mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-21 11:29:13 +03:00
178 lines
4.6 KiB
Cython
178 lines
4.6 KiB
Cython
# cython: infer_types=True
|
|
'''Do Levenshtein alignment, for evaluation of tokenized input.
|
|
|
|
Random notes:
|
|
|
|
r i n g
|
|
0 1 2 3 4
|
|
r 1 0 1 2 3
|
|
a 2 1 1 2 3
|
|
n 3 2 2 1 2
|
|
g 4 3 3 2 1
|
|
|
|
0,0: (1,1)=min(0+0,1+1,1+1)=0 S
|
|
1,0: (2,1)=min(1+1,0+1,2+1)=1 D
|
|
2,0: (3,1)=min(2+1,3+1,1+1)=2 D
|
|
3,0: (4,1)=min(3+1,4+1,2+1)=3 D
|
|
0,1: (1,2)=min(1+1,2+1,0+1)=1 D
|
|
1,1: (2,2)=min(0+1,1+1,1+1)=1 S
|
|
2,1: (3,2)=min(1+1,1+1,2+1)=2 S or I
|
|
3,1: (4,2)=min(2+1,2+1,3+1)=3 S or I
|
|
0,2: (1,3)=min(2+1,3+1,1+1)=2 I
|
|
1,2: (2,3)=min(1+1,2+1,1+1)=2 S or I
|
|
2,2: (3,3)
|
|
3,2: (4,3)
|
|
At state (i, j) we're asking "How do I transform S[:i+1] to T[:j+1]?"
|
|
|
|
We know the costs to transition:
|
|
|
|
S[:i] -> T[:j] (at D[i,j])
|
|
S[:i+1] -> T[:j] (at D[i+1,j])
|
|
S[:i] -> T[:j+1] (at D[i,j+1])
|
|
|
|
Further, we now we can tranform:
|
|
S[:i+1] -> S[:i] (DEL) for 1,
|
|
T[:j+1] -> T[:j] (INS) for 1.
|
|
S[i+1] -> T[j+1] (SUB) for 0 or 1
|
|
|
|
Therefore we have the costs:
|
|
SUB: Cost(S[:i]->T[:j]) + Cost(S[i]->S[j])
|
|
i.e. D[i, j] + S[i+1] != T[j+1]
|
|
INS: Cost(S[:i+1]->T[:j]) + Cost(T[:j+1]->T[:j])
|
|
i.e. D[i+1,j] + 1
|
|
DEL: Cost(S[:i]->T[:j+1]) + Cost(S[:i+1]->S[:i])
|
|
i.e. D[i,j+1] + 1
|
|
|
|
Source string S has length m, with index i
|
|
Target string T has length n, with index j
|
|
|
|
Output two alignment vectors: i2j (length m) and j2i (length n)
|
|
# function LevenshteinDistance(char s[1..m], char t[1..n]):
|
|
# for all i and j, d[i,j] will hold the Levenshtein distance between
|
|
# the first i characters of s and the first j characters of t
|
|
# note that d has (m+1)*(n+1) values
|
|
# set each element in d to zero
|
|
ring rang
|
|
- r i n g
|
|
- 0 0 0 0 0
|
|
r 0 0 0 0 0
|
|
a 0 0 0 0 0
|
|
n 0 0 0 0 0
|
|
g 0 0 0 0 0
|
|
|
|
# source prefixes can be transformed into empty string by
|
|
# dropping all characters
|
|
# d[i, 0] := i
|
|
ring rang
|
|
- r i n g
|
|
- 0 0 0 0 0
|
|
r 1 0 0 0 0
|
|
a 2 0 0 0 0
|
|
n 3 0 0 0 0
|
|
g 4 0 0 0 0
|
|
|
|
# target prefixes can be reached from empty source prefix
|
|
# by inserting every character
|
|
# d[0, j] := j
|
|
- r i n g
|
|
- 0 1 2 3 4
|
|
r 1 0 0 0 0
|
|
a 2 0 0 0 0
|
|
n 3 0 0 0 0
|
|
g 4 0 0 0 0
|
|
|
|
'''
|
