def test_networkx(self):
try:
import networkx as nx
except ImportError:
return
try:
GraphSet.converters['to_graph'] = nx.Graph
GraphSet.converters['to_edges'] = nx.Graph.edges
g = nx.grid_2d_graph(3, 3)
GraphSet.set_universe(g)
g = GraphSet.universe()
self.assertTrue(isinstance(g, nx.Graph))
self.assertEqual(len(g.edges()), 12)
v00, v01, v10 = (0, 0), (0, 1), (1, 0)
e1, e2 = (v00, v01), (v00, v10)
gs = GraphSet([nx.Graph([e1])])
self.assertEqual(len(gs), 1)
g = gs.pop()
self.assertEqual(len(gs), 0)
self.assertTrue(isinstance(g, nx.Graph))
self.assertTrue(g.edges() == [(v00, v01)]
or g.edges() == [(v01, v00)])
gs.add(nx.Graph([e2]))
self.assertEqual(len(gs), 1)
except:
raise
finally:
GraphSet.converters['to_graph'] = lambda edges: edges
GraphSet.converters['to_edges'] = lambda graph: graph
def test_networkx(self):
try:
import networkx as nx
except ImportError:
return
try:
if nx.__version__[0] == "1": # for NetworkX version 1.x
GraphSet.converters['to_graph'] = nx.Graph
GraphSet.converters['to_edges'] = nx.Graph.edges
else: # for NetworkX version 2.x
GraphSet.converters['to_graph'] = nx.from_edgelist
GraphSet.converters['to_edges'] = nx.to_edgelist
g = nx.grid_2d_graph(3, 3)
GraphSet.set_universe(g)
g = GraphSet.universe()
self.assertTrue(isinstance(g, nx.Graph))
self.assertEqual(len(g.edges()), 12)
v00, v01, v10 = (0,0), (0,1), (1,0)
e1, e2 = (v00, v01), (v00, v10)
gs = GraphSet([nx.Graph([e1])])
self.assertEqual(len(gs), 1)
g = gs.pop()
self.assertEqual(len(gs), 0)
self.assertTrue(isinstance(g, nx.Graph))
self.assertTrue(list(g.edges()) == [(v00, v01)] or list(g.edges()) == [(v01, v00)])
gs.add(nx.Graph([e2]))
self.assertEqual(len(gs), 1)
except:
raise
finally:
GraphSet.converters['to_graph'] = lambda edges: edges
GraphSet.converters['to_edges'] = lambda graph: graph
def test_modifiers(self):
v = [g0, g12, g13]
gs = GraphSet(v)
gs.add(g1)
self.assertTrue(g1 in gs)
gs.remove(g1)
self.assertTrue(g1 not in gs)
self.assertRaises(KeyError, gs.remove, g1)
gs.add(g0)
gs.discard(g0)
self.assertTrue(g0 not in gs)
gs.discard(g0) # no exception raised
gs = GraphSet(v)
gs.add(e2)
self.assertEqual(gs, GraphSet([g12, g123, g2]))
gs = GraphSet(v)
gs.remove(e2)
self.assertEqual(gs, GraphSet([g0, g1, g13]))
self.assertRaises(KeyError, gs.remove, e4)
gs = GraphSet(v)
gs.discard(e2)
self.assertEqual(gs, GraphSet([g0, g1, g13]))
gs.discard(e4) # no exception raised
v = [g1, g12, g13]
gs = GraphSet(v)
g = gs.pop()
self.assertTrue(isinstance(g, list))
self.assertTrue(g not in gs)
self.assertEqual(gs | GraphSet([g]), GraphSet(v))
self.assertTrue(gs)
gs.clear()
self.assertFalse(gs)
self.assertRaises(KeyError, gs.pop)
self.assertRaises(KeyError, gs.add, [(1,4)])
self.assertRaises(KeyError, gs.remove, [(1,4)])
self.assertRaises(KeyError, gs.discard, [(1,4)])
self.assertRaises(KeyError, gs.add, (1,4))
self.assertRaises(KeyError, gs.remove, (1,4))
self.assertRaises(KeyError, gs.discard, (1,4))
u = [g0, g1, g12, g123, g1234, g134, g14, g4]
gs = GraphSet(u)
gs.flip(e1)
self.assertEqual(gs, GraphSet([g0, g1, g14, g2, g23, g234, g34, g4]))
def test_modifiers(self):
v = [g0, g12, g13]
gs = GraphSet(v)
gs.add(g1)
self.assertTrue(g1 in gs)
gs.remove(g1)
self.assertTrue(g1 not in gs)
