def make_zssNode_from_tuple(t):
"""Convert my tuple representation into the Node object
representation used in zss."""
n = Node(t[0])
for s in t[1:]:
n.addkid(make_zssNode_from_tuple(s))
return n
def addnode(t, i):
if i >= 0:
n = ZSNode(names[i])
else:
n = ZSNode('c')
tn = t[-i - 1]
for k in [tn.left, tn.right]:
n.addkid(addnode(t, k))
return n
def randtree(depth=2, alpha='abcdefghijklmnopqrstuvwxyz', repeat=2, width=2):
labels = [''.join(x) for x in itertools.product(alpha, repeat=repeat)]
shuffle(labels)
labels = (x for x in labels)
root = Node("root")
p = [root]
c = list()
for x in xrange(depth - 1):
for y in p:
for z in xrange(randint(1, 1 + width)):
n = Node(labels.next())
y.addkid(n)
c.append(n)
p = c
c = list()
return root
def tree4():
return (Node("f").addkid(
Node("d").addkid(Node("q")).addkid(Node("c").addkid(
Node("b")))).addkid(Node("e")))
def tree3():
return (Node("a").addkid(
Node("d").addkid(Node("f")).addkid(Node("c").addkid(
Node("b")))).addkid(Node("e")))
def T(tree):
root = Node(tree.get_key())
for c in tree.get_children():
root.addkid(T(c))
return root
def _dict2zt(d):
n = ZSNode(d['lab'])
for kn in d['kids']:
n.addkid(_dict2zt(kn))
return n
def test_incorrect_behavior_regression():
A = (Node("a").addkid(Node("b").addkid(Node("x")).addkid(Node("y"))))
B = (Node("a").addkid(Node("x")).addkid(Node("b").addkid(Node("y"))))
dist = compare.distance(A, B)
print dist
assert dist == 2
def test_simplelabelchange():
A = (Node("f").addkid(
Node("a").addkid(Node("h")).addkid(Node("c").addkid(
Node("l")))).addkid(Node("e")))
B = (Node("f").addkid(
Node("a").addkid(Node("d")).addkid(Node("r").addkid(
Node("b")))).addkid(Node("e")))
dist = compare.distance(A, B)
print dist
assert dist == 3
def test_paper_tree():
A = (Node("f").addkid(
Node("d").addkid(Node("a")).addkid(Node("c").addkid(
Node("b")))).addkid(Node("e")))
B = (Node("f").addkid(
Node("c").addkid(Node("d").addkid(Node("a")).addkid(
Node("b")))).addkid(Node("e")))
#print A
#print
#print B
dist = compare.distance(A, B)
assert dist == 2
def test_empty_tree_distance():
assert compare.distance(Node(''), Node('')) == 0
assert compare.distance(Node('a'), Node('')) == 1
assert compare.distance(Node(''), Node('b')) == 1
