/* linalg/qr.c * * Copyright (C) 1996, 1997, 1998, 1999, 2000, 2007 Gerard Jungman, Brian Gough * Copyright (C) 2019 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. */ /* Author: G. Jungman */ #include #include #include #include #include #include #include #include #include "apply_givens.c" /* Factorise a general M x N matrix A into * * A = Q R * * where Q is orthogonal (M x M) and R is upper triangular (M x N). * * Q is stored as a packed set of Householder transformations in the * strict lower triangular part of the input matrix. * * R is stored in the diagonal and upper triangle of the input matrix. * * The full matrix for Q can be obtained as the product * * Q = Q_k .. Q_2 Q_1 * * where k = MIN(M,N) and * * Q_i = (I - tau_i * v_i * v_i') * * and where v_i is a Householder vector * * v_i = [1, m(i+1,i), m(i+2,i), ... , m(M,i)] * * This storage scheme is the same as in LAPACK. */ int gsl_linalg_QR_decomp (gsl_matrix * A, gsl_vector * tau) { const size_t N = A->size2; if (tau->size != N) { return gsl_linalg_QR_decomp_old (A, tau); } else { const size_t M = A->size1; size_t i; for (i = 0; i < GSL_MIN (M, N); i++) { /* Compute the Householder transformation to reduce the j-th column of the matrix to a multiple of the j-th unit vector */ gsl_vector_view c = gsl_matrix_subcolumn (A, i, i, M - i); double tau_i = gsl_linalg_householder_transform (&(c.vector)); double * ptr = gsl_vector_ptr(&(c.vector), 0); gsl_vector_set (tau, i, tau_i); /* Apply the transformation to the remaining columns and update the norms */ if (i + 1 < N) { gsl_matrix_view m = gsl_matrix_submatrix (A, i, i + 1, M - i, N - i - 1); gsl_vector_view work = gsl_vector_subvector(tau, i + 1, N - i - 1); double tmp = *ptr; *ptr = 1.0; gsl_linalg_householder_left(tau_i, &(c.vector), &(m.matrix), &(work.vector)); *ptr = tmp; } } return GSL_SUCCESS; } } int gsl_linalg_QR_decomp_old (gsl_matrix * A, gsl_vector * tau) { const size_t M = A->size1; const size_t N = A->size2; if (tau->size != GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN); } else { size_t i; for (i = 0; i < GSL_MIN (M, N); i++) { /* Compute the Householder transformation to reduce the j-th column of the matrix to a multiple of the j-th unit vector */ gsl_vector_view c = gsl_matrix_subcolumn (A, i, i, M - i); double tau_i = gsl_linalg_householder_transform (&(c.vector)); gsl_vector_set (tau, i, tau_i); /* Apply the transformation to the remaining columns and update the norms */ if (i + 1 < N) { gsl_matrix_view m = gsl_matrix_submatrix (A, i, i + 1, M - i, N - (i + 1)); gsl_linalg_householder_hm (tau_i, &(c.vector), &(m.matrix)); } } return GSL_SUCCESS; } } /* Solves the system A x = b using the QR factorisation, * R x = Q^T b * * to obtain x. Based on SLATEC code. */ int gsl_linalg_QR_solve (const gsl_matrix * QR, const gsl_vector * tau, const gsl_vector * b, gsl_vector * x) { if (QR->size1 != QR->size2) { GSL_ERROR ("QR matrix must be square", GSL_ENOTSQR); } else if (QR->size1 != b->size) { GSL_ERROR ("matrix size must match b size", GSL_EBADLEN); } else if (QR->size2 != x->size) { GSL_ERROR ("matrix size must match solution size", GSL_EBADLEN); } else { /* copy x <- b */ gsl_vector_memcpy (x, b); /* solve for x */ gsl_linalg_QR_svx (QR, tau, x); return GSL_SUCCESS; } } /* Solves the system A x = b in place using the QR factorisation, * R x = Q^T b * * to obtain x. Based on SLATEC code. */ int gsl_linalg_QR_svx (const