GCC Code Coverage Report

Directory: ./
File: src/eps/interface/epsdefault.c
Date: 2026-02-22 03:58:10
Exec Total Coverage
Lines: 224 235 95.3%
Functions: 14 14 100.0%
Branches: 630 1066 59.1%
Line Branch Exec Source
1 /*
2 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3 SLEPc - Scalable Library for Eigenvalue Problem Computations
4 Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
5
6 This file is part of SLEPc.
7 SLEPc is distributed under a 2-clause BSD license (see LICENSE).
8 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
9 */
10 /*
11 This file contains some simple default routines for common operations
12 */
13
14 #include <slepc/private/epsimpl.h> /*I "slepceps.h" I*/
15 #include <slepcvec.h>
16
17 5766 PetscErrorCode EPSBackTransform_Default(EPS eps)
18 {
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 5766 PetscFunctionBegin;
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 5766 PetscCall(STBackTransform(eps->st,eps->nconv,eps->eigr,eps->eigi));
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 1368 PetscFunctionReturn(PETSC_SUCCESS);
22 }
23
24 /*
25 EPSComputeVectors_Hermitian - Copies the Lanczos vectors as eigenvectors
26 using purification for generalized eigenproblems.
27 */
28 2375 PetscErrorCode EPSComputeVectors_Hermitian(EPS eps)
29 {
30 2375 PetscBool iscayley,indef;
31 2375 Mat B,C;
32
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 2375 PetscFunctionBegin;
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 2375 if (eps->purify) {
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 507 PetscCall(EPS_Purify(eps,eps->nconv));
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 507 PetscCall(BVNormalize(eps->V,NULL));
37 } else {
38 /* In the case of Cayley transform, eigenvectors need to be B-normalized */
39
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 1868 PetscCall(PetscObjectTypeCompare((PetscObject)eps->st,STCAYLEY,&iscayley));
40
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 1868 if (iscayley && eps->isgeneralized) {
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 8 PetscCall(STGetMatrix(eps->st,1,&B));
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 8 PetscCall(BVGetMatrix(eps->V,&C,&indef));
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 8 PetscCheck(!indef,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_WRONGSTATE,"The inner product should not be indefinite");
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 8 PetscCall(BVSetMatrix(eps->V,B,PETSC_FALSE));
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 8 PetscCall(BVNormalize(eps->V,NULL));
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 8 PetscCall(BVSetMatrix(eps->V,C,PETSC_FALSE)); /* restore original matrix */
47 }
48 }
49
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 583 PetscFunctionReturn(PETSC_SUCCESS);
50 }
51
52 /*
53 EPSComputeVectors_Indefinite - similar to the Schur version but
54 for indefinite problems
55 */
56 104 PetscErrorCode EPSComputeVectors_Indefinite(EPS eps)
57 {
58 104 PetscInt n;
59 104 Mat X;
60
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 104 PetscFunctionBegin;
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 104 PetscCall(DSGetDimensions(eps->ds,&n,NULL,NULL,NULL));
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 104 PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
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 104 PetscCall(DSGetMat(eps->ds,DS_MAT_X,&X));
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 104 PetscCall(BVMultInPlace(eps->V,X,0,n));
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 104 PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&X));
67
68 /* purification */
69
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 104 if (eps->purify) PetscCall(EPS_Purify(eps,eps->nconv));
70
71 /* normalization */
72
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 104 PetscCall(BVNormalize(eps->V,eps->eigi));
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 29 PetscFunctionReturn(PETSC_SUCCESS);
