vtk-m/vtkm/filter/ContourTreeUniformAugmented.h

//============================================================================
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//============================================================================
// Copyright (c) 2018, The Regents of the University of California, through
// Lawrence Berkeley National Laboratory (subject to receipt of any required approvals
// from the U.S. Dept. of Energy).  All rights reserved.
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//     Laboratory, U.S. Dept. of Energy nor the names of its contributors may be
//     used to endorse or promote products derived from this software without
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//=============================================================================
//
//  This code is an extension of 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.
//
//  The PPP2 algorithm and software were jointly developed by
//  Hamish Carr (University of Leeds), Gunther H. Weber (LBNL), and
//  Oliver Ruebel (LBNL)
//==============================================================================


#ifndef vtk_m_filter_ContourTreeUniformAugmented_h
#define vtk_m_filter_ContourTreeUniformAugmented_h

#include <vtkm/Types.h>
#include <vtkm/cont/ArrayHandle.h>
#include <vtkm/worklet/contourtree_augmented/ContourTree.h>
#include <vtkm/worklet/contourtree_augmented/Types.h>

#include <utility>
#include <vector>
#include <vtkm/Bounds.h>
#include <vtkm/filter/FilterCell.h>

namespace vtkm
{
namespace filter
{

namespace detail
{
class MultiBlockContourTreeHelper;
} // namespace detail

/// \brief Construct the Contour Tree for a 2D or 3D regular mesh
///
/// This filter implements the parallel peak pruning algorithm. In contrast to
/// the ContourTreeUniform filter, this filter is optimized to allow for the
/// computation of the augmented contour tree, i.e., the contour tree including
/// all regular mesh vertices. Augmentation with regular vertices is used in
/// practice to compute statistics (e.g., volume), to segment the input mesh,
/// facilitate iso-value selection, enable localization of all verticies of a
/// mesh in the tree among others.
///
/// In addition to single-block computation, the filter also supports multi-block
/// regular grids. The blocks are processed in parallel using DIY and then the
/// tree are merged progressively using a binary-reduction scheme to compute the
/// final contour tree. I.e., in the multi-block context, the final tree is
/// constructed on rank 0.
class ContourTreeAugmented : public vtkm::filter::FilterCell<ContourTreeAugmented>
{
public:
  using SupportedTypes = vtkm::TypeListScalarAll;
  ///
  /// Create the contour tree filter
  /// @param[in] useMarchingCubes Boolean indicating whether marching cubes (true) or freudenthal (false)
  ///                             connectivity should be used. Valid only for 3D input data. Default is false.
  /// @param[in] computeRegularStructure  Unsigned int indicating whether the tree should be augmented.
  ///                             0=no augmentation, 1=full augmentation, 2=boundary augmentation. The
  ///                             latter option (=2) is mainly relevant for multi-block input data to
  ///                             improve efficiency by considering only boundary vertices during the
  ///                             merging of data blocks.
  ///
  VTKM_CONT
  ContourTreeAugmented(bool useMarchingCubes = false, unsigned int computeRegularStructure = 1);

  ///
  /// Define the spatial decomposition of the data in case we run in parallel with a multi-block dataset
  ///
  /// Note: Only used when running on a multi-block dataset.
  /// @param[in] blocksPerDim  Number of data blocks used in each data dimension
  /// @param[in] globalSize  Global extends of the input mesh (i.e., number of mesh points in each dimension)
  /// @param[in] localBlockIndices  Array with the (x,y,z) index of each local data block with
  ///                               with respect to blocksPerDim
  /// @param[in] localBlockOrigins  Array with the (x,y,z) origin (with regard to mesh index) of each
  ///                               local data block
  /// @param[in] localBlockSizes    Array with the sizes (i.e., extends in number of mesh points) of each
  ///                               local data block
  VTKM_CONT
  void SetSpatialDecomposition(vtkm::Id3 blocksPerDim,
                               vtkm::Id3 globalSize,
                               const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockIndices,
                               const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockOrigins,
                               const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockSizes);

  /// Output field "saddlePeak" wich is pairs of vertex ids indicating saddle and peak of contour
  template <typename T, typename StorageType, typename DerivedPolicy>
  VTKM_CONT vtkm::cont::DataSet DoExecute(const vtkm::cont::DataSet& input,
                                          const vtkm::cont::ArrayHandle<T, StorageType>& field,
                                          const vtkm::filter::FieldMetadata& fieldMeta,
                                          vtkm::filter::PolicyBase<DerivedPolicy> policy);

