def test_network_skimming(self):
# graph
g = Graph()
g.load_from_disk(test_graph)
g.set_graph(cost_field="distance", skim_fields=None)
# None implies that only the cost field will be skimmed
# 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_network_skimming(self):
# graph
g = Graph()
g.load_from_disk(test_graph)
g.set_graph(cost_field='distance', skim_fields=None)
# None implies that only the cost field will be skimmed
# skimming results
res = SkimResults()
res.prepare(g)
aux_res = MultiThreadedNetworkSkimming()
aux_res.prepare(g, res)
a = 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))
def test_skimming_single_origin(self):
origin = 1
# graph
g = Graph()
g.load_from_disk(test_graph)
g.set_graph(cost_field="distance", skim_fields=None)
# g.block_centroid_flows = False
# None implies that only the cost field will be skimmed
# 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.")
if a != origin:
self.fail("Skimming returned an error: " + a)
def test_network_skimming(self):
self.network.build_graphs()
graph = self.network.graphs['c']
graph.set_graph(cost_field="distance")
graph.set_skimming("distance")
graph.set_blocked_centroid_flows(False)
# skimming results
res = SkimResults()
res.prepare(graph)
aux_res = MultiThreadedNetworkSkimming()
aux_res.prepare(graph, res)
_ = skimming_single_origin(12, graph, res, aux_res, 0)
skm = NetworkSkimming(graph)
skm.execute()
tot = np.nanmax(skm.results.skims.distance[:, :])
if tot > np.sum(graph.cost):
self.fail(
"Skimming was not successful. At least one np.inf returned.")
if skm.report:
self.fail("Skimming returned an error:" + str(skm.report))
skm.save_to_project('tEst_Skimming')
if not os.path.isfile(
os.path.join(self.proj_dir, 'matrices', 'test_skimming.omx')):
self.fail('Did not save project to project')
matrices = self.project.matrices
mat = matrices.get_record('TEsT_Skimming')
self.assertEqual(mat.name, 'tEst_Skimming',
'Matrix record name saved wrong')
self.assertEqual(mat.file_name, 'tEst_Skimming.omx',
'matrix file_name saved wrong')
self.assertEqual(mat.cores, 1,
'matrix saved number of matrix cores wrong')
self.assertEqual(mat.procedure, 'Network skimming',
'Matrix saved wrong procedure name')
self.assertEqual(mat.procedure_id, skm.procedure_id,
'Procedure ID saved wrong')
self.assertEqual(mat.timestamp, skm.procedure_date,
'Procedure ID saved wrong')