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import geopandas as gpd
import pytest
import momepy as mm
class TestGraph:
def setup_method(self):
test_file_path = mm.datasets.get_path("bubenec")
self.df_streets = gpd.read_file(test_file_path, layer="streets")
self.network = mm.gdf_to_nx(self.df_streets)
self.network = mm.node_degree(self.network)
self.dual = mm.gdf_to_nx(self.df_streets, approach="dual")
def test_node_degree(self):
deg1 = mm.node_degree(graph=self.network)
assert deg1.nodes[(1603650.450422848, 6464368.600601688)]["degree"] == 4
def test_meshedness(self):
net = mm.meshedness(self.network)
check = 0.14893617021276595
assert net.nodes[(1603650.450422848, 6464368.600601688)]["meshedness"] == check
assert mm.meshedness(self.network, radius=None) == 0.1320754716981132
def test_mean_node_dist(self):
net = mm.mean_node_dist(self.network)
check = 148.8166441307652
assert net.nodes[(1603650.450422848, 6464368.600601688)]["meanlen"] == check
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"
] == pytest.approx(sumval)
assert net2.nodes[(1603650.450422848, 6464368.600601688)][
"cds_mean"
] == pytest.approx(mean)
with pytest.raises(ValueError, match="Mode 'nonexistent' is not supported. "):
net2 = mm.cds_length(self.network, mode="nonexistent")
assert mm.cds_length(self.network, radius=None) == pytest.approx(
2291.4520621447705
)
def test_mean_node_degree(self):
net = mm.mean_node_degree(self.network)
check = 2.576923076923077
assert net.nodes[(1603650.450422848, 6464368.600601688)]["mean_nd"] == check
assert mm.mean_node_degree(self.network, radius=None) == 2.413793103448276
def test_proportion(self):
net = mm.proportion(self.network, three="three", four="four", dead="dead")
three = 0.23076923076923078
four = 0.2692307692307692
dead = 0.3076923076923077
assert net.nodes[(1603650.450422848, 6464368.600601688)]["dead"] == dead
assert net.nodes[(1603650.450422848, 6464368.600601688)]["four"] == four
assert net.nodes[(1603650.450422848, 6464368.600601688)]["three"] == three
glob = mm.proportion(
self.network, three="three", four="four", dead="dead", radius=None
)
assert glob["dead"] == 0.3793103448275862
assert glob["four"] == 0.2413793103448276
assert glob["three"] == 0.20689655172413793
def test_proportion_error(self):
with pytest.raises(ValueError, match="Nothing to calculate. "):
mm.proportion(self.network)
def test_cyclomatic(self):
net = mm.cyclomatic(self.network)
check = 7
assert net.nodes[(1603650.450422848, 6464368.600601688)]["cyclomatic"] == check
assert mm.cyclomatic(self.network, radius=None) == 7
def test_edge_node_ratio(self):
net = mm.edge_node_ratio(self.network)
check = 1.2307692307692308
assert (
net.nodes[(1603650.450422848, 6464368.600601688)]["edge_node_ratio"]
== check
)
assert mm.edge_node_ratio(self.network, radius=None) == 1.206896551724138
def test_gamma(self):
net = mm.gamma(self.network)
check = 0.4444444444444444
assert net.nodes[(1603650.450422848, 6464368.600601688)]["gamma"] == check
assert mm.gamma(self.network, radius=None) == 0.43209876543209874
def test_closeness_centrality(self):
net = mm.closeness_centrality(self.network, weight="mm_len")
check = 0.0016066095164175716
assert net.nodes[(1603650.450422848, 6464368.600601688)][
"closeness"
] == pytest.approx(check)
net = mm.closeness_centrality(self.network, radius=5, weight=None)
check = 0.27557319223985893
assert net.nodes[(1603650.450422848, 6464368.600601688)][
"closeness"
] == pytest.approx(check)
net2 = mm.closeness_centrality(self.network, weight="mm_len", radius=5)
check2 = 0.0015544070362478774
assert net2.nodes[(1603650.450422848, 6464368.600601688)][
"closeness"
] == pytest.approx(check2)
def test_betweenness_centrality(self):
net = mm.betweenness_centrality(self.network)
net2 = mm.betweenness_centrality(self.network, mode="edges")
angular = mm.betweenness_centrality(self.dual, weight="angle")
with pytest.raises(ValueError, match="Mode 'nonexistent' is not supported. "):
mm.betweenness_centrality(self.network, mode="nonexistent")
node = 0.2413793103448276
edge = 0.16995073891625617
ang_b = 0.16134453781512606
assert net.nodes[(1603650.450422848, 6464368.600601688)]["betweenness"] == node
assert (
net2.edges[
(1603226.9576840235, 6464160.158361825),
(1603039.9632033885, 6464087.491175889),
0,
]["betweenness"]
== edge
)
assert (
angular.nodes[(1603315.3564306537, 6464044.376339891)]["betweenness"]
== ang_b
)
net = mm.betweenness_centrality(self.network, radius=5, weight=None)
check = 53.74999999999999
assert net.nodes[(1603650.450422848, 6464368.600601688)]["betweenness"] == check
net2 = mm.betweenness_centrality(
self.network, radius=5, weight="mm_len", normalized=True
)
check2 = 0.21333333333333335
assert (
net2.nodes[(1603650.450422848, 6464368.600601688)]["betweenness"] == check2
)
def test_straightness_centrality(self):
net = mm.straightness_centrality(self.network)
net2 = mm.straightness_centrality(
self.network, normalized=False, name="nonnorm"
)
g = self.network.copy()
g.add_node(1)
net3 = mm.straightness_centrality(g)
check = 0.8574045143712158
nonnorm = 0.8574045143712158
assert (
net.nodes[(1603650.450422848, 6464368.600601688)]["straightness"] == check
)
assert net2.nodes[(1603650.450422848, 6464368.600601688)]["nonnorm"] == nonnorm
assert (
net3.nodes[(1603650.450422848, 6464368.600601688)]["straightness"] == check
)
net = mm.straightness_centrality(self.network, radius=5, normalized=False)
check = 0.8614261420539604
assert (
net.nodes[(1603650.450422848, 6464368.600601688)]["straightness"] == check
)
def test_mean_nodes(self):
net = mm.straightness_centrality(self.network)
mm.mean_nodes(net, "straightness")
edge = 0.8777302256084243
assert (
net.edges[
(1603226.9576840235, 6464160.158361825),
(1603039.9632033885, 6464087.491175889),
0,
]["straightness"]
== edge
)
def test_clustering(self):
net = mm.clustering(self.network)
check = 0.05555555555555555
assert net.nodes[(1603650.450422848, 6464368.600601688)]["cluster"] == check
def test_subgraph(self):
net = mm.subgraph(self.network)
nodes = mm.nx_to_gdf(net, lines=False)
cols = [
"meshedness",
"cds_length",
"mean_node_degree",
"proportion_3",
"proportion_4",
"proportion_0",
"cyclomatic",
"edge_node_ratio",
"gamma",
"local_closeness",
]
for c in cols:
assert c in nodes.columns
|
