Intrepid2
Intrepid2_DataTools.hpp
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1// @HEADER
2// *****************************************************************************
3// Intrepid2 Package
4//
5// Copyright 2007 NTESS and the Intrepid2 contributors.
6// SPDX-License-Identifier: BSD-3-Clause
7// *****************************************************************************
8// @HEADER
9
10#ifndef Intrepid2_DataTools_h
11#define Intrepid2_DataTools_h
12
13#include "Intrepid2_Data.hpp"
14
20namespace Intrepid2 {
21
23{
24public:
30 template<class Scalar, class DeviceType>
31 static void multiplyByCPWeights(Data<Scalar,DeviceType> &resultMatrixData, const Data<Scalar,DeviceType> &matrixDataIn, const Data<Scalar,DeviceType> &scalarDataIn)
32 {
33 const ordinal_type rank = scalarDataIn.rank();
34 const ordinal_type matrixRank = matrixDataIn.rank();
35 auto extents = scalarDataIn.getExtents();
36 auto variationTypes = scalarDataIn.getVariationTypes();
37 for (int r=rank; r<matrixRank; r++)
38 {
39 extents[r] = matrixDataIn.extent_int(r);
40 variationTypes[r] = CONSTANT;
41 }
42
43 auto scalarDataInExtended = scalarDataIn.shallowCopy(matrixRank, extents, variationTypes);
44 resultMatrixData.storeInPlaceProduct(matrixDataIn,scalarDataInExtended);
45 }
46
52 template<class Scalar, class DeviceType>
54 {
55 const ordinal_type rank = scalarDataIn.rank();
56 const ordinal_type matrixRank = matrixDataIn.rank();
57 auto extents = scalarDataIn.getExtents();
58 auto variationTypes = scalarDataIn.getVariationTypes();
59 for (int r=rank; r<matrixRank; r++)
60 {
61 extents[r] = matrixDataIn.extent_int(r);
62 variationTypes[r] = CONSTANT;
63 }
64
65 auto scalarDataInExtended = scalarDataIn.shallowCopy(matrixRank, extents, variationTypes);
66
67 auto result = Data<Scalar,DeviceType>::allocateInPlaceCombinationResult(scalarDataInExtended, matrixDataIn);
68
69 result.storeInPlaceProduct(matrixDataIn,scalarDataInExtended);
70 return result;
71 }
72
76 template<class Scalar, class DeviceType>
78 {
79 // A direct construction of the transpose could be more efficient, but here we take advantage of existing
80 // implementations within the Data class supporting matrix-matrix multiplication. We construct an identity
81 // matrix, and left-multiply this by the transpose of the input matrix.
82 const ordinal_type rank = matrixDataIn.rank();
83 auto extents = matrixDataIn.getExtents();
84 auto variationTypes = matrixDataIn.getVariationTypes();
85 const auto D1 = extents[rank-2];
86
87 extents[rank-2] = D1;
88 extents[rank-1] = D1;
89 variationTypes[rank-2] = BLOCK_PLUS_DIAGONAL;
90 variationTypes[rank-1] = BLOCK_PLUS_DIAGONAL;
91
92 Kokkos::View<Scalar*,DeviceType> identityUnderlyingView("Intrepid2::DataTools::transposeMatrix() - identity view",D1);
93 Kokkos::deep_copy(identityUnderlyingView, 1.0);
94 Data<Scalar,DeviceType> identityData(identityUnderlyingView,extents,variationTypes);
95
96 auto result = Data<Scalar,DeviceType>::allocateMatMatResult(true, matrixDataIn, false, identityData);
97 result.storeMatMat(true, matrixDataIn, false, identityData);
98
99 return result;
100 }
101};
102}
103
104#endif /* Intrepid2_DataTools_h */
@ BLOCK_PLUS_DIAGONAL
one of two dimensions in a matrix; bottom-right part of matrix is diagonal
Defines the Data class, a wrapper around a Kokkos::View that allows data that is constant or repeatin...
static Data< Scalar, DeviceType > multiplyByCPWeights(const Data< Scalar, DeviceType > &matrixDataIn, const Data< Scalar, DeviceType > &scalarDataIn)
static Data< Scalar, DeviceType > transposeMatrix(const Data< Scalar, DeviceType > &matrixDataIn)
static void multiplyByCPWeights(Data< Scalar, DeviceType > &resultMatrixData, const Data< Scalar, DeviceType > &matrixDataIn, const Data< Scalar, DeviceType > &scalarDataIn)
Wrapper around a Kokkos::View that allows data that is constant or repeating in various logical dimen...
void storeInPlaceProduct(const Data< DataScalar, DeviceType > &A, const Data< DataScalar, DeviceType > &B)
stores the in-place (entrywise) product, A .* B, into this container.
static Data< DataScalar, DeviceType > allocateMatMatResult(const bool transposeA, const Data< DataScalar, DeviceType > &A_MatData, const bool transposeB, const Data< DataScalar, DeviceType > &B_MatData)
KOKKOS_INLINE_FUNCTION int extent_int(const int &r) const
Returns the logical extent in the specified dimension.
static Data< DataScalar, DeviceType > allocateInPlaceCombinationResult(const Data< DataScalar, DeviceType > &A, const Data< DataScalar, DeviceType > &B)
KOKKOS_INLINE_FUNCTION const Kokkos::Array< DataVariationType, 7 > & getVariationTypes() const
Returns an array with the variation types in each logical dimension.
KOKKOS_INLINE_FUNCTION Kokkos::Array< int, 7 > getExtents() const
Returns an array containing the logical extents in each dimension.
Data shallowCopy(const int rank, const Kokkos::Array< int, 7 > &extents, const Kokkos::Array< DataVariationType, 7 > &variationTypes) const
Creates a new Data object with the same underlying view, but with the specified logical rank,...
KOKKOS_INLINE_FUNCTION unsigned rank() const
Returns the logical rank of the Data container.