def gtype_distance(gt):
n = len(gt)
gt_dist = np.zeros((n,n), dtype=int)
for i,gi in enumerate(gt):
for j,gj in enumerate(gt):
gt_dist[i,j] = min(strdist(gi,gj),strdist(gi,gj[::-1]))
return gt_dist
def treedist(i, j):
Al = A.lmds
Bl = B.lmds
An = A.nodes
Bn = B.nodes
m = i - Al[i] + 2
n = j - Bl[j] + 2
fd = forestdist = np.zeros((m,n), int)
ioff = Al[i] - 1
joff = Bl[j] - 1
for x in xrange(1, m): # δ(l(i1)..i, θ) = δ(l(1i)..1-1, θ) + γ(v → λ)
fd[x][0] = fd[x-1][0] + strdist(An[x-1].label, '')
for y in xrange(1, n): # δ(θ, l(j1)..j) = δ(θ, l(j1)..j-1) + γ(λ → w)
fd[0][y] = fd[0][y-1] + strdist('', Bn[y-1].label)
for x in xrange(1, m): ## the plus one is for the xrange impl
for y in xrange(1, n):
# only need to check if x is an ancestor of i
# and y is an ancestor of j
if Al[i] == Al[x+ioff] and Bl[j] == Bl[y+joff]:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..i-1, l(j1)..j-1) + γ(v → w)
# +-
fd[x][y] = min(
fd[x-1][y] + strdist(An[x+ioff].label, ''),
fd[x][y-1] + strdist('', Bn[y+joff].label),
fd[x-1][y-1] + strdist(An[x+ioff].label, Bn[y+joff].label)
)
treedists[x+ioff][y+joff] = fd[x][y]
else:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..l(i)-1, l(j1)..l(j)-1)
# | + treedist(i1,j1)
# +-
p = Al[x+ioff]-1-ioff
q = Bl[y+joff]-1-joff
#print (p, q), (len(fd), len(fd[0]))
fd[x][y] = min(
fd[x-1][y] + strdist(An[x+ioff].label, ''),
fd[x][y-1] + strdist('', Bn[y+joff].label),
fd[p][q] + treedists[x+ioff][y+joff]
)
def treedist(i, j):
Al = A.lmds
Bl = B.lmds
An = A.nodes
Bn = B.nodes
m = i - Al[i] + 2
n = j - Bl[j] + 2
fd = forestdist = np.zeros((m, n), int)
ioff = Al[i] - 1
joff = Bl[j] - 1
for x in xrange(1, m): # δ(l(i1)..i, θ) = δ(l(1i)..1-1, θ) + γ(v → λ)
fd[x][0] = fd[x - 1][0] + strdist(An[x - 1].label, '')
for y in xrange(1, n): # δ(θ, l(j1)..j) = δ(θ, l(j1)..j-1) + γ(λ → w)
fd[0][y] = fd[0][y - 1] + strdist('', Bn[y - 1].label)
for x in xrange(1, m): ## the plus one is for the xrange impl
for y in xrange(1, n):
# only need to check if x is an ancestor of i
# and y is an ancestor of j
if Al[i] == Al[x + ioff] and Bl[j] == Bl[y + joff]:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..i-1, l(j1)..j-1) + γ(v → w)
# +-
fd[x][y] = min(
fd[x - 1][y] + strdist(An[x + ioff].label, ''),
fd[x][y - 1] + strdist('', Bn[y + joff].label),
fd[x - 1][y - 1] +
strdist(An[x + ioff].label, Bn[y + joff].label))
treedists[x + ioff][y + joff] = fd[x][y]
else:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..l(i)-1, l(j1)..l(j)-1)
# | + treedist(i1,j1)
# +-
p = Al[x + ioff] - 1 - ioff
q = Bl[y + joff] - 1 - joff
#print (p, q), (len(fd), len(fd[0]))
fd[x][y] = min(
fd[x - 1][y] + strdist(An[x + ioff].label, ''),
fd[x][y - 1] + strdist('', Bn[y + joff].label),
fd[p][q] + treedists[x + ioff][y + joff])
def weird_dist(A, B):
return 10 * strdist(A, B)
def weird_dist(A, B):
return 10*strdist(A, B)
def compare_trees(tree_size, number_of_trees):
print('Create instances')
create_random_binary_trees(tree_size, number_of_trees)
file_name = 'examples/example_trees_size_' + tree_size.__str__() + '.json'
print('Instances created successfully!')
