INLINE Vector<max_n> solve_using_qr(
Int m, Int n, Matrix<max_m, max_n> a, Vector<max_m> b) {
auto qr = factorize_qr_householder(m, n, a);
auto qtb = implicit_q_trans_b(m, n, qr.v, b);
auto x = solve_upper_triangular(n, qr.r, qtb);
return x;
}
int main(){
char *filename = "data_F.dat";
int n_col=2;
int n_row = 884;
float *file_data = load_matrix(filename, n_row);
float *data = malloc(n_row*n_col*sizeof(float));
float *b = malloc(n_row*sizeof(float));
float *theta = malloc(n_row*sizeof(float));
make_data(file_data, data, b,theta, n_row);
float *data_traspose = traspose(data,n_row,n_col);
float *matrix = multiply(data_traspose,data, n_col,n_row,n_row,n_col);
float *new_b = multiply(data_traspose,b, n_col, n_row, n_row, 1);
float *U = malloc(n_col*n_col*sizeof(float));
float *L = malloc(n_col*n_col*sizeof(float));
lu_decomposition(matrix,new_b,U,L,n_col);
float a1,a2;
solve_upper_triangular(U,new_b,&a1,&a2);
print_in_file(a1,a2);
return 0;
}
/* Solve from the qr decomposition itself. Useful if multiple equations
with the same left hand side need to be solved.
*/
struct vector* linsolve_from_qr(struct qr_decomp* qr, struct vector* v) {
struct vector* rhs = matrix_vector_multiply_Mtv(qr->q, v);
struct vector* solution = solve_upper_triangular(qr->r, rhs);
vector_free(rhs);
return solution;
}
