GCC Code Coverage Report

Directory: ./
File: src/pep/impls/linear/linear.c
Date: 2025-11-19 04:19:03
Exec Total Coverage
Lines: 614 644 95.3%
Functions: 28 29 96.6%
Branches: 1797 3097 58.0%
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 Explicit linearization for polynomial eigenproblems
12 */
13
14 #include <slepc/private/pepimpl.h> /*I "slepcpep.h" I*/
15 #include "linear.h"
16
17 9221 static PetscErrorCode MatMult_Linear_Shift(Mat M,Vec x,Vec y)
18 {
19 9221 PEP_LINEAR *ctx;
20 9221 PEP pep;
21 9221 const PetscScalar *px;
22 9221 PetscScalar *py,a,sigma=0.0;
23 9221 PetscInt nmat,deg,i,m;
24 9221 Vec x1,x2,x3,y1,aux;
25 9221 PetscReal *ca,*cb,*cg;
26 9221 PetscBool flg;
27
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 9221 PetscFunctionBegin;
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 9221 PetscCall(MatShellGetContext(M,&ctx));
30 9221 pep = ctx->pep;
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 9221 PetscCall(STGetTransform(pep->st,&flg));
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 9221 if (!flg) PetscCall(STGetShift(pep->st,&sigma));
33 9221 nmat = pep->nmat;
34 9221 deg = nmat-1;
35 9221 m = pep->nloc;
36 9221 ca = pep->pbc;
37 9221 cb = pep->pbc+nmat;
38 9221 cg = pep->pbc+2*nmat;
39 9221 x1=ctx->w[0];x2=ctx->w[1];x3=ctx->w[2];y1=ctx->w[3];aux=ctx->w[4];
40
41
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 9221 PetscCall(VecSet(y,0.0));
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 9221 PetscCall(VecGetArrayRead(x,&px));
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 9221 PetscCall(VecGetArray(y,&py));
44 9221 a = 1.0;
45
46 /* first block */
47
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 9221 PetscCall(VecPlaceArray(x2,px));
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 9221 PetscCall(VecPlaceArray(x3,px+m));
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 9221 PetscCall(VecPlaceArray(y1,py));
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 9221 PetscCall(VecAXPY(y1,cb[0]-sigma,x2));
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 9221 PetscCall(VecAXPY(y1,ca[0],x3));
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 9221 PetscCall(VecResetArray(x2));
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 9221 PetscCall(VecResetArray(x3));
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 9221 PetscCall(VecResetArray(y1));
55
56 /* inner blocks */
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 10171 for (i=1;i<deg-1;i++) {
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 950 PetscCall(VecPlaceArray(x1,px+(i-1)*m));
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 950 PetscCall(VecPlaceArray(x2,px+i*m));
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 950 PetscCall(VecPlaceArray(x3,px+(i+1)*m));
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 950 PetscCall(VecPlaceArray(y1,py+i*m));
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 950 PetscCall(VecAXPY(y1,cg[i],x1));
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 950 PetscCall(VecAXPY(y1,cb[i]-sigma,x2));
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 950 PetscCall(VecAXPY(y1,ca[i],x3));
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 950 PetscCall(VecResetArray(x1));
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 950 PetscCall(VecResetArray(x2));
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 950 PetscCall(VecResetArray(x3));
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 950 PetscCall(VecResetArray(y1));
69 }
70
71 /* last block */
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 9221 PetscCall(VecPlaceArray(y1,py+(deg-1)*m));
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 28613 for (i=0;i<deg;i++) {
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 19392 PetscCall(VecPlaceArray(x1,px+i*m));
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 19392 PetscCall(STMatMult(pep->st,i,x1,aux));
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 19392 PetscCall(VecAXPY(y1,a,aux));
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 19392 PetscCall(VecResetArray(x1));
78 19392 a *= pep->sfactor;
79 }
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 9221 PetscCall(VecCopy(y1,aux));
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 9221 PetscCall(STMatSolve(pep->st,aux,y1));
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 9221 PetscCall(VecScale(y1,-ca[deg-1]/a));
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 9221 PetscCall(VecPlaceArray(x1,px+(deg-2)*m));
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 9221 PetscCall(VecPlaceArray(x2,px+(deg-1)*m));
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 9221 PetscCall(VecAXPY(y1,cg[deg-1],x1));
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 9221 PetscCall(VecAXPY(y1,cb[deg-1]-sigma,x2));
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 9221 PetscCall(VecResetArray(x1));
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 9221 PetscCall(VecResetArray(x2));
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 9221 PetscCall(VecResetArray(y1));
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 9221 PetscCall(VecRestoreArrayRead(x,&px));
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 9221 PetscCall(VecRestoreArray(y,&py));
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 1799 PetscFunctionReturn(PETSC_SUCCESS);
94 }
95
96 13220 static PetscErrorCode MatMult_Linear_Sinvert(Mat M,Vec x,Vec y)
97 {
98 13220 PEP_LINEAR *ctx;
99 13220 PEP pep;
100 13220 const PetscScalar *px;
101 13220 PetscScalar *py,a,sigma,t=1.0,tp=0.0,tt;
102 13220 PetscInt nmat,deg,i,m;
103 13220 Vec x1,y1,y2,y3,aux,aux2;
104 13220 PetscReal *ca,*cb,*cg;
105
106
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 13220 PetscFunctionBegin;
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 13220 PetscCall(MatShellGetContext(M,&ctx));
108 13220 pep = ctx->pep;
109 13220 nmat = pep->nmat;
110 13220 deg = nmat-1;
111 13220 m = pep->nloc;
112 13220 ca = pep->pbc;
113 13220 cb = pep->pbc+nmat;
114 13220 cg = pep->pbc+2*nmat;
115 13220 x1=ctx->w[0];y1=ctx->w[1];y2=ctx->w[2];y3=ctx->w[3];aux=ctx->w[4];aux2=ctx->w[5];
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 13220 PetscCall(EPSGetTarget(ctx->eps,&sigma));
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 13220 PetscCall(VecSet(y,0.0));
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 13220 PetscCall(VecGetArrayRead(x,&px));
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 13220 PetscCall(VecGetArray(y,&py));
120 13220 a = pep->sfactor;
121
122 /* first block */
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 13220 PetscCall(VecPlaceArray(x1,px));
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 13220 PetscCall(VecPlaceArray(y1,py+m));
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 13220 PetscCall(VecCopy(x1,y1));
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 13220 PetscCall(VecScale(y1,1.0/ca[0]));
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 13220 PetscCall(VecResetArray(x1));
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 13220 PetscCall(VecResetArray(y1));
129
130 /* second block */