74 }
75
76 /*
77 EPSComputeVectors_Twosided - Adjust left eigenvectors in generalized problems: y = B^-* y.
78 */
79 161 PetscErrorCode EPSComputeVectors_Twosided(EPS eps)
80 {
81 161 PetscInt i;
82 161 Vec w,y;
83
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 161 PetscFunctionBegin;
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 161 if (!eps->twosided || !eps->isgeneralized) PetscFunctionReturn(PETSC_SUCCESS);
86
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 34 PetscCall(EPSSetWorkVecs(eps,1));
87 34 w = eps->work[0];
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 204 for (i=0;i<eps->nconv;i++) {
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 170 PetscCall(BVCopyVec(eps->W,i,w));
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 170 PetscCall(BVGetColumn(eps->W,i,&y));
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 170 PetscCall(STMatSolveHermitianTranspose(eps->st,w,y));
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 170 PetscCall(BVRestoreColumn(eps->W,i,&y));
93 }
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 9 PetscFunctionReturn(PETSC_SUCCESS);
95 }
96
97 /*
98 EPSComputeVectors_Schur - Compute eigenvectors from the vectors
99 provided by the eigensolver. This version is intended for solvers
100 that provide Schur vectors. Given the partial Schur decomposition
101 OP*V=V*T, the following steps are performed:
102 1) compute eigenvectors of T: T*Z=Z*D
103 2) compute eigenvectors of OP: X=V*Z
104 */
105 2896 PetscErrorCode EPSComputeVectors_Schur(EPS eps)
106 {
107 2896 PetscInt i;
108 2896 Mat Z;
109 2896 Vec z;
110
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 2896 PetscFunctionBegin;
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 2896 if (eps->ishermitian) {
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 431 if (eps->isgeneralized && !eps->ispositive) PetscCall(EPSComputeVectors_Indefinite(eps));
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 431 else PetscCall(EPSComputeVectors_Hermitian(eps));
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 431 PetscFunctionReturn(PETSC_SUCCESS);
116 }
117
118 /* right eigenvectors */
119
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 2465 PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
120
121 /* V = V * Z */
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 2465 PetscCall(DSGetMat(eps->ds,DS_MAT_X,&Z));
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 2465 PetscCall(BVMultInPlace(eps->V,Z,0,eps->nconv));
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 2465 PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&Z));
125
126 /* Purify eigenvectors */
127
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 2465 if (eps->purify) PetscCall(EPS_Purify(eps,eps->nconv));
128
129 /* Fix eigenvectors if balancing was used */
130
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 2465 if (eps->balance!=EPS_BALANCE_NONE && eps->D) {
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 592 for (i=0;i<eps->nconv;i++) {
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 496 PetscCall(BVGetColumn(eps->V,i,&z));
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 496 PetscCall(VecPointwiseDivide(z,z,eps->D));
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 496 PetscCall(BVRestoreColumn(eps->V,i,&z));
135 }
136 }
137
138 /* normalize eigenvectors (when using purification or balancing) */
139
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 2465 if (eps->purify || (eps->balance!=EPS_BALANCE_NONE && eps->D)) PetscCall(BVNormalize(eps->V,eps->eigi));
140
141 /* left eigenvectors */
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 2465 if (eps->twosided) {
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 129 PetscCall(DSVectors(eps->ds,DS_MAT_Y,NULL,NULL));
144 /* W = W * Z */
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 129 PetscCall(DSGetMat(eps->ds,DS_MAT_Y,&Z));
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 129 PetscCall(BVMultInPlace(eps->W,Z,0,eps->nconv));
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 129 PetscCall(DSRestoreMat(eps->ds,DS_MAT_Y,&Z));
148 /* Fix left eigenvectors if balancing was used */
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 129 if (eps->balance!=EPS_BALANCE_NONE && eps->D) {
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 80 for (i=0;i<eps->nconv;i++) {
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 64 PetscCall(BVGetColumn(eps->W,i,&z));
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 64 PetscCall(VecPointwiseMult(z,z,eps->D));
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 64 PetscCall(BVRestoreColumn(eps->W,i,&z));
154 }
155 }
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 129 PetscCall(EPSComputeVectors_Twosided(eps));
157 /* normalize */
158
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 129 PetscCall(BVNormalize(eps->W,eps->eigi));
159 #if !defined(PETSC_USE_COMPLEX)
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 364 for (i=0;i<eps->nconv-1;i++) {
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 292 if (eps->eigi[i] != 0.0) {
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 20 if (eps->eigi[i] > 0.0) PetscCall(BVScaleColumn(eps->W,i+1,-1.0));
163 20 i++;
164 }
165 }
166 #endif
167 }
168
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 580 PetscFunctionReturn(PETSC_SUCCESS);
169 }
170
171 /*@
172 EPSSetWorkVecs - Sets a number of work vectors into an `EPS` object.
173
174 Collective
175
176 Input Parameters:
177 + eps - the linear eigensolver context
178 - nw - number of work vectors to allocate
179
180 Developer Note:
181 This is `SLEPC_EXTERN` because it may be required by user plugin `EPS`
182 implementations.
