mirror of
https://gitlab.kitware.com/vtk/vtk-m
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201 lines
8.8 KiB
C++
201 lines
8.8 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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//
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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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#ifndef vtk_m_worklet_NDimsHistMarginalization_h
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#define vtk_m_worklet_NDimsHistMarginalization_h
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#include <vtkm/Math.h>
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#include <vtkm/cont/Algorithm.h>
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#include <vtkm/cont/ArrayCopy.h>
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#include <vtkm/cont/ArrayHandle.h>
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#include <vtkm/cont/ArrayHandleCounting.h>
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#include <vtkm/cont/DataSet.h>
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#include <vtkm/worklet/DispatcherMapField.h>
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#include <vtkm/worklet/WorkletMapField.h>
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#include <vtkm/worklet/histogram/ComputeNDHistogram.h>
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#include <vtkm/worklet/histogram/MarginalizeNDHistogram.h>
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#include <vtkm/cont/Field.h>
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namespace vtkm
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{
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namespace worklet
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{
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class NDimsHistMarginalization
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{
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public:
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// Execute the histogram (conditional) marginalization,
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// given the multi-variable histogram(binId, freqIn)
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// , marginalVariable and marginal condition
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// Input arguments:
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// binId, freqsIn: input ND-histogram in the fashion of sparse representation
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// (definition of binId and frqIn please refer to NDimsHistogram.h),
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// (binId.size() is the number of variables)
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// numberOfBins: number of bins of each variable (length of numberOfBins must be the same as binId.size() )
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// marginalVariables: length is the same as number of variables.
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// 1 indicates marginal variable, otherwise 0.
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// conditionFunc: The Condition function for non-marginal variable.
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// This func takes two arguments (vtkm::Id var, vtkm::Id binId) and return bool
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// var is index of variable and binId is bin index in the variable var
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// return true indicates considering this bin into final marginal histogram
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// more details can refer to example in UnitTestNDimsHistMarginalization.cxx
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// marginalBinId, marginalFreqs: return marginalized histogram in the fashion of sparse representation
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// the definition is the same as (binId and freqsIn)
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template <typename BinaryCompare>
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void Run(const std::vector<vtkm::cont::ArrayHandle<vtkm::Id>>& binId,
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vtkm::cont::ArrayHandle<vtkm::Id>& freqsIn,
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vtkm::cont::ArrayHandle<vtkm::Id>& numberOfBins,
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vtkm::cont::ArrayHandle<bool>& marginalVariables,
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BinaryCompare conditionFunc,
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std::vector<vtkm::cont::ArrayHandle<vtkm::Id>>& marginalBinId,
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vtkm::cont::ArrayHandle<vtkm::Id>& marginalFreqs)
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{
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//total variables
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vtkm::Id numOfVariable = static_cast<vtkm::Id>(binId.size());
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const vtkm::Id numberOfValues = freqsIn.GetNumberOfValues();
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vtkm::cont::ArrayHandleConstant<vtkm::Id> constant0Array(0, numberOfValues);
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vtkm::cont::ArrayHandle<vtkm::Id> bin1DIndex;
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vtkm::cont::ArrayCopy(constant0Array, bin1DIndex);
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vtkm::cont::ArrayHandle<vtkm::Id> freqs;
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vtkm::cont::ArrayCopy(freqsIn, freqs);
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vtkm::Id numMarginalVariables = 0; //count num of marginal variables
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const auto marginalPortal = marginalVariables.ReadPortal();
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const auto numBinsPortal = numberOfBins.ReadPortal();
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for (vtkm::Id i = 0; i < numOfVariable; i++)
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{
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if (marginalPortal.Get(i) == true)
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{
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// Worklet to calculate 1D index for marginal variables
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numMarginalVariables++;
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const vtkm::Id nFieldBins = numBinsPortal.Get(i);
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vtkm::worklet::histogram::To1DIndex binWorklet(nFieldBins);
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vtkm::worklet::DispatcherMapField<vtkm::worklet::histogram::To1DIndex> to1DIndexDispatcher(
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binWorklet);
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size_t vecIndex = static_cast<size_t>(i);
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to1DIndexDispatcher.Invoke(binId[vecIndex], bin1DIndex, bin1DIndex);
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}
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else
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{ //non-marginal variable
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// Worklet to set the frequency of entities which does not meet the condition
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// to 0 on non-marginal variables
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vtkm::worklet::histogram::ConditionalFreq<BinaryCompare> conditionalFreqWorklet{
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conditionFunc
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};
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conditionalFreqWorklet.setVar(i);
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vtkm::worklet::DispatcherMapField<vtkm::worklet::histogram::ConditionalFreq<BinaryCompare>>
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cfDispatcher(conditionalFreqWorklet);
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size_t vecIndex = static_cast<size_t>(i);
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cfDispatcher.Invoke(binId[vecIndex], freqs, freqs);
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}
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}
