//============================================================================
//  Copyright (c) Kitware, Inc.
//  All rights reserved.
//  See LICENSE.txt for details.
//  This software is distributed WITHOUT ANY WARRANTY; without even
//  the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
//  PURPOSE.  See the above copyright notice for more information.
//
//  Copyright 2014 Sandia Corporation.
//  Copyright 2014 UT-Battelle, LLC.
//  Copyright 2014 Los Alamos National Security.
//
//  Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
//  the U.S. Government retains certain rights in this software.
//
//  Under the terms of Contract DE-AC52-06NA25396 with Los Alamos National
//  Laboratory (LANL), the U.S. Government retains certain rights in
//  this software.
//============================================================================
//  Copyright (c) 2016, Los Alamos National Security, LLC
//  All rights reserved.
//
//  Copyright 2016. Los Alamos National Security, LLC. 
//  This software was produced under U.S. Government contract DE-AC52-06NA25396 
//  for Los Alamos National Laboratory (LANL), which is operated by 
//  Los Alamos National Security, LLC for the U.S. Department of Energy. 
//  The U.S. Government has rights to use, reproduce, and distribute this 
//  software.  NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC 
//  MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE 
//  USE OF THIS SOFTWARE.  If software is modified to produce derivative works, 
//  such modified software should be clearly marked, so as not to confuse it 
//  with the version available from LANL.
//
//  Additionally, 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.
//  3. Neither the name of Los Alamos National Security, LLC, Los Alamos 
//     National Laboratory, LANL, the U.S. Government, nor the names of its 
//     contributors may be used to endorse or promote products derived from 
//     this software without specific prior written permission.
//
//  THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC AND 
//  CONTRIBUTORS "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 LOS ALAMOS 
//  NATIONAL SECURITY, LLC OR CONTRIBUTORS 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 
//  THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 
//  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF 
//  THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
//============================================================================

//  This code is based on the algorithm presented in the paper:  
//  “Parallel Peak Pruning for Scalable SMP Contour Tree Computation.” 
//  Hamish Carr, Gunther Weber, Christopher Sewell, and James Ahrens. 
//  Proceedings of the IEEE Symposium on Large Data Analysis and Visualization 
//  (LDAV), October 2016, Baltimore, Maryland.

//=======================================================================================
//
// COMMENTS:
//
//	If we have computed the merge max & merge saddles correctly, we have substantially
//	computed the merge tree already. However, it is not in the same format as we have
//	previously represented it - in particular, we have yet to define all the merge arcs
//      and the superarcs we have collected are not the same as before - i.e. they are already
//	partially collapsed, but not according to the same rule as branch decomposition
//	This unit is therefore to get the same result out as before so we can set up an
//	automated crosscheck on the computation
//
//	Compared to earlier versions, we have made a significant change - the merge tree
// 	is only computed on critical points, not on the full array.  We therefore have a 
//	final step: to extend it to the full array. To do this, we will keep the initial 
//	mergeArcs array which records a maximum for each vertex, as we need the information
//	
//	Each maximum is now labelled with the saddle it is mapped to, or to the global min
//	We therefore transfer this information back to the mergeArcs array, so that maxima
//	(including saddles) are marked with the (lower) vertex that is the low end of their
//	arc

//	BIG CHANGE: we can actually reuse the mergeArcs array for the final merge arc, for the
//	chain maximum for each (regular) point, and for the merge saddle for maxima.  This is
//	slightly tricky and has some extra memory traffic, but it avoids duplicating arrays
//	unnecessarily
//	
//	Initially, mergeArcs will be set to an outbound neighbour (or self for extrema), as the
//	chainMaximum array used to be.  
//
//	After chains are built, then it will hold *AN* accessible extremum for each vertex.
//
//	During the main processing, when an extremum is assigned a saddle, it will be stored 
//	here. Regular points will still store pointers to an extremum.
//
//	After this is done, if the mergeArc points lower/higher, it is pointing to a saddle. 
//      Otherwise it is pointing to an extremum.
//
//	And after the final pass, it will always point to the next along superarcs.
//
//=======================================================================================

#ifndef vtkm_worklet_contourtree_mergetree_h
#define vtkm_worklet_contourtree_mergetree_h

#include <vtkm/cont/ArrayHandle.h>
#include <vtkm/cont/ArrayHandleConstant.h>
#include <vtkm/cont/DataSet.h>

#include <vtkm/worklet/contourtree/PrintVectors.h>
#include <vtkm/worklet/contourtree/ChainDoubler.h>
#include <vtkm/worklet/contourtree/JoinSuperArcFinder.h>
#include <vtkm/worklet/contourtree/JoinArcConnector.h>
#include <vtkm/worklet/contourtree/VertexMergeComparator.h>

