Начнем с Дерева
from collections import defaultdict
def identity(x):
return x
class TreeReprMixin(object):
def __repr__(self):
base = dict(self)
return repr(base)
class PrefixTree(TreeReprMixin, defaultdict):
'''
A hash-based Prefix or Suffix Tree for testing for
sequence inclusion. This implementation works for any
slice-able sequence of hashable objects, not just strings.
'''
def __init__(self):
defaultdict.__init__(self, PrefixTree)
self.labels = set()
def add(self, sequence, label=None):
layer = self
if label is None:
label = sequence
if label:
layer.labels.add(label)
for i in range(len(sequence)):
layer = layer[sequence[i]]
if label:
layer.labels.add(label)
return self
def add_ngram(self, sequence, label=None):
if label is None:
label = sequence
for i in range(1, len(sequence) + 1):
self.add(sequence[:i], label)
def __contains__(self, sequence):
layer = self
j = 0
for i in sequence:
j += 1
if not dict.__contains__(layer, i):
break
layer = layer[i]
return len(sequence) == j
def depth_in(self, sequence):
layer = self
count = 0
for i in sequence:
if not dict.__contains__(layer, i):
print "Breaking"
break
else:
layer = layer[i]
count += 1
return count
def subsequences_of(self, sequence):
layer = self
for i in sequence:
layer = layer[i]
return layer.labels
def __iter__(self):
return iter(self.labels)
class SuffixTree(PrefixTree):
'''
A hash-based Prefix or Suffix Tree for testing for
sequence inclusion. This implementation works for any
slice-able sequence of hashable objects, not just strings.
'''
def __init__(self):
defaultdict.__init__(self, SuffixTree)
self.labels = set()
def add_ngram(self, sequence, label=None):
if label is None:
label = sequence
for i in range(len(sequence)):
self.add(sequence[i:], label=label)
Чтобы заполнить дерево, вы должны использовать метод .add_ngram.
Следующая часть немного сложнее, так как вы ищете параллельный обход строк, отслеживая координаты дерева. Чтобы все это реализовать, нам нужны некоторые функции, работающие с деревом, и строка запроса.
def overlapping_substrings(string, tree, solved=None):
if solved is None:
solved = PrefixTree()
i = 1
last = 0
matching = True
solutions = []
while i < len(string) + 1:
if string[last:i] in tree:
if not matching:
matching = True
else:
i += 1
continue
else:
if matching:
matching = False
solutions.append(string[last:i - 1])
last = i - 1
i -= 1
i += 1
if matching:
solutions.append(string[last:i])
for solution in solutions:
if solution in solved:
continue
else:
solved.add_ngram(solution)
yield solution
def slide_start(string):
for i in range(len(string)):
yield string[i:]
def seek_subtree(tree, sequence):
# Find the node of the search tree which
# is found by this sequence of items
node = tree
for i in sequence:
if i in node:
node = node[i]
else:
raise KeyError(i)
return node
def find_all_common_spans(string, tree):
# We can keep track of solutions to avoid duplicates
# and incomplete prefixes using a Prefix Tree
seen = PrefixTree()
for substring in slide_start(string):
# Drive generator forward
list(overlapping_substrings(substring, tree, seen))
# Some substrings are suffixes of other substrings which you do not
# want
compress = SuffixTree()
for solution in sorted(seen.labels, key=len, reverse=True):
# A substrings may be a suffix of another substrings, but that substrings
# is actually a repeating pattern. If a solution is
# a repeating pattern, `not solution in seek_subtree(tree, solution)` will tell us.
# Otherwise, discard the solution
if solution in compress and not solution in seek_subtree(tree, solution):
continue
else:
compress.add_ngram(solution)
return compress.labels
def search(query, corpus):
tree = SuffixTree()
if isinstance(corpus, SuffixTree):
tree = corpus
else:
for elem in corpus:
tree.add_ngram(elem)
return list(find_all_common_spans(query, tree))
Итак, теперь, чтобы сделать то, что вы хотели, сделайте следующее:
search("12345", ["51234"])
search("623456", ["12345623456"])
Если что-то неясно, пожалуйста, дайте мне знать, и я постараюсь уточнить.
person
mobiusklein
schedule
28.05.2016
