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- /* Kernel Independent Fast Multipole Method
- Copyright (C) 2004 Lexing Ying, New York University
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU General Public License as published by
- the Free Software Foundation; either version 2, or (at your option)
- any later version.
- This program is distributed in the hope that it will be useful, but WITHOUT
- ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
- for more details.
- You should have received a copy of the GNU General Public License
- along with this program; see the file COPYING. If not, write to the Free
- Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
- 02111-1307, USA. */
- #ifndef _LAPACK_H_
- #define _LAPACK_H_
- //EXTERN_C_BEGIN
- extern "C"
- {
- extern void sgesvd_(char *JOBU, char *JOBVT, int *M, int *N, float *A, int *LDA,
- float *S, float *U, int *LDU, float *VT, int *LDVT, float *WORK, int *LWORK, int *INFO);
- /*! DGESVD computes the singular value decomposition (SVD) of a real
- * M-by-N matrix A, optionally computing the left and/or right singular
- * vectors. The SVD is written
- *
- * A = U * SIGMA * transpose(V)
- *
- * where SIGMA is an M-by-N matrix which is zero except for its
- * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and
- * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA
- * are the singular values of A; they are real and non-negative, and
- * are returned in descending order. The first min(m,n) columns of
- * U and V are the left and right singular vectors of A.
- *
- * See http://www.netlib.org/lapack/double/dgesvd.f for more information
- */
- extern void dgesvd_(char *JOBU, char *JOBVT, int *M, int *N, double *A, int *LDA,
- double *S, double *U, int *LDU, double *VT, int *LDVT, double *WORK, int *LWORK, int *INFO);
- /*! DGESDD computes the singular value decomposition (SVD) of a real
- * M-by-N matrix A, optionally computing the left and right singular
- * vectors. If singular vectors are desired, it uses a
- * divide-and-conquer algorithm.
- *
- * The SVD is written
- *
- * A = U * SIGMA * transpose(V)
- *
- * where SIGMA is an M-by-N matrix which is zero except for its
- * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and
- * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA
- ` * are the singular values of A; they are real and non-negative, and
- * are returned in descending order. The first min(m,n) columns of
- * U and V are the left and right singular vectors of A.
- *
- * See http://www.netlib.org/lapack/double/dgesdd.f for more information
- */
- extern void dgesdd_(char *jobz, int* m, int* n, double* a, int* lda,
- double* s, double* u, int* ldu, double* vt, int* ldvt, double* work, int* lwork, int* iwork, int* info);
- /*! DGETRF computes an LU factorization of a general M-by-N matrix A
- * using partial pivoting with row interchanges.
- *
- * The factorization has the form
- *
- * A = P * L * U
- *
- * where P is a permutation matrix, L is lower triangular with unit
- * diagonal elements (lower trapezoidal if m > n), and U is upper
- * triangular (upper trapezoidal if m < n).
- *
- * See http://www.netlib.org/lapack/double/dgetrf.f for more information
- */
- extern void dgetrf_(int *M, int *N, double *A, int *LDA, int *IPIV, int *INFO);
- /*! DGETRI computes the inverse of a matrix using the LU factorization
- * computed by DGETRF.
- *
- * This method inverts U and then computes inv(A) by solving the system
- * inv(A)*L = inv(U) for inv(A).
- *
- * See http://www.netlib.org/lapack/double/dgetri.f for more information
- */
- extern void dgetri_(int *N, double *A, int *LDA, int *IPIV, double *WORK, int *LWORK, int *INFO);
- }
- //EXTERN_C_END
- #endif
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