gensymm.c
来自「math library from gnu」· C语言 代码 · 共 212 行
C
212 行
/* eigen/gensymm.c * * Copyright (C) 2007 Patrick Alken * * 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 3 of the License, 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; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */#include <stdlib.h>#include <config.h>#include <gsl/gsl_eigen.h>#include <gsl/gsl_linalg.h>#include <gsl/gsl_math.h>#include <gsl/gsl_blas.h>#include <gsl/gsl_vector.h>#include <gsl/gsl_matrix.h>/* * This module computes the eigenvalues of a real generalized * symmetric-definite eigensystem A x = \lambda B x, where A and * B are symmetric, and B is positive-definite. *//*gsl_eigen_gensymm_alloc()Allocate a workspace for solving the generalized symmetric-definiteeigenvalue problem. The size of this workspace is O(2n).Inputs: n - size of matricesReturn: pointer to workspace*/gsl_eigen_gensymm_workspace *gsl_eigen_gensymm_alloc(const size_t n){ gsl_eigen_gensymm_workspace *w; if (n == 0) { GSL_ERROR_NULL ("matrix dimension must be positive integer", GSL_EINVAL); } w = (gsl_eigen_gensymm_workspace *) calloc (1, sizeof (gsl_eigen_gensymm_workspace)); if (w == 0) { GSL_ERROR_NULL ("failed to allocate space for workspace", GSL_ENOMEM); } w->size = n; w->symm_workspace_p = gsl_eigen_symm_alloc(n); if (!w->symm_workspace_p) { gsl_eigen_gensymm_free(w); GSL_ERROR_NULL("failed to allocate space for symm workspace", GSL_ENOMEM); } return (w);} /* gsl_eigen_gensymm_alloc() *//*gsl_eigen_gensymm_free() Free workspace w*/voidgsl_eigen_gensymm_free (gsl_eigen_gensymm_workspace * w){ if (w->symm_workspace_p) gsl_eigen_symm_free(w->symm_workspace_p); free(w);} /* gsl_eigen_gensymm_free() *//*gsl_eigen_gensymm()Solve the generalized symmetric-definite eigenvalue problemA x = \lambda B xfor the eigenvalues \lambda.Inputs: A - real symmetric matrix B - real symmetric and positive definite matrix eval - where to store eigenvalues w - workspaceReturn: success or error*/intgsl_eigen_gensymm (gsl_matrix * A, gsl_matrix * B, gsl_vector * eval, gsl_eigen_gensymm_workspace * w){ const size_t N = A->size1; /* check matrix and vector sizes */ if (N != A->size2) { GSL_ERROR ("matrix must be square to compute eigenvalues", GSL_ENOTSQR); } else if ((N != B->size1) || (N != B->size2)) { GSL_ERROR ("B matrix dimensions must match A", GSL_EBADLEN); } else if (eval->size != N) { GSL_ERROR ("eigenvalue vector must match matrix size", GSL_EBADLEN); } else if (w->size != N) { GSL_ERROR ("matrix size does not match workspace", GSL_EBADLEN); } else { int s; /* compute Cholesky factorization of B */ s = gsl_linalg_cholesky_decomp(B); if (s != GSL_SUCCESS) return s; /* B is not positive definite */ /* transform to standard symmetric eigenvalue problem */ gsl_eigen_gensymm_standardize(A, B); s = gsl_eigen_symm(A, eval, w->symm_workspace_p); return s; }} /* gsl_eigen_gensymm() *//*gsl_eigen_gensymm_standardize() Reduce the generalized symmetric-definite eigenproblem tothe standard symmetric eigenproblem by computingC = L^{-1} A L^{-t}where L L^t is the Cholesky decomposition of BInputs: A - (input/output) real symmetric matrix B - real symmetric, positive definite matrix in Cholesky formReturn: successNotes: A is overwritten by L^{-1} A L^{-t}*/intgsl_eigen_gensymm_standardize(gsl_matrix *A, const gsl_matrix *B){ const size_t N = A->size1; size_t i; double a, b, c; for (i = 0; i < N; ++i) { /* update lower triangle of A(i:n, i:n) */ a = gsl_matrix_get(A, i, i); b = gsl_matrix_get(B, i, i); a /= b * b; gsl_matrix_set(A, i, i, a); if (i < N - 1) { gsl_vector_view ai = gsl_matrix_subcolumn(A, i, i + 1, N - i - 1); gsl_matrix_view ma = gsl_matrix_submatrix(A, i + 1, i + 1, N - i - 1, N - i - 1); gsl_vector_const_view bi = gsl_matrix_const_subcolumn(B, i, i + 1, N - i - 1); gsl_matrix_const_view mb = gsl_matrix_const_submatrix(B, i + 1, i + 1, N - i - 1, N - i - 1); gsl_blas_dscal(1.0 / b, &ai.vector); c = -0.5 * a; gsl_blas_daxpy(c, &bi.vector, &ai.vector); gsl_blas_dsyr2(CblasLower, -1.0, &ai.vector, &bi.vector, &ma.matrix); gsl_blas_daxpy(c, &bi.vector, &ai.vector); gsl_blas_dtrsv(CblasLower, CblasNoTrans, CblasNonUnit, &mb.matrix, &ai.vector); } } return GSL_SUCCESS;} /* gsl_eigen_gensymm_standardize() */
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