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// Copyright (C) 2016 EDF
// All Rights Reserved
// This code is published under the GNU Lesser General Public License (GNU LGPL)
#ifndef SPARSEGRIDCUBICNOBOUND_H
#define SPARSEGRIDCUBICNOBOUND_H
#include <array>
#include <Eigen/Dense>
#include "StOpt/core/sparse/sparseGridTypes.h"
#include "StOpt/core/sparse/SparseGridHierarDehierarNoBound.h"
/** \file SparseGridCubicNoBound.h
* \brief Regroup hierarchization and dehierarchization for cubic sparse grids eliminating boundary points
* \author Xavier Warin
*/
namespace StOpt
{
/// \defgroup cubicSparseNoBound Cubic Hierarchization and Deheriarchization without boundary points
/// \brief Regroup function used in hierarchization and dehierarchization for sparse grids without any points on the boundary and a cubic approximation per mesh
///@{
/// \class Hierar1DCubicNoBound SparseGridCubicNoBound.h
/// Hierarchization
class Hierar1DCubicNoBound: public HierarDehierarNoBound
{
protected :
/// \brief Hierarchization in given dimension in 1D : general cubic
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_leftParentNodalValue Left parent nodal value
/// \param p_rightParentNodalValue Right parent nodal value
/// \param p_parentLinearHierarValue Linear Hierarchical value of parent
/// \param p_grandParentLinearHierarValue Linear Hierarchical value of grandparent
/// \param p_dataSet Data structure with all the points
/// \param p_nodalValues Nodal values
/// \param p_hierarValues Hierarchical values
template< class T, class TT>
void recursive1DHierarchization(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentNodalValue,
const T &p_rightParentNodalValue,
const T &p_parentLinearHierarValue,
const T &p_grandParentLinearHierarValue,
const SparseSet &p_dataSet,
const TT &p_nodalValues,
TT &p_hierarValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
// position
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_nodalValues, iposPoint);
// hierarchization
T LinearHierar = valueMidle - 0.5 * (p_leftParentNodalValue + p_rightParentNodalValue);
int iBaseType = iNodeToFunc[p_positionCurrent(p_idim) % 4];
// begin by linear
DoubleOrArray().affect(p_hierarValues, iposPoint, LinearHierar + weightParent[iBaseType]*p_parentLinearHierarValue + weightGrandParent[iBaseType]*p_grandParentLinearHierarValue);
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// left
p_positionCurrent(p_idim) = 2 * oldPosition;
recursive1DHierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, p_leftParentNodalValue, valueMidle, LinearHierar, p_parentLinearHierarValue, p_dataSet, p_nodalValues,
p_hierarValues);
// right
p_positionCurrent(p_idim) += 1;
recursive1DHierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, p_rightParentNodalValue, LinearHierar, p_parentLinearHierarValue, p_dataSet, p_nodalValues,
p_hierarValues);
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Hierarchization in given dimension in 1D quadratic
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_leftParentNodalValue Left parent nodal value
/// \param p_rightParentNodalValue Right parent nodal value
/// \param p_parentLinearHierarValue Linear Hierarchical value of parent
/// \param p_dataSet Data structure with all the points
/// \param p_nodalValues Nodal values
/// \param p_iNodeNum Node number
/// \param p_hierarValues Hierarchical values
template< class T, class TT>
void HierarchizationStep3(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentNodalValue,
const T &p_rightParentNodalValue,
const T &p_parentLinearHierarValue,
const SparseSet &p_dataSet,
const TT &p_nodalValues,
const int &p_iNodeNum,
TT &p_hierarValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_nodalValues, iposPoint);
// hierarchization
T LinearHierar = valueMidle - 0.5 * (p_leftParentNodalValue + p_rightParentNodalValue);
// quadratic
DoubleOrArray().affect(p_hierarValues, iposPoint, LinearHierar - 0.25 * p_parentLinearHierarValue) ;
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// modified left and right values
T leftParentNodalValueLoc = p_leftParentNodalValue;
