all_indices.h

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/***********************************************************************
 * Software License Agreement (BSD License)
 *
 * Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
 * Copyright 2008-2009  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
 * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
 * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
 * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
 * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *************************************************************************/
 
 
#ifndef FLANN_ALL_INDICES_H_
#define FLANN_ALL_INDICES_H_
 
#include "FLANN/general.h"
 
#include "FLANN/algorithms/nn_index.h"
#include "FLANN/algorithms/kdtree_index.h"
#include "FLANN/algorithms/kdtree_single_index.h"
#include "FLANN/algorithms/kmeans_index.h"
#include "FLANN/algorithms/composite_index.h"
#include "FLANN/algorithms/linear_index.h"
#include "FLANN/algorithms/hierarchical_clustering_index.h"
#include "FLANN/algorithms/lsh_index.h"
#include "FLANN/algorithms/autotuned_index.h"
#ifdef FLANN_USE_CUDA
#include "FLANN/algorithms/kdtree_cuda_3d_index.h"
#endif
 
 
namespace flann
{
 
template<bool, typename T = void> struct enable_if{};
template<typename T> struct enable_if<true,T> { typedef T type; };
 
template<bool, typename T> struct disable_if{ typedef T type; };
template<typename T> struct disable_if<true,T> { };
 
template <typename T, typename U>
struct same_type
{
    enum {value = false};
};
 
template<typename T>
struct same_type<T,T>
{
    enum {value = true};
};
 
#define HAS_MEMBER(member) \
    template<typename T> \
    struct member { \
        typedef char No; \
        typedef long Yes; \
        template<typename C> static Yes test( typename C::member* ); \
        template<typename C> static No test( ... ); \
        enum { value = sizeof (test<T>(0))==sizeof(Yes) }; \
    };
 
HAS_MEMBER(needs_kdtree_distance)
HAS_MEMBER(needs_vector_space_distance)
HAS_MEMBER(is_kdtree_distance)
HAS_MEMBER(is_vector_space_distance)
 
struct DummyDistance
{
    typedef float ElementType;
    typedef float ResultType;
 
    template <typename Iterator1, typename Iterator2>
    ResultType operator()(Iterator1 a, Iterator2 b, size_t size, ResultType /*worst_dist*/ = -1) const
    {
        return ResultType(0);
    }
 
    template <typename U, typename V>
    inline ResultType accum_dist(const U& a, const V& b, int) const
    {
        return ResultType(0);
    }
};
 
template<template <typename> class Index, typename Distance, typename ElemType>
struct valid_combination
{
    static const bool value = same_type<ElemType,typename Distance::ElementType>::value &&
                    (!needs_kdtree_distance<Index<DummyDistance> >::value || is_kdtree_distance<Distance>::value) &&
                    (!needs_vector_space_distance<Index<DummyDistance> >::value || is_kdtree_distance<Distance>::value || is_vector_space_distance<Distance>::value);
 
};
 
 
/*********************************************************
 * Create index
 **********************************************************/
template <template<typename> class Index, typename Distance, typename T>
inline NNIndex<Distance>* create_index_(flann::Matrix<T> data, const flann::IndexParams& params, const Distance& distance,
        typename enable_if<valid_combination<Index,Distance,T>::value,void>::type* = 0)
{
    return new Index<Distance>(data, params, distance);
}
 
template <template<typename> class Index, typename Distance, typename T>
inline NNIndex<Distance>* create_index_(flann::Matrix<T> data, const flann::IndexParams& params, const Distance& distance,
        typename disable_if<valid_combination<Index,Distance,T>::value,void>::type* = 0)
{
    return NULL;
}
 
template<typename Distance>
inline NNIndex<Distance>*
  create_index_by_type(const flann_algorithm_t index_type,
        const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance)
{
    typedef typename Distance::ElementType ElementType;
 
    NNIndex<Distance>* nnIndex;
 
    switch (index_type) {
 
    case FLANN_INDEX_LINEAR:
        nnIndex = create_index_<LinearIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_KDTREE_SINGLE:
        nnIndex = create_index_<KDTreeSingleIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_KDTREE:
        nnIndex = create_index_<KDTreeIndex,Distance,ElementType>(dataset, params, distance);
        break;
#ifdef FLANN_USE_CUDA
    case FLANN_INDEX_KDTREE_CUDA:
        nnIndex = create_index_<KDTreeCuda3dIndex,Distance,ElementType>(dataset, params, distance);
        break;
#endif
 
    case FLANN_INDEX_KMEANS:
        nnIndex = create_index_<KMeansIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_COMPOSITE:
        nnIndex = create_index_<CompositeIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_AUTOTUNED:
        nnIndex = create_index_<AutotunedIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_HIERARCHICAL:
        nnIndex = create_index_<HierarchicalClusteringIndex,Distance,ElementType>(dataset, params, distance);
        break;
    case FLANN_INDEX_LSH:
        nnIndex = create_index_<LshIndex,Distance,ElementType>(dataset, params, distance);
        break;
    default:
        throw FLANNException("Unknown index type");
    }
 
    if (nnIndex==NULL) {
        throw FLANNException("Unsupported index/distance combination");
    }
    return nnIndex;
}
 
}
 
#endif /* FLANN_ALL_INDICES_H_ */