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SGESDD Example Program in C
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/*
SGESDD Example.
==============
Program computes the singular value decomposition of a general
rectangular matrix A using a divide and conquer method, where A is:
7.52 -1.10 -7.95 1.08
-0.76 0.62 9.34 -7.10
5.13 6.62 -5.66 0.87
-4.75 8.52 5.75 5.30
1.33 4.91 -5.49 -3.52
-2.40 -6.77 2.34 3.95
Description.
============
The routine computes the singular value decomposition (SVD) of a real
m-by-n matrix A, optionally computing the left and/or right singular
vectors. If singular vectors are desired, it uses a divide and conquer
algorithm. The SVD is written as
A = U*SIGMA*VT
where SIGMA is an m-by-n matrix which is zero except for its min(m,n)
diagonal elements, U is an m-by-m orthogonal matrix and VT (V transposed)
is an n-by-n orthogonal matrix. The diagonal elements of SIGMA
are the singular values of A; they are real and non-negative, and are
returned in descending order. The first min(m, n) columns of U and V are
the left and right singular vectors of A.
Note that the routine returns VT, not V.
Example Program Results.
========================
SGESDD Example Program Results
Singular values
18.37 13.63 10.85 4.49
Left singular vectors (stored columnwise)
-0.57 0.18 0.01 0.53
0.46 -0.11 -0.72 0.42
-0.45 -0.41 0.00 0.36
0.33 -0.69 0.49 0.19
-0.32 -0.31 -0.28 -0.61
0.21 0.46 0.39 0.09
Right singular vectors (stored rowwise)
-0.52 -0.12 0.85 -0.03
0.08 -0.99 -0.09 -0.01
-0.28 -0.02 -0.14 0.95
0.81 0.01 0.50 0.31
*/
#include <stdlib.h>
#include <stdio.h>
/* SGESDD prototype */
extern void sgesdd( char* jobz, int* m, int* n, float* a,
int* lda, float* s, float* u, int* ldu, float* vt, int* ldvt,
float* work, int* lwork, int* iwork, int* info );
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, int m, int n, float* a, int lda );
/* Parameters */
#define M 6
#define N 4
#define LDA M
#define LDU M
#define LDVT N
/* Main program */
int main() {
/* Locals */
int m = M, n = N, lda = LDA, ldu = LDU, ldvt = LDVT, info, lwork;
float wkopt;
float* work;
/* Local arrays */
/* iwork dimension should be at least 8*min(m,n) */
int iwork[8*N];
float s[N], u[LDU*M], vt[LDVT*N];
float a[LDA*N] = {
7.52f, -0.76f, 5.13f, -4.75f, 1.33f, -2.40f,
-1.10f, 0.62f, 6.62f, 8.52f, 4.91f, -6.77f,
-7.95f, 9.34f, -5.66f, 5.75f, -5.49f, 2.34f,
1.08f, -7.10f, 0.87f, 5.30f, -3.52f, 3.95f
};
/* Executable statements */
printf( " SGESDD Example Program Results\n" );
/* Query and allocate the optimal workspace */
lwork = -1;
sgesdd( "Singular vectors", &m, &n, a, &lda, s, u, &ldu, vt, &ldvt, &wkopt,
&lwork, iwork, &info );
lwork = (int)wkopt;
work = (float*)malloc( lwork*sizeof(float) );
/* Compute SVD */
sgesdd( "Singular vectors", &m, &n, a, &lda, s, u, &ldu, vt, &ldvt, work,
&lwork, iwork, &info );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm computing SVD failed to converge.\n" );
exit( 1 );
}
/* Print singular values */
print_matrix( "Singular values", 1, n, s, 1 );
/* Print left singular vectors */
print_matrix( "Left singular vectors (stored columnwise)", m, n, u, ldu );
/* Print right singular vectors */
print_matrix( "Right singular vectors (stored rowwise)", n, n, vt, ldvt );
/* Free workspace */
free( (void*)work );
exit( 0 );
} /* End of SGESDD 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: SGESDD Example