GCC Code Coverage Report

Directory: ./
File: src/svd/interface/svddefault.c
Date: 2026-05-04 03:58:11
Exec Total Coverage
Lines: 76 89 85.4%
Functions: 7 7 100.0%
Branches: 194 434 44.7%
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 Simple default routines for common SVD operations
12 */
13
14 #include <slepc/private/svdimpl.h> /*I "slepcsvd.h" I*/
15
16 /*
17 SVDConvergedAbsolute - Checks convergence absolutely.
18 */
19 12077 PetscErrorCode SVDConvergedAbsolute(SVD svd,PetscReal sigma,PetscReal res,PetscReal *errest,void *ctx)
20 {
21
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 12077 PetscFunctionBegin;
22 12077 *errest = res;
23
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 12077 PetscFunctionReturn(PETSC_SUCCESS);
24 }
25
26 /*
27 SVDConvergedRelative - Checks convergence relative to the singular value.
28 */
29 29058 PetscErrorCode SVDConvergedRelative(SVD svd,PetscReal sigma,PetscReal res,PetscReal *errest,void *ctx)
30 {
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 29058 PetscFunctionBegin;
32
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 29058 *errest = (sigma!=0.0)? res/sigma: PETSC_MAX_REAL;
33
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 29058 PetscFunctionReturn(PETSC_SUCCESS);
34 }
35
36 /*
37 SVDConvergedNorm - Checks convergence relative to the matrix norms.
38 */
39 200 PetscErrorCode SVDConvergedNorm(SVD svd,PetscReal sigma,PetscReal res,PetscReal *errest,void *ctx)
40 {
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 200 PetscFunctionBegin;
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 200 *errest = res/PetscMax(svd->nrma,svd->nrmb);
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 200 PetscFunctionReturn(PETSC_SUCCESS);
44 }
45
46 /*
47 SVDConvergedMaxIt - Always returns Inf to force reaching the maximum number of iterations.
48 */
49 18 PetscErrorCode SVDConvergedMaxIt(SVD svd,PetscReal sigma,PetscReal res,PetscReal *errest,void *ctx)
50 {
51
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 18 PetscFunctionBegin;
52 18 *errest = PETSC_MAX_REAL;
53
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 18 PetscFunctionReturn(PETSC_SUCCESS);
54 }
55
56 /*@C
57 SVDStoppingBasic - Default routine to determine whether the outer singular value
58 solver iteration must be stopped.
59
60 Collective
61
62 Input Parameters:
63 + svd - the singular value solver context
64 . its - current number of iterations
65 . max_it - maximum number of iterations
66 . nconv - number of currently converged singular triplets
67 . nsv - number of requested singular triplets
68 - ctx - context (not used here)
69
70 Output Parameter:
71 . reason - result of the stopping test
72
73 Notes:
74 `SVDStoppingBasic()` will stop if all requested singular values are converged, or if
75 the maximum number of iterations has been reached.
76
77 This is the default stopping test.
78 Use `SVDSetStoppingTest()` to provide your own test instead of using this one.
79
80 Level: advanced
81
82 .seealso: [](ch:svd), `SVDSetStoppingTest()`, `SVDStoppingThreshold()`, `SVDConvergedReason`, `SVDGetConvergedReason()`
83 @*/
84 27625 PetscErrorCode SVDStoppingBasic(SVD svd,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nsv,SVDConvergedReason *reason,void *ctx)
85 {
86
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 27625 PetscFunctionBegin;
87 27625 *reason = SVD_CONVERGED_ITERATING;
88
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 27625 if (nconv >= nsv && svd->conv != SVD_CONV_MAXIT) {
89
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 1310 PetscCall(PetscInfo(svd,"Singular value solver finished successfully: %" PetscInt_FMT " singular triplets converged at iteration %" PetscInt_FMT "\n",nconv,its));
90 1310 *reason = SVD_CONVERGED_TOL;
91
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 26315 } else if (its >= max_it) {
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 18 if (svd->conv == SVD_CONV_MAXIT) *reason = SVD_CONVERGED_MAXIT;
93 else {
94 ✗ *reason = SVD_DIVERGED_ITS;
95 ✗ PetscCall(PetscInfo(svd,"Singular value solver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its));
96 }
97 }
98
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 5218 PetscFunctionReturn(PETSC_SUCCESS);
99 }
100
101 /*@C
102 SVDStoppingThreshold - Routine to determine whether the outer singular value
103 solver iteration must be stopped, according to some threshold for the computed values.
