The zss
module provides a function (zss.distance
) that
computes the edit distance between the two given trees, as well as a small set
of utilities to make its use convenient.
If you'd like to learn more about how it works, see References below.
Brought to you by Tim Henderson ([email protected]).
Read the full documentation for more information.
You can get zss
and its soft requirements (
editdist
and numpy
>= 1.7) from PyPI:
pip install zss
Both modules are optional. editdist
uses string edit distance to
compare node labels rather than a simple equal/not-equal check, and
numpy
significantly speeds up the library. The only reason version
1.7 of numpy
is required is that earlier versions have trouble
installing on current versions of Mac OS X.
You can install zss
from the source code without dependencies in the
usual way:
python setup.py install
If you want to build the docs, you'll need to install Sphinx >= 1.0.
To compare the distance between two trees, you need:
- A tree.
- Another tree.
- A node-node distance function. By default,
zss
compares the edit distance between the nodes' labels.zss
currently only knows how to handle nodes with string labels. - Functions to let
zss.distance
traverse your tree.
Here is an example using the library's built-in default node structure and edit distance function
from zss import simple_distance, Node
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("c")
.addkid(Node("b"))))
.addkid(Node("e"))
)
assert simple_distance(A, B) == 2
Specifying custom tree formats and distance metrics is easy. The
zss.simple_distance
function takes 3 extra parameters besides the two tree
to compare:
get_children
- a function to retrieve a list of children from a node.get_label
- a function to retrieve the label object from a node.label_dist
- a function to compute the non-negative integer distance between two node labels.
#!/usr/bin/env python
import zss
try:
from editdist import distance as strdist
except ImportError:
def strdist(a, b):
if a == b:
return 0
else:
return 1
def weird_dist(A, B):
return 10*strdist(A, B)
class WeirdNode(object):
def __init__(self, label):
self.my_label = label
self.my_children = list()
@staticmethod
def get_children(node):
return node.my_children
@staticmethod
def get_label(node):
return node.my_label
def addkid(self, node, before=False):
if before: self.my_children.insert(0, node)
else: self.my_children.append(node)
return self
A = (
WeirdNode("f")
.addkid(WeirdNode("d")
.addkid(WeirdNode("a"))
.addkid(WeirdNode("c")
.addkid(WeirdNode("b"))
)
)
.addkid(WeirdNode("e"))
)
B = (
WeirdNode("f")
.addkid(WeirdNode("c")
.addkid(WeirdNode("d")
.addkid(WeirdNode("a"))
.addkid(WeirdNode("b"))
)
)
.addkid(WeirdNode("e"))
)
dist = zss.simple_distance(
A, B, WeirdNode.get_children, WeirdNode.get_label, weird_dist)
print dist
assert dist == 20
The algorithm used by zss
is taken directly from the original paper by
Zhang and Shasha. If you would like to discuss the paper, or the the tree edit
distance problem (we have implemented a few other algorithms as well) please
email the authors.
approxlib by Dr. Nikolaus Augstent contains a good Java implementation of Zhang-Shasha as well as a number of other useful tree distance algorithms.
Kaizhong Zhang and Dennis Shasha. Simple fast algorithms for the editing distance between trees and related problems. SIAM Journal of Computing, 18:1245–1262, 1989. (the original paper)