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// Sort the freq array for counting by key(1DIndex)
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vtkm::cont::Algorithm::SortByKey(bin1DIndex, freqs);
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// Add frequency within same 1d index bin (this get a nonSparse representation)
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vtkm::cont::ArrayHandle<vtkm::Id> nonSparseMarginalFreqs;
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vtkm::cont::Algorithm::ReduceByKey(
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bin1DIndex, freqs, bin1DIndex, nonSparseMarginalFreqs, vtkm::Add());
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// Convert to sparse representation(remove all zero freqncy entities)
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vtkm::cont::ArrayHandle<vtkm::Id> sparseMarginal1DBinId;
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vtkm::cont::Algorithm::CopyIf(bin1DIndex, nonSparseMarginalFreqs, sparseMarginal1DBinId);
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vtkm::cont::Algorithm::CopyIf(nonSparseMarginalFreqs, nonSparseMarginalFreqs, marginalFreqs);
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//convert back to multi variate binId
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marginalBinId.resize(static_cast<size_t>(numMarginalVariables));
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vtkm::Id marginalVarIdx = numMarginalVariables - 1;
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for (vtkm::Id i = numOfVariable - 1; i >= 0; i--)
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{
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if (marginalPortal.Get(i) == true)
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{
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const vtkm::Id nFieldBins = numBinsPortal.Get(i);
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vtkm::worklet::histogram::ConvertHistBinToND binWorklet(nFieldBins);
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vtkm::worklet::DispatcherMapField<vtkm::worklet::histogram::ConvertHistBinToND>
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convertHistBinToNDDispatcher(binWorklet);
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size_t vecIndex = static_cast<size_t>(marginalVarIdx);
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convertHistBinToNDDispatcher.Invoke(
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sparseMarginal1DBinId, sparseMarginal1DBinId, marginalBinId[vecIndex]);
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marginalVarIdx--;
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}
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}
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} //Run()
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// Execute the histogram marginalization WITHOUT CONDITION,
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// Please refer to the other Run() functions for the definition of input arguments.
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void Run(const std::vector<vtkm::cont::ArrayHandle<vtkm::Id>>& binId,
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vtkm::cont::ArrayHandle<vtkm::Id>& freqsIn,
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vtkm::cont::ArrayHandle<vtkm::Id>& numberOfBins,
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vtkm::cont::ArrayHandle<bool>& marginalVariables,
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std::vector<vtkm::cont::ArrayHandle<vtkm::Id>>& marginalBinId,
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vtkm::cont::ArrayHandle<vtkm::Id>& marginalFreqs)
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{
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//total variables
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vtkm::Id numOfVariable = static_cast<vtkm::Id>(binId.size());
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const vtkm::Id numberOfValues = freqsIn.GetNumberOfValues();
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vtkm::cont::ArrayHandleConstant<vtkm::Id> constant0Array(0, numberOfValues);
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vtkm::cont::ArrayHandle<vtkm::Id> bin1DIndex;
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vtkm::cont::ArrayCopy(constant0Array, bin1DIndex);
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vtkm::cont::ArrayHandle<vtkm::Id> freqs;
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vtkm::cont::ArrayCopy(freqsIn, freqs);
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vtkm::Id numMarginalVariables = 0; //count num of marginal variables
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const auto marginalPortal = marginalVariables.ReadPortal();
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const auto numBinsPortal = numberOfBins.ReadPortal();
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for (vtkm::Id i = 0; i < numOfVariable; i++)
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{
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if (marginalPortal.Get(i) == true)
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{
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// Worklet to calculate 1D index for marginal variables
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numMarginalVariables++;
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const vtkm::Id nFieldBins = numBinsPortal.Get(i);
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vtkm::worklet::histogram::To1DIndex binWorklet(nFieldBins);
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vtkm::worklet::DispatcherMapField<vtkm::worklet::histogram::To1DIndex> to1DIndexDispatcher(
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binWorklet);
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size_t vecIndex = static_cast<size_t>(i);
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to1DIndexDispatcher.Invoke(binId[vecIndex], bin1DIndex, bin1DIndex);
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}
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}
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// Sort the freq array for counting by key (1DIndex)
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vtkm::cont::Algorithm::SortByKey(bin1DIndex, freqs);
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// Add frequency within same 1d index bin
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vtkm::cont::Algorithm::ReduceByKey(bin1DIndex, freqs, bin1DIndex, marginalFreqs, vtkm::Add());
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//convert back to multi variate binId
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marginalBinId.resize(static_cast<size_t>(numMarginalVariables));
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vtkm::Id marginalVarIdx = numMarginalVariables - 1;
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for (vtkm::Id i = numOfVariable - 1; i >= 0; i--)
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{
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if (marginalPortal.Get(i) == true)
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{
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const vtkm::Id nFieldBins = numBinsPortal.Get(i);
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vtkm::worklet::histogram::ConvertHistBinToND binWorklet(nFieldBins);
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vtkm::worklet::DispatcherMapField<vtkm::worklet::histogram::ConvertHistBinToND>
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convertHistBinToNDDispatcher(binWorklet);
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size_t vecIndex = static_cast<size_t>(marginalVarIdx);
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convertHistBinToNDDispatcher.Invoke(bin1DIndex, bin1DIndex, marginalBinId[vecIndex]);
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marginalVarIdx--;
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}
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}
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} //Run()
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};
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}
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} // namespace vtkm::worklet
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#endif // vtk_m_worklet_NDimsHistMarginalization_h
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