Developer Reference

Intel® oneAPI Math Kernel Library LAPACK Examples

ID 766877
Date 3/22/2024
Public

A newer version of this document is available. Customers should click here to go to the newest version.

Document Table of Contents

CHEEVD Example Program in C

/*******************************************************************************
*  Copyright (C) 2009-2015 Intel Corporation. All Rights Reserved.
*  The information and material ("Material") provided below is owned by Intel
*  Corporation or its suppliers or licensors, and title to such Material remains
*  with Intel Corporation or its suppliers or licensors. The Material contains
*  proprietary information of Intel or its suppliers and licensors. The Material
*  is protected by worldwide copyright laws and treaty provisions. No part of
*  the Material may be copied, reproduced, published, uploaded, posted,
*  transmitted, or distributed in any way without Intel's prior express written
*  permission. No license under any patent, copyright or other intellectual
*  property rights in the Material is granted to or conferred upon you, either
*  expressly, by implication, inducement, estoppel or otherwise. Any license
*  under such intellectual property rights must be express and approved by Intel
*  in writing.
*
********************************************************************************
*/
/*
   CHEEVD Example.
   ==============

   Program computes all eigenvalues and eigenvectors of a complex Hermitian
   matrix A using divide and conquer algorithm, where A is:

   (  3.40,  0.00) ( -2.36, -1.93) ( -4.68,  9.55) (  5.37, -1.23)
   ( -2.36,  1.93) (  6.94,  0.00) (  8.13, -1.47) (  2.07, -5.78)
   ( -4.68, -9.55) (  8.13,  1.47) ( -2.14,  0.00) (  4.68,  7.44)
   (  5.37,  1.23) (  2.07,  5.78) (  4.68, -7.44) ( -7.42,  0.00)

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

   The routine computes all eigenvalues and, optionally, eigenvectors of an
   n-by-n complex Hermitian 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.
   If the eigenvectors are requested, then this routine uses a divide and
   conquer algorithm to compute eigenvalues and eigenvectors.

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

 CHEEVD Example Program Results

 Eigenvalues
 -21.97  -0.05   6.46  16.34

 Eigenvectors (stored columnwise)
 (  0.41,  0.00) ( -0.34,  0.00) ( -0.69,  0.00) (  0.49,  0.00)
 (  0.02, -0.30) (  0.32, -0.21) ( -0.57, -0.22) ( -0.59, -0.21)
 (  0.18,  0.57) ( -0.42, -0.32) (  0.06,  0.16) ( -0.35, -0.47)
 ( -0.62, -0.09) ( -0.58,  0.35) ( -0.15, -0.31) ( -0.10, -0.12)
*/
#include <stdlib.h>
#include <stdio.h>

/* Complex datatype */
struct _fcomplex { float re, im; };
typedef struct _fcomplex fcomplex;

/* CHEEVD prototype */
extern void cheevd( char* jobz, char* uplo, int* n, fcomplex* a, int* lda,
                float* w, fcomplex* work, int* lwork, float* rwork, int* lrwork,
                int* iwork, int* liwork, int* info );
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, int m, int n, fcomplex* a, int lda );
extern void print_rmatrix( char* desc, int m, int n, float* a, int lda );

/* Parameters */
#define N 4
#define LDA N

/* Main program */
int main() {
        /* Locals */
        int n = N, lda = LDA, info, lwork, lrwork, liwork;
        int iwkopt;
        int* iwork;
        float rwkopt;
        float* rwork;
        fcomplex wkopt;
        fcomplex* work;
        /* Local arrays */
        float w[N];
        fcomplex a[LDA*N] = {
           { 3.40f,  0.00f}, {-2.36f,  1.93f}, {-4.68f, -9.55f}, { 5.37f,  1.23f},
           { 0.00f,  0.00f}, { 6.94f,  0.00f}, { 8.13f,  1.47f}, { 2.07f,  5.78f},
           { 0.00f,  0.00f}, { 0.00f,  0.00f}, {-2.14f,  0.00f}, { 4.68f, -7.44f},
           { 0.00f,  0.00f}, { 0.00f,  0.00f}, { 0.00f,  0.00f}, {-7.42f,  0.00f}
        };
        /* Executable statements */
        printf( " CHEEVD Example Program Results\n" );
        /* Query and allocate the optimal workspace */
        lwork = -1;
        lrwork = -1;
        liwork = -1;
        cheevd( "Vectors", "Lower", &n, a, &lda, w, &wkopt, &lwork, &rwkopt,
                        &lrwork, &iwkopt, &liwork, &info );
        lwork = (int)wkopt.re;
        work = (fcomplex*)malloc( lwork*sizeof(fcomplex) );
        lrwork = (int)rwkopt;
        rwork = (float*)malloc( lrwork*sizeof(float) );
        liwork = iwkopt;
        iwork = (int*)malloc( liwork*sizeof(int) );
        /* Solve eigenproblem */
        cheevd( "Vectors", "Lower", &n, a, &lda, w, work, &lwork, rwork,
                        &lrwork, iwork, &liwork, &info );
        /* Check for convergence */
        if( info > 0 ) {
                printf( "The algorithm failed to compute eigenvalues.\n" );
                exit( 1 );
        }
        /* Print eigenvalues */
        print_rmatrix( "Eigenvalues", 1, n, w, 1 );
        /* Print eigenvectors */
        print_matrix( "Eigenvectors (stored columnwise)", n, n, a, lda );
        /* Free workspace */
        free( (void*)iwork );
        free( (void*)rwork );
        free( (void*)work );
        exit( 0 );
} /* End of CHEEVD Example */

/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, int m, int n, fcomplex* 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,%6.2f)", a[i+j*lda].re, a[i+j*lda].im );
                printf( "\n" );
        }
}

/* Auxiliary routine: printing a real matrix */
void print_rmatrix( 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" );
        }
}