  //@{
  /// when operating on vtkm::cont::MultiBlock we want to
  /// do processing across ranks as well. Just adding pre/post handles
  /// for the same does the trick.
  template <typename DerivedPolicy>
  VTKM_CONT void PreExecute(const vtkm::cont::PartitionedDataSet& input,
                            const vtkm::filter::PolicyBase<DerivedPolicy>& policy);

  template <typename DerivedPolicy>
  VTKM_CONT void PostExecute(const vtkm::cont::PartitionedDataSet& input,
                             vtkm::cont::PartitionedDataSet& output,
                             const vtkm::filter::PolicyBase<DerivedPolicy>&);


  ///
  /// Internal helper function that implements the actual functionality of PostExecute
  ///
  /// In the case we operate on vtkm::cont::MultiBlock we need to merge the trees
  /// computed on the block to compute the final contour tree.
  template <typename T, typename StorageType, typename DerivedPolicy>
  VTKM_CONT void DoPostExecute(
    const vtkm::cont::PartitionedDataSet& input,
    vtkm::cont::PartitionedDataSet& output,
    const vtkm::filter::FieldMetadata& fieldMeta,
    const vtkm::cont::ArrayHandle<T, StorageType>&, // dummy parameter to get the type
    vtkm::filter::PolicyBase<DerivedPolicy> policy);
  //@}

  //@{
  /// Get the contour tree computed by the filter
  const vtkm::worklet::contourtree_augmented::ContourTree& GetContourTree() const;
  /// Get the sort order for the mesh vertices
  const vtkm::worklet::contourtree_augmented::IdArrayType& GetSortOrder() const;
  /// Get the number of iterations used to compute the contour tree
  vtkm::Id GetNumIterations() const;
  //@}

private:
  /// Use marching cubes connectivity for computing the contour tree
  bool UseMarchingCubes;
  // 0=no augmentation, 1=full augmentation, 2=boundary augmentation
  unsigned int ComputeRegularStructure;

  // TODO Should the additional fields below be add to the vtkm::filter::ResultField and what is the best way to represent them
  // Additional result fields not included in the vtkm::filter::ResultField returned by DoExecute

  /// The contour tree computed by the filter
  vtkm::worklet::contourtree_augmented::ContourTree ContourTreeData;
  /// Number of iterations used to compute the contour tree
  vtkm::Id NumIterations;
  /// Array with the sorted order of the mesh vertices
  vtkm::worklet::contourtree_augmented::IdArrayType MeshSortOrder;
  /// Helper object to help with the parallel merge when running with DIY in parallel with MulitBlock data
  detail::MultiBlockContourTreeHelper* MultiBlockTreeHelper;
};

///
/// Helper struct to collect sizing information from the dataset
///
struct GetRowsColsSlices
{
  //@{
  /// Get the number of rows, cols, and slices of a vtkm::cont::CellSetStructured
  /// @param[in] cells  The input vtkm::cont::CellSetStructured
  /// @param[out] nRows  Number of rows (x) in the cell set
  /// @param[out[ nCols  Number of columns (y) in the cell set
  /// @param[out] nSlices Number of slices (z) in the cell set
  void operator()(const vtkm::cont::CellSetStructured<2>& cells,
                  vtkm::Id& nRows,
                  vtkm::Id& nCols,
                  vtkm::Id& nSlices) const
  {
    vtkm::Id2 pointDimensions = cells.GetPointDimensions();
    nRows = pointDimensions[0];
    nCols = pointDimensions[1];
    nSlices = 1;
  }
  void operator()(const vtkm::cont::CellSetStructured<3>& cells,
                  vtkm::Id& nRows,
                  vtkm::Id& nCols,
                  vtkm::Id& nSlices) const
  {
    vtkm::Id3 pointDimensions = cells.GetPointDimensions();
    nRows = pointDimensions[0];
    nCols = pointDimensions[1];
    nSlices = pointDimensions[2];
  }
  //@}

  ///  Raise ErrorBadValue if the input cell set is not a vtkm::cont::CellSetStructured<2> or <3>
  template <typename T>
  void operator()(const T& cells, vtkm::Id& nRows, vtkm::Id& nCols, vtkm::Id& nSlices) const
  {
    (void)nRows;
    (void)nCols;
    (void)nSlices;
    (void)cells;
    throw vtkm::cont::ErrorBadValue("Expected 2D or 3D structured cell cet! ");
  }
};

} // namespace filter
} // namespace vtkm

#include <vtkm/filter/ContourTreeUniformAugmented.hxx>

#endif // vtk_m_filter_ContourTreeUniformAugmented_h