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Diffstat (limited to 'python/cdec/vectors.pxi')
-rw-r--r-- | python/cdec/vectors.pxi | 151 |
1 files changed, 151 insertions, 0 deletions
diff --git a/python/cdec/vectors.pxi b/python/cdec/vectors.pxi new file mode 100644 index 00000000..46f58fd4 --- /dev/null +++ b/python/cdec/vectors.pxi @@ -0,0 +1,151 @@ +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 |