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 13220 if (deg>2) {
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 4745 PetscCall(VecPlaceArray(x1,px+m));
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 4745 PetscCall(VecPlaceArray(y1,py+m));
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 4745 PetscCall(VecPlaceArray(y2,py+2*m));
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 4745 PetscCall(VecCopy(x1,y2));
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 4745 PetscCall(VecAXPY(y2,sigma-cb[1],y1));
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 4745 PetscCall(VecScale(y2,1.0/ca[1]));
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 4745 PetscCall(VecResetArray(x1));
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 4745 PetscCall(VecResetArray(y1));
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 4745 PetscCall(VecResetArray(y2));
141 }
142
143 /* inner blocks */
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 17965 for (i=2;i<deg-1;i++) {
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 4745 PetscCall(VecPlaceArray(x1,px+i*m));
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 4745 PetscCall(VecPlaceArray(y1,py+(i-1)*m));
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 4745 PetscCall(VecPlaceArray(y2,py+i*m));
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 4745 PetscCall(VecPlaceArray(y3,py+(i+1)*m));
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 4745 PetscCall(VecCopy(x1,y3));
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 4745 PetscCall(VecAXPY(y3,sigma-cb[i],y2));
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 4745 PetscCall(VecAXPY(y3,-cg[i],y1));
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 4745 PetscCall(VecScale(y3,1.0/ca[i]));
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 4745 PetscCall(VecResetArray(x1));
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 4745 PetscCall(VecResetArray(y1));
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 4745 PetscCall(VecResetArray(y2));
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 4745 PetscCall(VecResetArray(y3));
157 }
158
159 /* last block */
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 13220 PetscCall(VecPlaceArray(y1,py));
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 22710 for (i=0;i<deg-2;i++) {
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 9490 PetscCall(VecPlaceArray(y2,py+(i+1)*m));
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 9490 PetscCall(STMatMult(pep->st,i+1,y2,aux));
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 9490 PetscCall(VecAXPY(y1,a,aux));
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 9490 PetscCall(VecResetArray(y2));
166 9490 a *= pep->sfactor;
167 }
168 13220 i = deg-2;
169
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 13220 PetscCall(VecPlaceArray(y2,py+(i+1)*m));
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 13220 PetscCall(VecPlaceArray(y3,py+i*m));
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 13220 PetscCall(VecCopy(y2,aux2));
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 13220 PetscCall(VecAXPY(aux2,cg[i+1]/ca[i+1],y3));
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 13220 PetscCall(STMatMult(pep->st,i+1,aux2,aux));
174
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 13220 PetscCall(VecAXPY(y1,a,aux));
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 13220 PetscCall(VecResetArray(y2));
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 13220 PetscCall(VecResetArray(y3));
177 13220 a *= pep->sfactor;
178 13220 i = deg-1;
179
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 13220 PetscCall(VecPlaceArray(x1,px+i*m));
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 13220 PetscCall(VecPlaceArray(y3,py+i*m));
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 13220 PetscCall(VecCopy(x1,aux2));
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 13220 PetscCall(VecAXPY(aux2,sigma-cb[i],y3));
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 13220 PetscCall(VecScale(aux2,1.0/ca[i]));
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 13220 PetscCall(STMatMult(pep->st,i+1,aux2,aux));
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 13220 PetscCall(VecAXPY(y1,a,aux));
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 13220 PetscCall(VecResetArray(x1));
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 13220 PetscCall(VecResetArray(y3));
188
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 13220 PetscCall(VecCopy(y1,aux));
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 13220 PetscCall(STMatSolve(pep->st,aux,y1));
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 13220 PetscCall(VecScale(y1,-1.0));
192
193 /* final update */
194
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 35930 for (i=1;i<deg;i++) {
195
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 22710 PetscCall(VecPlaceArray(y2,py+i*m));
196 22710 tt = t;
197 22710 t = ((sigma-cb[i-1])*t-cg[i-1]*tp)/ca[i-1]; /* i-th basis polynomial */
198 22710 tp = tt;
199
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 22710 PetscCall(VecAXPY(y2,t,y1));
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 22710 PetscCall(VecResetArray(y2));
201 }
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 13220 PetscCall(VecResetArray(y1));
203
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 13220 PetscCall(VecRestoreArrayRead(x,&px));
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 13220 PetscCall(VecRestoreArray(y,&py));
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 2644 PetscFunctionReturn(PETSC_SUCCESS);
207 }
208
209 303329 static PetscErrorCode BackTransform_Linear(ST st,PetscInt n,PetscScalar *eigr,PetscScalar *eigi)
210 {
211 303329 PEP_LINEAR *ctx;
212 303329 ST stctx;
213
214
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 303329 PetscFunctionBegin;
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 303329 PetscCall(STShellGetContext(st,&ctx));
216
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 303329 PetscCall(PEPGetST(ctx->pep,&stctx));
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 303329 PetscCall(STBackTransform(stctx,n,eigr,eigi));
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 60029 PetscFunctionReturn(PETSC_SUCCESS);
219 }
220
221 /*
222 Dummy backtransform operation
223 */
224 1090 static PetscErrorCode BackTransform_Skip(ST st,PetscInt n,PetscScalar *eigr,PetscScalar *eigi)
225 {
226
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 1090 PetscFunctionBegin;
227
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 1090 PetscFunctionReturn(PETSC_SUCCESS);
228 }
229
230 22441 static PetscErrorCode Apply_Linear(ST st,Vec x,Vec y)
231 {
232 22441 PEP_LINEAR *ctx;
233
234
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 22441 PetscFunctionBegin;
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 22441 PetscCall(STShellGetContext(st,&ctx));
236
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 22441 PetscCall(MatMult(ctx->A,x,y));
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 4443 PetscFunctionReturn(PETSC_SUCCESS);
238 }
239
240 413 static PetscErrorCode PEPSetUp_Linear(PEP pep)
