("distance")
# skimming results
res = SkimResults()
res.prepare(g)
aux_res = MultiThreadedNetworkSkimming()
aux_res.prepare(g, res)
_ = skimming_single_origin(26, g, res, aux_res, 0)
skm = NetworkSkimming(g, res)
skm.execute()
tot = np.nanmax(res.skims.distance[:, :])
if tot > 10e10:
self.fail("Skimming was not successful. At least one np.inf returned.")
if skm.report:
self.fail("Skimming returned an error:" + str(skm.report))
def test_skimming_single_origin(self):
g = Graph()
g.load_from_disk(test_graph)
g.set_graph(cost_field="distance")
g.set_skimming("distance")
origin = np.random.choice(g.centroids[:-1], 1)[0]
# skimming results
res = SkimResults()
res.prepare(g)
aux_result = MultiThreadedNetworkSkimming()
aux_result.prepare(g, res)
a = skimming_single_origin(origin, g, res, aux_result, 0)
tot = np.sum(res.skims.distance[origin, :])
if tot > 10e10:
self.fail(
"Skimming was not successful. At least one np.inf returned for origin {}."
.format(origin))
if a != origin:
self.fail("Skimming returned an error: {} for origin {}".format(
a, origin))
class TestGraph(TestCase):
def test_create_from_geography(self):
self.graph = Graph()
self.graph.create_from_geography(
test_network,
"link_id",
"dir",
"distance",
centroids=centroids,
skim_fields=[],
anode="A_NODE",
bnode="B_NODE",
)
self.graph.set_graph(cost_field="distance")
self.graph.set_blocked_centroid_flows(block_centroid_flows=True)
self.graph.set_skimming("distance")
def test_prepare_graph(self):
self.test_create_from_geography()
self.graph.prepare_graph(centroids)
reference_graph = Graph()
reference_graph.load_from_disk(test_graph)
if not np.array_equal(self.graph.graph, reference_graph.graph):
self.fail("Reference graph and newly-prepared graph are not equal")
def test_set_graph(self):
self.test_prepare_graph()
self.graph.set_graph(cost_field="distance")
self.graph.set_blocked_centroid_flows(block_centroid_flows=True)
if self.graph.num_zones != centroids.shape[0]:
self.fail("Number of centroids not properly set")
if self.graph.num_links != 222:
self.fail("Number of links not properly set")
if self.graph.num_nodes != 93:
self.fail("Number of nodes not properly set - " +
str(self.graph.num_nodes))
def test_save_to_disk(self):
self.test_create_from_geography()
self.graph.save_to_disk(join(path_test, "aequilibrae_test_graph.aeg"))
self.graph_id = self.graph.__id__
self.graph_version = self.graph.__version__
def test_load_from_disk(self):
self.test_save_to_disk()
reference_graph = Graph()
reference_graph.load_from_disk(test_graph)
new_graph = Graph()
new_graph.load_from_disk(join(path_test, "aequilibrae_test_graph.aeg"))
comparisons = [
("Graph", new_graph.graph, reference_graph.graph),
("b_nodes", new_graph.b_node, reference_graph.b_node),
("Forward-Star", new_graph.fs, reference_graph.fs),
("cost", new_graph.cost, reference_graph.cost),
("centroids", new_graph.centroids, reference_graph.centroids),
("skims", new_graph.skims, reference_graph.skims),
("link ids", new_graph.ids, reference_graph.ids),
("Network", new_graph.network, reference_graph.network),
("All Nodes", new_graph.all_nodes, reference_graph.all_nodes),
("Nodes to indices", new_graph.nodes_to_indices,
reference_graph.nodes_to_indices),
]
for comparison, newg, refg in comparisons:
if not np.array_equal(newg, refg):
self.fail(
"Reference %s and %s created and saved to disk are not equal"
% (comparison, comparison))
comparisons = [
("nodes", new_graph.num_nodes, reference_graph.num_nodes),
("links", new_graph.num_links, reference_graph.num_links),
