2018-08-08 18:38:06 +00:00
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//============================================================================
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// Copyright (c) Kitware, Inc.
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// All rights reserved.
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// See LICENSE.txt for details.
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2019-04-15 23:24:21 +00:00
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//
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2018-08-08 18:38:06 +00:00
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// This software is distributed WITHOUT ANY WARRANTY; without even
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// the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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// PURPOSE. See the above copyright notice for more information.
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//============================================================================
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// Copyright (c) 2018, The Regents of the University of California, through
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// Lawrence Berkeley National Laboratory (subject to receipt of any required approvals
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// from the U.S. Dept. of Energy). All rights reserved.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// (1) Redistributions of source code must retain the above copyright notice, this
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// list of conditions and the following disclaimer.
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//
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// (2) Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// (3) Neither the name of the University of California, Lawrence Berkeley National
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// Laboratory, U.S. Dept. of Energy nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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// ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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// WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
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// IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
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// INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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// BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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// DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
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// OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
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// OF THE POSSIBILITY OF SUCH DAMAGE.
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//
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//=============================================================================
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//
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// This code is an extension of the algorithm presented in the paper:
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// Parallel Peak Pruning for Scalable SMP Contour Tree Computation.
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// Hamish Carr, Gunther Weber, Christopher Sewell, and James Ahrens.
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// Proceedings of the IEEE Symposium on Large Data Analysis and Visualization
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// (LDAV), October 2016, Baltimore, Maryland.
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//
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// The PPP2 algorithm and software were jointly developed by
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// Hamish Carr (University of Leeds), Gunther H. Weber (LBNL), and
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// Oliver Ruebel (LBNL)
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//==============================================================================
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2018-09-26 17:48:37 +00:00
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#ifndef vtk_m_filter_ContourTreeUniformAugmented_h
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#define vtk_m_filter_ContourTreeUniformAugmented_h
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2018-08-08 18:38:06 +00:00
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#include <vtkm/Types.h>
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#include <vtkm/cont/ArrayHandle.h>
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2018-09-26 17:48:37 +00:00
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#include <vtkm/worklet/contourtree_augmented/ContourTree.h>
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2020-06-12 17:50:01 +00:00
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#include <vtkm/worklet/contourtree_distributed/MultiBlockContourTreeHelper.h>
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2018-08-08 18:38:06 +00:00
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2020-08-10 23:25:55 +00:00
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#include <vtkm/filter/FilterField.h>
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2020-06-12 17:50:01 +00:00
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#include <memory>
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2018-08-08 18:38:06 +00:00
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namespace vtkm
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{
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namespace filter
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{
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2020-01-27 10:57:02 +00:00
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/// \brief Construct the Contour Tree for a 2D or 3D regular mesh
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///
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/// This filter implements the parallel peak pruning algorithm. In contrast to
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/// the ContourTreeUniform filter, this filter is optimized to allow for the
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/// computation of the augmented contour tree, i.e., the contour tree including
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/// all regular mesh vertices. Augmentation with regular vertices is used in
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/// practice to compute statistics (e.g., volume), to segment the input mesh,
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/// facilitate iso-value selection, enable localization of all verticies of a
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/// mesh in the tree among others.
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///
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/// In addition to single-block computation, the filter also supports multi-block
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/// regular grids. The blocks are processed in parallel using DIY and then the
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/// tree are merged progressively using a binary-reduction scheme to compute the
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/// final contour tree. I.e., in the multi-block context, the final tree is
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/// constructed on rank 0.
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class ContourTreeAugmented : public vtkm::filter::FilterField<ContourTreeAugmented>
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{
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public:
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using SupportedTypes = vtkm::TypeListScalarAll;
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///
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/// Create the contour tree filter
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/// @param[in] useMarchingCubes Boolean indicating whether marching cubes (true) or freudenthal (false)
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/// connectivity should be used. Valid only for 3D input data. Default is false.
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/// @param[in] computeRegularStructure Unsigned int indicating whether the tree should be augmented.
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/// 0=no augmentation, 1=full augmentation, 2=boundary augmentation. The
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/// latter option (=2) is mainly relevant for multi-block input data to
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/// improve efficiency by considering only boundary vertices during the
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/// merging of data blocks.
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///
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VTKM_CONT
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ContourTreeAugmented(bool useMarchingCubes = false, unsigned int computeRegularStructure = 1);
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///
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/// Define the spatial decomposition of the data in case we run in parallel with a multi-block dataset
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///
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/// Note: Only used when running on a multi-block dataset.
