343 lines
15 KiB
C++
343 lines
15 KiB
C++
//============================================================================
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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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// 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 2014 Sandia Corporation.
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// Copyright 2014 UT-Battelle, LLC.
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// Copyright 2014 Los Alamos National Security.
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//
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// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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// the U.S. Government retains certain rights in this software.
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//
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// Under the terms of Contract DE-AC52-06NA25396 with Los Alamos National
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// Laboratory (LANL), the U.S. Government retains certain rights in
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// this software.
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//============================================================================
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// Copyright (c) 2016, Los Alamos National Security, LLC
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// All rights reserved.
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//
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// Copyright 2016. Los Alamos National Security, LLC.
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// This software was produced under U.S. Government contract DE-AC52-06NA25396
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// for Los Alamos National Laboratory (LANL), which is operated by
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// Los Alamos National Security, LLC for the U.S. Department of Energy.
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// The U.S. Government has rights to use, reproduce, and distribute this
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// software. NEITHER THE GOVERNMENT NOR LOS ALAMOS NATIONAL SECURITY, LLC
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// MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE
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// USE OF THIS SOFTWARE. If software is modified to produce derivative works,
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// such modified software should be clearly marked, so as not to confuse it
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// with the version available from LANL.
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//
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// Additionally, redistribution and use in source and binary forms, with or
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// without modification, are permitted provided that the following conditions
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// are met:
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//
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// 1. Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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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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// 3. Neither the name of Los Alamos National Security, LLC, Los Alamos
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// National Laboratory, LANL, the U.S. Government, nor the names of its
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// contributors may be used to endorse or promote products derived from
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// this software without specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY LOS ALAMOS NATIONAL SECURITY, LLC AND
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// CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING,
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// BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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// FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL LOS ALAMOS
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// NATIONAL SECURITY, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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// BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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// USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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// THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
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// THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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//============================================================================
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// This code is based on 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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//
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// COMMENTS:
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//
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// If we have computed the merge max & merge saddles correctly, we have substantially
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// computed the merge tree already. However, it is not in the same format as we have
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// previously represented it - in particular, we have yet to define all the merge arcs
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// and the superarcs we have collected are not the same as before - i.e. they are already
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// partially collapsed, but not according to the same rule as branch decomposition
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// This unit is therefore to get the same result out as before so we can set up an
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// automated crosscheck on the computation
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//
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// Compared to earlier versions, we have made a significant change - the merge tree
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// is only computed on critical points, not on the full array. We therefore have a
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// final step: to extend it to the full array. To do this, we will keep the initial
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// mergeArcs array which records a maximum for each vertex, as we need the information
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//
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// Each maximum is now labelled with the saddle it is mapped to, or to the global min
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// We therefore transfer this information back to the mergeArcs array, so that maxima
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// (including saddles) are marked with the (lower) vertex that is the low end of their
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// arc
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// BIG CHANGE: we can actually reuse the mergeArcs array for the final merge arc, for the
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// chain maximum for each (regular) point, and for the merge saddle for maxima. This is
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// slightly tricky and has some extra memory traffic, but it avoids duplicating arrays
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// unnecessarily
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//
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// Initially, mergeArcs will be set to an outbound neighbour (or self for extrema), as the
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// chainMaximum array used to be.
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//
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// After chains are built, then it will hold *AN* accessible extremum for each vertex.
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//
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// During the main processing, when an extremum is assigned a saddle, it will be stored
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// here. Regular points will still store pointers to an extremum.
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//
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// After this is done, if the mergeArc points lower/higher, it is pointing to a saddle.
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// Otherwise it is pointing to an extremum.
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//
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// And after the final pass, it will always point to the next along superarcs.