T rightParentNodalValueLoc = p_rightParentNodalValue;
T parentLinearHierarValueLoc = LinearHierar;
if (oldPosition == 0)
{
// First point for the level
// Only linear estimation of error in hierarchization
leftParentNodalValueLoc = 2 * valueMidle - p_rightParentNodalValue;
// LINEAR
DoubleOrArray().zero(parentLinearHierarValueLoc, p_nodalValues);
// son is linear quadratic for Left node
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum, p_hierarValues);
p_positionCurrent(p_idim) += 1;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum + 1, p_hierarValues);
}
else if (oldPosition == lastNode[oldLevel - 1])
{
// Last point for the level
// Only linear estimation of error in hierarchization
rightParentNodalValueLoc = 2 * valueMidle - p_leftParentNodalValue;
// LINEAR
DoubleOrArray().zero(parentLinearHierarValueLoc, p_nodalValues);
// son is linear quadratic for Left node
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum, p_hierarValues);
p_positionCurrent(p_idim) += 1;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum + 1, p_hierarValues);
}
else if ((oldPosition == 1) || (oldPosition == lastNode[oldLevel - 1] - 1))
{
// USE QUADRATIC
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum, p_hierarValues);
p_positionCurrent(p_idim) += 1;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum + 1, p_hierarValues);
}
else
{
T grandParentLinearHierarValueLoc = p_parentLinearHierarValue;
p_positionCurrent(p_idim) = 2 * oldPosition;
recursive1DHierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
grandParentLinearHierarValueLoc, p_dataSet, p_nodalValues, p_hierarValues);
p_positionCurrent(p_idim) += 1;
recursive1DHierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
grandParentLinearHierarValueLoc, p_dataSet, p_nodalValues, p_hierarValues);
}
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Hierarchization in given dimension in 1D linear
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_leftParentNodalValue Left parent nodal value
/// \param p_rightParentNodalValue Right parent nodal value
/// \param p_dataSet Data structure with all the points
/// \param p_nodalValues Nodal values
/// \param p_iNodeNum Node number
/// \param p_hierarValues Hierarchical values
template< class T, class TT>
void HierarchizationStep2(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentNodalValue,
const T &p_rightParentNodalValue,
const SparseSet &p_dataSet,
const TT &p_nodalValues,
const int &p_iNodeNum,
TT &p_hierarValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_nodalValues, iposPoint);
// hierarchization
T LinearHierar = valueMidle - 0.5 * (p_leftParentNodalValue + p_rightParentNodalValue);
// cubic
DoubleOrArray().affect(p_hierarValues, iposPoint, LinearHierar);
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// modified left and right values
T leftParentNodalValueLoc = p_leftParentNodalValue;
T rightParentNodalValueLoc = p_rightParentNodalValue;
T parentLinearHierarValueLoc = LinearHierar;
if (oldPosition == 0)
{
// LINEAR
DoubleOrArray().zero(parentLinearHierarValueLoc, p_nodalValues);
// cubic on the boundary not used. Use linear
leftParentNodalValueLoc = 2 * valueMidle - p_rightParentNodalValue;
// still linear on left for son
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum, p_hierarValues);
// quadratic on right for son
p_positionCurrent(p_idim) += 1;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum + 1, p_hierarValues);
}
else if (oldPosition == lastNode[oldLevel - 1])
{
// LINEAR
DoubleOrArray().zero(parentLinearHierarValueLoc, p_nodalValues);
// quadratic left
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum, p_hierarValues);
// cubic on the boundary not used. Use linear
rightParentNodalValueLoc = 2 * valueMidle - p_leftParentNodalValue;
// linear for right
p_positionCurrent(p_idim) += 1;
HierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc, parentLinearHierarValueLoc,
p_dataSet, p_nodalValues, 2 * p_iNodeNum + 1, p_hierarValues);
}
else
{
abort();
}
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Hierarchization in given dimension in 1D (first step : subtract constant value)
