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Eigen
3.3.3
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00001 /* 00002 Copyright (c) 2011, Intel Corporation. All rights reserved. 00003 00004 Redistribution and use in source and binary forms, with or without modification, 00005 are permitted provided that the following conditions are met: 00006 00007 * Redistributions of source code must retain the above copyright notice, this 00008 list of conditions and the following disclaimer. 00009 * Redistributions in binary form must reproduce the above copyright notice, 00010 this list of conditions and the following disclaimer in the documentation 00011 and/or other materials provided with the distribution. 00012 * Neither the name of Intel Corporation nor the names of its contributors may 00013 be used to endorse or promote products derived from this software without 00014 specific prior written permission. 00015 00016 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 00017 ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 00018 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 00019 DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 00020 ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 00021 (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00022 LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 00023 ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 00024 (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00025 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00026 00027 ******************************************************************************** 00028 * Content : Eigen bindings to LAPACKe 00029 * Singular Value Decomposition - SVD. 00030 ******************************************************************************** 00031 */ 00032 00033 #ifndef EIGEN_JACOBISVD_LAPACKE_H 00034 #define EIGEN_JACOBISVD_LAPACKE_H 00035 00036 namespace Eigen { 00037 00040 #define EIGEN_LAPACKE_SVD(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_PREFIX, EIGCOLROW, LAPACKE_COLROW) \ 00041 template<> inline \ 00042 JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \ 00043 JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \ 00044 { \ 00045 typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \ 00046 /*typedef MatrixType::Scalar Scalar;*/ \ 00047 /*typedef MatrixType::RealScalar RealScalar;*/ \ 00048 allocate(matrix.rows(), matrix.cols(), computationOptions); \ 00049 \ 00050 /*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \ 00051 m_nonzeroSingularValues = m_diagSize; \ 00052 \ 00053 lapack_int lda = internal::convert_index<lapack_int>(matrix.outerStride()), ldu, ldvt; \ 00054 lapack_int matrix_order = LAPACKE_COLROW; \ 00055 char jobu, jobvt; \ 00056 LAPACKE_TYPE *u, *vt, dummy; \ 00057 jobu = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \ 00058 jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \ 00059 if (computeU()) { \ 00060 ldu = internal::convert_index<lapack_int>(m_matrixU.outerStride()); \ 00061 u = (LAPACKE_TYPE*)m_matrixU.data(); \ 00062 } else { ldu=1; u=&dummy; }\ 00063 MatrixType localV; \ 00064 ldvt = (m_computeFullV) ? internal::convert_index<lapack_int>(m_cols) : (m_computeThinV) ? internal::convert_index<lapack_int>(m_diagSize) : 1; \ 00065 if (computeV()) { \ 00066 localV.resize(ldvt, m_cols); \ 00067 vt = (LAPACKE_TYPE*)localV.data(); \ 00068 } else { ldvt=1; vt=&dummy; }\ 00069 Matrix<LAPACKE_RTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \ 00070 MatrixType m_temp; m_temp = matrix; \ 00071 LAPACKE_##LAPACKE_PREFIX##gesvd( matrix_order, jobu, jobvt, internal::convert_index<lapack_int>(m_rows), internal::convert_index<lapack_int>(m_cols), (LAPACKE_TYPE*)m_temp.data(), lda, (LAPACKE_RTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \ 00072 if (computeV()) m_matrixV = localV.adjoint(); \ 00073 /* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \ 00074 m_isInitialized = true; \ 00075 return *this; \ 00076 } 00077 00078 EIGEN_LAPACKE_SVD(double, double, double, d, ColMajor, LAPACK_COL_MAJOR) 00079 EIGEN_LAPACKE_SVD(float, float, float , s, ColMajor, LAPACK_COL_MAJOR) 00080 EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, ColMajor, LAPACK_COL_MAJOR) 00081 EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float, float , c, ColMajor, LAPACK_COL_MAJOR) 00082 00083 EIGEN_LAPACKE_SVD(double, double, double, d, RowMajor, LAPACK_ROW_MAJOR) 00084 EIGEN_LAPACKE_SVD(float, float, float , s, RowMajor, LAPACK_ROW_MAJOR) 00085 EIGEN_LAPACKE_SVD(dcomplex, lapack_complex_double, double, z, RowMajor, LAPACK_ROW_MAJOR) 00086 EIGEN_LAPACKE_SVD(scomplex, lapack_complex_float, float , c, RowMajor, LAPACK_ROW_MAJOR) 00087 00088 } // end namespace Eigen 00089 00090 #endif // EIGEN_JACOBISVD_LAPACKE_H