def test_FI(self):
print("---FI---")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.fillIn_decomp(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_max_independent_set(self):
print("---maxIndependentSet---")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.minDegree_decomp(G)
S = tdlib.max_independent_set_with_treedecomposition(G, T)
def test_min_vertex_cover(self):
print("---minVertexCover--")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.minDegree_decomp(G)
S = tdlib.min_vertex_cover_with_treedecomposition(G, T, True, True)
def test_boost_MD(self):
print("---boost_MD---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
T, w = tdlib.boost_minDegree_decomp(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_PP_FI_TM(self):
print("---PP_FI_TM---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
T, w = tdlib.PP_FI_TM(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_seperator_algorithm(self):
print("---seperator_algorithm---")
for i in range(0, COUNT + 1):
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.seperator_algorithm(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_boost_MD(self):
print("---boost_MD---")
for i in range(0, COUNT + 1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
T, w = tdlib.boost_minDegree_decomp(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_MSVS_trivial(self):
print("---MSVS_trivial---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
T1, w1 = tdlib.trivial_decomposition(G)
T2, w2 = tdlib.MSVS(G, T1)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T2), True)
def test_PP_FI_TM(self):
print("---PP_FI_TM---")
for i in range(0, COUNT + 1):
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.PP_FI_TM(G)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_LB7(self):
print("---LBPC_deltaC---")
for i in range(0, COUNT+1):
if base.skip(PREFIX, i, lambda x,y: x > 300 or y > 300):
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
tdlib.lower_bound(G, "LBPC_deltaC")
def test_min_vertex_cover(self):
print("---minVertexCover--")
for i in range(0, COUNT + 1):
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.minDegree_decomp(G)
S = tdlib.min_vertex_cover_with_treedecomposition(G, T)
def test_max_independent_set(self):
print("---maxIndependentSet---")
for i in range(0, COUNT + 1):
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.minDegree_decomp(G)
S = tdlib.max_independent_set_with_treedecomposition(G, T)
def test_PP(self):
print("---PP---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
G_, B, lb = tdlib.preprocessing(G)
if G.vertices() is []:
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_MSVS_trivial(self):
print("---MSVS_trivial---")
for i in range(0, COUNT + 1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
T1, w1 = tdlib.trivial_decomposition(G)
T2, w2 = tdlib.MSVS(G, T1)
self.assertEqual(tdlib.is_valid_treedecomposition(G, T2), True)
def test_PP(self):
print("---PP---")
for i in range(0, COUNT + 1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
G_, B, lb = tdlib.preprocessing(G)
if G.vertices() is []:
self.assertEqual(tdlib.is_valid_treedecomposition(G, T), True)
def test_LB7(self):
print("---LBPC_deltaC---")
for i in range(0, COUNT + 1):
if base.skip(PREFIX, i, lambda x, y: x > 300 or y > 300):
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
tdlib.lower_bound(G, "LBPC_deltaC")
def test_conversion(self):
print("---conversion---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
T1, w1 = tdlib.minDegree_decomp(G)
O = tdlib.treedec_to_ordering(T1)
T2, w2 = tdlib.ordering_to_treedec(G, O)
self.assertEqual(w1, w2)
def test_conversion(self):
print("---conversion---")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
T1, w1 = tdlib.minDegree_decomp(G)
O = tdlib.treedec_to_ordering(T1)
T2, w2 = tdlib.ordering_to_treedec(G, O)
self.assertEqual(w1, w2)
def test_min_coloring(self):
print("---minColoring--")
for i in range(0, COUNT + 1):
if i == 999: #huge graph
continue
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
base.print_graph_name(PREFIX, i)
T, w = tdlib.minDegree_decomp(G)
S = tdlib.min_coloring_with_treedecomposition(G, T)
def test_long1(self):
print("---generic search - FILL config---")
for i in range(0, COUNT_NETWORKS+1):
if base.skip(PREFIX_NETWORKS, i, lambda x,y: x > 100 or y > 2000):
continue
base.print_graph_name(PREFIX_NETWORKS, i)
G = Graph(eval(PREFIX_NETWORKS+".V_"+str(i)), eval(PREFIX_NETWORKS+".E_"+str(i)))
tdlib.generic_elimination_search_p17_jumper(G, MAX_NODES, MAX_ORDERINGS)
print("")
def test_max_clique(self):
print("---max_clique---")
for i in range(0, COUNT + 1):
if base.skip(PREFIX, i, lambda x, y: y > 2000):
print("skip.. ")
base.print_graph_name(PREFIX, i)
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
T, w = tdlib.minDegree_decomp(G)
S = tdlib.max_clique_with_treedecomposition(G, T)
def test_long1(self):
print("---generic search - PACE config---")
for i in range(0, COUNT_DIMACS + 1):
if base.skip(PREFIX_DIMACS, i, lambda x, y: x > 100 or y > 2000):
continue
base.print_graph_name(PREFIX_DIMACS, i)
G = Graph(eval(PREFIX_DIMACS + ".V_" + str(i)),
eval(PREFIX_DIMACS + ".E_" + str(i)))
tdlib.generic_elimination_search_p17_jumper(
G, MAX_NODES, MAX_ORDERINGS)
print("")
def test_min_vertex_cover(self):
print("---vertex_cover---")
for i in range(0, COUNT + 1):
if base.skip(PREFIX, i, lambda x, y: y > 2000):
print("skip.. ")
base.print_graph_name(PREFIX, i)
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
T, w = tdlib.minDegree_decomp(G)
if w > 17:
print("...tw > 17, skipping...")