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_dataSet Data structure with all the points
/// \param p_nodalValues Nodal values
/// \param p_hierarValues Hierarchical values
template< class T, class TT>
void HierarchizationStep1(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const SparseSet &p_dataSet,
const TT &p_nodalValues,
TT &p_hierarValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_nodalValues, iposPoint);
// hierarchization
DoubleOrArray().affect(p_hierarValues, iposPoint, valueMidle) ;
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// modified left and right values
T leftParentNodalValueLoc = valueMidle;
T rightParentNodalValueLoc = valueMidle;
// left
p_positionCurrent(p_idim) = 2 * oldPosition;
HierarchizationStep2<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentNodalValueLoc, valueMidle,
p_dataSet, p_nodalValues, 0, p_hierarValues);
// right
p_positionCurrent(p_idim) += 1;
HierarchizationStep2<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentNodalValueLoc,
p_dataSet, p_nodalValues, 1, p_hierarValues);
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
public :
// default
Hierar1DCubicNoBound() {}
// operator for 1D Hierarchization
/// \brief Hierarchization in given dimension in 1D
/// \param p_levelCurrent Current index of the point
/// \param p_positionCurrent Current level of the point
/// \param p_iterLevel Iterator on current level
/// \param p_idim Current dimension
/// \param p_dataSet Data structure with all the points
/// \param p_nodalValues Nodal values
/// \param p_hierarValues Hierarchical values
template< class T, class TT>
void operator()(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const SparseSet &p_dataSet,
const TT &p_nodalValues,
TT &p_hierarValues)
{
// left and right value
HierarchizationStep1<T, TT>(p_levelCurrent, p_positionCurrent, p_iterLevel, p_idim, p_dataSet, p_nodalValues, p_hierarValues);
}
};
/// \class Dehierar1DCubicNoBound SparseGridCubicNoBound.h
/// Dehierarchization for cubic without bound
class Dehierar1DCubicNoBound: public HierarDehierarNoBound
{
protected :
/// \brief Dehierarchization 1D in given dimension (modified bound) (cubic so available after two level)
/// \param p_levelCurrent Current index of the point
/// \param p_positionCurrent Current level of the point
/// \param p_iterLevel Iterator on current level
/// \param p_idim Current dimension
/// \param p_leftParentHierarValue Left parent nodal value
/// \param p_rightParentHierarValue Right parent nodal value
/// \param p_linearHierarParent Linear hierarchical value of parent
/// \param p_linearHierarGrandParent Linear Hierarchical value of parent
/// \param p_dataSet Data structure with all the points
/// \param p_hierarValues Hierarchical values
/// \param p_nodalValues Nodal values
template< class T, class TT>
void recursive1DDehierarchization(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentHierarValue,
const T &p_rightParentHierarValue,
const T &p_linearHierarParent,
const T &p_linearHierarGrandParent,
const SparseSet &p_dataSet,
const TT &p_hierarValues,
TT &p_nodalValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
// position
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_hierarValues, iposPoint);
// do dehierarchization
// calculation linear hierarchical coefficient
int iBaseType = iNodeToFunc[p_positionCurrent(p_idim) % 4];
T LinearHierarchical = valueMidle - (weightParent[iBaseType] * p_linearHierarParent + weightGrandParent[iBaseType] * p_linearHierarGrandParent);
valueMidle = LinearHierarchical + 0.5 * (p_leftParentHierarValue + p_rightParentHierarValue);
DoubleOrArray().affect(p_nodalValues, iposPoint, valueMidle);
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// left
p_positionCurrent(p_idim) = 2 * oldPosition;
recursive1DDehierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, p_leftParentHierarValue, valueMidle, LinearHierarchical, p_linearHierarParent,
p_dataSet, p_hierarValues, p_nodalValues);
// right
p_positionCurrent(p_idim) += 1;
