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dot_product.hpp
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1 #ifndef STAN_MATH_REV_MAT_FUN_DOT_PRODUCT_HPP
2 #define STAN_MATH_REV_MAT_FUN_DOT_PRODUCT_HPP
3
4 #include <stan/math/prim/mat/fun/Eigen.hpp>
5 #include <stan/math/prim/mat/fun/typedefs.hpp>
6 #include <stan/math/prim/mat/err/check_vector.hpp>
7 #include <stan/math/prim/mat/err/check_matching_sizes.hpp>
8 #include <stan/math/prim/scal/fun/value_of.hpp>
9 #include <stan/math/rev/core.hpp>
10 #include <stan/math/rev/mat/fun/typedefs.hpp>
11 #include <stan/math/rev/scal/fun/value_of.hpp>
12 #include <boost/utility/enable_if.hpp>
13 #include <boost/type_traits.hpp>
14 #include <vector>
15
16 namespace stan {
17 namespace math {
18
19 namespace {
20 template<typename T>
21 struct dot_product_store_type;
22
23 template<>
24 struct dot_product_store_type<var> {
25 typedef vari** type;
26 };
27
28 template<>
29 struct dot_product_store_type<double> {
30 typedef double* type;
31 };
32
33 template<typename T1, typename T2>
34 class dot_product_vari : public vari {
35 protected:
36 typename dot_product_store_type<T1>::type v1_;
37 typename dot_product_store_type<T2>::type v2_;
38 size_t length_;
39
40 inline static double var_dot(vari** v1, vari** v2,
41 size_t length) {
42 Eigen::VectorXd vd1(length), vd2(length);
43 for (size_t i = 0; i < length; i++) {
44 vd1[i] = v1[i]->val_;
45 vd2[i] = v2[i]->val_;
46 }
47 return vd1.dot(vd2);
48 }
49
50 inline static double var_dot(const T1* v1, const T2* v2,
51 size_t length) {
52 using stan::math::value_of;
53 Eigen::VectorXd vd1(length), vd2(length);
54 for (size_t i = 0; i < length; i++) {
55 vd1[i] = value_of(v1[i]);
56 vd2[i] = value_of(v2[i]);
57 }
58 return vd1.dot(vd2);
59 }
60
61 template<typename Derived1, typename Derived2>
62 inline static double var_dot(const Eigen::DenseBase<Derived1> &v1,
63 const Eigen::DenseBase<Derived2> &v2) {
64 using stan::math::value_of;
65 using stan::math::value_of;
66 Eigen::VectorXd vd1(v1.size()), vd2(v1.size());
67 for (int i = 0; i < v1.size(); i++) {
68 vd1[i] = value_of(v1[i]);
69 vd2[i] = value_of(v2[i]);
70 }
71 return vd1.dot(vd2);
72 }
73 inline void chain(vari** v1, vari** v2) {
74 for (size_t i = 0; i < length_; i++) {
75 v1[i]->adj_ += adj_ * v2_[i]->val_;
76 v2[i]->adj_ += adj_ * v1_[i]->val_;
77 }
78 }
79 inline void chain(double* v1, vari** v2) {
80 for (size_t i = 0; i < length_; i++) {
81 v2[i]->adj_ += adj_ * v1_[i];
82 }
83 }
84 inline void chain(vari** v1, double* v2) {
85 for (size_t i = 0; i < length_; i++) {
86 v1[i]->adj_ += adj_ * v2_[i];
87 }
88 }
89 inline void initialize(vari** &mem_v, const var *inv,
90 vari **shared = NULL) {
91 if (shared == NULL) {
92 mem_v = reinterpret_cast<vari**>(ChainableStack::memalloc_
93 .alloc(length_*sizeof(vari*)));
94 for (size_t i = 0; i < length_; i++)
95 mem_v[i] = inv[i].vi_;
96 } else {
97 mem_v = shared;
98 }
99 }
100 template<typename Derived>
101 inline void initialize(vari** &mem_v,
102 const Eigen::DenseBase<Derived> &inv,
103 vari **shared = NULL) {
104 if (shared == NULL) {
105 mem_v = reinterpret_cast<vari**>(ChainableStack::memalloc_
106 .alloc(length_*sizeof(vari*)));
107 for (size_t i = 0; i < length_; i++)
108 mem_v[i] = inv(i).vi_;
109 } else {
110 mem_v = shared;
111 }
112 }
113
114 inline void initialize(double* &mem_d, const double *ind,
115 double *shared = NULL) {
116 if (shared == NULL) {
117 mem_d = reinterpret_cast<double*>(ChainableStack::memalloc_
118 .alloc(length_*sizeof(double)));
119 for (size_t i = 0; i < length_; i++)
120 mem_d[i] = ind[i];
121 } else {
122 mem_d = shared;
123 }
124 }
125 template<typename Derived>
126 inline void initialize(double* &mem_d,
127 const Eigen::DenseBase<Derived> &ind,
128 double *shared = NULL) {
129 if (shared == NULL) {
130 mem_d = reinterpret_cast<double*>
131 (ChainableStack::memalloc_.alloc(length_*sizeof(double)));
132 for (size_t i = 0; i < length_; i++)
133 mem_d[i] = ind(i);
134 } else {
135 mem_d = shared;
136 }
137 }
138
139 public:
140 dot_product_vari(typename dot_product_store_type<T1>::type v1,
141 typename dot_product_store_type<T2>::type v2,
142 size_t length)
143 : vari(var_dot(v1, v2, length)), v1_(v1), v2_(v2), length_(length) {}
144
145 dot_product_vari(const T1* v1, const T2* v2, size_t length,
146 dot_product_vari<T1, T2>* shared_v1 = NULL,
147 dot_product_vari<T1, T2>* shared_v2 = NULL) :
148 vari(var_dot(v1, v2, length)), length_(length) {