104
105 Collective
106
107 Input Parameters:
108 + svd - the singular value solver context
109 . its - current number of iterations
110 . max_it - maximum number of iterations
111 . nconv - number of currently converged singular triplets (ignored here)
112 . nsv - number of requested singular triplets (ignored here)
113 - ctx - context containing additional data (`SVDStoppingCtx`)
114
115 Output Parameter:
116 . reason - result of the stopping test
117
118 Notes:
119 `SVDStoppingThreshold()` will stop when one of the computed singular values is not
120 above/below the threshold given at `SVDSetThreshold()`. If a number of wanted singular
121 values has been specified via `SVDSetDimensions()` then it is also taken into account,
122 and the solver will stop when one of the two conditions (threshold or number of
123 converged values) is met.
124
125 Use `SVDSetStoppingTest()` to provide your own test instead of using this one.
126
127 Level: advanced
128
129 .seealso: [](ch:svd), `SVDSetStoppingTest()`, `SVDStoppingBasic()`, `SVDSetThreshold()`, `SVDSetDimensions()`, `SVDConvergedReason`, `SVDGetConvergedReason()`
130 @*/
131 962 PetscErrorCode SVDStoppingThreshold(SVD svd,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nsv,SVDConvergedReason *reason,void *ctx)
132 {
133 962 PetscReal thres,firstsv,firstnc,errest;
134 962 PetscBool rel;
135 962 PetscInt napprox;
136 962 SVDWhich which;
137
138
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 962 PetscFunctionBegin;
139 962 *reason = SVD_CONVERGED_ITERATING;
140 962 firstsv = ((SVDStoppingCtx)ctx)->firstsv;
141 962 firstnc = ((SVDStoppingCtx)ctx)->firstnc;
142 962 errest = ((SVDStoppingCtx)ctx)->errest;
143 962 thres = ((SVDStoppingCtx)ctx)->thres;
144 962 rel = ((SVDStoppingCtx)ctx)->threlative;
145 962 napprox = ((SVDStoppingCtx)ctx)->napprox;
146 962 which = ((SVDStoppingCtx)ctx)->which;
147
148
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 962 if (!nconv) { /* no converged singular values yet */
149
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 114 if (its >= max_it) {
150 ✗ if (svd->conv == SVD_CONV_MAXIT) *reason = SVD_CONVERGED_MAXIT;
151 else {
152 ✗ PetscCall(PetscInfo(svd,"Singular value solver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its));
153 ✗ *reason = SVD_DIVERGED_ITS;
154 }
155 }
156
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 114 PetscFunctionReturn(PETSC_SUCCESS);
157 }
158
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 848 if (nconv==napprox) { /* all approximations converged, very unusual */
159 ✗ PetscCall(PetscInfo(svd,"Singular value solver finished successfully: all available singular value approximations have converged\n"));
160 ✗ *reason = SVD_CONVERGED_TOL;
161 ✗ PetscFunctionReturn(PETSC_SUCCESS);
162 }
163
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 848 if ((which==SVD_LARGEST && ((rel && firstnc+errest<thres*firstsv) || (!rel && firstnc+errest<thres))) || (which==SVD_SMALLEST && firstnc-errest>thres)) {
164
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 124 if (its==((SVDStoppingCtx)ctx)->its+1) {
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 53 if (which==SVD_SMALLEST) PetscCall(PetscInfo(svd,"Singular value solver finished successfully: the approximation %g (minus error estimate %g) is above the threshold %g\n",(double)firstnc,(double)errest,(double)thres));
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 53 else if (!rel) PetscCall(PetscInfo(svd,"Singular value solver finished successfully: the approximation %g (plus error estimate %g) is below the threshold %g\n",(double)firstnc,(double)errest,(double)thres));
167
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 53 else PetscCall(PetscInfo(svd,"Singular value solver finished successfully: the ratio %g/%g is below the threshold %g\n",(double)(firstnc+errest),(double)firstsv,(double)thres));