("zones", new_graph.num_zones, reference_graph.num_zones),
("block through centroids", new_graph.block_centroid_flows,
reference_graph.block_centroid_flows),
("Graph ID", new_graph.__id__, self.graph_id),
("Graph Version", new_graph.__version__, self.graph_version),
]
for comparison, newg, refg in comparisons:
if newg != refg:
self.fail(
"Reference %s and %s created and saved to disk are not equal"
% (comparison, comparison))
def test_available_skims(self):
self.test_set_graph()
if self.graph.available_skims() != ["distance"]:
self.fail("Skim availability with problems")
def test_exclude_links(self):
p = Project()
p.load(siouxfalls_project)
p.network.build_graphs()
g = p.network.graphs['c'] # type: Graph
# excludes a link before any setting or preparation
g.exclude_links([12])
g.set_graph('distance')
r1 = PathResults()
r1.prepare(g)
r1.compute_path(1, 14)
self.assertEqual(list(r1.path), [2, 6, 10, 34])
# We exclude one link that we know was part of the last shortest path
g.exclude_links([10])
r2 = PathResults()
r2.prepare(g)
r2.compute_path(1, 14)
self.assertEqual(list(r2.path), [2, 7, 36, 34])
p.conn.close()
class TestAllOrNothing(TestCase):
def setUp(self) -> None:
self.mat_name = AequilibraeMatrix().random_name()
self.g = Graph()
self.g.load_from_disk(test_graph)
self.g.set_graph(cost_field="distance")
# Creates the matrix for assignment
args = {
"file_name": os.path.join(gettempdir(), self.mat_name),
"zones": self.g.num_zones,
"matrix_names": ["cars", "trucks"],
"index_names": ["my indices"],
}
matrix = AequilibraeMatrix()
matrix.create_empty(**args)
matrix.index[:] = self.g.centroids[:]
matrix.cars.fill(1.1)
matrix.trucks.fill(2.2)
# Exports matrix to OMX in order to have two matrices to work with
matrix.export(os.path.join(gettempdir(), "my_matrix.omx"))
matrix.close()
def test_skimming_on_assignment(self):
matrix = AequilibraeMatrix()
matrix.load(os.path.join(gettempdir(), self.mat_name))
matrix.computational_view(["cars"])
res = AssignmentResults()
res.prepare(self.g, matrix)
self.g.set_skimming([])
self.g.set_blocked_centroid_flows(True)
assig = allOrNothing(matrix, self.g, res)
assig.execute()
if res.skims.distance.sum() > 0:
self.fail(
"skimming for nothing during assignment returned something different than zero"
)
self.g.set_skimming("distance")
res.prepare(self.g, matrix)
assig = allOrNothing(matrix, self.g, res)
assig.execute()
if res.skims.distance.sum() != 2914644.0:
self.fail("skimming during assignment returned the wrong value")
matrix.close()
def test_execute(self):
# Loads and prepares the graph
car_loads = []
two_class_loads = []
for extension in ["omx", "aem"]:
matrix = AequilibraeMatrix()
if extension == 'omx':
mat_name = os.path.join(gettempdir(), "my_matrix." + extension)
else:
mat_name = self.mat_name
matrix.load(mat_name)
matrix.computational_view(["cars"])
# Performs assignment
res = AssignmentResults()
res.prepare(self.g, matrix)
assig = allOrNothing(matrix, self.g, res)
assig.execute()
car_loads.append(res.link_loads)
res.save_to_disk(
os.path.join(gettempdir(),
"link_loads_{}.aed".format(extension)))
res.save_to_disk(
os.path.join(gettempdir(),
"link_loads_{}.csv".format(extension)))
matrix.computational_view()
# Performs assignment
res = AssignmentResults()
res.prepare(self.g, matrix)
assig = allOrNothing(matrix, self.g, res)
assig.execute()
two_class_loads.append(res.link_loads)
res.save_to_disk(
os.path.join(gettempdir(),
"link_loads_2_classes_{}.aed".format(extension)))
res.save_to_disk(