241 {
242 413 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
243 413 ST st;
244 413 PetscInt i=0,deg=pep->nmat-1;
245 413 EPSWhich which = EPS_LARGEST_MAGNITUDE;
246 413 EPSProblemType ptype;
247 413 PetscBool trackall,istrivial,transf,sinv,ks;
248 413 PetscScalar sigma,*epsarray,*peparray;
249 413 Vec veps,w=NULL;
250 /* function tables */
251 413 PetscErrorCode (*fcreate[][2])(MPI_Comm,PEP_LINEAR*,Mat*) = {
252 { MatCreateExplicit_Linear_NA, MatCreateExplicit_Linear_NB },
253 { MatCreateExplicit_Linear_SA, MatCreateExplicit_Linear_SB },
254 { MatCreateExplicit_Linear_HA, MatCreateExplicit_Linear_HB },
255 };
256
257
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 413 PetscFunctionBegin;
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 413 PEPCheckShiftSinvert(pep);
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 413 PEPCheckUnsupported(pep,PEP_FEATURE_STOPPING);
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 413 PEPCheckIgnored(pep,PEP_FEATURE_CONVERGENCE);
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 413 PetscCall(STGetTransform(pep->st,&transf));
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 413 PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv));
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 413 if (!pep->which) PetscCall(PEPSetWhichEigenpairs_Default(pep));
264
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 413 PetscCheck(pep->which!=PEP_ALL,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"This solver does not support computing all eigenvalues");
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 413 PetscCall(STSetUp(pep->st));
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 413 if (!ctx->eps) PetscCall(PEPLinearGetEPS(pep,&ctx->eps));
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 413 PetscCall(EPSGetST(ctx->eps,&st));
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 413 if (!transf && !ctx->usereps) PetscCall(EPSSetTarget(ctx->eps,pep->target));
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 413 if (sinv && !transf && !ctx->usereps) PetscCall(STSetDefaultShift(st,pep->target));
270 /* compute scale factor if not set by user */
271
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 413 PetscCall(PEPComputeScaleFactor(pep));
272
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 413 if (ctx->explicitmatrix) {
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 174 PEPCheckQuadraticCondition(pep,PETSC_TRUE," (with explicit matrix)");
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 174 PEPCheckUnsupportedCondition(pep,PEP_FEATURE_NONMONOMIAL,PETSC_TRUE," (with explicit matrix)");
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 174 PetscCheck(!transf,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Explicit matrix option is not implemented with st-transform flag active");
277
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 174 PetscCheck(pep->scale!=PEP_SCALE_DIAGONAL && pep->scale!=PEP_SCALE_BOTH,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Diagonal scaling not allowed in PEPLINEAR with explicit matrices");
278
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 174 if (sinv && !transf) PetscCall(STSetType(st,STSINVERT));
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 174 PetscCall(RGPushScale(pep->rg,1.0/pep->sfactor));
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 174 PetscCall(STGetMatrixTransformed(pep->st,0,&ctx->K));
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 174 PetscCall(STGetMatrixTransformed(pep->st,1,&ctx->C));
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 174 PetscCall(STGetMatrixTransformed(pep->st,2,&ctx->M));
283 174 ctx->sfactor = pep->sfactor;
284 174 ctx->dsfactor = pep->dsfactor;
285
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 174 PetscCall(MatDestroy(&ctx->A));
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 174 PetscCall(MatDestroy(&ctx->B));
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 174 PetscCall(VecDestroy(&ctx->w[0]));
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 174 PetscCall(VecDestroy(&ctx->w[1]));
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 174 PetscCall(VecDestroy(&ctx->w[2]));
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 174 PetscCall(VecDestroy(&ctx->w[3]));
292
293
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 174 switch (pep->problem_type) {
294 case PEP_GENERAL: i = 0; break;
295 50 case PEP_HERMITIAN:
296 50 case PEP_HYPERBOLIC: i = 1; break;
297 30 case PEP_GYROSCOPIC: i = 2; break;
298 }
299
300
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 174 PetscCall((*fcreate[i][0])(PetscObjectComm((PetscObject)pep),ctx,&ctx->A));
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 174 PetscCall((*fcreate[i][1])(PetscObjectComm((PetscObject)pep),ctx,&ctx->B));
302
303 } else { /* implicit matrix */
304
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 239 PetscCheck(pep->problem_type==PEP_GENERAL,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Must use the explicit matrix option if problem type is not general");
305
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 239 if (!((PetscObject)ctx->eps)->type_name) PetscCall(EPSSetType(ctx->eps,EPSKRYLOVSCHUR));
306 else {
307
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 229 PetscCall(PetscObjectTypeCompare((PetscObject)ctx->eps,EPSKRYLOVSCHUR,&ks));
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 229 PetscCheck(ks,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Implicit matrix option only implemented for Krylov-Schur");
309 }
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 239 PetscCheck(ctx->alpha==1.0 && ctx->beta==0.0,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Implicit matrix option does not support setting alpha,beta parameters of the linearization");
311
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 239 PetscCall(STSetType(st,STSHELL));
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 239 PetscCall(STShellSetContext(st,ctx));
313
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 239 if (!transf) PetscCall(STShellSetBackTransform(st,BackTransform_Linear));
314
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 10 else PetscCall(STShellSetBackTransform(st,BackTransform_Skip));
315
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 239 PetscCall(MatCreateVecsEmpty(pep->A[0],&ctx->w[0],&ctx->w[1]));
316
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 239 PetscCall(MatCreateVecsEmpty(pep->A[0],&ctx->w[2],&ctx->w[3]));
317
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 239 PetscCall(MatCreateVecs(pep->A[0],&ctx->w[4],&ctx->w[5]));
318
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 239 PetscCall(MatCreateShell(PetscObjectComm((PetscObject)pep),deg*pep->nloc,deg*pep->nloc,deg*pep->n,deg*pep->n,ctx,&ctx->A));
319
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 239 if (sinv && !transf) PetscCall(MatShellSetOperation(ctx->A,MATOP_MULT,(PetscErrorCodeFn*)MatMult_Linear_Sinvert));
320
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 134 else PetscCall(MatShellSetOperation(ctx->A,MATOP_MULT,(PetscErrorCodeFn*)MatMult_Linear_Shift));
