This file is indexed.

/usr/include/vigra/python_graph.hxx is in libvigraimpex-dev 1.10.0+git20160211.167be93+dfsg-2+b5.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  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
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
/************************************************************************/
/*                                                                      */
/*     Copyright 2011-2012 Stefan Schmidt and Ullrich Koethe            */
/*                                                                      */
/*    This file is part of the VIGRA computer vision library.           */
/*    The VIGRA Website is                                              */
/*        http://hci.iwr.uni-heidelberg.de/vigra/                       */
/*    Please direct questions, bug reports, and contributions to        */
/*        ullrich.koethe@iwr.uni-heidelberg.de    or                    */
/*        vigra@informatik.uni-hamburg.de                               */
/*                                                                      */
/*    Permission is hereby granted, free of charge, to any person       */
/*    obtaining a copy of this software and associated documentation    */
/*    files (the "Software"), to deal in the Software without           */
/*    restriction, including without limitation the rights to use,      */
/*    copy, modify, merge, publish, distribute, sublicense, and/or      */
/*    sell copies of the Software, and to permit persons to whom the    */
/*    Software is furnished to do so, subject to the following          */
/*    conditions:                                                       */
/*                                                                      */
/*    The above copyright notice and this permission notice shall be    */
/*    included in all copies or substantial portions of the             */
/*    Software.                                                         */
/*                                                                      */
/*    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND    */
/*    EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES   */
/*    OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND          */
/*    NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT       */
/*    HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,      */
/*    WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING      */
/*    FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR     */
/*    OTHER DEALINGS IN THE SOFTWARE.                                   */
/*                                                                      */
/************************************************************************/

/**
 * This header provides definitions of graph-related types
 * and optionally provides a gateway to popular graph libraries
 * (for now, BGL is supported).
 */

#ifndef VIGRA_PYTHON_GRAPH_HXX
#define VIGRA_PYTHON_GRAPH_HXX

/*boost*/
#include <boost/python.hpp>
#include <boost/iterator/transform_iterator.hpp>

/*vigra*/
#include <vigra/graphs.hxx>
#include <vigra/numpy_array.hxx>
#include <vigra/multi_gridgraph.hxx>
#include <vigra/graph_generalization.hxx>
#include <vigra/multi_array.hxx>
#include <vigra/graphs.hxx>
#include <vigra/priority_queue.hxx>
#include <vigra/merge_graph_adaptor.hxx>
namespace vigra{






template<class MAP>
struct GraphMapTypeTraits;

template< unsigned int DIM,class T>
struct GraphMapTypeTraits<NumpyArray<DIM,T> >{
    typedef typename NumpyArray<DIM,T>::value_type Value;
    typedef Value &                                Reference;
    typedef const Value  &                         ConstReference;
};


    
template<class GRAPH>
struct NodeHolder :  GRAPH::Node
{
    typedef typename GRAPH::Node Node;
    NodeHolder(const lemon::Invalid & iv = lemon::INVALID)
    : Node(lemon::INVALID),
      graph_(NULL)
    {}
    NodeHolder(const GRAPH & g , const Node & item)
    : Node(item),
      graph_(&g)
    {}

    typename GRAPH::index_type id()const{
        return graph_->id(*this);
    }

    typename GraphDescriptorToMultiArrayIndex<GRAPH>::IntrinsicNodeMapShape
    intrinsicNodeCoordinate()const{
        return GraphDescriptorToMultiArrayIndex<GRAPH>::intrinsicNodeCoordinate(*graph_,*this);
    }

    const GRAPH * graph_;
};



template<class GRAPH>
struct EdgeHolder : GRAPH::Edge
{

    typedef typename GRAPH::Edge Edge;
    EdgeHolder(const lemon::Invalid & iv = lemon::INVALID)
    : Edge(lemon::INVALID),
      graph_(NULL)
    {}
    EdgeHolder(const GRAPH & g , const Edge & item)
    : Edge(item),
      graph_(&g)
    {}

