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SSYEVR Example Program in C
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/*
SSYEVR Example.
==============
Program computes the smallest eigenvalues and the corresponding
eigenvectors of a real symmetric matrix A using the Relatively Robust
Representations, where A is:
0.67 -0.20 0.19 -1.06 0.46
-0.20 3.82 -0.13 1.06 -0.48
0.19 -0.13 3.27 0.11 1.10
-1.06 1.06 0.11 5.86 -0.98
0.46 -0.48 1.10 -0.98 3.54
Description.
============
The routine computes selected eigenvalues and, optionally, eigenvectors of
an n-by-n real symmetric matrix A. The eigenvector v(j) of A satisfies
A*v(j) = lambda(j)*v(j)
where lambda(j) is its eigenvalue. The computed eigenvectors are
orthonormal.
Eigenvalues and eigenvectors can be selected by specifying either a range
of values or a range of indices for the desired eigenvalues.
Example Program Results.
========================
SSYEVR Example Program Results
The total number of eigenvalues found: 3
Selected eigenvalues
0.43 2.14 3.37
Selected eigenvectors (stored columnwise)
-0.98 -0.01 -0.08
0.01 0.02 -0.93
0.04 -0.69 -0.07
-0.18 0.19 0.31
0.07 0.69 -0.13
*/
#include <stdlib.h>
#include <stdio.h>
/* SSYEVR prototype */
extern void ssyevr( char* jobz, char* range, char* uplo, int* n, float* a,
int* lda, float* vl, float* vu, int* il, int* iu, float* abstol,
int* m, float* w, float* z, int* ldz, int* isuppz, float* work,
int* lwork, int* iwork, int* liwork, int* info );
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, int m, int n, float* a, int lda );
/* Parameters */
#define N 5
#define NSELECT 3
#define LDA N
#define LDZ N
/* Main program */
int main() {
/* Locals */
int n = N, il, iu, m, lda = LDA, ldz = LDZ, info, lwork, liwork;
float abstol, vl, vu;
int iwkopt;
int* iwork;
float wkopt;
float* work;
/* Local arrays */
int isuppz[N];
float w[N], z[LDZ*NSELECT];
float a[LDA*N] = {
0.67f, 0.00f, 0.00f, 0.00f, 0.00f,
-0.20f, 3.82f, 0.00f, 0.00f, 0.00f,
0.19f, -0.13f, 3.27f, 0.00f, 0.00f,
-1.06f, 1.06f, 0.11f, 5.86f, 0.00f,
0.46f, -0.48f, 1.10f, -0.98f, 3.54f
};
/* Executable statements */
printf( " SSYEVR Example Program Results\n" );
/* Negative abstol means using the default value */
abstol = -1.0;
/* Set il, iu to compute NSELECT smallest eigenvalues */
il = 1;
iu = NSELECT;
/* Query and allocate the optimal workspace */
lwork = -1;
liwork = -1;
ssyevr( "Vectors", "Indices", "Upper", &n, a, &lda, &vl, &vu, &il, &iu,
&abstol, &m, w, z, &ldz, isuppz, &wkopt, &lwork, &iwkopt, &liwork,
&info );
lwork = (int)wkopt;
work = (float*)malloc( lwork*sizeof(float) );
liwork = iwkopt;
iwork = (int*)malloc( liwork*sizeof(int) );
/* Solve eigenproblem */
ssyevr( "Vectors", "Indices", "Upper", &n, a, &lda, &vl, &vu, &il, &iu,
&abstol, &m, w, z, &ldz, isuppz, work, &lwork, iwork, &liwork,
&info );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm failed to compute eigenvalues.\n" );
exit( 1 );
}
/* Print the number of eigenvalues found */
printf( "\n The total number of eigenvalues found:%2i\n", m );
/* Print eigenvalues */
print_matrix( "Selected eigenvalues", 1, m, w, 1 );
/* Print eigenvectors */
print_matrix( "Selected eigenvectors (stored columnwise)", n, m, z, ldz );
/* Free workspace */
free( (void*)iwork );
free( (void*)work );
exit( 0 );
} /* End of SSYEVR Example */
/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, int m, int n, float* a, int lda ) {
int i, j;
printf( "\n %s\n", desc );
for( i = 0; i < m; i++ ) {
for( j = 0; j < n; j++ ) printf( " %6.2f", a[i+j*lda] );
printf( "\n" );
}
}
Parent topic: SSYEVR Example