Developer Reference

## Intel® oneAPI Math Kernel Library LAPACK Examples

ID 766877
Date 12/20/2021
Public

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## LAPACKE_dgeev Example Program in C for Column Major Data Layout

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/*
LAPACKE_dgeev Example.
======================

Program computes the eigenvalues and left and right eigenvectors of a general
rectangular matrix A:

-1.01   0.86  -4.60   3.31  -4.81
3.98   0.53  -7.04   5.29   3.55
3.30   8.26  -3.89   8.20  -1.51
4.43   4.96  -7.66  -7.33   6.18
7.31  -6.43  -6.16   2.47   5.58

Description.
============

The routine computes for an n-by-n real nonsymmetric matrix A, the
eigenvalues and, optionally, the left and/or right eigenvectors. The right
eigenvector v(j) of A satisfies

A*v(j)= lambda(j)*v(j)

where lambda(j) is its eigenvalue. The left eigenvector u(j) of A satisfies

u(j)H*A = lambda(j)*u(j)H

where u(j)H denotes the conjugate transpose of u(j). The computed
eigenvectors are normalized to have Euclidean norm equal to 1 and
largest component real.

Example Program Results.
========================

LAPACKE_dgeev (column-major, high-level) Example Program Results

Eigenvalues
(  2.86, 10.76) (  2.86,-10.76) ( -0.69,  4.70) ( -0.69, -4.70) -10.46

Left eigenvectors
(  0.04,  0.29) (  0.04, -0.29) ( -0.13, -0.33) ( -0.13,  0.33)   0.04
(  0.62,  0.00) (  0.62,  0.00) (  0.69,  0.00) (  0.69,  0.00)   0.56
( -0.04, -0.58) ( -0.04,  0.58) ( -0.39, -0.07) ( -0.39,  0.07)  -0.13
(  0.28,  0.01) (  0.28, -0.01) ( -0.02, -0.19) ( -0.02,  0.19)  -0.80
( -0.04,  0.34) ( -0.04, -0.34) ( -0.40,  0.22) ( -0.40, -0.22)   0.18

Right eigenvectors
(  0.11,  0.17) (  0.11, -0.17) (  0.73,  0.00) (  0.73,  0.00)   0.46
(  0.41, -0.26) (  0.41,  0.26) ( -0.03, -0.02) ( -0.03,  0.02)   0.34
(  0.10, -0.51) (  0.10,  0.51) (  0.19, -0.29) (  0.19,  0.29)   0.31
(  0.40, -0.09) (  0.40,  0.09) ( -0.08, -0.08) ( -0.08,  0.08)  -0.74
(  0.54,  0.00) (  0.54,  0.00) ( -0.29, -0.49) ( -0.29,  0.49)   0.16
*/
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"

/* Auxiliary routines prototypes */
extern void print_eigenvalues( char* desc, MKL_INT n, double* wr, double* wi );
extern void print_eigenvectors( char* desc, MKL_INT n, double* wi, double* v,
MKL_INT ldv );

/* Parameters */
#define N 5
#define LDA N
#define LDVL N
#define LDVR N

/* Main program */
int main() {
/* Locals */
MKL_INT n = N, lda = LDA, ldvl = LDVL, ldvr = LDVR, info;
/* Local arrays */
double wr[N], wi[N], vl[LDVL*N], vr[LDVR*N];
double a[LDA*N] = {
-1.01,  3.98,  3.30,  4.43,  7.31,
0.86,  0.53,  8.26,  4.96, -6.43,
-4.60, -7.04, -3.89, -7.66, -6.16,
3.31,  5.29,  8.20, -7.33,  2.47,
-4.81,  3.55, -1.51,  6.18,  5.58
};
/* Executable statements */
printf( "LAPACKE_dgeev (column-major, high-level) Example Program Results\n" );
/* Solve eigenproblem */
info = LAPACKE_dgeev( LAPACK_COL_MAJOR, 'V', 'V', n, a, lda, wr, wi,
vl, ldvl, vr, ldvr );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm failed to compute eigenvalues.\n" );
exit( 1 );
}
/* Print eigenvalues */
print_eigenvalues( "Eigenvalues", n, wr, wi );
/* Print left eigenvectors */
print_eigenvectors( "Left eigenvectors", n, wi, vl, ldvl );
/* Print right eigenvectors */
print_eigenvectors( "Right eigenvectors", n, wi, vr, ldvr );
exit( 0 );
} /* End of LAPACKE_dgeev Example */

/* Auxiliary routine: printing eigenvalues */
void print_eigenvalues( char* desc, MKL_INT n, double* wr, double* wi ) {
MKL_INT j;
printf( "\n %s\n", desc );
for( j = 0; j < n; j++ ) {
if( wi[j] == (double)0.0 ) {
printf( " %6.2f", wr[j] );
} else {
printf( " (%6.2f,%6.2f)", wr[j], wi[j] );
}
}
printf( "\n" );
}

/* Auxiliary routine: printing eigenvectors */
void print_eigenvectors( char* desc, MKL_INT n, double* wi, double* v, MKL_INT ldv ) {
MKL_INT i, j;
printf( "\n %s\n", desc );
for( i = 0; i < n; i++ ) {
j = 0;
while( j < n ) {
if( wi[j] == (double)0.0 ) {
printf( " %6.2f", v[i+j*ldv] );
j++;
} else {
printf( " (%6.2f,%6.2f)", v[i+j*ldv], v[i+(j+1)*ldv] );
printf( " (%6.2f,%6.2f)", v[i+j*ldv], -v[i+(j+1)*ldv] );
j += 2;
}
}
printf( "\n" );
}
}