321
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 239 PetscCall(STShellSetApply(st,Apply_Linear));
322 239 ctx->pep = pep;
323
324
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 239 PetscCall(PEPBasisCoefficients(pep,pep->pbc));
325
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 239 if (!transf) {
326
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 229 PetscCall(PetscMalloc1(pep->nmat,&pep->solvematcoeffs));
327
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 229 if (sinv) PetscCall(PEPEvaluateBasis(pep,pep->target,0,pep->solvematcoeffs,NULL));
328 else {
329
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 392 for (i=0;i<deg;i++) pep->solvematcoeffs[i] = 0.0;
330 124 pep->solvematcoeffs[deg] = 1.0;
331 }
332
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 229 PetscCall(STScaleShift(pep->st,1.0/pep->sfactor));
333
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 229 PetscCall(RGPushScale(pep->rg,1.0/pep->sfactor));
334 }
335
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 239 if (pep->sfactor!=1.0) {
336
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 20 for (i=0;i<pep->nmat;i++) {
337 15 pep->pbc[pep->nmat+i] /= pep->sfactor;
338 15 pep->pbc[2*pep->nmat+i] /= pep->sfactor*pep->sfactor;
339 }
340 }
341 }
342
343
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 413 PetscCall(EPSSetOperators(ctx->eps,ctx->A,ctx->B));
344
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 413 PetscCall(EPSGetProblemType(ctx->eps,&ptype));
345
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 413 if (!ptype) {
346
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 393 if (ctx->explicitmatrix) PetscCall(EPSSetProblemType(ctx->eps,EPS_GNHEP));
347
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 229 else PetscCall(EPSSetProblemType(ctx->eps,EPS_NHEP));
348 }
349
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 413 if (!ctx->usereps) {
350
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 403 if (transf) which = EPS_LARGEST_MAGNITUDE;
351 else {
352
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 393 switch (pep->which) {
353 case PEP_LARGEST_MAGNITUDE: which = EPS_LARGEST_MAGNITUDE; break;
354 ✗ case PEP_SMALLEST_MAGNITUDE: which = EPS_SMALLEST_MAGNITUDE; break;
355 ✗ case PEP_LARGEST_REAL: which = EPS_LARGEST_REAL; break;
356 ✗ case PEP_SMALLEST_REAL: which = EPS_SMALLEST_REAL; break;
357 ✗ case PEP_LARGEST_IMAGINARY: which = EPS_LARGEST_IMAGINARY; break;
358 ✗ case PEP_SMALLEST_IMAGINARY: which = EPS_SMALLEST_IMAGINARY; break;
359 165 case PEP_TARGET_MAGNITUDE: which = EPS_TARGET_MAGNITUDE; break;
360 ✗ case PEP_TARGET_REAL: which = EPS_TARGET_REAL; break;
361 ✗ case PEP_TARGET_IMAGINARY: which = EPS_TARGET_IMAGINARY; break;
362 ✗ case PEP_ALL: which = EPS_ALL; break;
363 5 case PEP_WHICH_USER: which = EPS_WHICH_USER;
364
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 5 PetscCall(EPSSetEigenvalueComparison(ctx->eps,pep->sc->comparison,pep->sc->comparisonctx));
365 break;
366 }
367 80 }
368
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 403 PetscCall(EPSSetWhichEigenpairs(ctx->eps,which));
369
370
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 403 PetscCall(EPSSetDimensions(ctx->eps,pep->nev,pep->ncv,pep->mpd));
371
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 588 PetscCall(EPSSetTolerances(ctx->eps,SlepcDefaultTol(pep->tol),pep->max_it));
372 }
373
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 413 PetscCall(RGIsTrivial(pep->rg,&istrivial));
374
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 413 if (!istrivial) {
375
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 10 PetscCheck(!transf,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"PEPLINEAR does not support a nontrivial region with st-transform");
376
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 10 PetscCall(EPSSetRG(ctx->eps,pep->rg));
377 }
378 /* Transfer the trackall option from pep to eps */
379
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 413 PetscCall(PEPGetTrackAll(pep,&trackall));
380
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 413 PetscCall(EPSSetTrackAll(ctx->eps,trackall));
381
382 /* temporary change of target */
383
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 413 if (pep->sfactor!=1.0) {
384
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 15 PetscCall(EPSGetTarget(ctx->eps,&sigma));
385
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 15 PetscCall(EPSSetTarget(ctx->eps,sigma/pep->sfactor));
386 }
387
388 /* process initial vector */
389
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 413 if (pep->nini<0) {
390
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 28 PetscCall(VecCreateMPI(PetscObjectComm((PetscObject)ctx->eps),deg*pep->nloc,deg*pep->n,&veps));
391
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 28 PetscCall(VecGetArray(veps,&epsarray));
392
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 84 for (i=0;i<deg;i++) {
393
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 56 if (i<-pep->nini) {
394
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 56 PetscCall(VecGetArray(pep->IS[i],&peparray));
395
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 56 PetscCall(PetscArraycpy(epsarray+i*pep->nloc,peparray,pep->nloc));
396
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 56 PetscCall(VecRestoreArray(pep->IS[i],&peparray));
397 } else {
398 ✗ if (!w) PetscCall(VecDuplicate(pep->IS[0],&w));
399 ✗ PetscCall(VecSetRandom(w,NULL));
400 ✗ PetscCall(VecGetArray(w,&peparray));
401 ✗ PetscCall(PetscArraycpy(epsarray+i*pep->nloc,peparray,pep->nloc));
402
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 56 PetscCall(VecRestoreArray(w,&peparray));
403 }
404 }
405
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 28 PetscCall(VecRestoreArray(veps,&epsarray));
406
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 28 PetscCall(EPSSetInitialSpace(ctx->eps,1,&veps));
407
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 28 PetscCall(VecDestroy(&veps));
408
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 28 PetscCall(VecDestroy(&w));
409
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 28 PetscCall(SlepcBasisDestroy_Private(&pep->nini,&pep->IS));
410 }
411
412
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 413 PetscCall(EPSSetUp(ctx->eps));
413
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 413 PetscCall(EPSGetDimensions(ctx->eps,NULL,&pep->ncv,&pep->mpd));
414
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 413 PetscCall(EPSGetTolerances(ctx->eps,NULL,&pep->max_it));
415
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 413 PetscCall(PEPAllocateSolution(pep,0));
416
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 81 PetscFunctionReturn(PETSC_SUCCESS);
417 }
418
419 /*
420 PEPLinearExtract_Residual - Auxiliary routine that copies the solution of the
421 linear eigenproblem to the PEP object. The eigenvector of the generalized
422 problem is supposed to be
423 z = [ x ]
424 [ l*x ]
425 The eigenvector is taken from z(1:n) or z(n+1:2*n) depending on the explicitly
426 computed residual norm.