168 53 *reason = SVD_CONVERGED_TOL;
169 71 } else ((SVDStoppingCtx)ctx)->its = its; /* wait until next iteration */
170
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 724 } else if (nsv && nconv >= nsv) {
171 ✗ PetscCall(PetscInfo(svd,"Singular value solver finished successfully: %" PetscInt_FMT " singular triplets converged at iteration %" PetscInt_FMT "\n",nconv,its));
172 ✗ *reason = SVD_CONVERGED_TOL;
173
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 724 } else if (its >= max_it) {
174 ✗ if (svd->conv == SVD_CONV_MAXIT) *reason = SVD_CONVERGED_MAXIT;
175 else {
176 ✗ PetscCall(PetscInfo(svd,"Singular value solver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its));
177 ✗ *reason = SVD_DIVERGED_ITS;
178 }
179 }
180
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 184 PetscFunctionReturn(PETSC_SUCCESS);
181 }
182
183 /*@
184 SVDSetWorkVecs - Sets a number of work vectors into an `SVD` object.
185
186 Collective
187
188 Input Parameters:
189 + svd - the singular value solver context
190 . nleft - number of work vectors of dimension equal to left singular vector
191 - nright - number of work vectors of dimension equal to right singular vector
192
193 Developer Note:
194 This is `SLEPC_EXTERN` because it may be required by user plugin `SVD`
195 implementations.
196
197 Level: developer
198
199 .seealso: [](ch:svd), `SVDSetUp()`
200 @*/
201 14997 PetscErrorCode SVDSetWorkVecs(SVD svd,PetscInt nleft,PetscInt nright)
202 {
203 14997 Vec t;
204
205
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 14997 PetscFunctionBegin;
206
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 14997 PetscValidHeaderSpecific(svd,SVD_CLASSID,1);
207
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 14997 PetscValidLogicalCollectiveInt(svd,nleft,2);
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 14997 PetscValidLogicalCollectiveInt(svd,nright,3);
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 14997 PetscCheck(nleft>=0,PetscObjectComm((PetscObject)svd),PETSC_ERR_ARG_OUTOFRANGE,"nleft must be >= 0: nleft = %" PetscInt_FMT,nleft);
210
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 14997 PetscCheck(nright>=0,PetscObjectComm((PetscObject)svd),PETSC_ERR_ARG_OUTOFRANGE,"nright must be >= 0: nright = %" PetscInt_FMT,nright);
211
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 14997 PetscCheck(nleft>0 || nright>0,PetscObjectComm((PetscObject)svd),PETSC_ERR_ARG_OUTOFRANGE,"nleft and nright cannot be both zero");
212
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 14997 if (svd->nworkl < nleft) {
213
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 2442 PetscCall(VecDestroyVecs(svd->nworkl,&svd->workl));
214 2442 svd->nworkl = nleft;
215
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 2442 if (svd->isgeneralized) PetscCall(SVDCreateLeftTemplate(svd,&t));
216
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 1591 else PetscCall(MatCreateVecsEmpty(svd->OP,NULL,&t));
217
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 2442 PetscCall(VecDuplicateVecs(t,nleft,&svd->workl));
218
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 2442 PetscCall(VecDestroy(&t));
219 }
220
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 14997 if (svd->nworkr < nright) {
221
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 2885 PetscCall(VecDestroyVecs(svd->nworkr,&svd->workr));
222 2885 svd->nworkr = nright;
223
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 2885 PetscCall(MatCreateVecsEmpty(svd->OP,&t,NULL));
224
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 2885 PetscCall(VecDuplicateVecs(t,nright,&svd->workr));
225
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 2885 PetscCall(VecDestroy(&t));
226 }
227
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 3182 PetscFunctionReturn(PETSC_SUCCESS);
228 }
229