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//
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//=======================================================================================
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#ifndef vtkm_worklet_contourtree_mergetree_h
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#define vtkm_worklet_contourtree_mergetree_h
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#include <vtkm/cont/ArrayHandle.h>
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#include <vtkm/cont/ArrayHandleConstant.h>
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#include <vtkm/cont/DataSet.h>
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#include <vtkm/worklet/contourtree/PrintVectors.h>
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#include <vtkm/worklet/contourtree/ChainDoubler.h>
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#include <vtkm/worklet/contourtree/JoinSuperArcFinder.h>
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#include <vtkm/worklet/contourtree/JoinArcConnector.h>
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#include <vtkm/worklet/contourtree/VertexMergeComparator.h>
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//#define DEBUG_PRINT 1
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//#define DEBUG_FUNCTION_ENTRY 1
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//#define DEBUG_TIMING 1
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namespace vtkm {
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namespace worklet {
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namespace contourtree {
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template <typename T, typename StorageType, typename DeviceAdapter>
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class MergeTree
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{
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public:
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typedef typename vtkm::cont::DeviceAdapterAlgorithm<DeviceAdapter> DeviceAlgorithm;
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// original data array
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const vtkm::cont::ArrayHandle<T,StorageType> &values;
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// size of mesh
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vtkm::Id nRows, nCols, nSlices, nVertices, nLogSteps;
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// whether it is join or split tree
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bool isJoinTree;
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// vector of arcs representing the merge tree
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vtkm::cont::ArrayHandle<vtkm::Id> mergeArcs;
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// vector storing an extremum for each vertex
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vtkm::cont::ArrayHandle<vtkm::Id> extrema;
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// vector storing a saddle for each vertex
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vtkm::cont::ArrayHandle<vtkm::Id> saddles;
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// merge tree constructor
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MergeTree(const vtkm::cont::ArrayHandle<T,StorageType> &Values,
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vtkm::Id NRows,
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vtkm::Id NCols,
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vtkm::Id NSlices,
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bool IsJoinTree);
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// routine that does pointer-doubling in the mergeArc array
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void BuildRegularChains();
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// routine that computes the augmented merge tree superarcs from the merge graph
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void ComputeAugmentedSuperarcs();
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// routine that computes the augmented merge arcs from the superarcs
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// this is separate from the previous routine because it also gets called separately
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// once saddle & extrema are set for a given set of vertices, the merge arcs can be
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// computed for any subset of those vertices that contains all of the critical points
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void ComputeAugmentedArcs(vtkm::cont::ArrayHandle<vtkm::Id> &vertices);
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// debug routine
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void DebugPrint(const char *message);
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};
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// creates merge tree
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template <typename T, typename StorageType, typename DeviceAdapter>
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MergeTree<T,StorageType,DeviceAdapter>::MergeTree(
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const vtkm::cont::ArrayHandle<T,StorageType> &Values,
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vtkm::Id NRows,
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vtkm::Id NCols,
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vtkm::Id NSlices,
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bool IsJoinTree) :
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values(Values),
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nRows(NRows),
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nCols(NCols),
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nSlices(NSlices),
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isJoinTree(IsJoinTree)
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{
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nVertices = nRows * nCols * nSlices;
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nLogSteps = 1;
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for (vtkm::Id shifter = nVertices; shifter != 0; shifter >>= 1)
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nLogSteps++;
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vtkm::cont::ArrayHandleConstant<vtkm::Id> nullArray(0, nVertices);
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mergeArcs.Allocate(nVertices);
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extrema.Allocate(nVertices);
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saddles.Allocate(nVertices);
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DeviceAlgorithm::Copy(nullArray, mergeArcs);
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DeviceAlgorithm::Copy(nullArray, extrema);
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DeviceAlgorithm::Copy(nullArray, saddles);
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}
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// routine that does pointer-doubling in the saddles array
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template<typename T, typename StorageType, typename DeviceAdapter>
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void MergeTree<T,StorageType,DeviceAdapter>::BuildRegularChains()
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{
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#ifdef DEBUG_FUNCTION_ENTRY
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std::cout << std::endl;
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std::cout << "====================" << std::endl;
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std::cout << "Build Regular Chains" << std::endl;
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std::cout << "====================" << std::endl;
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std::cout << std::endl;
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#endif
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// 2. Create a temporary array so that we can alternate writing between them
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vtkm::cont::ArrayHandle<vtkm::Id> temporaryArcs;
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temporaryArcs.Allocate(nVertices);
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vtkm::cont::ArrayHandleIndex vertexIndexArray(nVertices);
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ChainDoubler chainDoubler;
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vtkm::worklet::DispatcherMapField<ChainDoubler> chainDoublerDispatcher(chainDoubler);
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// 3. Apply pointer-doubling to build chains to maxima, rocking between two arrays
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for (vtkm::Id logStep = 0; logStep < nLogSteps; logStep++)
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{
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chainDoublerDispatcher.Invoke(vertexIndexArray, // input
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extrema); // i/o whole array
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}
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} // BuildRegularChains()
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// routine that computes the augmented merge tree from the merge graph
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template <typename T, typename StorageType, typename DeviceAdapter>
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void MergeTree<T,StorageType,DeviceAdapter>::ComputeAugmentedSuperarcs()
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{
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#ifdef DEBUG_FUNCTION_ENTRY
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std::cout << std::endl;
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std::cout << "=================================" << std::endl;
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std::cout << "Compute Augmented Merge Superarcs" << std::endl;
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std::cout << "=================================" << std::endl;
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std::cout << std::endl;
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#endif
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// our first step is to assign every vertex to a pseudo-extremum based on how the
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// vertex ascends to a extremum, and the sequence of pruning for the extremum
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// to do this, we iterate as many times as pruning occurred
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// we run a little loop for each element until it finds its join superarc
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// expressed as a functor.
