summaryrefslogtreecommitdiff
path: root/src/Bottleneck_distance/include/gudhi/CGAL/Kd_tree.h
blob: 5b63b290ad1ddcffffa1379b6c3dee5cf59b8b77 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
// Copyright (c) 2002,2011,2014 Utrecht University (The Netherlands), Max-Planck-Institute Saarbruecken (Germany).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
// You can redistribute it and/or modify it under the terms of the GNU
// General Public License as published by the Free Software Foundation,
// either version 3 of the License, or (at your option) any later version.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
//
// Author(s)     : Hans Tangelder (<hanst@cs.uu.nl>),
//               : Waqar Khan <wkhan@mpi-inf.mpg.de>

#ifndef CGAL_KD_TREE_H
#define CGAL_KD_TREE_H

#include "CGAL/Kd_tree_node.h"

#include <CGAL/basic.h>
#include <CGAL/assertions.h>
#include <vector>

#include <CGAL/algorithm.h>
#include <CGAL/Splitters.h>
#include <CGAL/internal/Get_dimension_tag.h>
#include <CGAL/Search_traits.h>


#include <deque>
#include <boost/container/deque.hpp>
#include <boost/optional.hpp>

#ifdef CGAL_HAS_THREADS
#include <CGAL/mutex.h>
#endif

namespace CGAL {

//template <class SearchTraits, class Splitter_=Median_of_rectangle<SearchTraits>, class UseExtendedNode = Tag_true >
template <class SearchTraits, class Splitter_=Sliding_midpoint<SearchTraits>, class UseExtendedNode = Tag_true >
class Kd_tree {

public:
    typedef SearchTraits Traits;
    typedef Splitter_ Splitter;
    typedef typename SearchTraits::Point_d Point_d;
    typedef typename Splitter::Container Point_container;

    typedef typename SearchTraits::FT FT;
    typedef Kd_tree_node<SearchTraits, Splitter, UseExtendedNode > Node;
    typedef Kd_tree_leaf_node<SearchTraits, Splitter, UseExtendedNode > Leaf_node;
    typedef Kd_tree_internal_node<SearchTraits, Splitter, UseExtendedNode > Internal_node;
    typedef Kd_tree<SearchTraits, Splitter> Tree;
    typedef Kd_tree<SearchTraits, Splitter,UseExtendedNode> Self;

    typedef Node* Node_handle;
    typedef const Node* Node_const_handle;
    typedef Leaf_node* Leaf_node_handle;
    typedef const Leaf_node* Leaf_node_const_handle;
    typedef Internal_node* Internal_node_handle;
    typedef const Internal_node* Internal_node_const_handle;
    typedef typename std::vector<const Point_d*>::const_iterator Point_d_iterator;
    typedef typename std::vector<const Point_d*>::const_iterator Point_d_const_iterator;
    typedef typename Splitter::Separator Separator;
    typedef typename std::vector<Point_d>::const_iterator iterator;
    typedef typename std::vector<Point_d>::const_iterator const_iterator;

    typedef typename std::vector<Point_d>::size_type size_type;

    typedef typename internal::Get_dimension_tag<SearchTraits>::Dimension D;

private:
    SearchTraits traits_;
    Splitter split;


    // wokaround for https://svn.boost.org/trac/boost/ticket/9332
#if   (_MSC_VER == 1800) && (BOOST_VERSION == 105500)
    std::deque<Internal_node> internal_nodes;
    std::deque<Leaf_node> leaf_nodes;
#else
    boost::container::deque<Internal_node> internal_nodes;
    boost::container::deque<Leaf_node> leaf_nodes;
#endif

    Node_handle tree_root;

    Kd_tree_rectangle<FT,D>* bbox;
    std::vector<Point_d> pts;

    // Instead of storing the points in arrays in the Kd_tree_node
    // we put all the data in a vector in the Kd_tree.
    // and we only store an iterator range in the Kd_tree_node.
    //
    std::vector<const Point_d*> data;


#ifdef CGAL_HAS_THREADS
    mutable CGAL_MUTEX building_mutex;//mutex used to protect const calls inducing build()
#endif
    bool built_;
    bool removed_;

    // protected copy constructor
    Kd_tree(const Tree& tree)
        : traits_(tree.traits_),built_(tree.built_)
    {};


    // Instead of the recursive construction of the tree in the class Kd_tree_node
    // we do this in the tree class. The advantage is that we then can optimize
    // the allocation of the nodes.

