spaCy/spacy/index.pyx
2014-12-16 22:46:55 +11:00

128 lines
4.2 KiB
Cython

"""Create a term-document matrix"""
cimport cython
from libc.string cimport memmove
from cymem.cymem cimport Address
from .lexeme cimport Lexeme, get_attr
from .tokens cimport TokenC
from .typedefs cimport hash_t
from preshed.maps cimport MapStruct, Cell, map_get, map_set, map_init
cdef class Index:
def __init__(self, attr_id_t attr_id):
self.attr_id = attr_id
self.max_value = 0
cpdef int count(self, Tokens tokens) except -1:
cdef PreshCounter counts = PreshCounter(2 ** 8)
cdef attr_id_t attr_id = self.attr_id
cdef attr_t term
cdef int i
for i in range(tokens.length):
term = get_attr(tokens.data[i].lex, attr_id)
counts.inc(term, 1)
if term > self.max_value:
self.max_value = term
cdef count_t count
cdef count_vector_t doc_counts
for term, count in counts:
doc_counts.push_back(pair[id_t, count_t](term, count))
self.counts.push_back(doc_counts)
cdef class PosMemory:
def __init__(self, tag_names):
self.tag_names = tag_names
self.nr_tags = len(tag_names)
self.mem = Pool()
self._counts = PreshCounter()
self._pos_counts = PreshCounter()
def __getitem__(self, ids):
cdef id_t[2] ngram
ngram[0] = ids[0]
ngram[1] = ids[1]
cdef hash_t ngram_key = hash64(ngram, 2 * sizeof(id_t), 0)
cdef hash_t[2] pos_context
pos_context[0] = ngram_key
counts = {}
cdef id_t i
for i, tag in enumerate(self.tag_names):
pos_context[1] = <hash_t>i
key = hash64(pos_context, sizeof(hash_t) * 2, 0)
count = self._pos_counts[key]
counts[tag] = count
return counts
@cython.cdivision(True)
def iter_ngrams(self, float min_acc=0.99, count_t min_freq=10):
cdef Address counts_addr = Address(self.nr_tags, sizeof(count_t))
cdef count_t* counts = <count_t*>counts_addr.ptr
cdef MapStruct* ngram_counts = self._counts.c_map
cdef hash_t ngram_key
cdef count_t ngram_freq
cdef int best_pos
cdef float acc
cdef int i
for i in range(ngram_counts.length):
ngram_key = ngram_counts.cells[i].key
ngram_freq = <count_t>ngram_counts.cells[i].value
if ngram_key != 0 and ngram_freq >= min_freq:
best_pos = self.find_best_pos(counts, ngram_key)
acc = counts[best_pos] / ngram_freq
if acc >= min_acc:
yield counts[best_pos], ngram_key, best_pos
cpdef int count(self, Tokens tokens) except -1:
cdef int i
cdef TokenC* t
for i in range(tokens.length):
t = &tokens.data[i]
if t.lex.prob != 0 and t.lex.prob >= -14:
self.inc(t, 1)
cdef int inc(self, TokenC* word, count_t inc) except -1:
cdef hash_t[2] ngram_pos_context
cdef hash_t ngram_key = self._ngram_key(word)
ngram_pos_context[0] = ngram_key
ngram_pos_context[1] = <hash_t>word.pos
ngram_pos_key = hash64(ngram_pos_context, 2 * sizeof(hash_t), 0)
self._counts.inc(ngram_key, inc)
self._pos_counts.inc(ngram_pos_key, inc)
cdef int find_best_pos(self, count_t* counts, hash_t ngram_key) except -1:
cdef hash_t[2] unhashed_key
unhashed_key[0] = ngram_key
cdef count_t total = 0
cdef hash_t key
cdef int pos
cdef int best
cdef int mode = 0
for pos in range(self.nr_tags):
unhashed_key[1] = <hash_t>pos
key = hash64(unhashed_key, sizeof(hash_t) * 2, 0)
count = self._pos_counts[key]
counts[pos] = count
if count >= mode:
mode = count
best = pos
total += count
return best
cdef count_t ngram_count(self, TokenC* word) except -1:
cdef hash_t ngram_key = self._ngram_key(word)
return self._counts[ngram_key]
cdef hash_t _ngram_key(self, TokenC* word) except 0:
cdef id_t[2] context
context[0] = word.lex.sic
context[1] = word[-1].lex.sic
return hash64(context, sizeof(id_t) * 2, 0)