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LAPACKE_cgesdd Example Program in C for Column Major Data Layout
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/*
LAPACKE_cgesdd Example.
=======================
Program computes the singular value decomposition of a general
rectangular complex matrix A using a divide and conquer method, where A is:
( -5.40, 7.40) ( 6.00, 6.38) ( 9.91, 0.16) ( -5.28, -4.16)
( 1.09, 1.55) ( 2.60, 0.07) ( 3.98, -5.26) ( 2.03, 1.11)
( 9.88, 1.91) ( 4.92, 6.31) ( -2.11, 7.39) ( -9.81, -8.98)
Description.
============
The routine computes the singular value decomposition (SVD) of a complex
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*VH
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 unitary matrix and VH (V conjugate
transposed) is an n-by-n unitary 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 VH, not V.
Example Program Results.
========================
LAPACKE_cgesdd (column-major, high-level) Example Program Results
Singular values
21.76 16.60 3.97
Left singular vectors (stored columnwise)
( 0.55, 0.00) ( 0.76, 0.00) ( -0.34, 0.00)
( -0.04, -0.15) ( 0.27, -0.23) ( 0.55, -0.74)
( 0.81, 0.12) ( -0.52, -0.14) ( 0.13, -0.11)
Right singular vectors (stored rowwise)
( 0.23, 0.21) ( 0.37, 0.39) ( 0.24, 0.33) ( -0.56, -0.37)
( -0.58, 0.40) ( 0.11, 0.17) ( 0.60, -0.27) ( 0.16, 0.06)
( 0.60, 0.12) ( -0.19, 0.30) ( 0.39, 0.20) ( 0.45, 0.31)
*/
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex8* a, MKL_INT lda );
extern void print_rmatrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda );
/* Parameters */
#define M 3
#define N 4
#define LDA M
#define LDU M
#define LDVT N
/* Main program */
int main() {
/* Locals */
MKL_INT m = M, n = N, lda = LDA, ldu = LDU, ldvt = LDVT, info;
/* Local arrays */
float s[M];
MKL_Complex8 u[LDU*M], vt[LDVT*N];
MKL_Complex8 a[LDA*N] = {
{-5.40f, 7.40f}, { 1.09f, 1.55f}, { 9.88f, 1.91f},
{ 6.00f, 6.38f}, { 2.60f, 0.07f}, { 4.92f, 6.31f},
{ 9.91f, 0.16f}, { 3.98f, -5.26f}, {-2.11f, 7.39f},
{-5.28f, -4.16f}, { 2.03f, 1.11f}, {-9.81f, -8.98f}
};
/* Executable statements */
printf( "LAPACKE_cgesdd (column-major, high-level) Example Program Results\n" );
/* Compute SVD */
info = LAPACKE_cgesdd( LAPACK_COL_MAJOR, 'S', m, n, a, lda, s, u,
ldu, vt, ldvt );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm computing SVD failed to converge.\n" );
exit( 1 );
}
/* Print singular values */
print_rmatrix( "Singular values", 1, m, s, 1 );
/* Print left singular vectors */
print_matrix( "Left singular vectors (stored columnwise)", m, m, u, ldu );
/* Print right singular vectors */
print_matrix( "Right singular vectors (stored rowwise)", m, n, vt, ldvt );
exit( 0 );
} /* End of LAPACKE_cgesdd Example */
/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex8* a, MKL_INT lda ) {
MKL_INT i, j;
printf( "\n %s\n", desc );
for( i = 0; i < m; i++ ) {
for( j = 0; j < n; j++ )
printf( " (%6.2f,%6.2f)", a[i+j*lda].real, a[i+j*lda].imag );
printf( "\n" );
}
}
/* Auxiliary routine: printing a real matrix */
void print_rmatrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda ) {
MKL_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: CGESDD Example