xref: /petsc/src/mat/tests/ex116.c (revision ebead697dbf761eb322f829370bbe90b3bd93fa3)
1 static char help[] = "Test LAPACK routine DSYEV() or DSYEVX(). \n\
2 Reads PETSc matrix A \n\
3 then computes selected eigenvalues, and optionally, eigenvectors of \n\
4 a real generalized symmetric-definite eigenproblem \n\
5  A*x = lambda*x \n\
6 Input parameters include\n\
7   -f <input_file> : file to load\n\
8 e.g. ./ex116 -f $DATAFILESPATH/matrices/small  \n\n";
9 
10 #include <petscmat.h>
11 #include <petscblaslapack.h>
12 
13 extern PetscErrorCode CkEigenSolutions(PetscInt,Mat,PetscInt,PetscInt,PetscReal*,Vec*,PetscReal*);
14 
15 int main(int argc,char **args)
16 {
17   Mat            A,A_dense;
18   Vec            *evecs;
19   PetscViewer    fd;                /* viewer */
20   char           file[1][PETSC_MAX_PATH_LEN];     /* input file name */
21   PetscBool      flg,TestSYEVX=PETSC_TRUE;
22   PetscBool      isSymmetric;
23   PetscScalar    *arrayA,*evecs_array,*work,*evals;
24   PetscMPIInt    size;
25   PetscInt       m,n,i,cklvl=2;
26   PetscBLASInt   nevs,il,iu,in;
27   PetscReal      vl,vu,abstol=1.e-8;
28   PetscBLASInt   *iwork,*ifail,lwork,lierr,bn;
29   PetscReal      tols[2];
30 
31   PetscFunctionBeginUser;
32   PetscCall(PetscInitialize(&argc,&args,(char*)0,help));
33   PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD,&size));
34   PetscCheck(size == 1,PETSC_COMM_WORLD,PETSC_ERR_WRONG_MPI_SIZE,"This is a uniprocessor example only!");
35 
36   PetscCall(PetscOptionsHasName(NULL,NULL, "-test_syev", &flg));
37   if (flg) {
38     TestSYEVX = PETSC_FALSE;
39   }
40 
41   /* Determine files from which we read the two matrices */
42   PetscCall(PetscOptionsGetString(NULL,NULL,"-f",file[0],sizeof(file[0]),&flg));
43 
44   /* Load matrix A */
45   PetscCall(PetscViewerBinaryOpen(PETSC_COMM_WORLD,file[0],FILE_MODE_READ,&fd));
46   PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
47   PetscCall(MatSetType(A,MATSEQAIJ));
48   PetscCall(MatLoad(A,fd));
49   PetscCall(PetscViewerDestroy(&fd));
50   PetscCall(MatGetSize(A,&m,&n));
51 
52   /* Check whether A is symmetric */
53   PetscCall(PetscOptionsHasName(NULL,NULL, "-check_symmetry", &flg));
54   if (flg) {
55     Mat Trans;
56     PetscCall(MatTranspose(A,MAT_INITIAL_MATRIX, &Trans));
57     PetscCall(MatEqual(A, Trans, &isSymmetric));
58     PetscCheck(isSymmetric,PETSC_COMM_SELF,PETSC_ERR_USER,"A must be symmetric");
59     PetscCall(MatDestroy(&Trans));
60   }
61 
62   /* Solve eigenvalue problem: A_dense*x = lambda*B*x */
63   /*==================================================*/
64   /* Convert aij matrix to MatSeqDense for LAPACK */
65   PetscCall(MatConvert(A,MATSEQDENSE,MAT_INITIAL_MATRIX,&A_dense));
66 
67   PetscCall(PetscBLASIntCast(8*n,&lwork));
68   PetscCall(PetscBLASIntCast(n,&bn));
69   PetscCall(PetscMalloc1(n,&evals));
70   PetscCall(PetscMalloc1(lwork,&work));
71   PetscCall(MatDenseGetArray(A_dense,&arrayA));
72 
73   if (!TestSYEVX) { /* test syev() */
74     PetscCall(PetscPrintf(PETSC_COMM_SELF," LAPACKsyev: compute all %" PetscInt_FMT " eigensolutions...\n",m));
75     LAPACKsyev_("V","U",&bn,arrayA,&bn,evals,work,&lwork,&lierr);
76     evecs_array = arrayA;
77     PetscCall(PetscBLASIntCast(m,&nevs));
78     il          = 1;
79     PetscCall(PetscBLASIntCast(m,&iu));
80   } else { /* test syevx()  */
81     il   = 1;
82     PetscCall(PetscBLASIntCast(0.2*m,&iu));
83     PetscCall(PetscBLASIntCast(n,&in));
84     PetscCall(PetscPrintf(PETSC_COMM_SELF," LAPACKsyevx: compute %" PetscBLASInt_FMT " to %" PetscBLASInt_FMT "-th eigensolutions...\n",il,iu));
85     PetscCall(PetscMalloc1(m*n+1,&evecs_array));
86     PetscCall(PetscMalloc1(6*n+1,&iwork));
87     ifail = iwork + 5*n;
88 
89     /* in the case "I", vl and vu are not referenced */
90     vl = 0.0; vu = 8.0;