183
184 Level: developer
185
186 .seealso: [](ch:eps), `EPSSetUp()`
187 @*/
188 36246 PetscErrorCode EPSSetWorkVecs(EPS eps,PetscInt nw)
189 {
190 36246 Vec t;
191
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 36246 PetscFunctionBegin;
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 36246 PetscValidHeaderSpecific(eps,EPS_CLASSID,1);
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 36246 PetscValidLogicalCollectiveInt(eps,nw,2);
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 36246 PetscCheck(nw>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"nw must be > 0: nw = %" PetscInt_FMT,nw);
196
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 36246 if (eps->nwork < nw) {
197
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 6083 PetscCall(VecDestroyVecs(eps->nwork,&eps->work));
198 6083 eps->nwork = nw;
199
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 6083 PetscCall(BVGetColumn(eps->V,0,&t));
200
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 6083 PetscCall(VecDuplicateVecs(t,nw,&eps->work));
201
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 6083 PetscCall(BVRestoreColumn(eps->V,0,&t));
202 }
203
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 8940 PetscFunctionReturn(PETSC_SUCCESS);
204 }
205
206 /*
207 EPSSetWhichEigenpairs_Default - Sets the default value for which,
208 depending on the ST.
209 */
210 999 PetscErrorCode EPSSetWhichEigenpairs_Default(EPS eps)
211 {
212 999 PetscBool target;
213
214
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 999 PetscFunctionBegin;
215
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 999 PetscCall(PetscObjectTypeCompareAny((PetscObject)eps->st,&target,STSINVERT,STCAYLEY,""));
216
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 999 if (target) eps->which = EPS_TARGET_MAGNITUDE;
217 818 else eps->which = EPS_LARGEST_MAGNITUDE;
218
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 234 PetscFunctionReturn(PETSC_SUCCESS);
219 }
220
221 /*
222 EPSConvergedRelative - Checks convergence relative to the eigenvalue.
223 */
224 385702 PetscErrorCode EPSConvergedRelative(EPS eps,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
225 {
226 385702 PetscReal w;
227
228
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 385702 PetscFunctionBegin;
229 385702 w = SlepcAbsEigenvalue(eigr,eigi);
230
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 385702 *errest = (w!=0.0)? res/w: PETSC_MAX_REAL;
231
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 385702 PetscFunctionReturn(PETSC_SUCCESS);
232 }
233
234 /*
235 EPSConvergedAbsolute - Checks convergence absolutely.
236 */
237 27096 PetscErrorCode EPSConvergedAbsolute(EPS eps,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
238 {
239
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 27096 PetscFunctionBegin;
240 27096 *errest = res;
241
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 27096 PetscFunctionReturn(PETSC_SUCCESS);
242 }
243
244 /*
245 EPSConvergedNorm - Checks convergence relative to the eigenvalue and
246 the matrix norms.
247 */
248 43379 PetscErrorCode EPSConvergedNorm(EPS eps,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx)
249 {
250 43379 PetscReal w;
251
252
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 43379 PetscFunctionBegin;
253 43379 w = SlepcAbsEigenvalue(eigr,eigi);
254 43379 *errest = res / (eps->nrma + w*eps->nrmb);
255
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 43379 PetscFunctionReturn(PETSC_SUCCESS);
256 }
257
258 /*@C
259 EPSStoppingBasic - Default routine to determine whether the outer eigensolver
260 iteration must be stopped.
261
262 Collective
263
264 Input Parameters:
265 + eps - the linear eigensolver context
266 . its - current number of iterations
267 . max_it - maximum number of iterations
268 . nconv - number of currently converged eigenpairs
269 . nev - number of requested eigenpairs
270 - ctx - context (not used here)
271
272 Output Parameter:
273 . reason - result of the stopping test
274
275 Notes:
276 `EPSStoppingBasic()` will stop if all requested eigenvalues are converged, or if
277 the maximum number of iterations has been reached.
