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
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
|
from cython.operator cimport preincrement as pinc
cdef class DenseVector:
cdef vector[weight_t]* vector
cdef bint owned # if True, do not manage memory
def __init__(self):
"""DenseVector() -> Dense weight/feature vector."""
self.vector = new vector[weight_t]()
self.owned = False
def __dealloc__(self):
if not self.owned:
del self.vector
def __len__(self):
return self.vector.size()
def __getitem__(self, char* fname):
cdef int fid = FDConvert(fname)
if 0 <= fid < self.vector.size():
return self.vector[0][fid]
raise KeyError(fname)
def __setitem__(self, char* fname, float value):
cdef int fid = FDConvert(fname)
if fid < 0: raise KeyError(fname)
if self.vector.size() <= fid:
self.vector.resize(fid + 1)
self.vector[0][fid] = value
def __iter__(self):
cdef unsigned fid
for fid in range(1, self.vector.size()):
yield str(FDConvert(fid).c_str()), self.vector[0][fid]
def dot(self, SparseVector other):
"""vector.dot(SparseVector other) -> Dot product of the two vectors."""
return other.dot(self)
def tosparse(self):
"""vector.tosparse() -> Equivalent SparseVector."""
cdef SparseVector sparse = SparseVector.__new__(SparseVector)
sparse.vector = new FastSparseVector[weight_t]()
InitSparseVector(self.vector[0], sparse.vector)
return sparse
cdef class SparseVector:
cdef FastSparseVector[weight_t]* vector
def __init__(self):
"""SparseVector() -> Sparse feature/weight vector."""
self.vector = new FastSparseVector[weight_t]()
def __dealloc__(self):
del self.vector
def copy(self):
"""vector.copy() -> SparseVector copy."""
return self * 1
def __getitem__(self, char* fname):
cdef int fid = FDConvert(fname)
if fid < 0: raise KeyError(fname)
return self.vector.value(fid)
def __setitem__(self, char* fname, float value):
cdef int fid = FDConvert(fname)
if fid < 0: raise KeyError(fname)
self.vector.set_value(fid, value)
def __iter__(self):
cdef FastSparseVector[weight_t].const_iterator* it = new FastSparseVector[weight_t].const_iterator(self.vector[0], False)
cdef unsigned i
try:
for i in range(self.vector.size()):
yield (str(FDConvert(it[0].ptr().first).c_str()), it[0].ptr().second)
pinc(it[0]) # ++it
finally:
del it
def dot(self, other):
"""vector.dot(SparseVector/DenseVector other) -> Dot product of the two vectors."""
if isinstance(other, DenseVector):
return self.vector.dot((<DenseVector> other).vector[0])
elif isinstance(other, SparseVector):
return self.vector.dot((<SparseVector> other).vector[0])
raise TypeError('cannot take the dot product of %s and SparseVector' % type(other))
def __richcmp__(SparseVector x, SparseVector y, int op):
if op == 2: # ==
return x.vector[0] == y.vector[0]
elif op == 3: # !=
return not (x == y)
raise NotImplemented('comparison not implemented for SparseVector')
def __len__(self):
return self.vector.size()
def __contains__(self, char* fname):
return self.vector.nonzero(FDConvert(fname))
def __neg__(self):
cdef SparseVector result = SparseVector.__new__(SparseVector)
result.vector = new FastSparseVector[weight_t](self.vector[0])
result.vector[0] *= -1.0
return result
def __iadd__(SparseVector self, SparseVector other):
self.vector[0] += other.vector[0]
return self
def __isub__(SparseVector self, SparseVector other):
self.vector[0] -= other.vector[0]
return self
def __imul__(SparseVector self, float scalar):
self.vector[0] *= scalar
return self
def __idiv__(SparseVector self, float scalar):
self.vector[0] /= scalar
return self
def __add__(SparseVector x, SparseVector y):
cdef SparseVector result = SparseVector.__new__(SparseVector)
result.vector = new FastSparseVector[weight_t](x.vector[0] + y.vector[0])
return result
def __sub__(SparseVector x, SparseVector y):
cdef SparseVector result = SparseVector.__new__(SparseVector)
result.vector = new FastSparseVector[weight_t](x.vector[0] - y.vector[0])
return result
def __mul__(x, y):
cdef SparseVector vector
cdef float scalar
if isinstance(x, SparseVector): vector, scalar = x, y
else: vector, scalar = y, x
cdef SparseVector result = SparseVector.__new__(SparseVector)
result.vector = new FastSparseVector[weight_t](vector.vector[0] * scalar)
return result
def __div__(x, y):
cdef SparseVector vector
cdef float scalar
if isinstance(x, SparseVector): vector, scalar = x, y
else: vector, scalar = y, x
cdef SparseVector result = SparseVector.__new__(SparseVector)
result.vector = new FastSparseVector[weight_t](vector.vector[0] / scalar)
return result
|