427 Finally, x is normalized so that ||x||_2 = 1.
428 */
429 20 static PetscErrorCode PEPLinearExtract_Residual(PEP pep,EPS eps)
430 {
431 20 PetscInt i,k;
432 20 const PetscScalar *px;
433 20 PetscScalar *er=pep->eigr,*ei=pep->eigi;
434 20 PetscReal rn1,rn2;
435 20 Vec xr,xi=NULL,wr;
436 20 Mat A;
437 #if !defined(PETSC_USE_COMPLEX)
438 10 Vec wi;
439 10 const PetscScalar *py;
440 #endif
441
442
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 20 PetscFunctionBegin;
443 #if defined(PETSC_USE_COMPLEX)
444
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 10 PetscCall(PEPSetWorkVecs(pep,2));
445 #else
446
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 10 PetscCall(PEPSetWorkVecs(pep,4));
447 #endif
448
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 20 PetscCall(EPSGetOperators(eps,&A,NULL));
449
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 20 PetscCall(MatCreateVecs(A,&xr,NULL));
450
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 20 PetscCall(MatCreateVecsEmpty(pep->A[0],&wr,NULL));
451 #if !defined(PETSC_USE_COMPLEX)
452
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 10 PetscCall(VecDuplicate(xr,&xi));
453
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 10 PetscCall(VecDuplicateEmpty(wr,&wi));
454 #endif
455
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 185 for (i=0;i<pep->nconv;i++) {
456
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 165 PetscCall(EPSGetEigenpair(eps,i,NULL,NULL,xr,xi));
457 #if !defined(PETSC_USE_COMPLEX)
458
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 80 if (ei[i]!=0.0) { /* complex conjugate pair */
459
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 10 PetscCall(VecGetArrayRead(xr,&px));
460
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 10 PetscCall(VecGetArrayRead(xi,&py));
461
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 10 PetscCall(VecPlaceArray(wr,px));
462
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 10 PetscCall(VecPlaceArray(wi,py));
463
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 10 PetscCall(VecNormalizeComplex(wr,wi,PETSC_TRUE,NULL));
464
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 10 PetscCall(PEPComputeResidualNorm_Private(pep,er[i],ei[i],wr,wi,pep->work,&rn1));
465
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 10 PetscCall(BVInsertVec(pep->V,i,wr));
466
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 10 PetscCall(BVInsertVec(pep->V,i+1,wi));
467
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 20 for (k=1;k<pep->nmat-1;k++) {
468
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 10 PetscCall(VecResetArray(wr));
469
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 10 PetscCall(VecResetArray(wi));
470
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 10 PetscCall(VecPlaceArray(wr,px+k*pep->nloc));
471
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 10 PetscCall(VecPlaceArray(wi,py+k*pep->nloc));
472
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 10 PetscCall(VecNormalizeComplex(wr,wi,PETSC_TRUE,NULL));
473
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 10 PetscCall(PEPComputeResidualNorm_Private(pep,er[i],ei[i],wr,wi,pep->work,&rn2));
474
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 10 if (rn1>rn2) {
475 ✗ PetscCall(BVInsertVec(pep->V,i,wr));
476 ✗ PetscCall(BVInsertVec(pep->V,i+1,wi));
477 ✗ rn1 = rn2;
478 }
479 }
480
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 10 PetscCall(VecResetArray(wr));
481
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 10 PetscCall(VecResetArray(wi));
482
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 10 PetscCall(VecRestoreArrayRead(xr,&px));
483
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 10 PetscCall(VecRestoreArrayRead(xi,&py));
484 i++;
485 } else /* real eigenvalue */
486 #endif
487 {
488
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 155 PetscCall(VecGetArrayRead(xr,&px));
489
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 155 PetscCall(VecPlaceArray(wr,px));
490
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 155 PetscCall(VecNormalizeComplex(wr,NULL,PETSC_FALSE,NULL));
491
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 155 PetscCall(PEPComputeResidualNorm_Private(pep,er[i],ei[i],wr,NULL,pep->work,&rn1));
492
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 155 PetscCall(BVInsertVec(pep->V,i,wr));
493
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 310 for (k=1;k<pep->nmat-1;k++) {
494
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 155 PetscCall(VecResetArray(wr));
495
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 155 PetscCall(VecPlaceArray(wr,px+k*pep->nloc));
496
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 155 PetscCall(VecNormalizeComplex(wr,NULL,PETSC_FALSE,NULL));
497
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 155 PetscCall(PEPComputeResidualNorm_Private(pep,er[i],ei[i],wr,NULL,pep->work,&rn2));
498
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 155 if (rn1>rn2) {
499
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 135 PetscCall(BVInsertVec(pep->V,i,wr));
500 135 rn1 = rn2;
501 }
502 }
503
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 155 PetscCall(VecResetArray(wr));
504
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 165 PetscCall(VecRestoreArrayRead(xr,&px));
505 }
506 }
507
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 20 PetscCall(VecDestroy(&wr));
508
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 20 PetscCall(VecDestroy(&xr));
509 #if !defined(PETSC_USE_COMPLEX)
510
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 10 PetscCall(VecDestroy(&wi));
511
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 10 PetscCall(VecDestroy(&xi));
512 #endif
513
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 4 PetscFunctionReturn(PETSC_SUCCESS);
514 }
515
516 /*
517 PEPLinearExtract_None - Same as PEPLinearExtract_Norm but always takes
518 the first block.