recursive1DDehierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, p_rightParentHierarValue, LinearHierarchical, p_linearHierarParent,
p_dataSet, p_hierarValues, p_nodalValues);
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Dehierarchization 1D in given dimension (modified bound, step 2 quadratic)
/// \param p_levelCurrent Current index of the point
/// \param p_positionCurrent Current level of the point
/// \param p_iterLevel Iterator on current level
/// \param p_idim Current dimension
/// \param p_leftParentHierarValue Left parent nodal value
/// \param p_rightParentHierarValue Right parent nodal value
/// \param p_linearHierarParent Linear hierarchical value of parent
/// \param p_dataSet Data structure with all the points
/// \param p_hierarValues Hierarchical values
/// \param p_iNodeNum Node number
/// \param p_nodalValues Nodal values
template< class T, class TT>
void dehierarchizationStep3(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentHierarValue,
const T &p_rightParentHierarValue,
const T &p_linearHierarParent,
const SparseSet &p_dataSet,
const TT &p_hierarValues,
const int &p_iNodeNum,
TT &p_nodalValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_hierarValues, iposPoint);
// do dehierarchization
// calculation linear hierarchical coefficient
T LinearHierarchical = valueMidle + 0.25 * p_linearHierarParent;
valueMidle = LinearHierarchical + 0.5 * (p_leftParentHierarValue + p_rightParentHierarValue);
DoubleOrArray().affect(p_nodalValues, iposPoint, valueMidle);
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// modified left and right values
T leftParentHierarValueLoc = p_leftParentHierarValue;
T rightParentHierarValueLoc = p_rightParentHierarValue;
T LinearHierarchicalLoc = LinearHierarchical;
if (oldPosition == 0)
{
// extrapolation use linear
leftParentHierarValueLoc = 2 * valueMidle - p_rightParentHierarValue;
DoubleOrArray().zero(LinearHierarchicalLoc, p_nodalValues);
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum, p_nodalValues);
p_positionCurrent(p_idim) += 1;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum + 1, p_nodalValues);
}
else if (oldPosition == lastNode[oldLevel - 1])
{
// linear extrapolation and not cubic
rightParentHierarValueLoc = 2 * valueMidle - p_leftParentHierarValue;
DoubleOrArray().zero(LinearHierarchicalLoc, p_nodalValues);
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum, p_nodalValues);
p_positionCurrent(p_idim) += 1;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum + 1, p_nodalValues);
}
else if ((oldPosition == 1) || (oldPosition == lastNode[oldLevel - 1] - 1))
{
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc, p_dataSet, p_hierarValues, 2 * p_iNodeNum, p_nodalValues);
p_positionCurrent(p_idim) += 1;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc, p_dataSet, p_hierarValues, 2 * p_iNodeNum + 1, p_nodalValues);
}
else
{
T GrandLinearHierarchicalLoc = p_linearHierarParent;
p_positionCurrent(p_idim) = 2 * oldPosition;
recursive1DDehierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc,
GrandLinearHierarchicalLoc, p_dataSet, p_hierarValues, p_nodalValues);
p_positionCurrent(p_idim) += 1;
recursive1DDehierarchization<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc,
GrandLinearHierarchicalLoc, p_dataSet, p_hierarValues, p_nodalValues);
}
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Dehierarchization 1D in given dimension (modified bound, step 2 quadratic)
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_leftParentHierarValue Left parent nodal value
/// \param p_rightParentHierarValue Right parent nodal value
/// \param p_dataSet Data structure with all the points
/// \param p_hierarValues Hierarchical values
/// \param p_iNodeNum Node number
/// \param p_nodalValues Nodal values
template< class T, class TT>
void dehierarchizationStep2(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const T &p_leftParentHierarValue,
const T &p_rightParentHierarValue,
const SparseSet &p_dataSet,
const TT &p_hierarValues,
const int &p_iNodeNum,
TT &p_nodalValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_hierarValues, iposPoint);
// do dehierarchization