278
279 This is the default stopping test.
280 Use `EPSSetStoppingTest()` to provide your own test instead of using this one.
281
282 Level: advanced
283
284 .seealso: [](ch:eps), `EPSSetStoppingTest()`, `EPSStoppingThreshold()`, `EPSConvergedReason`, `EPSGetConvergedReason()`
285 @*/
286 349551 PetscErrorCode EPSStoppingBasic(EPS eps,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,EPSConvergedReason *reason,void *ctx)
287 {
288
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 349551 PetscFunctionBegin;
289 349551 *reason = EPS_CONVERGED_ITERATING;
290
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 349551 if (nconv >= nev) {
291
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 6768 PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: %" PetscInt_FMT " eigenpairs converged at iteration %" PetscInt_FMT "\n",nconv,its));
292 6768 *reason = EPS_CONVERGED_TOL;
293
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 342783 } else if (its >= max_it) {
294 104 *reason = EPS_DIVERGED_ITS;
295
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 104 PetscCall(PetscInfo(eps,"Linear eigensolver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its));
296 }
297
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 86771 PetscFunctionReturn(PETSC_SUCCESS);
298 }
299
300 /*@C
301 EPSStoppingThreshold - Routine to determine whether the outer eigenvalue solver
302 iteration must be stopped, according to some threshold for the computed values.
303
304 Collective
305
306 Input Parameters:
307 + eps - the linear eigensolver context
308 . its - current number of iterations
309 . max_it - maximum number of iterations
310 . nconv - number of currently converged eigenpairs (ignored here)
311 . nev - number of requested eigenpairs (ignored here)
312 - ctx - context containing additional data (`EPSStoppingCtx`)
313
314 Output Parameter:
315 . reason - result of the stopping test
316
317 Notes:
318 `EPSStoppingThreshold()` will stop when one of the computed eigenvalues is not
319 above/below the threshold given at `EPSSetThreshold()`. If a number of wanted
320 eigenvalues has been specified via `EPSSetDimensions()` then it is also taken into
321 account, and the solver will stop when one of the two conditions (threshold or
322 number of converged values) is met.
323
324 Use `EPSSetStoppingTest()` to provide your own test instead of using this one.
325
326 Level: advanced
327
328 .seealso: [](ch:eps), `EPSSetStoppingTest()`, `EPSStoppingBasic()`, `EPSSetThreshold()`, `EPSSetDimensions()`, `EPSConvergedReason`, `EPSGetConvergedReason()`
329 @*/
330 7189 PetscErrorCode EPSStoppingThreshold(EPS eps,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,EPSConvergedReason *reason,void *ctx)
331 {
332 7189 PetscReal thres,firstev,lastev;
333 7189 PetscBool magnit,rel;
334 7189 EPSWhich which;
335
336
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 7189 PetscFunctionBegin;
337 7189 *reason = EPS_CONVERGED_ITERATING;
338 7189 firstev = ((EPSStoppingCtx)ctx)->firstev;
339 7189 lastev = ((EPSStoppingCtx)ctx)->lastev;
340 7189 thres = ((EPSStoppingCtx)ctx)->thres;
341 7189 rel = ((EPSStoppingCtx)ctx)->threlative;
342 7189 which = ((EPSStoppingCtx)ctx)->which;
343 7189 magnit = (which==EPS_SMALLEST_MAGNITUDE || which==EPS_LARGEST_MAGNITUDE || which==EPS_TARGET_MAGNITUDE)? PETSC_TRUE: PETSC_FALSE;
344
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 7189 if (nconv && magnit && which==EPS_TARGET_MAGNITUDE && ((rel && ((thres>1.0 && lastev>thres*firstev) || (thres<1.0 && lastev<thres*firstev))) || (!rel && lastev>thres))) {
345
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 26 if (!rel) PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the eigenvalue magnitude %g is above the threshold %g\n",(double)lastev,(double)thres));
346
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 16 else if (thres>1.0) PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the ratio %g/%g is above the threshold %g\n",(double)lastev,(double)firstev,(double)thres));
347
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 8 else PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the ratio %g/%g is below the threshold %g\n",(double)lastev,(double)firstev,(double)thres));
348 26 *reason = EPS_CONVERGED_TOL;
349
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 7163 } else if (nconv && magnit && ((which==EPS_LARGEST_MAGNITUDE && ((rel && lastev<thres*firstev) || (!rel && lastev<thres))) || (which==EPS_SMALLEST_MAGNITUDE && lastev>thres))) {
350
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 92 if (which==EPS_SMALLEST_MAGNITUDE) PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the eigenvalue magnitude %g is above the threshold %g\n",(double)lastev,(double)thres));
351
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 36 else if (!rel) PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the eigenvalue magnitude %g is below the threshold %g\n",(double)lastev,(double)thres));