149 if (shared_v1 == NULL) {
150 initialize(v1_, v1);
151 } else {
152 initialize(v1_, v1, shared_v1->v1_);
153 }
154 if (shared_v2 == NULL) {
155 initialize(v2_, v2);
156 } else {
157 initialize(v2_, v2, shared_v2->v2_);
158 }
159 }
160 template<typename Derived1, typename Derived2>
161 dot_product_vari(const Eigen::DenseBase<Derived1> &v1,
162 const Eigen::DenseBase<Derived2> &v2,
163 dot_product_vari<T1, T2>* shared_v1 = NULL,
164 dot_product_vari<T1, T2>* shared_v2 = NULL) :
165 vari(var_dot(v1, v2)), length_(v1.size()) {
166 if (shared_v1 == NULL) {
167 initialize(v1_, v1);
168 } else {
169 initialize(v1_, v1, shared_v1->v1_);
170 }
171 if (shared_v2 == NULL) {
172 initialize(v2_, v2);
173 } else {
174 initialize(v2_, v2, shared_v2->v2_);
175 }
176 }
177 template<int R1, int C1, int R2, int C2>
178 dot_product_vari(const Eigen::Matrix<T1, R1, C1> &v1,
179 const Eigen::Matrix<T2, R2, C2> &v2,
180 dot_product_vari<T1, T2>* shared_v1 = NULL,
181 dot_product_vari<T1, T2>* shared_v2 = NULL) :
182 vari(var_dot(v1, v2)), length_(v1.size()) {
183 if (shared_v1 == NULL) {
184 initialize(v1_, v1);
185 } else {
186 initialize(v1_, v1, shared_v1->v1_);
187 }
188 if (shared_v2 == NULL) {
189 initialize(v2_, v2);
190 } else {
191 initialize(v2_, v2, shared_v2->v2_);
192 }
193 }
194 virtual void chain() {
195 chain(v1_, v2_);
196 }
197 };
198 }
199
208 template<typename T1, int R1, int C1, typename T2, int R2, int C2>
209 inline
210 typename boost::enable_if_c<boost::is_same<T1, var>::value ||
211 boost::is_same<T2, var>::value, var>::type
212 dot_product(const Eigen::Matrix<T1, R1, C1>& v1,
213 const Eigen::Matrix<T2, R2, C2>& v2) {
214 stan::math::check_vector("dot_product", "v1", v1);
215 stan::math::check_vector("dot_product", "v2", v2);
216 stan::math::check_matching_sizes("dot_product",
217 "v1", v1,
218 "v2", v2);
219 return var(new dot_product_vari<T1, T2>(v1, v2));
220 }
229 template<typename T1, typename T2>
230 inline
231 typename boost::enable_if_c<boost::is_same<T1, var>::value ||
232 boost::is_same<T2, var>::value, var>::type
233 dot_product(const T1* v1, const T2* v2, size_t length) {
234 return var(new dot_product_vari<T1, T2>(v1, v2, length));
235 }
236
245 template<typename T1, typename T2>
246 inline
247 typename boost::enable_if_c<boost::is_same<T1, var>::value ||
248 boost::is_same<T2, var>::value, var>::type
249 dot_product(const std::vector<T1>& v1,
250 const std::vector<T2>& v2) {
251 stan::math::check_matching_sizes("dot_product",
252 "v1", v1,
253 "v2", v2);
254 return var(new dot_product_vari<T1, T2>(&v1[0], &v2[0], v1.size()));
255 }
256
257 }
258 }
259 #endif
core.hpp
stan::math::check_vector
bool check_vector(const char *function, const char *name, const Eigen::Matrix< T, R, C > &x)
Return true if the matrix is either a row vector or column vector.
Definition: check_vector.hpp:34
stan
Definition: log_sum_exp.hpp:8
stan::math::value_of
T value_of(const fvar< T > &v)
Return the value of the specified variable.
Definition: value_of.hpp:16
v1_
dot_product_store_type< T1 >::type v1_
Definition: dot_product.hpp:36
stan::math::AutodiffStackStorage::memalloc_
static stack_alloc memalloc_
Definition: autodiffstackstorage.hpp:16
stan::length
size_t length(const std::vector< T > &x)
Definition: length.hpp:10
check_matching_sizes.hpp
stan::math::var
Independent (input) and dependent (output) variables for gradients.
Definition: var.hpp:31
v2_
dot_product_store_type< T2 >::type v2_
Definition: dot_product.hpp:37
stan::math::initialize
void initialize(T &x, const T &v)
Definition: initialize.hpp:17
typedefs.hpp
stan::math::check_matching_sizes
bool check_matching_sizes(const char *function, const char *name1, const T_y1 &y1, const char *name2, const T_y2 &y2)
Return true if two structures at the same size.
Definition: check_matching_sizes.hpp:29
stan::math::dot_product
fvar< T > dot_product(const Eigen::Matrix< fvar< T >, R1, C1 > &v1, const Eigen::Matrix< fvar< T >, R2, C2 > &v2)
Definition: dot_product.hpp:20
Eigen.hpp
check_vector.hpp
stan::math::size
int size(const std::vector< T > &x)
Return the size of the specified standard vector.
Definition: size.hpp:17
length_
size_t length_
Definition: dot_product.hpp:38
value_of.hpp
value_of.hpp
stan::math::stack_alloc::alloc
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...
Definition: stack_alloc.hpp:166
stan::math::inv
fvar< T > inv(const fvar< T > &x)
Definition: inv.hpp:15
typedefs.hpp

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