//#define DEBUG_PRINT 1
//#define DEBUG_FUNCTION_ENTRY 1
//#define DEBUG_TIMING 1

namespace vtkm {
namespace worklet {
namespace contourtree {

template <typename T, typename StorageType, typename DeviceAdapter>
class MergeTree
{
public:	
        typedef typename vtkm::cont::DeviceAdapterAlgorithm<DeviceAdapter> DeviceAlgorithm;

        // original data array
        const vtkm::cont::ArrayHandle<T,StorageType> &values;

        // size of mesh
	vtkm::Id nRows, nCols, nSlices, nVertices, nLogSteps;

	// whether it is join or split tree
	bool isJoinTree;
	
	// vector of arcs representing the merge tree
	vtkm::cont::ArrayHandle<vtkm::Id> mergeArcs;
	
	// vector storing an extremum for each vertex
	vtkm::cont::ArrayHandle<vtkm::Id> extrema;
	
	// vector storing a saddle for each vertex
	vtkm::cont::ArrayHandle<vtkm::Id> saddles;
	
	// merge tree constructor
	MergeTree(const vtkm::cont::ArrayHandle<T,StorageType> &Values,
                  vtkm::Id NRows, 
                  vtkm::Id NCols, 
                  vtkm::Id NSlices, 
                  bool IsJoinTree);

	// routine that does pointer-doubling in the mergeArc array
	void BuildRegularChains();

	// routine that computes the augmented merge tree superarcs from the merge graph
	void ComputeAugmentedSuperarcs();

	// routine that computes the augmented merge arcs from the superarcs
	// this is separate from the previous routine because it also gets called separately
	// once saddle & extrema are set for a given set of vertices, the merge arcs can be
	// computed for any subset of those vertices that contains all of the critical points
	void ComputeAugmentedArcs(vtkm::cont::ArrayHandle<vtkm::Id> &vertices);

	// debug routine
	void DebugPrint(const char *message);
};

// creates merge tree
template <typename T, typename StorageType, typename DeviceAdapter>
MergeTree<T,StorageType,DeviceAdapter>::MergeTree(
                  const vtkm::cont::ArrayHandle<T,StorageType> &Values,
                  vtkm::Id NRows, 
                  vtkm::Id NCols, 
                  vtkm::Id NSlices, 
                  bool IsJoinTree) :
                                     values(Values),
                                     nRows(NRows),
                                     nCols(NCols),
                                     nSlices(NSlices),
                                     isJoinTree(IsJoinTree)
{
  nVertices = nRows * nCols * nSlices;
  nLogSteps = 1;
  for (vtkm::Id shifter = nVertices; shifter != 0; shifter >>= 1)
    nLogSteps++;

  vtkm::cont::ArrayHandleConstant<vtkm::Id> nullArray(0, nVertices);

  mergeArcs.Allocate(nVertices);
  extrema.Allocate(nVertices);
  saddles.Allocate(nVertices);

  DeviceAlgorithm::Copy(nullArray, mergeArcs);
  DeviceAlgorithm::Copy(nullArray, extrema);
  DeviceAlgorithm::Copy(nullArray, saddles);
}

// routine that does pointer-doubling in the saddles array
template<typename T, typename StorageType, typename DeviceAdapter>
void MergeTree<T,StorageType,DeviceAdapter>::BuildRegularChains()
{
#ifdef DEBUG_FUNCTION_ENTRY
		std::cout << std::endl;
		std::cout << "====================" << std::endl;
		std::cout << "Build Regular Chains" << std::endl;
		std::cout << "====================" << std::endl;
		std::cout << std::endl;
#endif
	// 2. Create a temporary array so that we can alternate writing between them
	vtkm::cont::ArrayHandle<vtkm::Id> temporaryArcs;
        temporaryArcs.Allocate(nVertices);

        vtkm::cont::ArrayHandleIndex vertexIndexArray(nVertices);
        ChainDoubler chainDoubler;
        vtkm::worklet::DispatcherMapField<ChainDoubler> chainDoublerDispatcher(chainDoubler);

        // 3. Apply pointer-doubling to build chains to maxima, rocking between two arrays
        for (vtkm::Id logStep = 0; logStep < nLogSteps; logStep++)
        {
          chainDoublerDispatcher.Invoke(vertexIndexArray,  // input
                                        extrema);          // i/o whole array
        }
} // BuildRegularChains()