self.assertRaises(KeyError, gs.remove, g1)
gs.add(g0)
gs.discard(g0)
self.assertTrue(g0 not in gs)
gs.discard(g0) # no exception raised
gs = GraphSet(v)
gs.add(e2)
self.assertEqual(gs, GraphSet([g12, g123, g2]))
gs = GraphSet(v)
gs.remove(e2)
self.assertEqual(gs, GraphSet([g0, g1, g13]))
self.assertRaises(KeyError, gs.remove, e4)
gs = GraphSet(v)
gs.discard(e2)
self.assertEqual(gs, GraphSet([g0, g1, g13]))
gs.discard(e4) # no exception raised
v = [g1, g12, g13]
gs = GraphSet(v)
g = gs.pop()
self.assertTrue(isinstance(g, list))
self.assertTrue(g not in gs)
self.assertEqual(gs | GraphSet([g]), GraphSet(v))
self.assertTrue(gs)
gs.clear()
self.assertFalse(gs)
self.assertRaises(KeyError, gs.pop)
self.assertRaises(KeyError, gs.add, [(1, 4)])
self.assertRaises(KeyError, gs.remove, [(1, 4)])
self.assertRaises(KeyError, gs.discard, [(1, 4)])
self.assertRaises(KeyError, gs.add, (1, 4))
self.assertRaises(KeyError, gs.remove, (1, 4))
self.assertRaises(KeyError, gs.discard, (1, 4))
u = [g0, g1, g12, g123, g1234, g134, g14, g4]
gs = GraphSet(u)
gs.flip(e1)
self.assertEqual(gs, GraphSet([g0, g1, g14, g2, g23, g234, g34, g4]))
print(weights_opt)
# -----alpha----------
f = calc_f(nk)
m_np = calc_mnp(nk, f)
failure_list = GraphSet()
for i in range(0, f):
failure_list.update(gc.len(E - i))
print(failure_list.len())
cand_select = gc.len(E - f)
#print(cand_select.len())
for cnt in range(0, m_np):
rand_graph = next(cand_select.rand_iter())
failure_list.add(rand_graph)
cand_select.remove(rand_graph)
print("total {0} patterns to consider".format(failure_list.len()))
# weights_opt = {(0,1):1,(0,2):3,(0,3):2,(1,2):4,(1,3):2,(2,3):1}
r = []
# cng_list = []
for i in failure_list:
# print(i)
G_fail = failed_G_cap(G_cap, i)
# print(G_fail)
cng_s, cng_d, r_val, congestion = calc_r(universe, i, tr, weights_opt,
G_fail)
r.append((cng_s, cng_d,
round(r_val,
tl_so = []
R_min_so = np.inf
w_opt_so = copy.deepcopy(weights)
#-----Set F_mf in PSO-M and non-failure case in SO-----
cand_mf = GraphSet()
cand_so = GraphSet()
#Setting for F_mf
for i in range(0, f):
cand_mf.update(gc.len(E - i))
cand_select = gc.len(E - f)
for cnt in range(0, m_np):
rand_graph = next(cand_select.rand_iter())
cand_mf.add(rand_graph)
cand_select.remove(rand_graph)
#Setting non-failure set
cand_so = GraphSet()
cand_so.update(gc.len(E))
# for i in cand_so:
# print(i)
# print("total {0} patterns to consider".format(cand_mf.len()))
# print("total {0} patterns to consider".format(cand_so.len()))
# for i in cand_mf:
# print(i)
for loop in range(0, I_max):
tl = []
R_min_global = np.inf
for itr_cand in range(1):
cand_list = GraphSet()
#fより小さい故障本数を持つものはcand_listへ
for i in range(0, f):
cand_list.update(gc.len(E - i))
#print(cand_list.len())
#f本故障はm_npの数だけ抽出（ひとまずランダムに）
cand_select = gc.len(E - f)
#print(cand_select.len())
for cnt in range(0, m_np):
rand_graph = next(cand_select.rand_iter())
cand_list.add(rand_graph)
cand_select.remove(rand_graph)
print("total {0} patterns to consider".format(cand_list.len()))
for i in cand_list:
print(i)
#-------------Optimization------------------
I_max = 5
tl = []
R_min = np.inf
MAX_loop = 100
weights_opt = copy.deepcopy(weights)
for i in range(0, I_max):
C_cnt = 0
C_max = 15