os.path.join(gettempdir(),
"link_loads_2_classes_{}.csv".format(extension)))
matrix.close()
load_diff = two_class_loads[0] - two_class_loads[1]
if load_diff.max() > 0.0000000001 or load_diff.max() < -0.0000000001:
self.fail(
"Loads for two classes differ for OMX and AEM matrix types")
load_diff = car_loads[0] - car_loads[1]
if load_diff.max() > 0.0000000001 or load_diff.max() < -0.0000000001:
self.fail(
"Loads for a single class differ for OMX and AEM matrix types")
class TestGraph(TestCase):
def test_create_from_geography(self):
self.graph = Graph()
self.graph.create_from_geography(
test_network,
"link_id",
"dir",
"distance",
centroids=centroids,
skim_fields=[],
anode="A_NODE",
bnode="B_NODE",
)
self.graph.set_graph(cost_field="distance")
self.graph.set_blocked_centroid_flows(block_centroid_flows=True)
self.graph.set_skimming("distance")
def test_prepare_graph(self):
self.test_create_from_geography()
self.graph.prepare_graph(centroids)
reference_graph = Graph()
reference_graph.load_from_disk(test_graph)
if not np.array_equal(self.graph.graph, reference_graph.graph):
self.fail("Reference graph and newly-prepared graph are not equal")
def test_set_graph(self):
self.test_prepare_graph()
self.graph.set_graph(cost_field="distance")
self.graph.set_blocked_centroid_flows(block_centroid_flows=True)
if self.graph.num_zones != centroids.shape[0]:
self.fail("Number of centroids not properly set")
if self.graph.num_links != 222:
self.fail("Number of links not properly set")
if self.graph.num_nodes != 93:
self.fail("Number of nodes not properly set - " +
str(self.graph.num_nodes))
def test_save_to_disk(self):
self.test_create_from_geography()
self.graph.save_to_disk(join(path_test, "aequilibrae_test_graph.aeg"))
self.graph_id = self.graph.__id__
self.graph_version = self.graph.__version__
def test_load_from_disk(self):
self.test_save_to_disk()
reference_graph = Graph()
reference_graph.load_from_disk(test_graph)
new_graph = Graph()
new_graph.load_from_disk(join(path_test, "aequilibrae_test_graph.aeg"))
comparisons = [
("Graph", new_graph.graph, reference_graph.graph),
("b_nodes", new_graph.b_node, reference_graph.b_node),
("Forward-Star", new_graph.fs, reference_graph.fs),
("cost", new_graph.cost, reference_graph.cost),
("centroids", new_graph.centroids, reference_graph.centroids),
("skims", new_graph.skims, reference_graph.skims),
("link ids", new_graph.ids, reference_graph.ids),
("Network", new_graph.network, reference_graph.network),
("All Nodes", new_graph.all_nodes, reference_graph.all_nodes),
("Nodes to indices", new_graph.nodes_to_indices,
reference_graph.nodes_to_indices),
]
for comparison, newg, refg in comparisons:
if not np.array_equal(newg, refg):
self.fail(
"Reference %s and %s created and saved to disk are not equal"
% (comparison, comparison))
comparisons = [
("nodes", new_graph.num_nodes, reference_graph.num_nodes),
("links", new_graph.num_links, reference_graph.num_links),
("zones", new_graph.num_zones, reference_graph.num_zones),
("block through centroids", new_graph.block_centroid_flows,
reference_graph.block_centroid_flows),
("Graph ID", new_graph.__id__, self.graph_id),
("Graph Version", new_graph.__version__, self.graph_version),
]
for comparison, newg, refg in comparisons:
if newg != refg:
self.fail(
"Reference %s and %s created and saved to disk are not equal"
% (comparison, comparison))
def test_available_skims(self):
self.test_set_graph()
if self.graph.available_skims() != ["distance"]:
self.fail("Skim availability with problems")