print('Instances can be found in ' + file_name)
if os.path.exists(file_name):
with open(file_name) as tree_file:
tree_list = json.load(tree_file)
#Only compare with ated
keys = {"ATED": 0.5, "CTED": 0, "STED": 1}
size_start = time.time()
for i in range(0, min(len(tree_list),number_of_trees)):
#Loop output
loop_time = time.time()
j = i + 1
needed_time = loop_time - size_start
estimation = needed_time / j * number_of_trees
print("(" + str(timedelta(seconds=round(needed_time))) + " / " + str(timedelta(seconds=round(estimation)))
+ ") (" + str(j) + "/" + str(number_of_trees) + ") tree size: " + str(tree_size))
tree_one = create_binary_tree_from_list(tree_list[i]['one'])
tree_two = create_binary_tree_from_list(tree_list[i]['two'])
if ('one_adapted' not in tree_list[i]):
tree_one_adapted = adapt_tree_one(tree_one, tree_two)
tree_list[i]['one_adapted'] = tree_one_adapted.get_tree_list(tree_one_adapted)
tree_one_adapted = create_binary_tree_from_list(tree_list[i]['one_adapted'])
if ('#GRFRestr' not in tree_list[i]):
I = compute_invalid_edges(tree_one.get_clusters(1), tree_two.get_clusters(1))
tree_list[i]['#GRFRestr'] = len(I)
#Compute gRF distance with varying 'k'
for k in [1,4,16,64]:
key = 'GRF' + str(k)
if (key not in tree_list[i] and tree_size <= 32):
start = time.time()
print( "k is " + str(k))
lpProblem = createLPproblem(tree_one, tree_two, k)
lp = lpProblem.get("lp")
time_creation = time.time() - start
lp.solve()
c1 = lpProblem.get("c1")
c2 = lpProblem.get("c2")
if LpStatus[lp.status] == "Optimal":
end = time.time()
varsdict = {}
for v in lp.variables():
varsdict[v.name] = v.varValue
gRF = 0
for m in range(0,len(c1)):
gRF = gRF + 1
for l in range(0,len(c2)):
kex = "x_" + str(m) + "_" + str(l)
if (varsdict[kex] == 1.0):
cup = [i for i in c1[m] if i in c2[l]]
gRF = gRF - len(cup)/(len(c1[m]) + len(c2[l]) - len(cup))
for m in range(0,len(c2)):
used = 0
for l in range(0,len(c1)):
kex = "x_" + str(l) + "_" + str(m)
if (varsdict[kex] == 1.0):
used = 1
if used == 0:
gRF = gRF + 1
solution = {'clusterOne': c1,
'clusterTwo': c2,
'vardsDict': json.dumps(varsdict)}
tree_list[i]['GRF' + str(k)] = {"cost": gRF, "time": end - start,
"time_creation": time_creation}
#Compute all TEDs defined in variable 'keys'
for key,k in keys.items():
if (key not in tree_list[i]):
start = time.time()
print(key)
cost = zss.distance(
tree_one, tree_two, tree_one.get_children,insert_cost_delta(k), remove_cost_delta(k),
update_cost=lambda a, b: strdist(ExtendedNode.get_label(a), ExtendedNode.get_label(b)))
end = time.time()
tree_list[i][key] = {"cost": cost, "time": end - start}
key2 = key + "_a"
if (key2 not in tree_list[i]):
start = time.time()
print(key2)
cost = zss.distance(
tree_one_adapted, tree_two, tree_one.get_children,insert_cost_delta(k), remove_cost_delta(k),
update_cost=lambda a, b: strdist(ExtendedNode.get_label(a), ExtendedNode.get_label(b)))
end = time.time()
tree_list[i][key2] = {"cost": cost, "time": end - start}
with open(file_name, 'w') as outfile:
json.dump(tree_list, outfile)
def remove_cost(node):
if (ExtendedNode.get_label(node) != 0):
return strdist(ExtendedNode.get_label(node), '')
else:
return delta
def insert_cost(node):
if (ExtendedNode.get_label(node) != 0):
return strdist('', ExtendedNode.get_label(node))
else:
return delta
def weird_update_dist(A, B):
return strdist(A,B)
def treedist(i, j):
if i in treedists and j in treedists[i]: return treedists[i][j]
def s(i, j, v):
if i not in treedists: treedists[i] = dict()
treedists[i][j] = v
fd = forestdists = dict()
def gfd(a, b): # get an item from the forest dists array
if (a,b) in forestdists:
return forestdists[(a,b)]
if a[0] >= a[1] and b[0] >= b[1]: # δ(θ, θ) = 0
return 0
if b[0] >= b[1]:
return forestdists[(a,(0,0))]
if a[0] >= a[1]:
return forestdists[((0,0),b)]
raise KeyError, (a,b)
Al = A.lmds
Bl = B.lmds
An = A.nodes
Bn = B.nodes
for x in xrange(Al[i], i+1): # δ(l(i1)..i, θ) = δ(l(1i)..1-1, θ) + γ(v → λ)
fd[(Al[i], x), (0, 0)] = (
gfd((Al[i],x-1), (0, 0)) + strdist(An[x].label, '')
)
for y in xrange(Bl[j], j+1): # δ(θ, l(j1)..j) = δ(θ, l(j1)..j-1) + γ(λ → w)
fd[(0, 0), (Bl[j], y)] = (
gfd((0,0), (Bl[j],y-1)) + strdist('', Bn[y].label)
)
for x in xrange(Al[i], i+1): ## the plus one is for the xrange impl
for y in xrange(Bl[j], j+1):
# only need to check if x is an ancestor of i
# and y is an ancestor of j
if (A.lmds[i] == A.lmds[x] and B.lmds[j] == B.lmds[y] or
(x == i and y == j)):
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..i-1, l(j1)..j-1) + γ(v → w)
# +-
fd[((Al[i], x), (Bl[j], y))] = min(
(
gfd((Al[i],x-1), (Bl[j], y))
+ strdist(An[x].label, '')
),
(
gfd((Al[i], x), (Bl[j],y-1))
+ strdist('', Bn[y].label)
),
(
gfd((Al[i],x-1), (Bl[j],y-1))
+strdist(An[x].label, Bn[y].label)
)
)
s(x, y, fd[((Al[i], x), (Bl[j], y))])
else:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..l(i)-1, l(j1)..l(j)-1) + treedist(i,j)
# +-
fd[((Al[i], x), (Bl[j], y))] = min(
(
gfd((Al[i],x-1), (Bl[j], y))
+ strdist(An[x].label, '')
),
(
gfd((Al[i], x), (Bl[j],y-1))
+ strdist('', Bn[y].label)
),
(
gfd((Al[i],Al[x]-1), (Bl[j],Bl[y]-1))
+ treedist(x, y)
)
)
if i in treedists and j in treedists[i]:
return treedists[i][j]
else:
print 'WTF'
print (A.lmds[i], i), (B.lmds[j], j), tuple(xrange(A.lmds[i], i+1)), tuple(xrange(B.lmds[j], j+1))
print x,y
print treedists
sys.exit(1)
def my_distance(node1, node2):
return strdist(node1, node2)
def weird_dist(A, B):
return strdist(A, B)
def treedist(i, j):
if i in treedists and j in treedists[i]: return treedists[i][j]
def s(i, j, v):
if i not in treedists: treedists[i] = dict()
treedists[i][j] = v
fd = forestdists = dict()
def gfd(a, b): # get an item from the forest dists array
if (a,b) in forestdists:
return forestdists[(a,b)]
if a[0] >= a[1] and b[0] >= b[1]: # δ(θ, θ) = 0
return 0
if b[0] >= b[1]:
return forestdists[(a,(0,0))]
if a[0] >= a[1]:
return forestdists[((0,0),b)]
raise KeyError, (a,b)
Al = A.lmds
Bl = B.lmds
An = A.nodes
Bn = B.nodes
for x in xrange(Al[i], i+1): # δ(l(i1)..i, θ) = δ(l(1i)..1-1, θ) + γ(v → λ)
fd[(Al[i], x), (0, 0)] = (
gfd((Al[i],x-1), (0, 0)) + strdist(An[x].label, '')
)
for y in xrange(Bl[j], j+1): # δ(θ, l(j1)..j) = δ(θ, l(j1)..j-1) + γ(λ → w)
fd[(0, 0), (Bl[j], y)] = (
gfd((0,0), (Bl[j],y-1)) + strdist('', Bn[y].label)
)
for x in xrange(Al[i], i+1): ## the plus one is for the xrange impl
for y in xrange(Bl[j], j+1):
# only need to check if x is an ancestor of i
# and y is an ancestor of j
if A.lmds[i] == A.lmds[x] and B.lmds[j] == B.lmds[y]:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..i-1, l(j1)..j-1) + γ(v → w)
# +-
fd[((Al[i], x), (Bl[j], y))] = min(
(
gfd((Al[i],x-1), (Bl[j], y))
+ strdist(An[x].label, '')
),
(
gfd((Al[i], x), (Bl[j],y-1))
+ strdist('', Bn[y].label)
),
(
gfd((Al[i],x-1), (Bl[j],y-1))
+strdist(An[x].label, Bn[y].label)
)
)
s(x, y, fd[((Al[i], x), (Bl[j], y))])
else:
# +-
# | δ(l(i1)..i-1, l(j1)..j) + γ(v → λ)
# δ(F1 , F2 ) = min-+ δ(l(i1)..i , l(j1)..j-1) + γ(λ → w)
# | δ(l(i1)..l(i)-1, l(j1)..l(j)-1) + treedist(i,j)
# +-
fd[((Al[i], x), (Bl[j], y))] = min(
(
gfd((Al[i],x-1), (Bl[j], y))
+ strdist(An[x].label, '')
),
(
gfd((Al[i], x), (Bl[j],y-1))
+ strdist('', Bn[y].label)
),
(
gfd((Al[i],Al[x]-1), (Bl[j],Bl[y]-1))
+ treedist(x, y)
)
)
if i in treedists and j in treedists[i]:
return treedists[i][j]
else:
print('WTF')
print(A.lmds[i], i), (B.lmds[j], j), tuple(xrange(A.lmds[i], i+1)), tuple(xrange(B.lmds[j], j+1))
print(x, y)
print(treedists)
sys.exit(1)