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/// @param[in] blocksPerDim Number of data blocks used in each data dimension
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/// @param[in] globalSize Global extends of the input mesh (i.e., number of mesh points in each dimension)
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/// @param[in] localBlockIndices Array with the (x,y,z) index of each local data block with
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/// with respect to blocksPerDim
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/// @param[in] localBlockOrigins Array with the (x,y,z) origin (with regard to mesh index) of each
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/// local data block
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/// @param[in] localBlockSizes Array with the sizes (i.e., extends in number of mesh points) of each
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/// local data block
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VTKM_CONT
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void SetSpatialDecomposition(vtkm::Id3 blocksPerDim,
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vtkm::Id3 globalSize,
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const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockIndices,
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const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockOrigins,
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const vtkm::cont::ArrayHandle<vtkm::Id3>& localBlockSizes);
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2020-01-27 10:57:02 +00:00
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/// Output field "saddlePeak" wich is pairs of vertex ids indicating saddle and peak of contour
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2018-08-30 15:53:18 +00:00
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template <typename T, typename StorageType, typename DerivedPolicy>
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VTKM_CONT vtkm::cont::DataSet DoExecute(const vtkm::cont::DataSet& input,
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const vtkm::cont::ArrayHandle<T, StorageType>& field,
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const vtkm::filter::FieldMetadata& fieldMeta,
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vtkm::filter::PolicyBase<DerivedPolicy> policy);
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2018-08-08 18:38:06 +00:00
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2019-08-28 18:34:42 +00:00
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//@{
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/// when operating on vtkm::cont::MultiBlock we want to
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/// do processing across ranks as well. Just adding pre/post handles
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/// for the same does the trick.
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template <typename DerivedPolicy>
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VTKM_CONT void PreExecute(const vtkm::cont::PartitionedDataSet& input,
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const vtkm::filter::PolicyBase<DerivedPolicy>& policy);
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template <typename DerivedPolicy>
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VTKM_CONT void PostExecute(const vtkm::cont::PartitionedDataSet& input,
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vtkm::cont::PartitionedDataSet& output,
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const vtkm::filter::PolicyBase<DerivedPolicy>&);
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///
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/// Internal helper function that implements the actual functionality of PostExecute
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///
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/// In the case we operate on vtkm::cont::MultiBlock we need to merge the trees
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/// computed on the block to compute the final contour tree.
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2019-08-28 18:34:42 +00:00
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template <typename T, typename StorageType, typename DerivedPolicy>
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VTKM_CONT void DoPostExecute(
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const vtkm::cont::PartitionedDataSet& input,
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vtkm::cont::PartitionedDataSet& output,
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const vtkm::filter::FieldMetadata& fieldMeta,
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const vtkm::cont::ArrayHandle<T, StorageType>&, // dummy parameter to get the type
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vtkm::filter::PolicyBase<DerivedPolicy> policy);
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//@}
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2020-01-27 10:57:02 +00:00
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//@{
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/// Get the contour tree computed by the filter
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const vtkm::worklet::contourtree_augmented::ContourTree& GetContourTree() const;
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/// Get the sort order for the mesh vertices
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const vtkm::worklet::contourtree_augmented::IdArrayType& GetSortOrder() const;
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/// Get the number of iterations used to compute the contour tree
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vtkm::Id GetNumIterations() const;
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//@}
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private:
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/// Use marching cubes connectivity for computing the contour tree
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2018-08-21 18:41:22 +00:00
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bool UseMarchingCubes;
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2019-09-07 00:48:45 +00:00
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// 0=no augmentation, 1=full augmentation, 2=boundary augmentation
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unsigned int ComputeRegularStructure;
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2019-08-28 18:34:42 +00:00
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// TODO Should the additional fields below be add to the vtkm::filter::ResultField and what is the best way to represent them
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// Additional result fields not included in the vtkm::filter::ResultField returned by DoExecute
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/// The contour tree computed by the filter
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vtkm::worklet::contourtree_augmented::ContourTree ContourTreeData;
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/// Number of iterations used to compute the contour tree
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vtkm::Id NumIterations;
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/// Array with the sorted order of the mesh vertices
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vtkm::worklet::contourtree_augmented::IdArrayType MeshSortOrder;
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/// Helper object to help with the parallel merge when running with DIY in parallel with MulitBlock data
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std::unique_ptr<vtkm::worklet::contourtree_distributed::MultiBlockContourTreeHelper>
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MultiBlockTreeHelper;
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2018-08-21 18:41:22 +00:00
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};
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} // namespace filter
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} // namespace vtkm
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2018-08-08 18:38:06 +00:00
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2018-09-26 17:48:37 +00:00
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#include <vtkm/filter/ContourTreeUniformAugmented.hxx>
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#endif // vtk_m_filter_ContourTreeUniformAugmented_h
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