Moved things around so they are easier to link to the in the docs.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403328

dlib/svm/empirical_kernel_map.h

@@ -13,6 +13,32 @@
 namespace dlib
 {
 
+// ----------------------------------------------------------------------------------------
+
+    template <typename kernel_type, typename EXP>
+    const decision_function<kernel_type> convert_to_decision_function (
+        const projection_function<kernel_type>& project_funct,
+        const matrix_exp<EXP>& vect
+    ) 
+    {
+        // make sure requires clause is not broken
+        DLIB_ASSERT(project_funct.out_vector_size() > 0 && is_vector(vect) && 
+                    project_funct.out_vector_size() == vect.size() && project_funct.weights.nc() == project_funct.basis_vectors.size(),
+            "\t const decision_function convert_to_decision_function()"
+            << "\n\t Invalid inputs to this function."
+            << "\n\t project_funct.out_vector_size():    " << project_funct.out_vector_size() 
+            << "\n\t project_funct.weights.nc():         " << project_funct.weights.nc() 
+            << "\n\t project_funct.basis_vectors.size(): " << project_funct.basis_vectors.size() 
+            << "\n\t is_vector(vect):                    " << is_vector(vect) 
+            << "\n\t vect.size():                        " << vect.size() 
+            );
+
+        return decision_function<kernel_type>(trans(project_funct.weights)*vect, 
+                                              0, 
+                                              project_funct.kernel_function,
+                                              project_funct.basis_vectors);
+    }
+
 // ----------------------------------------------------------------------------------------
 
     template <typename kern_type>
@@ -259,32 +285,6 @@ namespace dlib
         empirical_kernel_map<kernel_type>& b
     ) { a.swap(b); }
     
-// ----------------------------------------------------------------------------------------
-
-    template <typename kernel_type, typename EXP>
-    const decision_function<kernel_type> convert_to_decision_function (
-        const projection_function<kernel_type>& project_funct,
-        const matrix_exp<EXP>& vect
-    ) 
-    {
-        // make sure requires clause is not broken
-        DLIB_ASSERT(project_funct.out_vector_size() > 0 && is_vector(vect) && 
-                    project_funct.out_vector_size() == vect.size() && project_funct.weights.nc() == project_funct.basis_vectors.size(),
-            "\t const decision_function convert_to_decision_function()"
-            << "\n\t Invalid inputs to this function."
-            << "\n\t project_funct.out_vector_size():    " << project_funct.out_vector_size() 
-            << "\n\t project_funct.weights.nc():         " << project_funct.weights.nc() 
-            << "\n\t project_funct.basis_vectors.size(): " << project_funct.basis_vectors.size() 
-            << "\n\t is_vector(vect):                    " << is_vector(vect) 
-            << "\n\t vect.size():                        " << vect.size() 
-            );
-
-        return decision_function<kernel_type>(trans(project_funct.weights)*vect, 
-                                              0, 
-                                              project_funct.kernel_function,
-                                              project_funct.basis_vectors);
-    }
-
 // ----------------------------------------------------------------------------------------
 
 }

dlib/svm/empirical_kernel_map_abstract.h

@@ -12,6 +12,35 @@
 namespace dlib
 {
 
+// ----------------------------------------------------------------------------------------
+
+    template <
+        typename kernel_type, 
+        typename EXP
+        >
+    const decision_function<kernel_type> convert_to_decision_function (
+        const projection_function<kernel_type>& project_funct,
+        const matrix_exp<EXP>& vect
+    );
+    /*!
+        requires
+            - is_vector(vect) == true
+            - vect.size() == project_funct.out_vector_size()
+            - project_funct.out_vector_size() > 0
+            - project_funct.weights.nc() == project_funct.basis_vectors.size()
+        ensures
+            - This function interprets the given vector as a point in the kernel feature space defined 
+              by the given projection function.  The return value of this function is a decision 
+              function, DF, that represents the given vector in the following sense:
+                - for all possible sample_type objects, S, it is the case that DF(S) == dot(project_funct(S), vect)
+                  (i.e. the returned decision function computes dot products, in kernel feature space, 
+                  between vect and any argument you give it.  Note also that this equality is exact, even
+                  for sample_type objects not in the span of the basis_vectors.)
+                - DF.kernel_function == project_funct.kernel_function
+                - DF.b == 0
+                - DF.basis_vectors == project_funct.basis_vectors.  
+    !*/
+
 // ----------------------------------------------------------------------------------------
 
     template <
@@ -264,35 +293,6 @@ namespace dlib
         provides serialization support for empirical_kernel_map objects
     !*/
 
-// ----------------------------------------------------------------------------------------
-
-    template <
-        typename kernel_type, 
-        typename EXP
-        >
-    const decision_function<kernel_type> convert_to_decision_function (
-        const projection_function<kernel_type>& project_funct,
-        const matrix_exp<EXP>& vect
-    );
-    /*!
-        requires
-            - is_vector(vect) == true
-            - vect.size() == project_funct.out_vector_size()
-            - project_funct.out_vector_size() > 0
-            - project_funct.weights.nc() == project_funct.basis_vectors.size()
-        ensures
-            - This function interprets the given vector as a point in the kernel feature space defined 
-              by the given projection function.  The return value of this function is a decision 
-              function, DF, that represents the given vector in the following sense:
-                - for all possible sample_type objects, S, it is the case that DF(S) == dot(project_funct(S), vect)
-                  (i.e. the returned decision function computes dot products, in kernel feature space, 
-                  between vect and any argument you give it.  Note also that this equality is exact, even
-                  for sample_type objects not in the span of the basis_vectors.)
-                - DF.kernel_function == project_funct.kernel_function
-                - DF.b == 0
-                - DF.basis_vectors == project_funct.basis_vectors.  
-    !*/
-
 // ----------------------------------------------------------------------------------------
 
 }