|
from __future__ import unicode_literals
|
|
from libc.stdint cimport uint32_t
|
|
import numpy
|
|
cimport numpy as np
|
|
from .compat import unicode_
|
|
from murmurhash.mrmr cimport hash32
|
|
|
|
|
|
def align(S, T):
|
|
cdef int m = len(S)
|
|
cdef int n = len(T)
|
|
cdef np.ndarray matrix = numpy.zeros((m+1, n+1), dtype='int32')
|
|
cdef np.ndarray i2j = numpy.zeros((m,), dtype='i')
|
|
cdef np.ndarray j2i = numpy.zeros((n,), dtype='i')
|
|
|
|
cdef np.ndarray S_arr = _convert_sequence(S)
|
|
cdef np.ndarray T_arr = _convert_sequence(T)
|
|
|
|
fill_matrix(<int*>matrix.data,
|
|
<const int*>S_arr.data, m, <const int*>T_arr.data, n)
|
|
fill_i2j(i2j, matrix)
|
|
fill_j2i(j2i, matrix)
|
|
return matrix[-1,-1], i2j, j2i, matrix
|
|
|
|
def _convert_sequence(seq):
|
|
if isinstance(seq, numpy.ndarray):
|
|
return numpy.ascontiguousarray(seq, dtype='uint32_t')
|
|
cdef np.ndarray output = numpy.zeros((len(seq),), dtype='uint32')
|
|
cdef bytes item_bytes
|
|
for i, item in enumerate(seq):
|
|
if isinstance(item, unicode):
|
|
item_bytes = item.encode('utf8')
|
|
else:
|
|
item_bytes = item
|
|
output[i] = hash32(<void*><char*>item_bytes, len(item_bytes), 0)
|
|
return output
|
|
|
|
|
|
cdef void fill_matrix(int* D,
|
|
const int* S, int m, const int* T, int n) nogil:
|
|
m1 = m+1
|
|
n1 = n+1
|
|
for i in range(m1*n1):
|
|
D[i] = 0
|
|
|
|
for i in range(m1):
|
|
D[i*n1] = i
|
|
|
|
for j in range(n1):
|
|
D[j] = j
|
|
|
|
cdef int sub_cost, ins_cost, del_cost
|
|
for j in range(n):
|
|
for i in range(m):
|
|
i_j = i*n1 + j
|
|
i1_j1 = (i+1)*n1 + j+1
|
|
i1_j = (i+1)*n1 + j
|
|
i_j1 = i*n1 + j+1
|
|
if S[i] != T[j]:
|
|
sub_cost = D[i_j] + 1
|
|
else:
|
|
sub_cost = D[i_j]
|
|
del_cost = D[i_j1] + 1
|
|
ins_cost = D[i1_j] + 1
|
|
best = min(min(sub_cost, ins_cost), del_cost)
|
|
D[i1_j1] = best
|
|
|
|
|
|
cdef void fill_i2j(np.ndarray i2j, np.ndarray D) except *:
|
|
j = D.shape[1]-2
|
|
cdef int i = D.shape[0]-2
|
|
while i >= 0:
|
|
while D[i+1, j] < D[i+1, j+1]:
|
|
j -= 1
|
|
if D[i, j+1] < D[i+1, j+1]:
|
|
i2j[i] = -1
|
|
else:
|
|
i2j[i] = j
|
|
j -= 1
|
|
i -= 1
|
|
|
|
cdef void fill_j2i(np.ndarray j2i, np.ndarray D) except *:
|
|
i = D.shape[0]-2
|
|
cdef int j = D.shape[1]-2
|
|
while j >= 0:
|
|
while D[i, j+1] < D[i+1, j+1]:
|
|
i -= 1
|
|
if D[i+1, j] < D[i+1, j+1]:
|
|
j2i[j] = -1
|
|
else:
|
|
j2i[j] = i
|
|
i -= 1
|
|
j -= 1
|