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128 lines
10 KiB
C++
128 lines
10 KiB
C++
/*
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Copyright (c) 2011, Intel Corporation. All rights reserved.
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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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* 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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* 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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* Neither the name of Intel Corporation nor the names of its contributors may
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be used to endorse or promote products derived from this software without
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specific prior written permission.
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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
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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ANY 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 THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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********************************************************************************
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* Content : Eigen bindings to LAPACKe
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* Singular Value Decomposition - SVD.
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********************************************************************************
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*/
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#ifndef EIGEN_JACOBISVD_LAPACKE_H
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#define EIGEN_JACOBISVD_LAPACKE_H
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// IWYU pragma: private
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#include "./InternalHeaderCheck.h"
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namespace Eigen {
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/** \internal Specialization for the data types supported by LAPACKe */
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#define EIGEN_LAPACKE_SVD(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_PREFIX, EIGCOLROW, LAPACKE_COLROW, OPTIONS) \
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template <> \
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inline JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, OPTIONS>& \
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JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, OPTIONS>::compute_impl( \
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const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) { \
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typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
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/*typedef MatrixType::Scalar Scalar;*/ \
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/*typedef MatrixType::RealScalar RealScalar;*/ \
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allocate(matrix.rows(), matrix.cols(), computationOptions); \
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\
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/*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \
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m_nonzeroSingularValues = diagSize(); \
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\
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lapack_int lda = internal::convert_index<lapack_int>(matrix.outerStride()), ldu, ldvt; \
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lapack_int matrix_order = LAPACKE_COLROW; \
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char jobu, jobvt; \
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LAPACKE_TYPE *u, *vt, dummy; \
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jobu = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \
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jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \
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if (computeU()) { \
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ldu = internal::convert_index<lapack_int>(m_matrixU.outerStride()); \
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u = (LAPACKE_TYPE*)m_matrixU.data(); \
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} else { \
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ldu = 1; \
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u = &dummy; \
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} \
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MatrixType localV; \
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lapack_int vt_rows = (m_computeFullV) ? internal::convert_index<lapack_int>(cols()) \
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: (m_computeThinV) ? internal::convert_index<lapack_int>(diagSize()) \
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: 1; \
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if (computeV()) { \
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localV.resize(vt_rows, cols()); \
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ldvt = internal::convert_index<lapack_int>(localV.outerStride()); \
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vt = (LAPACKE_TYPE*)localV.data(); \
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} else { \
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ldvt = 1; \
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vt = &dummy; \
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} \
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Matrix<LAPACKE_RTYPE, Dynamic, Dynamic> superb; \
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superb.resize(diagSize(), 1); \
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MatrixType m_temp; \
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m_temp = matrix; \
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lapack_int info = LAPACKE_##LAPACKE_PREFIX##gesvd( \
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matrix_order, jobu, jobvt, internal::convert_index<lapack_int>(rows()), \
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internal::convert_index<lapack_int>(cols()), (LAPACKE_TYPE*)m_temp.data(), lda, \
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(LAPACKE_RTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
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/* Check the result of the LAPACK call */ \
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if (info < 0 || !m_singularValues.allFinite()) { \
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m_info = InvalidInput; \
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} else if (info > 0) { \
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m_info = NoConvergence; \
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} else { \
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m_info = Success; \
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if (computeV()) m_matrixV = localV.adjoint(); \
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} \
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/* for(int i=0;i<diagSize();i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; \
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* m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
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m_isInitialized = true; \
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return *this; \
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}
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#define EIGEN_LAPACK_SVD_OPTIONS(OPTIONS) \
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EIGEN_LAPACKE_SVD(double, double, double, d, ColMajor, LAPACK_COL_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(float, float, float, s, ColMajor, LAPACK_COL_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, ColMajor, LAPACK_COL_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float, float, c, ColMajor, LAPACK_COL_MAJOR, OPTIONS) \
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\
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EIGEN_LAPACKE_SVD(double, double, double, d, RowMajor, LAPACK_ROW_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(float, float, float, s, RowMajor, LAPACK_ROW_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, RowMajor, LAPACK_ROW_MAJOR, OPTIONS) \
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EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float, float, c, RowMajor, LAPACK_ROW_MAJOR, OPTIONS)
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EIGEN_LAPACK_SVD_OPTIONS(0)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeThinU)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeThinV)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeFullU)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeFullV)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeThinU | ComputeThinV)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeFullU | ComputeFullV)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeThinU | ComputeFullV)
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EIGEN_LAPACK_SVD_OPTIONS(ComputeFullU | ComputeThinV)
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} // end namespace Eigen
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#endif // EIGEN_JACOBISVD_LAPACKE_H
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