continue
S = tdlib.min_vertex_cover_with_treedecomposition(G, T)
def test_min_dominating_set(self):
print("---dominating_set---")
for i in range(0, COUNT + 1):
if i == 91:
continue
if base.skip(PREFIX, i, lambda x, y: y > 2000):
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
T, w = tdlib.minDegree_decomp(G)
if w > 8:
print("...tw > 8, skipping...")
continue
S = tdlib.min_dominating_set_with_treedecomposition(G, T)
def test_min_vertex_cover(self):
print("---vertex_cover---")
for i in range(0, COUNT+1):
if i == 91:
continue
if base.skip(PREFIX, i, lambda x,y: y > 10000):
continue
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
T, w = tdlib.minDegree_decomp(G)
if w > 25:
print("...tw > 25, skipping...")
continue
S = tdlib.min_vertex_cover_with_treedecomposition(G, T)
print(str(S))
def test_max_clique(self):
print("---max_clique---")
max_vc = 0
avg_vc = 0.0
max_time = 0
avg_time = 0.0
passed = 0
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
start = time.time()
T, w = tdlib.minDegree_decomp(G)
print("...width " + str(w))
if w > 30:
print("......skip")
continue
S = tdlib.max_clique_with_treedecomposition(G, T)
end = time.time()
t = end-start
max_vc = len(S) if len(S) > max_vc else max_vc
avg_vc += len(S)
max_time = t if t > max_time else max_time
avg_time += t
avg_vc /= (COUNT-passed)
avg_time /= (COUNT-passed)
print("max clique: " + str(max_vc))
print("avg clique: " + str(avg_vc))
print("max time: " + str(max_time))
print("avg time: " + str(avg_time))
def test_max_clique(self):
print("---max_clique---")
max_vc = 0
avg_vc = 0.0
max_time = 0
avg_time = 0.0
for n in [50,100,200,250,500]:
for k in range(1, 16):
for p in [.97, .95, .90, .80, .70]:
for c in range(5):
suffix = str(n) + '_' + str(k) + '_' + str(p).replace('.','') + '_' + str(c)
base.print_graph_name(PREFIX, suffix)
G = Graph(eval(PREFIX+".V_"+str(suffix)), eval(PREFIX+".E_"+str(suffix)))
start = time.time()
T, w = tdlib.minDegree_decomp(G)
S = tdlib.max_clique_with_treedecomposition(G, T)
end = time.time()
t = end-start
max_vc = len(S) if len(S) > max_vc else max_vc
avg_vc += len(S)
max_time = t if t > max_time else max_time
avg_time += t
avg_vc /= COUNT
avg_time /= COUNT
print("max clique: " + str(max_vc))
print("avg clique: " + str(avg_vc))
print("max time: " + str(max_time))
print("avg time: " + str(avg_time))
def test_min_vertex_cover(self):
print("---vertex_cover---")
max_n = 0
avg_n = 0.0
max_m = 0
avg_m = 0.0
max_vc = 0
avg_vc = 0.0
max_tw = 0
avg_tw = 0.0
max_time = 0
avg_time = 0.0
Ns = list()
Ms = list()
VCs = list()
TWs = list()
TIMEs = list()
for i in range(0, COUNT + 1):
#for i in range(1224, 1752+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX + ".V_" + str(i)),
eval(PREFIX + ".E_" + str(i)))
start = time.time()
#T, w = tdlib.minDegree_decomp(G)
T, w = tdlib.PP_FI_TM(G)
s, S = tdlib.min_vertex_cover_with_treedecomposition2(G, T, False)
end = time.time()
t = end - start
max_n = len(G.vertices()) if len(G.vertices()) > max_n else max_n
avg_n += len(G.vertices())
Ns.append(len(G.vertices()))
max_m = len(G.edges()) if len(G.edges()) > max_m else max_m
avg_m += len(G.edges())
Ms.append(len(G.edges()))
max_vc = s if s > max_vc else max_vc
avg_vc += s
VCs.append(s)
max_tw = w if w > max_tw else max_tw
avg_tw += w
TWs.append(w)
max_time = t if t > max_time else max_time
avg_time += t
TIMEs.append(t)
#COUNT = 1752-1224
avg_n /= COUNT
avg_m /= COUNT
avg_vc /= COUNT
avg_tw /= COUNT
avg_time /= COUNT
med_n = median(Ns)
med_m = median(Ms)
med_vc = median(VCs)
med_tw = median(TWs)
med_time = median(TIMEs)
print("avg n: " + str(avg_n))
print("med n: " + str(med_n))
print("max n: " + str(max_n))
print("")
print("avg m: " + str(avg_m))
print("med m: " + str(med_m))
print("max m: " + str(max_m))
print("")
print("avg tw: " + str(avg_tw))
print("med tw: " + str(med_tw))
print("max tw: " + str(max_tw))
print("")
print("avg vc: " + str(avg_vc))
print("med vc: " + str(med_vc))
print("max vc: " + str(max_vc))
print("")
print("avg time: " + str(avg_time))
print("med time: " + str(med_time))
print("max time: " + str(max_time))
def test_LB3(self):
print("---deltaC_least_c---")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
tdlib.lower_bound(G, "deltaC_least_c")
def test_LB4(self):
print("---LBN_deltaC---")
for i in range(0, COUNT+1):
base.print_graph_name(PREFIX, i)
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
tdlib.lower_bound(G, "LBN_deltaC")
def test_LB4(self):
print("---LBN_deltaC---")
for i in range(0, COUNT+1):
G = Graph(eval(PREFIX+".V_"+str(i)), eval(PREFIX+".E_"+str(i)))
base.print_graph_name(PREFIX, i)
tdlib.lower_bound(G, "LBN_deltaC")