    typename GRAPH::index_type id()const{
        return graph_->id(*this);
    }

    NodeHolder<GRAPH> u()const{
        return NodeHolder<GRAPH>(*graph_,graph_->u(*this));
    }
    NodeHolder<GRAPH> v()const{
        return NodeHolder<GRAPH>(*graph_,graph_->v(*this));
    }

    typename GraphDescriptorToMultiArrayIndex<GRAPH>::IntrinsicEdgeMapShape
    intrinsicEdgeCoordinate()const{
        return GraphDescriptorToMultiArrayIndex<GRAPH>::intrinsicEdgeCoordinate(*graph_,*this);
    }

    const GRAPH * graph_; 
};



template<class GRAPH>
struct ArcHolder: GRAPH::Arc {
    typedef typename GRAPH::Arc Arc;
    ArcHolder(const lemon::Invalid & iv = lemon::INVALID)
    : Arc(lemon::INVALID),
      graph_(NULL)
    {}
    ArcHolder(const GRAPH & g , const Arc & item)
    : Arc(item),
      graph_(&g)
    {}

    typename GRAPH::index_type id()const{
        return graph_->id(*this);
    }

    typename GraphDescriptorToMultiArrayIndex<GRAPH>::IntrinsicArcMapShape
    intrinsicArcCoordinate()const{
        return GraphDescriptorToMultiArrayIndex<GRAPH>::intrinsicArcCoordinate(*graph_,*this);
    }


    const GRAPH * graph_;
};


namespace detail_python_graph{

template<class GRAPH>
struct ArcToTargetNodeHolder{
    typedef typename GRAPH::Node Node;
    typedef typename GRAPH::Arc Arc;
    ArcToTargetNodeHolder(const GRAPH & graph)
    : graph_(&graph){
    }
    NodeHolder<GRAPH> operator()(const Arc & arc)const{
        return NodeHolder<GRAPH>(*graph_,graph_->target(arc));
    }
    const GRAPH * graph_;
};

template<class GRAPH>
struct ArcToEdgeHolder{
    typedef typename GRAPH::Edge Edge;
    typedef typename GRAPH::Arc Arc;
    ArcToEdgeHolder(const GRAPH & graph)
    : graph_(&graph){
    }
    EdgeHolder<GRAPH> operator()(const Arc & arc)const{
        const Edge edge(arc);
        return EdgeHolder<GRAPH>(*graph_,edge);
    }
    const GRAPH * graph_;
};

template<class GRAPH>
struct ArcToArcHolder{
    typedef typename GRAPH::Edge Edge;
    typedef typename GRAPH::Arc Arc;
    ArcToArcHolder(const GRAPH & graph)
    : graph_(&graph){
    }
    ArcHolder<GRAPH> operator()(const Arc & arc)const{
        return ArcHolder<GRAPH>(*graph_,arc);
    }
    const GRAPH * graph_;
};


template<class GRAPH>
struct NodeToNodeHolder{
    typedef typename GRAPH::Node Node;
    NodeToNodeHolder(const GRAPH & graph)
    : graph_(&graph){
    }
    NodeHolder<GRAPH> operator()(const Node & node)const{
        return NodeHolder<GRAPH>(*graph_,node);
    }
    const GRAPH * graph_;
};

template<class GRAPH>
struct EdgeToEdgeHolder{
    typedef typename GRAPH::Edge Edge;
    EdgeToEdgeHolder(const GRAPH & graph)
    : graph_(&graph){
    }
    EdgeHolder<GRAPH> operator()(const Edge & edge)const{
        return EdgeHolder<GRAPH>(*graph_,edge);
    }
    const GRAPH * graph_;
};

} // end namespace detail_python_graph



template<class GRAPH>
struct NodeIteratorHolder{
    typedef typename GRAPH::Node Node;
    typedef typename GRAPH::NodeIt Iter;
    typedef detail_python_graph::NodeToNodeHolder<GRAPH> Transform;
    typedef boost::transform_iterator<Transform ,Iter ,NodeHolder<GRAPH>, NodeHolder<GRAPH> > const_iterator;
    NodeIteratorHolder(const GRAPH & graph,const Node & node = Node(lemon::INVALID) )
    : graph_(&graph),
      node_(node){
    }
    const_iterator begin()const{