// routine that computes the augmented merge tree from the merge graph
template <typename T, typename StorageType, typename DeviceAdapter>
void MergeTree<T,StorageType,DeviceAdapter>::ComputeAugmentedSuperarcs()
{
#ifdef DEBUG_FUNCTION_ENTRY
		std::cout << std::endl;
		std::cout << "=================================" << std::endl;
		std::cout << "Compute Augmented Merge Superarcs" << std::endl;
		std::cout << "=================================" << std::endl;
		std::cout << std::endl;
#endif

  // our first step is to assign every vertex to a pseudo-extremum based on how the
  // vertex ascends to a extremum, and the sequence of pruning for the extremum
  // to do this, we iterate as many times as pruning occurred
	
  // we run a little loop for each element until it finds its join superarc
  // expressed as a functor.
  vtkm::Id nExtrema = extrema.GetNumberOfValues();

  JoinSuperArcFinder<T> joinSuperArcFinder(isJoinTree);
  vtkm::worklet::DispatcherMapField<JoinSuperArcFinder<T> >
                 joinSuperArcFinderDispatcher(joinSuperArcFinder);
  vtkm::cont::ArrayHandleIndex vertexIndexArray(nExtrema);

  joinSuperArcFinderDispatcher.Invoke(vertexIndexArray, // input
                                      values,           // input (whole array)
                                      saddles,          // i/o (whole array)
                                      extrema);         // i/o (whole array)

  // at the end of this, all vertices should have a pseudo-extremum in the extrema array 
  // and a pseudo-saddle in the saddles array
#ifdef DEBUG_PRINT
  DebugPrint("Merge Superarcs Set");
#endif
} // ComputeAugmentedSuperarcs()

// routine that computes the augmented merge arcs from the superarcs
// this is separate from the previous routine because it also gets called separately
// once saddle & extrema are set for a given set of vertices, the merge arcs can be
// computed for any subset of those vertices that contains all of the critical points
template <typename T, typename StorageType, typename DeviceAdapter>
void MergeTree<T,StorageType,DeviceAdapter>::ComputeAugmentedArcs(
                             vtkm::cont::ArrayHandle<vtkm::Id> &vertices)
{
#ifdef DEBUG_FUNCTION_ENTRY
		std::cout << std::endl;
		std::cout << "============================" << std::endl;
		std::cout << "Compute Augmented Merge Arcs" << std::endl;
		std::cout << "============================" << std::endl;
		std::cout << std::endl;
#endif

  // create a vector of indices for sorting
  vtkm::Id nCriticalVerts = vertices.GetNumberOfValues();
  vtkm::cont::ArrayHandle<vtkm::Id> vertexSorter;
  DeviceAlgorithm::Copy(vertices, vertexSorter);

  // We sort by pseudo-maximum to establish the extents
  DeviceAlgorithm::Sort(vertexSorter,
                        VertexMergeComparator<T,StorageType,DeviceAdapter>(
                                              values.PrepareForInput(DeviceAdapter()),
                                              extrema.PrepareForInput(DeviceAdapter()),
                                              isJoinTree));
#ifdef DEBUG_PRINT
  DebugPrint("Sorting Complete");
#endif

  vtkm::cont::ArrayHandleConstant<vtkm::Id> noVertArray(NO_VERTEX_ASSIGNED, nVertices);
  DeviceAlgorithm::Copy(noVertArray, mergeArcs);

  vtkm::cont::ArrayHandleIndex critVertexIndexArray(nCriticalVerts);
  JoinArcConnector joinArcConnector;
  vtkm::worklet::DispatcherMapField<JoinArcConnector>
                 joinArcConnectorDispatcher(joinArcConnector);

  joinArcConnectorDispatcher.Invoke(critVertexIndexArray,  // input
                                    vertexSorter,          // input (whole array)
                                    extrema,               // input (whole array)
                                    saddles,               // input (whole array)
                                    mergeArcs);            // output (whole array)
#ifdef DEBUG_PRINT
  DebugPrint("Augmented Arcs Set");	
#endif
} // ComputeAugmentedArcs()
	
// debug routine
template<typename T, typename StorageType, typename DeviceAdapter>
void MergeTree<T,StorageType,DeviceAdapter>::DebugPrint(const char *message)
{
  std::cout << "---------------------------" << std::endl;
  std::cout << std::string(message) << std::endl;
  std::cout << "---------------------------" << std::endl;
  std::cout << std::endl;

  printLabelledBlock("Values", values, nRows*nSlices, nCols);
  std::cout << std::endl;
  printLabelledBlock("MergeArcs", mergeArcs, nRows, nCols);
  std::cout << std::endl;
  printLabelledBlock("Extrema", extrema, nRows, nCols);
  std::cout << std::endl;
  printLabelledBlock("Saddles", saddles, nRows, nCols);
  std::cout << std::endl;
} // DebugPrint()	

}
}
}
#endif