def actree(FRA_database, excludefile):
"""
create actree for muti-string-search.
Parameters
----------
FRA_database: str
database txt file of FRA.
excludefile: str
exclude names from excludefile,
some words are not abbr of some proteins.
Returns
-------
tree
ahocorasick keywordTree.
lower_name_dic: dict
map of keyword to protein information.
"""
tree_nodes, lower_name_dic = actree_pre(FRA_database, excludefile)
tree = ahocorasick.KeywordTree()
for node in tree_nodes:
tree.add(node)
tree.make()
return tree, lower_name_dic
def ahocorasick_test():
"""
test the use of ahocorasick
"""
tree = ahocorasick.KeywordTree()
tree.add("alpha")
tree.add("alpha beta")
tree.add("gamma")
tree.make()
result = tree.search("I went to alpha beta the other day to pick up some \
spam")
print(result)
result = tree.search_long("I went to alpha beta the other day to pick up \
some spam")
print(result)
result = tree.search("and also got some alphabet soup")
print(result)
result = tree.search("but no waffles")
print(result)
result = tree.search_long("on, gamma rays are not tasty")
print(result)
result = tree.findall("I went to alpha beta to pick up alphabet soup")
for match in result:
print(match)
def load(self):
"""Load entities from file to Aho-Corasick tree"""
assert FLAGS.entities_path
f = codecs.open(FLAGS.entities_path,
encoding=FLAGS.config_encoding,
mode='r')
lines = f.read().split('\n')
f.close()
blacklist_pattern = re.compile(r'^[a-zA-Z0-9]{,4}$')
self.tree = ahocorasick.KeywordTree()
self.weights = {}
for line in lines:
parts = line.strip().split('\t ')
if len(parts) == 1:
entity = line
weight = 1.0
else:
entity = parts[0]
weight = float(parts[1])
if len(entity) < 2 or blacklist_pattern.match(entity):
continue
entity = entity.encode(FLAGS.runtime_encoding).upper()
self.tree.add(entity)
self.weights[entity] = weight
self.tree.make()
def getLabels():
tree = ahocorasick.KeywordTree()
tree.add("he")
tree.add("she")
tree.add("his")
tree.add("hers")
tree.make()
return tree.zerostate().labels()
def testEmptyConstruction(self):
"""Make sure that we can safely construct and dealloc a tree
with no initial keywords. Important because the C
implementation assumes keywords exist on its dealloc, so we
have to do some work on the back end to avoid silly segmentation
errors."""
tree = ahocorasick.KeywordTree()
del tree
def build_actries(profiles_keywords):
actries = ahocorasick.KeywordTree()
for profile_keywords in profiles_keywords:
for keyword in profile_keywords:
actries.add(keyword)
actries.make()
return actries
def __init__(self, dictFile):
self.__tree = ahocorasick.KeywordTree()
try:
fp = open(dictFile)
for line in fp:
self.__tree.add(line.rstrip("\n"))
fp.close()
self.__tree.make()
except Exception, e:
log.critical("Exception caught in Confilter.__init__ function. \
[Exception]: %s" % e)
return None
def build(name):
tree = None
count = 0
for line in open(name2fn(name), 'rb').readlines():
s = line.strip('\r\n')
if s: # empty check
if 0 == count:
tree = ahocorasick.KeywordTree()
tree.add(s)
count = count + 1
if count != 0:
tree.make()
return tree
def __init__(self, filename, delimiter):
self._tree = ahocorasick.KeywordTree()
with open(filename, 'rb') as fp:
data = fp.read()
#if not isinstance(data, unicode):
# data = data.decode('utf-8')
words = data.split(delimiter)
for word in words:
if word:
self._tree.add(word)
self._tree.make()
def __init__(self, sigs, min_fx=MIN_FIXED_STRING_LENGHT):
self.sigs = sigs
start_time = datetime.datetime.now()
self.tree = ahocorasick.KeywordTree()
for fixedstring_sig in sigs.get_fixedstrings():
if fixedstring_sig > min_fx:
self.tree.add(fixedstring_sig)
else:
logging.warning(
"Ignoring signature %s because fixed string representation is less than % i "
% (fixedstring_sig, min_fx))
self.tree.make()
end_time = datetime.datetime.now()
logging.debug("Signature download and index build time" +
str(end_time - start_time))
def solve(T):
print "Case #%d:" % (T + 1),
K, W, L = map(int, raw_input().split())
key = raw_input()
word = raw_input()
tree = ahocorasick.KeywordTree()
tree.add(word)
tree.make()
MAX = 0
num = K**L
SUM = 0
for n in itertools.product(key, repeat=L):
mam = "".join(n)
ter = len(re.findall('(?=%s)' % word, mam))
SUM += ter
MAX = max(MAX, ter)
print "%.8f" % (MAX - ((SUM + 0.0) / num))
def MultipleStringMatch(patterns, corpus):
"""Search a list of strings in a corpus string.
Args:
patterns: A list of strings.
corpus: The text where to search for the strings.
Result:
A list of Booleans stating whether each pattern string was found in the
corpus or not.
"""
tree = ahocorasick.KeywordTree()
for word in patterns:
tree.add(word)
tree.make()
result = [False] * len(patterns)
for i, j in tree.findall(corpus):
match = corpus[i:j]
result[patterns.index(match)] = True
return result
from distutils.util import get_platform
import sys
sys.path.insert(0, "build/lib.%s-%s" % (get_platform(), sys.version[0:3]))
import ahocorasick
"""We just want to exercise the code and monitor its memory usage."""
n = 0
while True:
sys.stdout.write("iteration %s\n" % n)
sys.stdout.flush()
tree = ahocorasick.KeywordTree()
f = open("/usr/share/dict/words")
for i, word in enumerate(f):
tree.add(word.strip())
f.close()
tree.make()
tree.search("foo bar baz")
n += 1
def setUp(self):
self.tree = ahocorasick.KeywordTree()
def getZerostate():
tree = ahocorasick.KeywordTree()
tree.add("foobar")
tree.make()
return tree.zerostate()