        Iter iter = GraphIteratorAccessor<GRAPH>::nodesBegin(*graph_);
        return const_iterator(iter,Transform(*graph_));
    }
    const_iterator end()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::nodesEnd(*graph_);
        return const_iterator(iter,Transform(*graph_));
    }
    const GRAPH * graph_;
    Node node_;
};

template<class GRAPH>
struct EdgeIteratorHolder{
    typedef typename GRAPH::Edge Edge;
    typedef typename GRAPH::EdgeIt Iter;
    typedef detail_python_graph::EdgeToEdgeHolder<GRAPH> Transform;
    typedef boost::transform_iterator<Transform ,Iter ,EdgeHolder<GRAPH>, EdgeHolder<GRAPH> > const_iterator;
    EdgeIteratorHolder(const GRAPH & graph,const Edge & edge = Edge(lemon::INVALID) )
    : graph_(&graph),
      edge_(edge){
    }
    const_iterator begin()const{

        Iter iter = GraphIteratorAccessor<GRAPH>::edgesBegin(*graph_);
        return const_iterator(iter,Transform(*graph_));
    }
    const_iterator end()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::edgesEnd(*graph_);
        return const_iterator(iter,Transform(*graph_));
    }
    const GRAPH * graph_;
    Edge edge_;
};


template<class GRAPH>
struct NeighbourNodeIteratorHolder{
    typedef typename GRAPH::Node Node;
    typedef typename GRAPH::OutArcIt Iter;
    typedef detail_python_graph::ArcToTargetNodeHolder<GRAPH> Transform;
    typedef boost::transform_iterator<Transform ,Iter ,NodeHolder<GRAPH>, NodeHolder<GRAPH> > const_iterator;
    NeighbourNodeIteratorHolder(const GRAPH & graph,const Node & node)
    : graph_(&graph),
      node_(node){
    }
    const_iterator begin()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::outArcBegin(*graph_,node_);
        return const_iterator(iter,Transform(*graph_));
    }
    const_iterator end()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::outArcEnd(*graph_,node_);
        return const_iterator(iter,Transform(*graph_));
    }
    const GRAPH * graph_;
    Node node_;
};


template<class GRAPH>
struct IncEdgeIteratorHolder{
    typedef typename GRAPH::Node Node;
    typedef typename GRAPH::Edge Edge;
    typedef typename GRAPH::OutArcIt Iter;
    typedef detail_python_graph::ArcToArcHolder<GRAPH> Transform;
    typedef boost::transform_iterator<Transform ,Iter ,ArcHolder<GRAPH>, ArcHolder<GRAPH> > const_iterator;
    IncEdgeIteratorHolder(const GRAPH & graph,const Node & node)
    : graph_(&graph),
      node_(node){
    }
    const_iterator begin()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::outArcBegin(*graph_,node_);
        return const_iterator(iter,Transform(*graph_));
    }
    const_iterator end()const{
        Iter iter = GraphIteratorAccessor<GRAPH>::outArcEnd(*graph_,node_);
        return const_iterator(iter,Transform(*graph_));
    }
    const GRAPH * graph_;
    Node node_;
};


template<class G,class AV>
class NumpyScalarEdgeMap{

public:
    typedef G  Graph;
    typedef AV ArrayView;
    typedef typename  Graph::Edge                Key;
    typedef typename  ArrayView::value_type      Value;
    typedef typename  ArrayView::reference       Reference;
    typedef typename  ArrayView::const_reference ConstReference;

    typedef typename  Graph::Edge                key_type;
    typedef typename  ArrayView::value_type      value_type;
    typedef typename  ArrayView::reference       reference;
    typedef typename  ArrayView::const_reference const_reference;

    NumpyScalarEdgeMap()
    :   graph_(NULL),
        array_(){
    }

    NumpyScalarEdgeMap(const Graph & graph,ArrayView array)
    :   graph_(&graph),
        array_(array){
    }

