def test_cds_length(self):
net = mm.cds_length(self.network)
net2 = mm.cds_length(self.network, mode='mean', name='cds_mean')
sumval = 1753.626758955522
mean = 219.20334486944023
assert net.nodes[(1603650.450422848, 6464368.600601688)]['cds_len'] == sumval
assert net2.nodes[(1603650.450422848, 6464368.600601688)]['cds_mean'] == mean
def test_cds_length(self):
net = mm.cds_length(self.network)
net2 = mm.cds_length(self.network, mode="mean", name="cds_mean")
sumval = 1753.626758955522
mean = 219.20334486944023
assert net.nodes[(1603650.450422848, 6464368.600601688)]["cds_len"] == sumval
assert net2.nodes[(1603650.450422848, 6464368.600601688)]["cds_mean"] == mean
with pytest.raises(ValueError):
net2 = mm.cds_length(self.network, mode="nonexistent")
assert mm.cds_length(self.network, radius=None) == 2291.4520621447705
def time_cds_length(self):
mm.cds_length(self.network)
degree="degree",
length="mm_len",
mean_node_degree=False,
proportion={
0: True,
3: True,
4: True
},
cyclomatic=False,
edge_node_ratio=False,
gamma=False,
local_closeness=True,
closeness_distance="mm_len",
)
print("cds length")
graph = mm.cds_length(graph, radius=3, name="ldsCDL")
print("eigenvector")
try:
graph = mm.eigenvector(graph, name="xcnEiC", max_iter=500)
except Exception:
graph = mm.eigenvector(graph, name="xcnEiC", max_iter=1000)
print("clustering")
graph = mm.clustering(graph, name="xcnSCl")
print("mean_node_dist")
graph = mm.mean_node_dist(graph, name="mtdMDi")
nodes, edges, sw = mm.nx_to_gdf(graph, spatial_weights=True)