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Diffstat (limited to 'src/eigenlib.cpp')
-rw-r--r-- | src/eigenlib.cpp | 107 |
1 files changed, 0 insertions, 107 deletions
diff --git a/src/eigenlib.cpp b/src/eigenlib.cpp deleted file mode 100644 index 470aa08..0000000 --- a/src/eigenlib.cpp +++ /dev/null @@ -1,107 +0,0 @@ -/* - Genome-wide Efficient Mixed Model Association (GEMMA) - Copyright (C) 2011-2017, Xiang Zhou - - 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, see <http://www.gnu.org/licenses/>. -*/ - -#include "Eigen/Dense" -// #include "gsl/gsl_linalg.h" -#include "gsl/gsl_matrix.h" -// #include "gsl/gsl_vector.h" -#include <cmath> -#include <iostream> -#include <vector> -// #include <cblas.h> - -using namespace std; -using namespace Eigen; - - -// On two different clusters, compare eigen vs lapack/gsl: -// -// dgemm, 5x or 0.5x faster or slower than lapack, 5x or 4x faster than gsl -// dgemv, 20x or 4x faster than gsl, -// eigen, 1x or 0.3x slower than lapack -// invert, 20x or 10x faster than lapack -// -void eigenlib_dgemm(const char *TransA, const char *TransB, const double alpha, - const gsl_matrix *A, const gsl_matrix *B, const double beta, - gsl_matrix *C) { - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda)); - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - B_mat(B->data, B->size1, B->size2, OuterStride<Dynamic>(B->tda)); - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - C_mat(C->data, C->size1, C->size2, OuterStride<Dynamic>(C->tda)); - - if (*TransA == 'N' || *TransA == 'n') { - if (*TransB == 'N' || *TransB == 'n') { - C_mat = alpha * A_mat * B_mat + beta * C_mat; - } else { - C_mat = alpha * A_mat * B_mat.transpose() + beta * C_mat; - } - } else { - if (*TransB == 'N' || *TransB == 'n') { - C_mat = alpha * A_mat.transpose() * B_mat + beta * C_mat; - } else { - C_mat = alpha * A_mat.transpose() * B_mat.transpose() + beta * C_mat; - } - } -} - -void eigenlib_dgemv(const char *TransA, const double alpha, const gsl_matrix *A, - const gsl_vector *x, const double beta, gsl_vector *y) { - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda)); - Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic>> x_vec( - x->data, x->size, InnerStride<Dynamic>(x->stride)); - Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic>> y_vec( - y->data, y->size, InnerStride<Dynamic>(y->stride)); - - if (*TransA == 'N' || *TransA == 'n') { - y_vec = alpha * A_mat * x_vec + beta * y_vec; - } else { - y_vec = alpha * A_mat.transpose() * x_vec + beta * y_vec; - } -} - -void eigenlib_invert(gsl_matrix *A) { - Map<Matrix<double, Dynamic, Dynamic, RowMajor>> A_mat(A->data, A->size1, - A->size2); - A_mat = A_mat.inverse(); -} - -void eigenlib_dsyr(const double alpha, const gsl_vector *b, gsl_matrix *A) { - Map<Matrix<double, Dynamic, Dynamic, RowMajor>> A_mat(A->data, A->size1, - A->size2); - Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic>> b_vec( - b->data, b->size, OuterStride<Dynamic>(b->stride)); - A_mat = alpha * b_vec * b_vec.transpose() + A_mat; -} - -void eigenlib_eigensymm(const gsl_matrix *G, gsl_matrix *U, gsl_vector *eval) { - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - G_mat(G->data, G->size1, G->size2, OuterStride<Dynamic>(G->tda)); - Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic>> - U_mat(U->data, U->size1, U->size2, OuterStride<Dynamic>(U->tda)); - Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic>> eval_vec( - eval->data, eval->size, OuterStride<Dynamic>(eval->stride)); - - SelfAdjointEigenSolver<MatrixXd> es(G_mat); - if (es.info() != Success) - abort(); - eval_vec = es.eigenvalues(); - U_mat = es.eigenvectors(); -} |