352
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 36 else PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: the ratio %g/%g is below the threshold %g\n",(double)lastev,(double)firstev,(double)thres));
353 92 *reason = EPS_CONVERGED_TOL;
354
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 7071 } else if (nconv && !magnit && ((which==EPS_LARGEST_REAL && lastev<thres) || (which==EPS_SMALLEST_REAL && lastev>thres))) {
355 ✗ if (which==EPS_LARGEST_REAL) PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: eigenvalue %g is below the threshold %g\n",(double)lastev,(double)thres));
356 ✗ else PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: eigenvalue %g is above the threshold %g\n",(double)lastev,(double)thres));
357 ✗ *reason = EPS_CONVERGED_TOL;
358
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 7071 } else if (nev && nconv >= nev) {
359
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 2 PetscCall(PetscInfo(eps,"Linear eigensolver finished successfully: %" PetscInt_FMT " eigenpairs converged at iteration %" PetscInt_FMT "\n",nconv,its));
360 2 *reason = EPS_CONVERGED_TOL;
361
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 7069 } else if (its >= max_it) {
362 ✗ *reason = EPS_DIVERGED_ITS;
363 ✗ PetscCall(PetscInfo(eps,"Linear eigensolver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its));
364 }
365
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 1805 PetscFunctionReturn(PETSC_SUCCESS);
366 }
367
368 /*
369 EPSComputeRitzVector - Computes the current Ritz vector.
370
371 Simple case (complex scalars or real scalars with Zi=NULL):
372 x = V*Zr (V is a basis of nv vectors, Zr has length nv)
373
374 Split case:
375 x = V*Zr y = V*Zi (Zr and Zi have length nv)
376 */
377 3388 PetscErrorCode EPSComputeRitzVector(EPS eps,PetscScalar *Zr,PetscScalar *Zi,BV V,Vec x,Vec y)
378 {
379 3388 PetscInt l,k;
380 3388 PetscReal norm;
381 #if !defined(PETSC_USE_COMPLEX)
382 1664 Vec z;
383 #endif
384
385
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 3388 PetscFunctionBegin;
386 /* compute eigenvector */
387
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 3388 PetscCall(BVGetActiveColumns(V,&l,&k));
388
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 3388 PetscCall(BVSetActiveColumns(V,0,k));
389
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 3388 PetscCall(BVMultVec(V,1.0,0.0,x,Zr));
390
391 /* purify eigenvector if necessary */
392
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 3388 if (eps->purify) {
393
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 212 PetscCall(STApply(eps->st,x,y));
394
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 212 if (eps->ishermitian) PetscCall(BVNormVec(eps->V,y,NORM_2,&norm));
395
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 116 else PetscCall(VecNorm(y,NORM_2,&norm));
396
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 212 PetscCall(VecScale(y,1.0/norm));
397
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 212 PetscCall(VecCopy(y,x));
398 }
399 /* fix eigenvector if balancing is used */
400
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 3388 if (!eps->ishermitian && eps->balance!=EPS_BALANCE_NONE && eps->D) PetscCall(VecPointwiseDivide(x,x,eps->D));
401 #if !defined(PETSC_USE_COMPLEX)
402 /* compute imaginary part of eigenvector */
403
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 1664 if (Zi) {
404
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 100 PetscCall(BVMultVec(V,1.0,0.0,y,Zi));
405
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 100 if (eps->ispositive) {
406 ✗ PetscCall(BVCreateVec(V,&z));
407 ✗ PetscCall(STApply(eps->st,y,z));
408 ✗ PetscCall(VecNorm(z,NORM_2,&norm));
409 ✗ PetscCall(VecScale(z,1.0/norm));
410 ✗ PetscCall(VecCopy(z,y));
411 ✗ PetscCall(VecDestroy(&z));
412 }
413
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 100 if (eps->balance!=EPS_BALANCE_NONE && eps->D) PetscCall(VecPointwiseDivide(y,y,eps->D));
414 } else
415 #endif
416
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 3288 PetscCall(VecSet(y,0.0));
417
418 /* normalize eigenvectors (when using balancing) */
419
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 3388 if (eps->balance!=EPS_BALANCE_NONE && eps->D) {
420 #if !defined(PETSC_USE_COMPLEX)
421
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 48 if (Zi) PetscCall(VecNormalizeComplex(x,y,PETSC_TRUE,NULL));
422 else
423 #endif
424
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 64 PetscCall(VecNormalize(x,NULL));
425 }
426
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 3388 PetscCall(BVSetActiveColumns(V,l,k));
427
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 803 PetscFunctionReturn(PETSC_SUCCESS);
428 }
429
430 /*
431 EPSBuildBalance_Krylov - uses a Krylov subspace method to compute the
432 diagonal matrix to be applied for balancing in non-Hermitian problems.