519 */
520 20 static PetscErrorCode PEPLinearExtract_None(PEP pep,EPS eps)
521 {
522 20 PetscInt i;
523 20 const PetscScalar *px;
524 20 Mat A;
525 20 Vec xr,xi=NULL,w;
526 #if !defined(PETSC_USE_COMPLEX)
527 10 PetscScalar *ei=pep->eigi;
528 #endif
529
530
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 20 PetscFunctionBegin;
531
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 20 PetscCall(EPSGetOperators(eps,&A,NULL));
532
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 20 PetscCall(MatCreateVecs(A,&xr,NULL));
533 #if !defined(PETSC_USE_COMPLEX)
534
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 10 PetscCall(VecDuplicate(xr,&xi));
535 #endif
536
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 20 PetscCall(MatCreateVecsEmpty(pep->A[0],&w,NULL));
537
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 185 for (i=0;i<pep->nconv;i++) {
538
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 165 PetscCall(EPSGetEigenvector(eps,i,xr,xi));
539 #if !defined(PETSC_USE_COMPLEX)
540
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 80 if (ei[i]!=0.0) { /* complex conjugate pair */
541
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 10 PetscCall(VecGetArrayRead(xr,&px));
542
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 10 PetscCall(VecPlaceArray(w,px));
543
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 10 PetscCall(BVInsertVec(pep->V,i,w));
544
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 10 PetscCall(VecResetArray(w));
545
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 10 PetscCall(VecRestoreArrayRead(xr,&px));
546
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 10 PetscCall(VecGetArrayRead(xi,&px));
547
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 10 PetscCall(VecPlaceArray(w,px));
548
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 10 PetscCall(BVInsertVec(pep->V,i+1,w));
549
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 10 PetscCall(VecResetArray(w));
550
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 10 PetscCall(VecRestoreArrayRead(xi,&px));
551 i++;
552 } else /* real eigenvalue */
553 #endif
554 {
555
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 155 PetscCall(VecGetArrayRead(xr,&px));
556
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 155 PetscCall(VecPlaceArray(w,px));
557
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 155 PetscCall(BVInsertVec(pep->V,i,w));
558
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 155 PetscCall(VecResetArray(w));
559
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 165 PetscCall(VecRestoreArrayRead(xr,&px));
560 }
561 }
562
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 20 PetscCall(VecDestroy(&w));
563
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 20 PetscCall(VecDestroy(&xr));
564 #if !defined(PETSC_USE_COMPLEX)
565
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 10 PetscCall(VecDestroy(&xi));
566 #endif
567
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 4 PetscFunctionReturn(PETSC_SUCCESS);
568 }
569
570 /*
571 PEPLinearExtract_Norm - Auxiliary routine that copies the solution of the
572 linear eigenproblem to the PEP object. The eigenvector of the generalized
573 problem is supposed to be
574 z = [ x ]
575 [ l*x ]
576 If |l|<1.0, the eigenvector is taken from z(1:n), otherwise from z(n+1:2*n).
577 Finally, x is normalized so that ||x||_2 = 1.
578 */
579 373 static PetscErrorCode PEPLinearExtract_Norm(PEP pep,EPS eps)
580 {
581 373 PetscInt i,offset;
582 373 const PetscScalar *px;
583 373 PetscScalar *er=pep->eigr;
584 373 Mat A;
585 373 Vec xr,xi=NULL,w;
586 #if !defined(PETSC_USE_COMPLEX)
587 184 PetscScalar *ei=pep->eigi;
588 #endif
589
590
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 373 PetscFunctionBegin;
591
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 373 PetscCall(EPSGetOperators(eps,&A,NULL));
592
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 373 PetscCall(MatCreateVecs(A,&xr,NULL));
593 #if !defined(PETSC_USE_COMPLEX)
594
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 184 PetscCall(VecDuplicate(xr,&xi));
595 #endif
596
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 373 PetscCall(MatCreateVecsEmpty(pep->A[0],&w,NULL));
597
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 2196 for (i=0;i<pep->nconv;i++) {
598
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 1823 PetscCall(EPSGetEigenpair(eps,i,NULL,NULL,xr,xi));
599
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 1823 if (SlepcAbsEigenvalue(er[i],ei[i])>1.0) offset = (pep->nmat-2)*pep->nloc;
600 else offset = 0;
601 #if !defined(PETSC_USE_COMPLEX)
602
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 829 if (ei[i]!=0.0) { /* complex conjugate pair */
603
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 255 PetscCall(VecGetArrayRead(xr,&px));
604
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 255 PetscCall(VecPlaceArray(w,px+offset));
605
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 255 PetscCall(BVInsertVec(pep->V,i,w));
606
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 255 PetscCall(VecResetArray(w));
607
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 255 PetscCall(VecRestoreArrayRead(xr,&px));
608
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 255 PetscCall(VecGetArrayRead(xi,&px));
609
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 255 PetscCall(VecPlaceArray(w,px+offset));
610
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 255 PetscCall(BVInsertVec(pep->V,i+1,w));
611
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 255 PetscCall(VecResetArray(w));
612
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 255 PetscCall(VecRestoreArrayRead(xi,&px));
613 i++;
614 } else /* real eigenvalue */
615 #endif
616 {
617
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 1568 PetscCall(VecGetArrayRead(xr,&px));
618
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 1568 PetscCall(VecPlaceArray(w,px+offset));
619
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 1568 PetscCall(BVInsertVec(pep->V,i,w));
620
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 1568 PetscCall(VecResetArray(w));
621
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 1823 PetscCall(VecRestoreArrayRead(xr,&px));
622 }
623 }
624
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 373 PetscCall(VecDestroy(&w));
625
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 373 PetscCall(VecDestroy(&xr));
626 #if !defined(PETSC_USE_COMPLEX)
627
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 184 PetscCall(VecDestroy(&xi));
628 #endif
629
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 73 PetscFunctionReturn(PETSC_SUCCESS);