    Reference operator[](const Key & key){
        return array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicEdgeCoordinate(*graph_,key)];
    }
    ConstReference operator[](const Key & key)const{
        return   array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicEdgeCoordinate(*graph_,key)];
    }
private:
    bool any()const{
        return array_.any();
    }
    const Graph * graph_;
    MultiArrayView<IntrinsicGraphShape<Graph>::IntrinsicEdgeMapDimension,Value> array_;

};

template<class G,class AV>
class NumpyScalarNodeMap{

public:
    typedef G  Graph;
    typedef AV ArrayView;
    typedef typename  Graph::Node                Key;
    typedef typename  ArrayView::value_type      Value;
    typedef typename  ArrayView::reference       Reference;
    typedef typename  ArrayView::const_reference ConstReference;

    typedef typename  Graph::Node                key_type;
    typedef typename  ArrayView::value_type      value_type;
    typedef typename  ArrayView::reference       reference;
    typedef typename  ArrayView::const_reference const_reference;
    //typedef Value &                                Reference;
    //typedef const Value &                          ConstReference;

    NumpyScalarNodeMap()
    :   graph_(NULL),
        array_(){
    }

    NumpyScalarNodeMap(const Graph & graph,ArrayView array)
    :   graph_(&graph),
        array_(array){
    }

    Reference operator[](const Key & key){
        return array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicNodeCoordinate(*graph_,key)];
    }
    ConstReference operator[](const Key & key)const{
        return   array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicNodeCoordinate(*graph_,key)];
    }
    bool any()const{
        return array_.any();
    }
private:
    const Graph * graph_;
    MultiArrayView<IntrinsicGraphShape<Graph>::IntrinsicNodeMapDimension,Value> array_;

};


template<class G,class AV>
class NumpyMultibandNodeMap{

public:
    typedef G  Graph;
    typedef AV ArrayView;
    typedef typename  Graph::Node                Key;
    typedef typename  Graph::Node                key_type;

    //typedef typename  ArrayView::value_type      Value;
    //typedef typename  ArrayView::reference       Reference;
    //typedef typename  ArrayView::const_reference ConstReference;

    typedef  MultiArray<1,typename AV::value_type>           Value;
    typedef  MultiArrayView<1,typename AV::value_type>       Reference;
    typedef  MultiArrayView<1,typename AV::value_type> ConstReference;
    typedef  MultiArray<1,typename AV::value_type>           value_type;
    typedef  MultiArrayView<1,typename AV::value_type>       reference;
    typedef  MultiArrayView<1,typename AV::value_type> const_reference;
    //typedef Value &                                Reference;
    //typedef const Value &                          ConstReference;

    NumpyMultibandNodeMap()
    :   graph_(NULL),
        array_(){
    }

    NumpyMultibandNodeMap(const Graph & graph,ArrayView array)
    :   graph_(&graph),
        array_(array){
    }

    Reference operator[](const Key & key){
        return array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicNodeCoordinate(*graph_,key)];
    }
    ConstReference operator[](const Key & key)const{
        return array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicNodeCoordinate(*graph_,key)];
    }
    bool any()const{
        return array_.any();
    }
private:
    const Graph * graph_;
    mutable AV array_;

};


template<class G,class AV>
class NumpyMultibandEdgeMap{

public:
    typedef G  Graph;
    typedef AV ArrayView;
    typedef typename  Graph::Edge                Key;
    typedef typename  Graph::Edge                key_type;

    //typedef typename  ArrayView::value_type      Value;
    //typedef typename  ArrayView::reference       Reference;
    //typedef typename  ArrayView::const_reference ConstReference;

    typedef  MultiArray<1,typename AV::value_type>           Value;
    typedef  MultiArrayView<1,typename AV::value_type>       Reference;
    typedef  MultiArrayView<1,typename AV::value_type> ConstReference;
    typedef  MultiArray<1,typename AV::value_type>           value_type;
    typedef  MultiArrayView<1,typename AV::value_type>       reference;
    typedef  MultiArrayView<1,typename AV::value_type> const_reference;
    //typedef Value &                                Reference;
    //typedef const Value &                          ConstReference;

