gensymm.c

来自「math library from gnu」· C语言 代码 · 共 212 行

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/* 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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