gsl_matrix * QR, const gsl_vector * tau, gsl_vector * x) { if (QR->size1 != QR->size2) { GSL_ERROR ("QR matrix must be square", GSL_ENOTSQR); } else if (QR->size1 != x->size) { GSL_ERROR ("matrix size must match x/rhs size", GSL_EBADLEN); } else { /* compute rhs = Q^T b */ gsl_linalg_QR_QTvec (QR, tau, x); /* Solve R x = rhs, storing x in-place */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, QR, x); return GSL_SUCCESS; } } /* Find the least squares solution to the overdetermined system * * A x = b * * for M >= N using the QR factorization A = Q R. */ int gsl_linalg_QR_lssolve (const gsl_matrix * QR, const gsl_vector * tau, const gsl_vector * b, gsl_vector * x, gsl_vector * residual) { const size_t M = QR->size1; const size_t N = QR->size2; if (M < N) { GSL_ERROR ("QR matrix must have M>=N", GSL_EBADLEN); } else if (M != b->size) { GSL_ERROR ("matrix size must match b size", GSL_EBADLEN); } else if (N != x->size) { GSL_ERROR ("matrix size must match solution size", GSL_EBADLEN); } else if (M != residual->size) { GSL_ERROR ("matrix size must match residual size", GSL_EBADLEN); } else { gsl_matrix_const_view R = gsl_matrix_const_submatrix (QR, 0, 0, N, N); gsl_vector_view c = gsl_vector_subvector(residual, 0, N); gsl_vector_memcpy(residual, b); /* compute rhs = Q^T b */ gsl_linalg_QR_QTvec (QR, tau, residual); /* Solve R x = rhs */ gsl_vector_memcpy(x, &(c.vector)); gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, &(R.matrix), x); /* Compute residual = b - A x = Q (Q^T b - R x) */ gsl_vector_set_zero(&(c.vector)); gsl_linalg_QR_Qvec(QR, tau, residual); return GSL_SUCCESS; } } int gsl_linalg_QR_Rsolve (const gsl_matrix * QR, const gsl_vector * b, gsl_vector * x) { if (QR->size1 != QR->size2) { GSL_ERROR ("QR matrix must be square", GSL_ENOTSQR); } else if (QR->size1 != b->size) { GSL_ERROR ("matrix size must match b size", GSL_EBADLEN); } else if (QR->size2 != x->size) { GSL_ERROR ("matrix size must match x size", GSL_EBADLEN); } else { /* copy x <- b */ gsl_vector_memcpy (x, b); /* solve R x = b, storing x in-place */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, QR, x); return GSL_SUCCESS; } } int gsl_linalg_QR_Rsvx (const gsl_matrix * QR, gsl_vector * x) { if (QR->size1 != QR->size2) { GSL_ERROR ("QR matrix must be square", GSL_ENOTSQR); } else if (QR->size1 != x->size) { GSL_ERROR ("matrix size must match rhs size", GSL_EBADLEN); } else { /* solve R x = b, storing x in-place */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, QR, x); return GSL_SUCCESS; } } int gsl_linalg_R_solve (const gsl_matrix * R, const gsl_vector * b, gsl_vector * x) { if (R->size1 != R->size2) { GSL_ERROR ("R matrix must be square", GSL_ENOTSQR); } else if (R->size1 != b->size) { GSL_ERROR ("matrix size must match b size", GSL_EBADLEN); } else if (R->size2 != x->size) { GSL_ERROR ("matrix size must match solution size", GSL_EBADLEN); } else { /* copy x <- b */ gsl_vector_memcpy (x, b); /* solve R x = b, storing x inplace in b */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, R, x); return GSL_SUCCESS; } } int gsl_linalg_R_svx (const gsl_matrix * R, gsl_vector * x) { if (R->size1 != R->size2) { GSL_ERROR ("R matrix must be square", GSL_ENOTSQR); } else if (R->size2 != x->size) { GSL_ERROR ("matrix size must match solution size", GSL_EBADLEN); } else { /* solve R x = b, storing x inplace in b */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, R, x); return