// calculation linear hierarchical coefficient
T LinearHierarchical = valueMidle ;
valueMidle = LinearHierarchical + 0.5 * (p_leftParentHierarValue + p_rightParentHierarValue);
DoubleOrArray().affect(p_nodalValues, iposPoint, valueMidle);
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// modified left and right values
T leftParentHierarValueLoc = p_leftParentHierarValue;
T rightParentHierarValueLoc = p_rightParentHierarValue;
T LinearHierarchicalLoc = LinearHierarchical;
if (oldPosition == 0)
{
// extrapolation use linear
leftParentHierarValueLoc = 2 * valueMidle - p_rightParentHierarValue;
DoubleOrArray().zero(LinearHierarchicalLoc, p_nodalValues);
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum, p_nodalValues);
p_positionCurrent(p_idim) += 1;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum + 1, p_nodalValues);
}
else if (oldPosition == lastNode[oldLevel - 1])
{
// linear extrapolation and not cubic
rightParentHierarValueLoc = 2 * valueMidle - p_leftParentHierarValue;
DoubleOrArray().zero(LinearHierarchicalLoc, p_nodalValues);
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum, p_nodalValues);
p_positionCurrent(p_idim) += 1;
dehierarchizationStep3<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc, LinearHierarchicalLoc,
p_dataSet, p_hierarValues, 2 * p_iNodeNum + 1, p_nodalValues);
}
else
{
abort();
}
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
/// \brief Dehierarchization 1D in given dimension (modified bound, step 1 linear)
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel iterator to locate the current level
/// \param p_idim Current dimension
/// \param p_dataSet Data structure with all the points
/// \param p_hierarValues Hierarchical values
/// \param p_nodalValues Nodal values
template< class T, class TT>
void dehierarchizationStep1(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const SparseSet &p_dataSet,
const TT &p_hierarValues,
TT &p_nodalValues)
{
if (p_iterLevel == p_dataSet.end())
return ;
// position
SparseLevel::const_iterator iterPosition = p_iterLevel->second.find(p_positionCurrent);
if (iterPosition == p_iterLevel->second.end())
return ;
int iposPoint = iterPosition->second;
T valueMidle = DoubleOrArray()(p_hierarValues, iposPoint);
// do dehierarchization
DoubleOrArray().affect(p_nodalValues, iposPoint, valueMidle);
// modified left and right values
T leftParentHierarValueLoc = valueMidle;
T rightParentHierarValueLoc = valueMidle;
char oldLevel = p_levelCurrent(p_idim);
unsigned int oldPosition = p_positionCurrent(p_idim);
// child level
p_levelCurrent(p_idim) += 1;
SparseSet::const_iterator iterLevelChild = p_dataSet.find(p_levelCurrent);
// left
p_positionCurrent(p_idim) = 2 * oldPosition;
dehierarchizationStep2<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, leftParentHierarValueLoc, valueMidle, p_dataSet, p_hierarValues, 0, p_nodalValues);
// right
p_positionCurrent(p_idim) += 1;
dehierarchizationStep2<T, TT>(p_levelCurrent, p_positionCurrent, iterLevelChild, p_idim, valueMidle, rightParentHierarValueLoc,
p_dataSet, p_hierarValues, 1, p_nodalValues);
p_positionCurrent(p_idim) = oldPosition;
p_levelCurrent(p_idim) = oldLevel;
}
public :
Dehierar1DCubicNoBound() {}
/// \brief Dehierarchization 1D in given dimension
/// \param p_levelCurrent Current level of the point
/// \param p_positionCurrent Current position of the point
/// \param p_iterLevel Iteration on level
/// \param p_idim Current dimension
/// \param p_dataSet Data structure with all the points
/// \param p_hierarValues Hierarchical values
/// \param p_nodalValues Nodal values
template< class T, class TT>
void operator()(Eigen::ArrayXc &p_levelCurrent,
Eigen::ArrayXui &p_positionCurrent,
const SparseSet::const_iterator &p_iterLevel,
const unsigned int &p_idim,
const SparseSet &p_dataSet,
const TT &p_hierarValues,
TT &p_nodalValues)
{
dehierarchizationStep1<T, TT>(p_levelCurrent, p_positionCurrent, p_iterLevel, p_idim, p_dataSet, p_hierarValues, p_nodalValues);
}
};
///@}
}
#endif /* SPARSEGRIDCUBICNONOUND_H */
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