91     LAPACKsyevx_("V","I","U",&bn,arrayA,&bn,&vl,&vu,&il,&iu,&abstol,&nevs,evals,evecs_array,&in,work,&lwork,iwork,ifail,&lierr);
92     PetscCall(PetscFree(iwork));
93   }
94   PetscCall(MatDenseRestoreArray(A_dense,&arrayA));
95   PetscCheck(nevs > 0,PETSC_COMM_SELF,PETSC_ERR_CONV_FAILED, "nev=%" PetscBLASInt_FMT ", no eigensolution has found", nevs);
96 
97   /* View eigenvalues */
98   PetscCall(PetscOptionsHasName(NULL,NULL, "-eig_view", &flg));
99   if (flg) {
100     PetscCall(PetscPrintf(PETSC_COMM_SELF," %" PetscBLASInt_FMT " evals: \n",nevs));
101     for (i=0; i<nevs; i++) PetscCall(PetscPrintf(PETSC_COMM_SELF,"%" PetscInt_FMT "  %g\n",(PetscInt)(i+il),(double)evals[i]));
102   }
103 
104   /* Check residuals and orthogonality */
105   PetscCall(PetscMalloc1(nevs+1,&evecs));
106   for (i=0; i<nevs; i++) {
107     PetscCall(VecCreate(PETSC_COMM_SELF,&evecs[i]));
108     PetscCall(VecSetSizes(evecs[i],PETSC_DECIDE,n));
109     PetscCall(VecSetFromOptions(evecs[i]));
110     PetscCall(VecPlaceArray(evecs[i],evecs_array+i*n));
111   }
112 
113   tols[0] = tols[1] = PETSC_SQRT_MACHINE_EPSILON;
114   PetscCall(CkEigenSolutions(cklvl,A,il-1,iu-1,evals,evecs,tols));
115 
116   /* Free work space. */
117   for (i=0; i<nevs; i++) PetscCall(VecDestroy(&evecs[i]));
118   PetscCall(PetscFree(evecs));
119   PetscCall(MatDestroy(&A_dense));
120   PetscCall(PetscFree(work));
121   if (TestSYEVX) PetscCall(PetscFree(evecs_array));
122 
123   /* Compute SVD: A_dense = U*SIGMA*transpose(V),
124      JOBU=JOBV='S':  the first min(m,n) columns of U and V are returned in the arrayU and arrayV; */
125   /*==============================================================================================*/
126   {
127     /* Convert aij matrix to MatSeqDense for LAPACK */
128     PetscScalar  *arrayU,*arrayVT,*arrayErr,alpha=1.0,beta=-1.0;
129     Mat          Err;
130     PetscBLASInt minMN,maxMN,im,in;
131     PetscInt     j;
132     PetscReal    norm;
133 
134     PetscCall(MatConvert(A,MATSEQDENSE,MAT_INITIAL_MATRIX,&A_dense));
135 
136     minMN = PetscMin(m,n);
137     maxMN = PetscMax(m,n);
138     lwork = 5*minMN + maxMN;
139     PetscCall(PetscMalloc4(m*minMN,&arrayU,m*minMN,&arrayVT,m*minMN,&arrayErr,lwork,&work));
140 
141     /* Create matrix Err for checking error */
142     PetscCall(MatCreate(PETSC_COMM_WORLD,&Err));
143     PetscCall(MatSetSizes(Err,PETSC_DECIDE,PETSC_DECIDE,m,minMN));
144     PetscCall(MatSetType(Err,MATSEQDENSE));
145     PetscCall(MatSeqDenseSetPreallocation(Err,(PetscScalar*)arrayErr));
146 
147     /* Save A to arrayErr for checking accuracy later. arrayA will be destroyed by LAPACKgesvd_() */
148     PetscCall(MatDenseGetArray(A_dense,&arrayA));
149     PetscCall(PetscArraycpy(arrayErr,arrayA,m*minMN));
150 
151     PetscCall(PetscBLASIntCast(m,&im));
152     PetscCall(PetscBLASIntCast(n,&in));
153     /* Compute A = U*SIGMA*VT */
154     LAPACKgesvd_("S","S",&im,&in,arrayA,&im,evals,arrayU,&minMN,arrayVT,&minMN,work,&lwork,&lierr);
155     PetscCall(MatDenseRestoreArray(A_dense,&arrayA));
156     if (!lierr) {
157       PetscCall(PetscPrintf(PETSC_COMM_SELF," 1st 10 of %" PetscBLASInt_FMT " singular values: \n",minMN));
158       for (i=0; i<10; i++) PetscCall(PetscPrintf(PETSC_COMM_SELF,"%" PetscInt_FMT "  %g\n",i,(double)evals[i]));
159     } else {
160       PetscCall(PetscPrintf(PETSC_COMM_SELF,"LAPACKgesvd_ fails!"));
161     }
162 
163     /* Check Err = (U*Sigma*V^T - A) using BLASgemm() */
164     /* U = U*Sigma */
165     for (j=0; j<minMN; j++) { /* U[:,j] = sigma[j]*U[:,j] */
166       for (i=0; i<m; i++) arrayU[j*m+i] *= evals[j];
167     }
168     /* Err = U*VT - A = alpha*U*VT + beta*Err */
169     BLASgemm_("N","N",&im,&minMN,&minMN,&alpha,arrayU,&im,arrayVT,&minMN,&beta,arrayErr,&im);