    NumpyMultibandEdgeMap()
    :   graph_(NULL),
        array_(){
    }

    NumpyMultibandEdgeMap(const Graph & graph,ArrayView array)
    :   graph_(&graph),
        array_(array){
    }

    Reference operator[](const Key & key){
        return array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicEdgeCoordinate(*graph_,key)];
    }
    ConstReference operator[](const Key & key)const{
        return   array_[GraphDescriptorToMultiArrayIndex<Graph>::intrinsicEdgeCoordinate(*graph_,key)];
    }
    bool any()const{
        return array_.any();
    }
private:
    const Graph * graph_;
    mutable AV array_;

};






// tagged shape for lemon graphs
// edge map / node map / arc map 
template<class G>
class TaggedGraphShape{
public:
    typedef G Graph;
    const static unsigned int ND = IntrinsicGraphShape<Graph>::IntrinsicNodeMapDimension;
    const static unsigned int ED = IntrinsicGraphShape<Graph>::IntrinsicEdgeMapDimension;
    const static unsigned int AD = IntrinsicGraphShape<Graph>::IntrinsicArcMapDimension;
    static TaggedShape  taggedNodeMapShape(const Graph & graph){
        return NumpyArray<ND,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicNodeMapShape(graph),"n");
    }
    static TaggedShape  taggedEdgeMapShape(const Graph & graph){
        return NumpyArray<ED,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicEdgeMapShape(graph),"e");
    }
    static TaggedShape  taggedArcMapShape(const Graph & graph){
        return NumpyArray<AD,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicArcMapShape(graph),"e");
    }

    static AxisInfo  axistagsNodeMap(const Graph & graph){
        return AxisInfo("n");
    }
    static AxisInfo  axistagsEdgeMap(const Graph & graph){
        return AxisInfo("e");
    }
    static AxisTags  axistagsArcMap(const Graph & graph){
        return AxisInfo("e");
    }
};

// macro to specialize TaggedGraphShape for 
// grid graphs up to 4 dimensions
#define VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO(DIM,tn,te,ta) \
template<class BOOST_DIRECTED_TAG> \
class TaggedGraphShape<GridGraph<DIM,BOOST_DIRECTED_TAG> >{ \
public: \
    typedef GridGraph<DIM,BOOST_DIRECTED_TAG> Graph; \
    const static unsigned int ND = IntrinsicGraphShape<Graph>::IntrinsicNodeMapDimension; \
    const static unsigned int ED = IntrinsicGraphShape<Graph>::IntrinsicEdgeMapDimension; \
    const static unsigned int AD = IntrinsicGraphShape<Graph>::IntrinsicArcMapDimension; \
    static TaggedShape  taggedNodeMapShape(const Graph & graph){ \
       return NumpyArray<ND,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicNodeMapShape(graph),tn); \
    } \
    static TaggedShape  taggedEdgeMapShape(const Graph & graph){  \
       return NumpyArray<ED,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicEdgeMapShape(graph),te);  \
    } \
    static TaggedShape  taggedArcMapShape(const Graph & graph){  \
       return NumpyArray<AD,int>::ArrayTraits::taggedShape(IntrinsicGraphShape<Graph>::intrinsicArcMapShape(graph),ta);  \
    } \
    static AxisInfo  axistagsNodeMap(const Graph & graph){ \
        return AxisInfo(tn); \
    } \
    static AxisInfo  axistagsEdgeMap(const Graph & graph){ \
        return AxisInfo(te); \
    } \
    static AxisTags  axistagsArcMap(const Graph & graph){ \
        return AxisInfo(ta); \
    } \
};

VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO(1,"x","xe","xe");
VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO(2,"xy","xye","xye");
VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO(3,"xyz","xyze","xyze");
VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO(4,"xyzt","xyzte","xyzte");

