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LAPACKE_sgeev Example Program in C for Row Major Data Layout
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/*
LAPACKE_sgeev 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_sgeev (row-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, float* wr, float* wi );
extern void print_eigenvectors( char* desc, MKL_INT n, float* wi, float* 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 */
float wr[N], wi[N], vl[LDVL*N], vr[LDVR*N];
float a[LDA*N] = {
-1.01f, 0.86f, -4.60f, 3.31f, -4.81f,
3.98f, 0.53f, -7.04f, 5.29f, 3.55f,
3.30f, 8.26f, -3.89f, 8.20f, -1.51f,
4.43f, 4.96f, -7.66f, -7.33f, 6.18f,
7.31f, -6.43f, -6.16f, 2.47f, 5.58f
};
/* Executable statements */
printf( "LAPACKE_sgeev (row-major, high-level) Example Program Results\n" );
/* Solve eigenproblem */
info = LAPACKE_sgeev( LAPACK_ROW_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_sgeev Example */
/* Auxiliary routine: printing eigenvalues */
void print_eigenvalues( char* desc, MKL_INT n, float* wr, float* wi ) {
MKL_INT j;
printf( "\n %s\n", desc );
for( j = 0; j < n; j++ ) {
if( wi[j] == (float)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, float* wi, float* 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] == (float)0.0 ) {
printf( " %6.2f", v[i*ldv+j] );
j++;
} else {
printf( " (%6.2f,%6.2f)", v[i*ldv+j], v[i*ldv+(j+1)] );
printf( " (%6.2f,%6.2f)", v[i*ldv+j], -v[i*ldv+(j+1)] );
j += 2;
}
}
printf( "\n" );
}
}
Parent topic: SGEEV Example