/
hmm_utils.py
85 lines (68 loc) · 2.86 KB
/
hmm_utils.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
import os
import nltk
from tag_utils import sets_of_tags, serialize_tags
import cPickle as pickle
import tree_utils
import cmd_utils
def prob_of_all_transitions(transitions, counts, gram_size=2):
transitions = ['START'] + transitions
probs = []
for i in range(0, len(transitions) - gram_size + 1):
sub_transitions = transitions[i:(i+gram_size)]
probs.append(prob_of_transition(sub_transitions, counts))
return probs
def prob_of_transition(transition, counts):
top = serialize_tags(transition)
count_top = counts[top]
bottom = serialize_tags(transition[:-1])
count_bottom = counts[bottom]
prob = float(count_top) / count_bottom
return prob
def store_transitions(tags):
if not hasattr(store_transitions, '_counts'):
store_transitions._counts = dict(START=0)
store_transitions._counts['START'] += 1
for a_chunk_size in range(1, 4):
for set_of_tags in sets_of_tags(tags, chunk_size=min(a_chunk_size, len(tags))):
serialized = serialize_tags(set_of_tags)
store_transitions._counts.setdefault(serialized, 0)
store_transitions._counts[serialized] += 1
def get_leaf_transitions():
file_name = 'penn_leaf_transition_counts.data'
try:
f = open(os.path.join('cache', file_name), 'rb')
data = pickle.load(f)
f.close()
return data
except (IOError, EOFError):
from tag_utils import is_valid_tag
cmd_utils.log("Building leaf counts from Penn Treebank corpus", 1)
f = open(os.path.join('cache', file_name), 'wb')
for sentence in nltk.corpus.treebank.parsed_sents():
leaves = list(sentence.subtrees(lambda x: len(x) > 0 and isinstance(x[0], basestring)))
leaves = [n[0].node.split("-")[0] for n in leaves if n.node not in is_valid_tag(n[0].node)]
leaves = ['START'] + leaves
cmd_utils.log("Finished building tag counts", 1)
pickle.dump(store_transitions._counts, f)
f.close()
return store_transitions._counts
def get_transition_counts():
file_name = 'penn_transition_counts.data'
try:
f = open(os.path.join('cache', file_name), 'rb')
data = pickle.load(f)
f.close()
return data
except (IOError, EOFError):
cmd_utils.log("Building counts from Penn Treebank corpus", 1)
f = open(os.path.join('cache', file_name), 'wb')
for sentence in nltk.corpus.treebank.parsed_sents():
all_transitions = tree_utils.transitions_in_tree(sentence)
for transitions in all_transitions:
transitions = ['START'] + transitions
if len(transitions) > 1:
store_transitions(transitions)
cmd_utils.log("Finished building tag counts", 1)
pickle.dump(store_transitions._counts, f)
f.close()
return store_transitions._counts