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vtkm::Id nExtrema = extrema.GetNumberOfValues();
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JoinSuperArcFinder<T> joinSuperArcFinder(isJoinTree);
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vtkm::worklet::DispatcherMapField<JoinSuperArcFinder<T> >
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joinSuperArcFinderDispatcher(joinSuperArcFinder);
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vtkm::cont::ArrayHandleIndex vertexIndexArray(nExtrema);
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joinSuperArcFinderDispatcher.Invoke(vertexIndexArray, // input
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values, // input (whole array)
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saddles, // i/o (whole array)
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extrema); // i/o (whole array)
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// at the end of this, all vertices should have a pseudo-extremum in the extrema array
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// and a pseudo-saddle in the saddles array
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#ifdef DEBUG_PRINT
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DebugPrint("Merge Superarcs Set");
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#endif
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} // ComputeAugmentedSuperarcs()
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// routine that computes the augmented merge arcs from the superarcs
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// this is separate from the previous routine because it also gets called separately
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// once saddle & extrema are set for a given set of vertices, the merge arcs can be
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// computed for any subset of those vertices that contains all of the critical points
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template <typename T, typename StorageType, typename DeviceAdapter>
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void MergeTree<T,StorageType,DeviceAdapter>::ComputeAugmentedArcs(
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vtkm::cont::ArrayHandle<vtkm::Id> &vertices)
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{
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#ifdef DEBUG_FUNCTION_ENTRY
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std::cout << std::endl;
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std::cout << "============================" << std::endl;
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std::cout << "Compute Augmented Merge Arcs" << std::endl;
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std::cout << "============================" << std::endl;
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std::cout << std::endl;
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#endif
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// create a vector of indices for sorting
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vtkm::Id nCriticalVerts = vertices.GetNumberOfValues();
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vtkm::cont::ArrayHandle<vtkm::Id> vertexSorter;
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DeviceAlgorithm::Copy(vertices, vertexSorter);
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// We sort by pseudo-maximum to establish the extents
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DeviceAlgorithm::Sort(vertexSorter,
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VertexMergeComparator<T,StorageType,DeviceAdapter>(
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values.PrepareForInput(DeviceAdapter()),
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extrema.PrepareForInput(DeviceAdapter()),
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isJoinTree));
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#ifdef DEBUG_PRINT
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DebugPrint("Sorting Complete");
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#endif
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vtkm::cont::ArrayHandleConstant<vtkm::Id> noVertArray(NO_VERTEX_ASSIGNED, nVertices);
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DeviceAlgorithm::Copy(noVertArray, mergeArcs);
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vtkm::cont::ArrayHandleIndex critVertexIndexArray(nCriticalVerts);
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JoinArcConnector joinArcConnector;
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vtkm::worklet::DispatcherMapField<JoinArcConnector>
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joinArcConnectorDispatcher(joinArcConnector);
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joinArcConnectorDispatcher.Invoke(critVertexIndexArray, // input
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vertexSorter, // input (whole array)
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extrema, // input (whole array)
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saddles, // input (whole array)
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mergeArcs); // output (whole array)
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#ifdef DEBUG_PRINT
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DebugPrint("Augmented Arcs Set");
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#endif
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} // ComputeAugmentedArcs()
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// debug routine
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template<typename T, typename StorageType, typename DeviceAdapter>
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void MergeTree<T,StorageType,DeviceAdapter>::DebugPrint(const char *message)
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{
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std::cout << "---------------------------" << std::endl;
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std::cout << std::string(message) << std::endl;
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std::cout << "---------------------------" << std::endl;
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std::cout << std::endl;
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printLabelledBlock("Values", values, nRows*nSlices, nCols);
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std::cout << std::endl;
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printLabelledBlock("MergeArcs", mergeArcs, nRows, nCols);
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std::cout << std::endl;
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printLabelledBlock("Extrema", extrema, nRows, nCols);
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std::cout << std::endl;
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printLabelledBlock("Saddles", saddles, nRows, nCols);
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std::cout << std::endl;
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} // DebugPrint()
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}
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}
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}
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#endif
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