Nicer way of controling index instantiation for different distance combinations

src/cpp/flann/algorithms/all_indices.h

@@ -47,111 +47,6 @@
 namespace flann
 {
 
-template<typename KDTreeCapability, typename VectorSpace, typename Distance>
-struct index_creator
-{
-    static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance)
-    {
-        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
-
-        NNIndex<Distance>* nnIndex;
-        switch (index_type) {
-        case FLANN_INDEX_LINEAR:
-            nnIndex = new LinearIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_KDTREE_SINGLE:
-            nnIndex = new KDTreeSingleIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_KDTREE:
-            nnIndex = new KDTreeIndex<Distance>(dataset, params, distance);
-            break;
-			//! #define this symbol before including flann.h to enable GPU search algorithms. But you have
-			//! to link libflann_cuda then!
-		#ifdef FLANN_USE_CUDA
-		case FLANN_INDEX_KDTREE_CUDA:
-            nnIndex = new KDTreeCuda3dIndex<Distance>(dataset, params, distance);
-            break;
-		#endif
-
-        case FLANN_INDEX_KMEANS:
-            nnIndex = new KMeansIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_COMPOSITE:
-            nnIndex = new CompositeIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_AUTOTUNED:
-            nnIndex = new AutotunedIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_HIERARCHICAL:
-            nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_LSH:
-            nnIndex = new LshIndex<Distance>(dataset, params, distance);
-            break;
-        default:
-            throw FLANNException("Unknown index type");
-        }
-
-        return nnIndex;
-    }
-};
-
-template<typename VectorSpace, typename Distance>
-struct index_creator<FalseType,VectorSpace,Distance>
-{
-    static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance)
-    {
-        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
-
-        NNIndex<Distance>* nnIndex;
-        switch (index_type) {
-        case FLANN_INDEX_LINEAR:
-            nnIndex = new LinearIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_KMEANS:
-            nnIndex = new KMeansIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_HIERARCHICAL:
-            nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_LSH:
-            nnIndex = new LshIndex<Distance>(dataset, params, distance);
-            break;
-        default:
-            throw FLANNException("Unknown index type");
-        }
-
-        return nnIndex;
-    }
-};
-
-template<typename Distance>
-struct index_creator<FalseType,FalseType,Distance>
-{
-    static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance)
-    {
-        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
-
-        NNIndex<Distance>* nnIndex;
-        switch (index_type) {
-        case FLANN_INDEX_LINEAR:
-            nnIndex = new LinearIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_HIERARCHICAL:
-            nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance);
-            break;
-        case FLANN_INDEX_LSH:
-            nnIndex = new LshIndex<Distance>(dataset, params, distance);
-            break;
-        default:
-            throw FLANNException("Unknown index type");
-        }
-
-        return nnIndex;
-    }
-};
-
-
 
 /**
  * enable_if sfinae helper
@@ -205,7 +100,7 @@ struct valid_combination
 
     static const bool value = same_type<ElementType,typename Distance::ElementType>::value &&
     				(!needs_kdtree_distance<Index<Distance> >::value || is_kdtree_distance<Distance>::value) &&
-    				(!needs_vector_space_distance<Index<Distance> >::value || is_vector_space_distance<Distance>::value);
+    				(!needs_vector_space_distance<Index<Distance> >::value || is_kdtree_distance<Distance>::value || is_vector_space_distance<Distance>::value);
 
 };
 

src/cpp/flann/algorithms/composite_index.h

@@ -74,6 +74,8 @@ public:
     typedef typename Distance::ElementType ElementType;
     typedef typename Distance::ResultType DistanceType;
 
+    typedef bool needs_kdtree_distance;
+
     /**
      * Index constructor
      * @param inputData dataset containing the points to index

src/cpp/flann/algorithms/kdtree_cuda_3d_index.h

@@ -76,6 +76,7 @@ public:
 
     int visited_leafs;
 
+    typedef bool needs_kdtree_distance;
 
     /**
      * KDTree constructor

src/cpp/flann/algorithms/kdtree_single_index.h

@@ -72,6 +72,7 @@ public:
     typedef typename Distance::ElementType ElementType;
     typedef typename Distance::ResultType DistanceType;
 
+    typedef bool needs_kdtree_distance;
 
     /**
      * KDTree constructor

test/flann_simple_test.cpp

@@ -620,7 +620,7 @@ TEST_F(Flann_3D, SavedTest2)
 class Flann_Brief100K_Test : public FLANNTestFixture
 {
 protected:
-  typedef flann::Hamming2<unsigned char> Distance;
+  typedef flann::Hamming<unsigned char> Distance;
   typedef Distance::ElementType ElementType;
   typedef Distance::ResultType DistanceType;
   flann::Matrix<unsigned char> data;