#undef VIGRA_MAKE_TAGGED_GRAPH_SHAPE_MACRO


/*
// TODO ASK UKOETHE FOR HELP HERE
template<unsigned int G_DIM ,class T,class G,unsigned int OG_DIM>
void reshapeNodeMapIfEmpty(
    const G & graph,
    const NumpyArray<OG_DIM,T> & otherArray,
    NumpyArray<G_DIM ,T> & toReshapeArray
){
    const static unsigned int GraphNodeMapDim = IntrinsicGraphShape<G>::IntrinsicNodeMapDimension;
    const static unsigned int OutShapeLength  = GraphNodeMapDim == G_DIM ? G_DIM  : GraphNodeMapDim +1;
    typedef typename MultiArray<OutShapeLength,int>::difference_type OutShapeType;
    OutShapeType outShape;
    for(size_t d=0;d<GraphNodeMapDim;++d){
        outShape[d]=IntrinsicGraphShape<G>::intrinsicNodeMapShape(graph)[d];
    }
    if( G_DIM == GraphNodeMapDim + 1){

        outShape[GraphNodeMapDim]=otherArray.shape(OG_DIM);
        if(GraphNodeMapDim==1)
            toReshapeArray.reshapeIfEmpty( NumpyArray<G_DIM ,T>::ArrayTraits::taggedShape(outShape,"xc"));
        else if(GraphNodeMapDim==2)
            toReshapeArray.reshapeIfEmpty( NumpyArray<G_DIM ,T>::ArrayTraits::taggedShape(outShape,"xyc"));
        else if(GraphNodeMapDim==3)
            toReshapeArray.reshapeIfEmpty( NumpyArray<G_DIM ,T>::ArrayTraits::taggedShape(outShape,"xyzc"));
        else if(GraphNodeMapDim==4)
            toReshapeArray.reshapeIfEmpty( NumpyArray<G_DIM ,T>::ArrayTraits::taggedShape(outShape,"xyztc"));
        else
            throw std::runtime_error("reshapeNodeMapIfEmpty does onnly support graphs with an intrinsic node map shape <=4");
    }
    else{
        toReshapeArray.reshapeIfEmpty(outShape);
    }
}
*/



template<class G,class T>
struct NumpyNodeMap
: 
    IfBool<
        IsMultiband<T>::value,
        NumpyMultibandNodeMap< G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension+1,T> > , 
        NumpyScalarNodeMap<    G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension  ,T> >
    >::type

{
    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension+1,T> , 
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension  ,T>
    >::type NumpyArrayType;


    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyMultibandNodeMap< G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension+1,T> > , 
        NumpyScalarNodeMap<    G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension  ,T> >
    >::type BaseType;

    NumpyNodeMap(const G & g, NumpyArrayType numpyArray)
    :BaseType(g,numpyArray){
    }

};


template<class G,class T>
struct NumpyEdgeMap
: 
    IfBool<
        IsMultiband<T>::value,
        NumpyMultibandEdgeMap< G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension+1,T> > , 
        NumpyScalarEdgeMap<    G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension  ,T> >
    >::type

{
    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension+1,T> , 
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension  ,T>
    >::type NumpyArrayType;


    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyMultibandEdgeMap< G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension+1,T> > , 
        NumpyScalarEdgeMap<    G ,  NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension  ,T> >
    >::type BaseType;

    NumpyEdgeMap(const G & g, NumpyArrayType numpyArray)
    :BaseType(g,numpyArray){
    }

