Added sparse_matrix_vector_multiply()

dlib/svm/sparse_vector.h

@@ -9,8 +9,7 @@
 #include "../algs.h"
 #include <vector>
 #include <map>
-// This is included just so we can do some disable_if stuff on it in the max_index_plus_one routine().
-#include "../manifold_regularization/sample_pair.h"
+#include "../manifold_regularization/graph_creation.h"
 #include "../matrix.h"
 
 
@@ -545,7 +544,8 @@ namespace dlib
 
     template <typename T>
     typename disable_if_c<is_pair<typename T::value_type>::value ||
-                          is_same_type<typename T::value_type,sample_pair>::value,unsigned long>::type 
+                          is_same_type<typename T::value_type,sample_pair>::value ||
+                          is_same_type<typename T::value_type,ordered_sample_pair>::value , unsigned long>::type 
     max_index_plus_one (
         const T& samples
     ) 
@@ -908,6 +908,73 @@ namespace dlib
         return T(temp.begin(), temp.end());
     }
 
+// ----------------------------------------------------------------------------------------
+
+    template <typename EXP, typename T, long NR, long NC, typename MM, typename L>
+    void sparse_matrix_vector_multiply (
+        const std::vector<sample_pair>& edges,
+        const matrix_exp<EXP>& v,
+        matrix<T,NR,NC,MM,L>& result
+    )
+    {
+        // make sure requires clause is not broken
+        DLIB_ASSERT(max_index_plus_one(edges) <= (unsigned long)v.size() &&
+                    is_col_vector(v),
+                    "\t void sparse_matrix_vector_multiply()"
+                    << "\n\t Invalid inputs were given to this function"
+                    << "\n\t max_index_plus_one(edges): " << max_index_plus_one(edges)
+                    << "\n\t v.size():                  " << v.size() 
+                    << "\n\t is_col_vector(v):          " << is_col_vector(v) 
+        );
+
+        result.set_size(v.nr(),v.nc());
+        result = 0;
+
+        for (unsigned long k = 0; k < edges.size(); ++k)
+        {
+            const long i = edges[k].index1();
+            const long j = edges[k].index2();
+            const double d = edges[k].distance();
+
+            result(i) += v(j)*d;
+            if (i != j)
+                result(j) += v(i)*d;
+        }
+    }
+
+// ----------------------------------------------------------------------------------------
+
+    template <typename EXP, typename T, long NR, long NC, typename MM, typename L>
+    void sparse_matrix_vector_multiply (
+        const std::vector<ordered_sample_pair>& edges,
+        const matrix_exp<EXP>& v,
+        matrix<T,NR,NC,MM,L>& result
+    )
+    {
+        // make sure requires clause is not broken
+        DLIB_ASSERT(max_index_plus_one(edges) <= (unsigned long)v.size() &&
+                    is_col_vector(v),
+                    "\t void sparse_matrix_vector_multiply()"
+                    << "\n\t Invalid inputs were given to this function"
+                    << "\n\t max_index_plus_one(edges): " << max_index_plus_one(edges)
+                    << "\n\t v.size():                  " << v.size() 
+                    << "\n\t is_col_vector(v):          " << is_col_vector(v) 
+        );
+
+
+        result.set_size(v.nr(),v.nc());
+        result = 0;
+
+        for (unsigned long k = 0; k < edges.size(); ++k)
+        {
+            const long i = edges[k].index1();
+            const long j = edges[k].index2();
+            const double d = edges[k].distance();
+
+            result(i) += v(j)*d;
+        }
+    }
+
 // ----------------------------------------------------------------------------------------
 
 }

dlib/svm/sparse_vector_abstract.h

@@ -9,6 +9,8 @@
 #include "../matrix.h"
 #include <map>
 #include <vector>
+#include "../manifold_regularization/sample_pair_abstract.h"
+#include "../manifold_regularization/ordered_sample_pair_abstract.h"
 
 namespace dlib
 {
@@ -500,6 +502,70 @@ namespace dlib
               key values).
     !*/
 
+// ----------------------------------------------------------------------------------------
+
+    template <
+        typename EXP, 
+        typename T, 
+        long NR, 
+        long NC, 
+        typename MM, 
+        typename L
+        >
+    void sparse_matrix_vector_multiply (
+        const std::vector<sample_pair>& edges,
+        const matrix_exp<EXP>& v,
+        matrix<T,NR,NC,MM,L>& result
+    );
+    /*!
+        requires
+            - is_col_vector(v) == true
+            - max_index_plus_one(edges) <= v.size()
+        ensures
+            - Interprets edges as representing a symmetric sparse matrix M.  The elements
+              of M are defined such that, for all valid i,j:
+                - M(i,j) == sum of edges[k].distance() for all k where edges[k]==sample_pair(i,j) 
+                - This means that any element of M that doesn't have any edges associated
+                  with it will have a value of 0.
+            - #result == M*v
+              (i.e. this function multiplies the vector v with the sparse matrix
+              represented by edges and stores the output into result)
+            - get_rect(#result) == get_rect(v)
+              (i.e. result will have the same dimensions as v)
+    !*/
+
+// ----------------------------------------------------------------------------------------
+
+    template <
+        typename EXP, 
+        typename T, 
+        long NR, 
+        long NC, 
+        typename MM, 
+        typename L
+        >
+    void sparse_matrix_vector_multiply (
+        const std::vector<ordered_sample_pair>& edges,
+        const matrix_exp<EXP>& v,
+        matrix<T,NR,NC,MM,L>& result
+    );
+    /*!
+        requires
+            - is_col_vector(v) == true
+            - max_index_plus_one(edges) <= v.size()
+        ensures
+            - Interprets edges as representing a square sparse matrix M.  The elements of M
+              are defined such that, for all valid i,j:
+                - M(i,j) == sum of edges[k].distance() for all k where edges[k]==ordered_sample_pair(i,j) 
+                - This means that any element of M that doesn't have any edges associated
+                  with it will have a value of 0.
+            - #result == M*v
+              (i.e. this function multiplies the vector v with the sparse matrix
+              represented by edges and stores the output into result)
+            - get_rect(#result) == get_rect(v)
+              (i.e. result will have the same dimensions as v)
+    !*/
+
 // ----------------------------------------------------------------------------------------
 
 }