GSL_SUCCESS; } } /* Form the product Q^T v from a QR factorized matrix */ int gsl_linalg_QR_QTvec (const gsl_matrix * QR, const gsl_vector * tau, gsl_vector * v) { const size_t M = QR->size1; const size_t N = QR->size2; if (tau->size != GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN); } else if (v->size != M) { GSL_ERROR ("vector size must be M", GSL_EBADLEN); } else { size_t i; /* compute Q^T v */ for (i = 0; i < GSL_MIN (M, N); i++) { gsl_vector_const_view h = gsl_matrix_const_subcolumn (QR, i, i, M - i); gsl_vector_view w = gsl_vector_subvector (v, i, M - i); double ti = gsl_vector_get (tau, i); gsl_linalg_householder_hv (ti, &(h.vector), &(w.vector)); } return GSL_SUCCESS; } } int gsl_linalg_QR_Qvec (const gsl_matrix * QR, const gsl_vector * tau, gsl_vector * v) { const size_t M = QR->size1; const size_t N = QR->size2; if (tau->size != GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN); } else if (v->size != M) { GSL_ERROR ("vector size must be M", GSL_EBADLEN); } else { size_t i; /* compute Q v */ for (i = GSL_MIN (M, N); i-- > 0;) { gsl_vector_const_view c = gsl_matrix_const_column (QR, i); gsl_vector_const_view h = gsl_vector_const_subvector (&(c.vector), i, M - i); gsl_vector_view w = gsl_vector_subvector (v, i, M - i); double ti = gsl_vector_get (tau, i); gsl_linalg_householder_hv (ti, &h.vector, &w.vector); } return GSL_SUCCESS; } } /* Form the product Q^T A from a QR factorized matrix */ int gsl_linalg_QR_QTmat (const gsl_matrix * QR, const gsl_vector * tau, gsl_matrix * A) { const size_t M = QR->size1; const size_t N = QR->size2; if (tau->size != GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN); } else if (A->size1 != M) { GSL_ERROR ("matrix must have M rows", GSL_EBADLEN); } else { size_t i; /* compute Q^T A */ for (i = 0; i < GSL_MIN (M, N); i++) { gsl_vector_const_view c = gsl_matrix_const_column (QR, i); gsl_vector_const_view h = gsl_vector_const_subvector (&(c.vector), i, M - i); gsl_matrix_view m = gsl_matrix_submatrix(A, i, 0, M - i, A->size2); double ti = gsl_vector_get (tau, i); gsl_linalg_householder_hm (ti, &(h.vector), &(m.matrix)); } return GSL_SUCCESS; } } /* Form the product A Q from a QR factorized matrix */ int gsl_linalg_QR_matQ (const gsl_matrix * QR, const gsl_vector * tau, gsl_matrix * A) { const size_t M = QR->size1; const size_t N = QR->size2; if (tau->size != GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be MIN(M,N)", GSL_EBADLEN); } else if (A->size2 != M) { GSL_ERROR ("matrix must have M columns", GSL_EBADLEN); } else { size_t i; /* compute A Q */ for (i = 0; i < GSL_MIN (M, N); i++) { gsl_vector_const_view c = gsl_matrix_const_column (QR, i); gsl_vector_const_view h = gsl_vector_const_subvector (&(c.vector), i, M - i); gsl_matrix_view m = gsl_matrix_submatrix(A, 0, i, A->size1, M - i); double ti = gsl_vector_get (tau, i); gsl_linalg_householder_mh (ti, &(h.vector), &(m.matrix)); } return GSL_SUCCESS; } } /* Form the orthogonal matrix Q from the packed QR matrix */ int gsl_linalg_QR_unpack (const gsl_matrix * QR, const gsl_vector * tau, gsl_matrix * Q, gsl_matrix * R) { const size_t M = QR->size1; const size_t N = QR->size2; if (Q->size1 != M || Q->size2 != M) { GSL_ERROR ("Q matrix must be M x M", GSL_ENOTSQR); } else if (R->size1 != M || R->size2 != N) { GSL_ERROR ("R matrix must be M x N", GSL_ENOTSQR); } else if (tau->size < GSL_MIN (M, N)) { GSL_ERROR ("size of tau