630 }
631
632 413 static PetscErrorCode PEPExtractVectors_Linear(PEP pep)
633 {
634 413 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
635
636
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 413 PetscFunctionBegin;
637
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 413 switch (pep->extract) {
638 20 case PEP_EXTRACT_NONE:
639
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 20 PetscCall(PEPLinearExtract_None(pep,ctx->eps));
640 break;
641 373 case PEP_EXTRACT_NORM:
642
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 373 PetscCall(PEPLinearExtract_Norm(pep,ctx->eps));
643 break;
644 20 case PEP_EXTRACT_RESIDUAL:
645
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 20 PetscCall(PEPLinearExtract_Residual(pep,ctx->eps));
646 break;
647 ✗ case PEP_EXTRACT_STRUCTURED:
648 ✗ SETERRQ(PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Extraction not implemented in this solver");
649 }
650
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 81 PetscFunctionReturn(PETSC_SUCCESS);
651 }
652
653 413 static PetscErrorCode PEPSolve_Linear(PEP pep)
654 {
655 413 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
656 413 PetscScalar sigma;
657 413 PetscBool flg;
658 413 PetscInt i;
659
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 413 PetscFunctionBegin;
661
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 413 PetscCall(EPSSolve(ctx->eps));
662
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 413 PetscCall(EPSGetConverged(ctx->eps,&pep->nconv));
663
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 413 PetscCall(EPSGetIterationNumber(ctx->eps,&pep->its));
664
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 413 PetscCall(EPSGetConvergedReason(ctx->eps,(EPSConvergedReason*)&pep->reason));
665
666 /* recover eigenvalues */
667
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 2841 for (i=0;i<pep->nconv;i++) {
668
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 2428 PetscCall(EPSGetEigenpair(ctx->eps,i,&pep->eigr[i],&pep->eigi[i],NULL,NULL));
669 2428 pep->eigr[i] *= pep->sfactor;
670 2428 pep->eigi[i] *= pep->sfactor;
671 }
672
673 /* restore target */
674
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 413 PetscCall(EPSGetTarget(ctx->eps,&sigma));
675
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 413 PetscCall(EPSSetTarget(ctx->eps,sigma*pep->sfactor));
676
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 413 PetscCall(STGetTransform(pep->st,&flg));
678
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 413 if (flg) PetscTryTypeMethod(pep,backtransform);
679
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 413 if (pep->sfactor!=1.0) {
680 /* Restore original values */
681
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 60 for (i=0;i<pep->nmat;i++) {
682 45 pep->pbc[pep->nmat+i] *= pep->sfactor;
683 45 pep->pbc[2*pep->nmat+i] *= pep->sfactor*pep->sfactor;
684 }
685
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 15 if (!flg && !ctx->explicitmatrix) PetscCall(STScaleShift(pep->st,pep->sfactor));
686 }
687
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 413 if (ctx->explicitmatrix || !flg) PetscCall(RGPopScale(pep->rg));
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 81 PetscFunctionReturn(PETSC_SUCCESS);
689 }
690
691 5205 static PetscErrorCode EPSMonitor_Linear(EPS eps,PetscInt its,PetscInt nconv,PetscScalar *eigr,PetscScalar *eigi,PetscReal *errest,PetscInt nest,void *ctx)
692 {
693 5205 PEP pep = (PEP)ctx;
694
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 5205 PetscFunctionBegin;
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 5205 PetscCall(PEPMonitor(pep,its,nconv,eigr,eigi,errest,nest));
697
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 943 PetscFunctionReturn(PETSC_SUCCESS);
698 }
699
700 383 static PetscErrorCode PEPSetFromOptions_Linear(PEP pep,PetscOptionItems PetscOptionsObject)
701 {
702 383 PetscBool set,val;
703 383 PetscInt k;
704 383 PetscReal array[2]={0,0};
705 383 PetscBool flg;
706 383 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
707
708
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 383 PetscFunctionBegin;
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 383 PetscOptionsHeadBegin(PetscOptionsObject,"PEP Linear Options");
710
711 383 k = 2;
712
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 383 PetscCall(PetscOptionsRealArray("-pep_linear_linearization","Parameters of the linearization","PEPLinearSetLinearization",array,&k,&flg));
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 383 if (flg) PetscCall(PEPLinearSetLinearization(pep,array[0],array[1]));
714
715
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 383 PetscCall(PetscOptionsBool("-pep_linear_explicitmatrix","Use explicit matrix in linearization","PEPLinearSetExplicitMatrix",ctx->explicitmatrix,&val,&set));
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 383 if (set) PetscCall(PEPLinearSetExplicitMatrix(pep,val));
717
718
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 383 PetscOptionsHeadEnd();
719
720
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 383 if (!ctx->eps) PetscCall(PEPLinearGetEPS(pep,&ctx->eps));
721
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 383 PetscCall(EPSSetFromOptions(ctx->eps));
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 75 PetscFunctionReturn(PETSC_SUCCESS);
723 }
724
725 100 static PetscErrorCode PEPLinearSetLinearization_Linear(PEP pep,PetscReal alpha,PetscReal beta)
726 {
727 100 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
728
729
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 100 PetscFunctionBegin;
730
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 100 PetscCheck(beta!=0.0 || alpha!=0.0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONG,"Parameters alpha and beta cannot be zero simultaneously");
731 100 ctx->alpha = alpha;
732 100 ctx->beta = beta;
733
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 100 PetscFunctionReturn(PETSC_SUCCESS);
734 }
735
736 /*@
737 PEPLinearSetLinearization - Set the coefficients that define
738 the linearization of a quadratic eigenproblem.
739
740 Logically Collective
741
742 Input Parameters:
743 + pep - the polynomial eigensolver context
744 . alpha - first parameter of the linearization
745 - beta - second parameter of the linearization
746
747 Options Database Key:
748 . -pep_linear_linearization <alpha,beta> - sets the coefficients
749
750 Notes:
751 See section [](#sec:linearization) for the general expressions of
752 the linearizations. Note that the expressions are different depending
753 on `PEPProblemType`.
754
755 Cannot pass zero for both `alpha` and `beta`. The default values are
756 `alpha`=1 and `beta`=0.