170     PetscCall(MatNorm(Err,NORM_FROBENIUS,&norm));
171     PetscCall(PetscPrintf(PETSC_COMM_SELF," || U*Sigma*VT - A || = %g\n",(double)norm));
172 
173     PetscCall(PetscFree4(arrayU,arrayVT,arrayErr,work));
174     PetscCall(PetscFree(evals));
175     PetscCall(MatDestroy(&A_dense));
176     PetscCall(MatDestroy(&Err));
177   }
178 
179   PetscCall(MatDestroy(&A));
180   PetscCall(PetscFinalize());
181   return 0;
182 }
183 /*------------------------------------------------
184   Check the accuracy of the eigen solution
185   ----------------------------------------------- */
186 /*
187   input:
188      cklvl      - check level:
189                     1: check residual
190                     2: 1 and check B-orthogonality locally
191      A          - matrix
192      il,iu      - lower and upper index bound of eigenvalues
193      eval, evec - eigenvalues and eigenvectors stored in this process
194      tols[0]    - reporting tol_res: || A * evec[i] - eval[i]*evec[i] ||
195      tols[1]    - reporting tol_orth: evec[i]^T*evec[j] - delta_ij
196 */
197 PetscErrorCode CkEigenSolutions(PetscInt cklvl,Mat A,PetscInt il,PetscInt iu,PetscReal *eval,Vec *evec,PetscReal *tols)
198 {
199   PetscInt  i,j,nev;
200   Vec       vt1,vt2;    /* tmp vectors */
201   PetscReal norm,tmp,dot,norm_max,dot_max;
202 
203   PetscFunctionBegin;
204   nev = iu - il;
205   if (nev <= 0) PetscFunctionReturn(0);
206 
207   /*ierr = VecView(evec[0],PETSC_VIEWER_STDOUT_WORLD);*/
208   PetscCall(VecDuplicate(evec[0],&vt1));
209   PetscCall(VecDuplicate(evec[0],&vt2));
210 
211   switch (cklvl) {
212   case 2:
213     dot_max = 0.0;
214     for (i = il; i<iu; i++) {
215       PetscCall(VecCopy(evec[i], vt1));
216       for (j=il; j<iu; j++) {
217         PetscCall(VecDot(evec[j],vt1,&dot));
218         if (j == i) {
219           dot = PetscAbsScalar(dot - 1);
220         } else {
221           dot = PetscAbsScalar(dot);
222         }
223         if (dot > dot_max) dot_max = dot;
224         if (dot > tols[1]) {
225           PetscCall(VecNorm(evec[i],NORM_INFINITY,&norm));
226           PetscCall(PetscPrintf(PETSC_COMM_SELF,"|delta(%" PetscInt_FMT ",%" PetscInt_FMT ")|: %g, norm: %g\n",i,j,(double)dot,(double)norm));
227         }
228       }
229     }
230     PetscCall(PetscPrintf(PETSC_COMM_SELF,"    max|(x_j^T*x_i) - delta_ji|: %g\n",(double)dot_max));
231 
232   case 1:
233     norm_max = 0.0;
234     for (i = il; i< iu; i++) {
235       PetscCall(MatMult(A, evec[i], vt1));
236       PetscCall(VecCopy(evec[i], vt2));
237       tmp  = -eval[i];
238       PetscCall(VecAXPY(vt1,tmp,vt2));
239       PetscCall(VecNorm(vt1, NORM_INFINITY, &norm));
240       norm = PetscAbsScalar(norm);
241       if (norm > norm_max) norm_max = norm;
242       /* sniff, and bark if necessary */
243       if (norm > tols[0]) {
244         PetscCall(PetscPrintf(PETSC_COMM_SELF,"  residual violation: %" PetscInt_FMT ", resi: %g\n",i, (double)norm));
245       }
246     }
247     PetscCall(PetscPrintf(PETSC_COMM_SELF,"    max_resi:                    %g\n", (double)norm_max));
248     break;
249   default:
250     PetscCall(PetscPrintf(PETSC_COMM_SELF,"Error: cklvl=%" PetscInt_FMT " is not supported \n",cklvl));
251   }
252   PetscCall(VecDestroy(&vt2));
253   PetscCall(VecDestroy(&vt1));
254   PetscFunctionReturn(0);
255 }
256 
257 /*TEST
258 
259    build:
260       requires: !complex
261 
262    test:
263       requires: datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES)
264       args: -f ${DATAFILESPATH}/matrices/small
265       output_file: output/ex116_1.out
266 
267    test:
268       suffix: 2
269       requires: datafilespath !complex double !defined(PETSC_USE_64BIT_INDICES)
270       args: -f ${DATAFILESPATH}/matrices/small -test_syev -check_symmetry
271 
272 TEST*/
273