must be at least MIN(M,N)", GSL_EBADLEN); } else { size_t i, j; /* Initialize Q to the identity */ gsl_matrix_set_identity (Q); for (i = GSL_MIN (M, N); i-- > 0;) { gsl_vector_const_view h = gsl_matrix_const_subcolumn (QR, i, i, M - i); gsl_matrix_view m = gsl_matrix_submatrix (Q, i, i, M - i, M - i); double ti = gsl_vector_get (tau, i); gsl_linalg_householder_hm (ti, &h.vector, &m.matrix); } /* form the right triangular matrix R from a packed QR matrix */ for (i = 0; i < M; i++) { for (j = 0; j < i && j < N; j++) gsl_matrix_set (R, i, j, 0.0); for (j = i; j < N; j++) gsl_matrix_set (R, i, j, gsl_matrix_get (QR, i, j)); } return GSL_SUCCESS; } } /* Update a QR factorisation for A= Q R , A' = A + u v^T, * Q' R' = QR + u v^T * = Q (R + Q^T u v^T) * = Q (R + w v^T) * * where w = Q^T u. * * Algorithm from Golub and Van Loan, "Matrix Computations", Section * 12.5 (Updating Matrix Factorizations, Rank-One Changes) */ int gsl_linalg_QR_update (gsl_matrix * Q, gsl_matrix * R, gsl_vector * w, const gsl_vector * v) { const size_t M = R->size1; const size_t N = R->size2; if (Q->size1 != M || Q->size2 != M) { GSL_ERROR ("Q matrix must be M x M if R is M x N", GSL_ENOTSQR); } else if (w->size != M) { GSL_ERROR ("w must be length M if R is M x N", GSL_EBADLEN); } else if (v->size != N) { GSL_ERROR ("v must be length N if R is M x N", GSL_EBADLEN); } else { size_t j, k; double w0; /* Apply Given's rotations to reduce w to (|w|, 0, 0, ... , 0) J_1^T .... J_(n-1)^T w = +/- |w| e_1 simultaneously applied to R, H = J_1^T ... J^T_(n-1) R so that H is upper Hessenberg. (12.5.2) */ for (k = M - 1; k > 0; k--) /* loop from k = M-1 to 1 */ { double c, s; double wk = gsl_vector_get (w, k); double wkm1 = gsl_vector_get (w, k - 1); gsl_linalg_givens (wkm1, wk, &c, &s); gsl_linalg_givens_gv (w, k - 1, k, c, s); apply_givens_qr (M, N, Q, R, k - 1, k, c, s); } w0 = gsl_vector_get (w, 0); /* Add in w v^T (Equation 12.5.3) */ for (j = 0; j < N; j++) { double r0j = gsl_matrix_get (R, 0, j); double vj = gsl_vector_get (v, j); gsl_matrix_set (R, 0, j, r0j + w0 * vj); } /* Apply Givens transformations R' = G_(n-1)^T ... G_1^T H Equation 12.5.4 */ for (k = 1; k < GSL_MIN(M,N+1); k++) { double c, s; double diag = gsl_matrix_get (R, k - 1, k - 1); double offdiag = gsl_matrix_get (R, k, k - 1); gsl_linalg_givens (diag, offdiag, &c, &s); apply_givens_qr (M, N, Q, R, k - 1, k, c, s); gsl_matrix_set (R, k, k - 1, 0.0); /* exact zero of G^T */ } return GSL_SUCCESS; } } int gsl_linalg_QR_QRsolve (gsl_matrix * Q, gsl_matrix * R, const gsl_vector * b, gsl_vector * x) { const size_t M = R->size1; const size_t N = R->size2; if (M != N) { return GSL_ENOTSQR; } else if (Q->size1 != M || b->size != M || x->size != M) { return GSL_EBADLEN; } else { /* compute sol = Q^T b */ gsl_blas_dgemv (CblasTrans, 1.0, Q, b, 0.0, x); /* solve R x = sol, storing x in-place */ gsl_blas_dtrsv (CblasUpper, CblasNoTrans, CblasNonUnit, R, x); return GSL_SUCCESS; } } int gsl_linalg_QR_rcond(const gsl_matrix * QR, double * rcond, gsl_vector * work) { const size_t M = QR->size1; const size_t N = QR->size2; if (M < N) { GSL_ERROR ("M must be >= N", GSL_EBADLEN); } else if (work->size != 3 * N) { GSL_ERROR ("work vector must have length 3*N", GSL_EBADLEN); } else { gsl_matrix_const_view R = gsl_matrix_const_submatrix (QR, 0, 0, N, N); int status; status = gsl_linalg_tri_rcond(CblasUpper, &R.matrix, rcond, work); return status; } }