};



template<class G,class T>
struct PyEdgeMapTraits{
    typedef NumpyEdgeMap<G,T> Map;
    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension+1,T> , 
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicEdgeMapDimension  ,T>
    >::type Array;
};




template<class G,class T>
struct PyNodeMapTraits{
    typedef NumpyNodeMap<G,T> Map;
    typedef typename IfBool<
        IsMultiband<T>::value,
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension+1,T> , 
        NumpyArray<IntrinsicGraphShape<G>::IntrinsicNodeMapDimension  ,T>
    >::type Array;
};


namespace cluster_operators{

template<class MERGE_GRAPH>
class PythonOperator{
    
    typedef PythonOperator<MERGE_GRAPH > SelfType;
public:


    typedef float WeightType;
    typedef MERGE_GRAPH MergeGraph;
    typedef typename MergeGraph::Graph Graph;
    typedef typename Graph::Edge GraphEdge;
    typedef typename Graph::Node GraphNode;
    typedef typename MergeGraph::Edge Edge;
    typedef typename MergeGraph::Node Node;
    typedef typename MergeGraph::EdgeIt EdgeIt;
    typedef typename MergeGraph::NodeIt NodeIt;
    typedef typename MergeGraph::IncEdgeIt IncEdgeIt;
    typedef typename MergeGraph::index_type index_type;
    typedef MergeGraphItemHelper<MergeGraph,Edge> EdgeHelper;
    typedef MergeGraphItemHelper<MergeGraph,Node> NodeHelper;


    typedef NodeHolder<MERGE_GRAPH> NodeHolderType;
    typedef EdgeHolder<MERGE_GRAPH> EdgeHolderType;

    PythonOperator(
        MergeGraph & mergeGraph,
        boost::python::object object,
        const bool useMergeNodeCallback,
        const bool useMergeEdgesCallback,
        const bool useEraseEdgeCallback
    )
    :   mergeGraph_(mergeGraph),
        object_(object)
    {
        if(useMergeNodeCallback){
            typedef typename MergeGraph::MergeNodeCallBackType Callback;
            Callback cb(Callback:: template from_method<SelfType,&SelfType::mergeNodes>(this));
            mergeGraph_.registerMergeNodeCallBack(cb);

        }
        if(useMergeEdgesCallback){
            typedef typename MergeGraph::MergeEdgeCallBackType Callback;
            Callback cb(Callback:: template from_method<SelfType,&SelfType::mergeEdges>(this));
            mergeGraph_.registerMergeEdgeCallBack(cb);
        }
        if(useEraseEdgeCallback){
            typedef typename MergeGraph::EraseEdgeCallBackType Callback;
            Callback cb(Callback:: template from_method<SelfType,&SelfType::eraseEdge>(this));
            mergeGraph_.registerEraseEdgeCallBack(cb);
        }

    }
    bool done(){
        bool retVal;
        try{
            retVal =  boost::python::extract<bool>(object_.attr("done")());
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::done");
        }
        return retVal;
    }
    void mergeEdges(const Edge & a,const Edge & b){
        try{
            const EdgeHolderType aa(mergeGraph_,a);
            const EdgeHolderType bb(mergeGraph_,b);
            object_.attr("mergeEdges")(aa,bb);
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::mergeEdges");
        }
    }
    void mergeNodes(const Node & a,const Node & b){\
        try{
            const NodeHolderType aa(mergeGraph_,a);
            const NodeHolderType bb(mergeGraph_,b);
            object_.attr("mergeNodes")(aa,bb);
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::mergeNodes");
        }
    }
    void eraseEdge(const Edge & e){
        try{
            const EdgeHolderType ee(mergeGraph_,e);
            object_.attr("eraseEdge")(ee);
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::eraseEdge");
        }
    }
    Edge contractionEdge(){
        EdgeHolderType eh;
        try{
            eh = boost::python::extract<EdgeHolderType>(object_.attr("contractionEdge")());
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::contractionEdge");
        }
        return eh;
    }
    WeightType contractionWeight()const{
        WeightType w;
        try{
            w = boost::python::extract<WeightType>(object_.attr("contractionWeight")());
        }
        catch(std::exception & e){
            std::cout<<"reason: "<<e.what()<<"\n";
            throw std::runtime_error("error while calling cluster_operators PythonOperator::contractionWeight");
        }
        return w;
    }

    MergeGraph & mergeGraph(){
        return mergeGraph_;
    }
private:
    MergeGraph & mergeGraph_;
    boost::python::object object_;
};

} // end namespace cluster_operators


} // namespace vigra

#endif // VIGRA_PYTHON_GRAPH_HXX