    // The leaf node
    Node_handle
    create_leaf_node(Point_container& c)
    {
        Leaf_node node(true , static_cast<unsigned int>(c.size()));
        std::ptrdiff_t tmp = c.begin() - data.begin();
        node.data = pts.begin() + tmp;

        leaf_nodes.push_back(node);
        Leaf_node_handle nh = &leaf_nodes.back();


        return nh;
    }


    // The internal node

    Node_handle
    create_internal_node(Point_container& c, const Tag_true&)
    {
        return create_internal_node_use_extension(c);
    }

    Node_handle
    create_internal_node(Point_container& c, const Tag_false&)
    {
        return create_internal_node(c);
    }



    // TODO: Similiar to the leaf_init function above, a part of the code should be
    //       moved to a the class Kd_tree_node.
    //       It is not proper yet, but the goal was to see if there is
    //       a potential performance gain through the Compact_container
    Node_handle
    create_internal_node_use_extension(Point_container& c)
    {
        Internal_node node(false);
        internal_nodes.push_back(node);
        Internal_node_handle nh = &internal_nodes.back();

        Separator sep;
        Point_container c_low(c.dimension(),traits_);
        split(sep, c, c_low);
        nh->set_separator(sep);

        int cd  = nh->cutting_dimension();
        if(!c_low.empty())
            nh->low_val = c_low.tight_bounding_box().max_coord(cd);
        else
            nh->low_val = c_low.bounding_box().min_coord(cd);
        if(!c.empty())
            nh->high_val = c.tight_bounding_box().min_coord(cd);
        else
            nh->high_val = c.bounding_box().max_coord(cd);

        CGAL_assertion(nh->cutting_value() >= nh->low_val);
        CGAL_assertion(nh->cutting_value() <= nh->high_val);

        if (c_low.size() > split.bucket_size()){
            nh->lower_ch = create_internal_node_use_extension(c_low);
        }else{
            nh->lower_ch = create_leaf_node(c_low);
        }
        if (c.size() > split.bucket_size()){
            nh->upper_ch = create_internal_node_use_extension(c);
        }else{
            nh->upper_ch = create_leaf_node(c);
        }




        return nh;
    }


    // Note also that I duplicated the code to get rid if the if's for
    // the boolean use_extension which was constant over the construction
    Node_handle
    create_internal_node(Point_container& c)
    {
        Internal_node node(false);
        internal_nodes.push_back(node);
        Internal_node_handle nh = &internal_nodes.back();
        Separator sep;

        Point_container c_low(c.dimension(),traits_);
        split(sep, c, c_low);
        nh->set_separator(sep);

        if (c_low.size() > split.bucket_size()){
            nh->lower_ch = create_internal_node(c_low);
        }else{
            nh->lower_ch = create_leaf_node(c_low);
        }
        if (c.size() > split.bucket_size()){
            nh->upper_ch = create_internal_node(c);
        }else{
            nh->upper_ch = create_leaf_node(c);
        }



        return nh;
    }



public:

    Kd_tree(Splitter s = Splitter(),const SearchTraits traits=SearchTraits())
        : traits_(traits),split(s), built_(false), removed_(false)
    {}

    template <class InputIterator>
    Kd_tree(InputIterator first, InputIterator beyond,
            Splitter s = Splitter(),const SearchTraits traits=SearchTraits())
        : traits_(traits),split(s), built_(false), removed_(false)
    {
        pts.insert(pts.end(), first, beyond);
    }

    bool empty() const {
        return pts.empty();
    }

    void
    build()
    {
        const Point_d& p = *pts.begin();
        typename SearchTraits::Construct_cartesian_const_iterator_d ccci=traits_.construct_cartesian_const_iterator_d_object();
        int dim = static_cast<int>(std::distance(ccci(p), ccci(p,0)));

        data.reserve(pts.size());
        for(unsigned int i = 0; i < pts.size(); i++){
            data.push_back(&pts[i]);
        }
        Point_container c(dim, data.begin(), data.end(),traits_);
        bbox = new Kd_tree_rectangle<FT,D>(c.bounding_box());
        if (c.size() <= split.bucket_size()){
            tree_root = create_leaf_node(c);
        }else {
            tree_root = create_internal_node(c, UseExtendedNode());
        }

        //Reorder vector for spatial locality
        std::vector<Point_d> ptstmp;
        ptstmp.resize(pts.size());
        for (std::size_t i = 0; i < pts.size(); ++i){
            ptstmp[i] = *data[i];
        }
        for(std::size_t i = 0; i < leaf_nodes.size(); ++i){
            std::ptrdiff_t tmp = leaf_nodes[i].begin() - pts.begin();
            leaf_nodes[i].data = ptstmp.begin() + tmp;
        }
        pts.swap(ptstmp);

        data.clear();

        built_ = true;
    }

private:
    //any call to this function is for the moment not threadsafe
    void const_build() const {
#ifdef CGAL_HAS_THREADS
        //this ensure that build() will be called once
        CGAL_SCOPED_LOCK(building_mutex);
        if(!is_built())
#endif
            const_cast<Self*>(this)->build(); //THIS IS NOT THREADSAFE
    }
public:

    bool is_built() const
    {
        return built_;
    }

    void invalidate_built()
    {
        if(is_built()){
            internal_nodes.clear();
            leaf_nodes.clear();
            data.clear();
            delete bbox;
            built_ = false;
        }
    }

    void clear()
    {
        invalidate_built();
        pts.clear();
        removed_ = false;
    }

    void
    insert(const Point_d& p)
    {
        if (removed_) throw std::logic_error("Once you start removing points, you cannot insert anymore, you need to start again from scratch.");
        invalidate_built();
        pts.push_back(p);
    }

    template <class InputIterator>
    void
    insert(InputIterator first, InputIterator beyond)
    {
        if (removed_ && first != beyond) throw std::logic_error("Once you start removing points, you cannot insert anymore, you need to start again from scratch.");
        invalidate_built();
        pts.insert(pts.end(),first, beyond);
    }

    void
    remove(const Point_d& p)
    {
        // This does not actually remove points, and further insertions
        // would make the points reappear, so we disallow it.
        removed_ = true;
        // Locate the point
        Internal_node_handle grandparent = 0;
        Internal_node_handle parent = 0;
        bool islower = false, islower2;
        Node_handle node = root(); // Calls build() if needed.
        while (!node->is_leaf()) {
            grandparent = parent; islower2 = islower;
            parent = static_cast<Internal_node_handle>(node);
            islower = traits().construct_cartesian_const_iterator_d_object()(p)[parent->cutting_dimension()] < parent->cutting_value();
            if (islower) {
                node = parent->lower();
            } else {
                node = parent->upper();
            }
        }
        Leaf_node_handle lnode = static_cast<Leaf_node_handle>(node);
        if (lnode->size() > 1) {
            iterator pi = std::find(lnode->begin(), lnode->end(), p);
            CGAL_assertion (pi != lnode->end());
            iterator lasti = lnode->end() - 1;
            if (pi != lasti) {
                // Hack to get a non-const iterator
                std::iter_swap(pts.begin()+(pi-pts.begin()), pts.begin()+(lasti-pts.begin()));
            }
            lnode->drop_last_point();
        } else if (grandparent) {
             CGAL_assertion (p == *lnode->begin());
            Node_handle brother = islower ? parent->upper() : parent->lower();
            if (islower2)
                grandparent->set_lower(brother);
            else
                grandparent->set_upper(brother);
        } else if (parent) {
            tree_root = islower ? parent->upper() : parent->lower();
        } else {
            clear();
        }
    }

    //For efficiency; reserve the size of the points vectors in advance (if the number of points is already known).
    void reserve(size_t size)
    {
        pts.reserve(size);
    }

    //Get the capacity of the underlying points vector.
    size_t capacity()
    {
        return pts.capacity();
    }


    template <class OutputIterator, class FuzzyQueryItem>
    OutputIterator
    search(OutputIterator it, const FuzzyQueryItem& q) const
    {
        if(! pts.empty()){

            if(! is_built()){
                const_build();
            }
            Kd_tree_rectangle<FT,D> b(*bbox);
            return tree_root->search(it,q,b);
        }
        return it;
    }


    template <class FuzzyQueryItem>
    boost::optional<Point_d>
    search_any_point(const FuzzyQueryItem& q) const
    {
        if(! pts.empty()){

            if(! is_built()){
                const_build();
            }
            Kd_tree_rectangle<FT,D> b(*bbox);
            return tree_root->search_any_point(q,b);
        }
        return boost::none;
    }


    ~Kd_tree() {
        if(is_built()){
            delete bbox;
        }
    }


    const SearchTraits&
    traits() const
    {
        return traits_;
    }

    Node_const_handle
    root() const
    {
        if(! is_built()){
            const_build();
        }
        return tree_root;
    }

    Node_handle
    root()
    {
        if(! is_built()){
            build();
        }
        return tree_root;
    }

    void
    print() const
    {
        if(! is_built()){
            const_build();
        }
        root()->print();
    }

    const Kd_tree_rectangle<FT,D>&
    bounding_box() const
    {
        if(! is_built()){
            const_build();
        }
        return *bbox;
    }

    const_iterator
    begin() const
    {
        return pts.begin();
    }

    const_iterator
    end() const
    {
        return pts.end();
    }

    size_type
    size() const
    {
        return pts.size();
    }

    // Print statistics of the tree.
    std::ostream&
    statistics(std::ostream& s) const
    {
        if(! is_built()){
            const_build();
        }
        s << "Tree statistics:" << std::endl;
        s << "Number of items stored: "
          << root()->num_items() << std::endl;
        s << "Number of nodes: "
          << root()->num_nodes() << std::endl;
        s << " Tree depth: " << root()->depth() << std::endl;
        return s;
    }


};

} // namespace CGAL

#endif // CGAL_KD_TREE_H