def test_algo2(self):
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),"temp_rues2")
if not os.path.exists(folder) : os.mkdir(folder)
edges = get_data(whereTo=folder)
edges = edges[:1000]
added = eulerien_extension(edges, fLOG = fLOG, alpha = 1/8)
assert len(added)>0
fLOG ("nb added",len(added))
def test_algo_euler4(self):
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),"temp_rues5")
if not os.path.exists(folder) : os.mkdir(folder)
edges = get_data(whereTo=folder)
edges = edges[:3]
vertices = { }
for e in edges :
for i in range(0,2):
_ = e[i]
p = e[i+3]
vertices[_] = p
connex = connected_components(edges)
v = [ v for k,v in connex.items() ]
mi,ma = min(v), max(v)
while mi != ma :
edges.append( (mi, ma, 2, vertices[mi], vertices[ma],
distance_haversine( * (vertices[mi] + vertices[ma]) ) ) )
connex = connected_components(edges)
v = [ v for k,v in connex.items() ]
mi,ma = min(v), max(v)
if __name__ == "__main__":
import matplotlib.pyplot as plt
import networkx as nx
fig = plt.figure()
G = nx.Graph()
for e in edges :
a,b = e[:2]
G.add_edge(a,b)
pos = nx.spring_layout(G)
nx.draw(G,pos,node_color='#A0CBE2')
plt.savefig(os.path.join(folder, "graph1.png"))
added = eulerien_extension( edges, fLOG=lambda *l : None,
distance = distance_paris)
if __name__ == "__main__":
for e in added :
a,b = e[:2]
G.add_edge(a,b)
fig = plt.figure()
pos = nx.spring_layout(G)
deg = graph_degree(edges + added)
#labels={ v:"{0}".format(deg[v]) for v in G.nodes() }
nx.draw(G,pos,node_color='#A0CBE2'#,labels=labels
)
plt.savefig(os.path.join(folder, "graph2.png"))
path = euler_path(edges, added)
all = edges + added
fLOG(len(all),len(path))
def test_algo3(self):
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
return
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),"temp_rues2")
if not os.path.exists(folder) : os.mkdir(folder)
edges = get_data(whereTo=folder)
fLOG("start")
added = eulerien_extension(edges, fLOG=fLOG, distance = distance_paris)
assert len(added)>0
fLOG ("nb added",len(added))
with open(os.path.join(folder,"added.txt"),"w") as f :
f.write(str(added))
def test_algo3(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
folder = get_temp_folder(__file__, "temp_algo3")
edges = get_data(whereTo=folder, fLOG=fLOG)
fLOG("start")
added = eulerien_extension(edges, fLOG=fLOG, distance=distance_paris)
assert len(added) > 0
fLOG("nb added", len(added))
with open(os.path.join(folder, "added.txt"), "w") as f:
f.write(str(added))
def test_algo2(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),
"temp_algo2")
if not os.path.exists(folder):
os.mkdir(folder)
edges = get_data(whereTo=folder, fLOG=fLOG)
edges = edges[:1000]
added = eulerien_extension(edges, fLOG=fLOG, alpha=1 / 8)
assert len(added) > 0
fLOG("nb added", len(added))
def test_algo3(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
return
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),
"temp_rues2")
if not os.path.exists(folder):
os.mkdir(folder)
edges = get_data(whereTo=folder, fLOG=fLOG)
fLOG("start")
added = eulerien_extension(edges, fLOG=fLOG, distance=distance_paris)
assert len(added) > 0
fLOG("nb added", len(added))
with open(os.path.join(folder, "added.txt"), "w") as f:
f.write(str(added))
def test_algo_euler4(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
folder = os.path.join(os.path.abspath(os.path.dirname(__file__)),
"temp_algo_euler4")
if not os.path.exists(folder):
os.mkdir(folder)
edges = get_data(whereTo=folder, fLOG=fLOG)
edges = edges[:3]
vertices = {}
for e in edges:
for i in range(0, 2):
_ = e[i]
p = e[i + 3]
vertices[_] = p
connex = connected_components(edges)
v = [v for k, v in connex.items()]
mi, ma = min(v), max(v)
while mi != ma:
edges.append((mi, ma, 2, vertices[mi], vertices[ma],
distance_haversine(*(vertices[mi] + vertices[ma]))))
connex = connected_components(edges)
v = [v for k, v in connex.items()]
mi, ma = min(v), max(v)
fix_tkinter_issues_virtualenv()
import matplotlib.pyplot as plt
import networkx as nx
plt.figure()
G = nx.Graph()
for e in edges:
a, b = e[:2]
G.add_edge(a, b)
pos = nx.spring_layout(G)
nx.draw(G, pos, node_color='#A0CBE2')
plt.savefig(os.path.join(folder, "graph1.png"))
plt.close('all')
added = eulerien_extension(edges,
fLOG=lambda *l: None,
distance=distance_paris)
for e in added:
a, b = e[:2]
G.add_edge(a, b)
plt.figure()
pos = nx.spring_layout(G)
graph_degree(edges + added)
#labels={ v:"{0}".format(deg[v]) for v in G.nodes() }
nx.draw(
G,
pos,
node_color='#A0CBE2' # ,labels=labels
)
plt.savefig(os.path.join(folder, "graph2.png"))
plt.close('all')
path = euler_path(edges, added)
alls = edges + added
fLOG(len(alls), len(path))