433 */
434 104 PetscErrorCode EPSBuildBalance_Krylov(EPS eps)
435 {
436 104 Vec z,p,r;
437 104 PetscInt i,j;
438 104 PetscReal norma;
439 104 PetscScalar *pz,*pD;
440 104 const PetscScalar *pr,*pp;
441 104 PetscRandom rand;
442
443
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 104 PetscFunctionBegin;
444
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 104 PetscCall(EPSSetWorkVecs(eps,3));
445
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 104 PetscCall(BVGetRandomContext(eps->V,&rand));
446 104 r = eps->work[0];
447 104 p = eps->work[1];
448 104 z = eps->work[2];
449
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 104 PetscCall(VecSet(eps->D,1.0));
450
451
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 624 for (j=0;j<eps->balance_its;j++) {
452
453 /* Build a random vector of +-1's */
454
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 520 PetscCall(VecSetRandom(z,rand));
455
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 520 PetscCall(VecGetArray(z,&pz));
456
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 40760 for (i=0;i<eps->nloc;i++) {
457
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 40240 if (PetscRealPart(pz[i])<0.5) pz[i]=-1.0;
458 19540 else pz[i]=1.0;
459 }
460
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 520 PetscCall(VecRestoreArray(z,&pz));
461
462 /* Compute p=DA(D\z) */
463
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 520 PetscCall(VecPointwiseDivide(r,z,eps->D));
464
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 520 PetscCall(STApply(eps->st,r,p));
465
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 520 PetscCall(VecPointwiseMult(p,p,eps->D));
466
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 520 if (eps->balance == EPS_BALANCE_TWOSIDE) {
467
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 320 if (j==0) {
468 /* Estimate the matrix inf-norm */
469
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 64 PetscCall(VecAbs(p));
470
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 64 PetscCall(VecMax(p,NULL,&norma));
471 }
472 /* Compute r=D\(A'Dz) */
473
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 320 PetscCall(VecPointwiseMult(z,z,eps->D));
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 320 PetscCall(STApplyHermitianTranspose(eps->st,z,r));
475
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 320 PetscCall(VecPointwiseDivide(r,r,eps->D));
476 }
477
478 /* Adjust values of D */
479
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 520 PetscCall(VecGetArrayRead(r,&pr));
480
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 520 PetscCall(VecGetArrayRead(p,&pp));
481
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 520 PetscCall(VecGetArray(eps->D,&pD));
482
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 40760 for (i=0;i<eps->nloc;i++) {
483
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 40240 if (eps->balance == EPS_BALANCE_TWOSIDE) {
484
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 23200 if (PetscAbsScalar(pp[i])>eps->balance_cutoff*norma && pr[i]!=0.0)
485 22592 pD[i] *= PetscSqrtReal(PetscAbsScalar(pr[i]/pp[i]));
486 } else {
487
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 17040 if (pp[i]!=0.0) pD[i] /= PetscAbsScalar(pp[i]);
488 }
489 }
490
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 520 PetscCall(VecRestoreArrayRead(r,&pr));
491
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 520 PetscCall(VecRestoreArrayRead(p,&pp));
492
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 520 PetscCall(VecRestoreArray(eps->D,&pD));
493 }
494
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 26 PetscFunctionReturn(PETSC_SUCCESS);
495 }
496