Made this function capable of accepting anything that can be converted to

a matrix via vector_to_matrix()

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403891

dlib/svm/sort_basis_vectors.h

@@ -45,7 +45,6 @@ namespace dlib
             // Build the inverse matrix.  This is basically a pseudo-inverse.
             return make_symmetric(eig.get_pseudo_v()*diagm(reciprocal(vals))*trans(eig.get_pseudo_v()));
         }
-    }
 
 // ----------------------------------------------------------------------------------------
 
@@ -55,12 +54,12 @@ namespace dlib
             typename vect2_type,
             typename vect3_type
             >
-    const std::vector<typename kernel_type::sample_type> sort_basis_vectors (
+        const std::vector<typename kernel_type::sample_type> sort_basis_vectors_impl (
             const kernel_type& kern,
             const vect1_type& samples,
             const vect2_type& labels,
             const vect3_type& basis,
-        double eps = 0.99
+            double eps 
         )
         {
             DLIB_ASSERT(is_binary_classification_problem(samples, labels) &&
@@ -88,16 +87,16 @@ namespace dlib
             // compute the covariance matrix and the means of the two classes.
             for (unsigned long i = 0; i < samples.size(); ++i)
             {
-            temp = kernel_matrix(kern, basis, samples[i]);
+                temp = kernel_matrix(kern, basis, samples(i));
                 cov.add(temp);
-            if (labels[i] > 0)
+                if (labels(i) > 0)
                     c1_mean += temp;
                 else
                     c2_mean += temp;
             }
 
-        c1_mean /= sum(vector_to_matrix(labels) > 0);
-        c2_mean /= sum(vector_to_matrix(labels) < 0);
+            c1_mean /= sum(labels > 0);
+            c2_mean /= sum(labels < 0);
 
             delta = c1_mean - c2_mean;
 
@@ -185,12 +184,37 @@ namespace dlib
             {
                 // Note that we load sorted_basis backwards so that the most important
                 // basis elements come first.  
-            sorted_basis[i] = vector_to_matrix(basis)(best_total_perm(basis.size()-i-1));
+                sorted_basis[i] = basis(best_total_perm(basis.size()-i-1));
             }
 
             return sorted_basis;
         }
 
+    }
+
+// ----------------------------------------------------------------------------------------
+
+    template <
+        typename kernel_type,
+        typename vect1_type,
+        typename vect2_type,
+        typename vect3_type
+        >
+    const std::vector<typename kernel_type::sample_type> sort_basis_vectors (
+        const kernel_type& kern,
+        const vect1_type& samples,
+        const vect2_type& labels,
+        const vect3_type& basis,
+        double eps = 0.99
+    )
+    {
+        return bs_impl::sort_basis_vectors_impl(kern, 
+                                                vector_to_matrix(samples),
+                                                vector_to_matrix(labels),
+                                                vector_to_matrix(basis),
+                                                eps);
+    }
+
 // ----------------------------------------------------------------------------------------
 
 }