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/*
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();
}
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