757
758 Level: advanced
759
760 .seealso: [](ch:pep), [](#sec:linearization), `PEPLINEAR`, `PEPProblemType`, `PEPLinearGetLinearization()`
761 @*/
762 100 PetscErrorCode PEPLinearSetLinearization(PEP pep,PetscReal alpha,PetscReal beta)
763 {
764
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 100 PetscFunctionBegin;
765
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 100 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
766
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 100 PetscValidLogicalCollectiveReal(pep,alpha,2);
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 100 PetscValidLogicalCollectiveReal(pep,beta,3);
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 100 PetscTryMethod(pep,"PEPLinearSetLinearization_C",(PEP,PetscReal,PetscReal),(pep,alpha,beta));
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 100 PetscFunctionReturn(PETSC_SUCCESS);
770 }
771
772 10 static PetscErrorCode PEPLinearGetLinearization_Linear(PEP pep,PetscReal *alpha,PetscReal *beta)
773 {
774 10 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
775
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 10 PetscFunctionBegin;
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 10 if (alpha) *alpha = ctx->alpha;
778
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 10 if (beta) *beta = ctx->beta;
779
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 10 PetscFunctionReturn(PETSC_SUCCESS);
780 }
781
782 /*@
783 PEPLinearGetLinearization - Returns the coefficients that define
784 the linearization of a quadratic eigenproblem.
785
786 Not Collective
787
788 Input Parameter:
789 . pep - the polynomial eigensolver context
790
791 Output Parameters:
792 + alpha - the first parameter of the linearization
793 - beta - the second parameter of the linearization
794
795 Level: advanced
796
797 .seealso: [](ch:pep), `PEPLINEAR`, `PEPLinearSetLinearization()`
798 @*/
799 10 PetscErrorCode PEPLinearGetLinearization(PEP pep,PetscReal *alpha,PetscReal *beta)
800 {
801
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 10 PetscFunctionBegin;
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 10 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
803
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 10 PetscUseMethod(pep,"PEPLinearGetLinearization_C",(PEP,PetscReal*,PetscReal*),(pep,alpha,beta));
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 10 PetscFunctionReturn(PETSC_SUCCESS);
805 }
806
807 174 static PetscErrorCode PEPLinearSetExplicitMatrix_Linear(PEP pep,PetscBool explicitmatrix)
808 {
809 174 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
810
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 174 PetscFunctionBegin;
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 174 if (ctx->explicitmatrix != explicitmatrix) {
813 174 ctx->explicitmatrix = explicitmatrix;
814 174 pep->state = PEP_STATE_INITIAL;
815 }
816
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 174 PetscFunctionReturn(PETSC_SUCCESS);
817 }
818
819 /*@
820 PEPLinearSetExplicitMatrix - Indicate if the matrices $A$ and $B$ for the
821 linearization of the problem must be built explicitly.
822
823 Logically Collective
824
825 Input Parameters:
826 + pep - the polynomial eigensolver context
827 - explicitmat - boolean flag indicating if the matrices are built explicitly
828
829 Options Database Key:
830 . -pep_linear_explicitmatrix - set the boolean flag
831
832 Level: advanced
833
834 .seealso: [](ch:pep), `PEPLINEAR`, `PEPLinearGetExplicitMatrix()`
835 @*/
836 174 PetscErrorCode PEPLinearSetExplicitMatrix(PEP pep,PetscBool explicitmat)
837 {
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 174 PetscFunctionBegin;
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 174 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
840
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 174 PetscValidLogicalCollectiveBool(pep,explicitmat,2);
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 174 PetscTryMethod(pep,"PEPLinearSetExplicitMatrix_C",(PEP,PetscBool),(pep,explicitmat));
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 174 PetscFunctionReturn(PETSC_SUCCESS);
843 }
844
845 10 static PetscErrorCode PEPLinearGetExplicitMatrix_Linear(PEP pep,PetscBool *explicitmat)
846 {
847 10 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
848
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 10 PetscFunctionBegin;
850 10 *explicitmat = ctx->explicitmatrix;
851
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 10 PetscFunctionReturn(PETSC_SUCCESS);
852 }
853
854 /*@
855 PEPLinearGetExplicitMatrix - Returns the flag indicating if the matrices
856 $A$ and $B$ for the linearization are built explicitly.
857
858 Not Collective
859
860 Input Parameter:
861 . pep - the polynomial eigensolver context
862
863 Output Parameter:
864 . explicitmat - the mode flag
865
866 Level: advanced
867
868 .seealso: [](ch:pep), `PEPLINEAR`, `PEPLinearSetExplicitMatrix()`
869 @*/
870 10 PetscErrorCode PEPLinearGetExplicitMatrix(PEP pep,PetscBool *explicitmat)
871 {
872
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 10 PetscFunctionBegin;
873
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 10 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
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 10 PetscAssertPointer(explicitmat,2);
875
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 10 PetscUseMethod(pep,"PEPLinearGetExplicitMatrix_C",(PEP,PetscBool*),(pep,explicitmat));
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 10 PetscFunctionReturn(PETSC_SUCCESS);
877 }
878
879 10 static PetscErrorCode PEPLinearSetEPS_Linear(PEP pep,EPS eps)
880 {
881 10 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
882
883
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 10 PetscFunctionBegin;
884
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 10 PetscCall(PetscObjectReference((PetscObject)eps));
885
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 10 PetscCall(EPSDestroy(&ctx->eps));
886 10 ctx->eps = eps;
887 10 ctx->usereps = PETSC_TRUE;
888 10 pep->state = PEP_STATE_INITIAL;
889
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 10 PetscFunctionReturn(PETSC_SUCCESS);
890 }
891
892 /*@
893 PEPLinearSetEPS - Associate a linear eigensolver object (`EPS`) to the
894 polynomial eigenvalue solver.
895
896 Collective
897
898 Input Parameters:
899 + pep - the polynomial eigensolver context
900 - eps - the linear eigensolver context
901
902 Level: advanced
903
904 .seealso: [](ch:pep), `PEPLINEAR`, `PEPLinearGetEPS()`
905 @*/
906 10 PetscErrorCode PEPLinearSetEPS(PEP pep,EPS eps)
907 {
908
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 10 PetscFunctionBegin;
909
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 10 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
910
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 10 PetscValidHeaderSpecific(eps,EPS_CLASSID,2);
911
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 10 PetscCheckSameComm(pep,1,eps,2);
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 10 PetscTryMethod(pep,"PEPLinearSetEPS_C",(PEP,EPS),(pep,eps));
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 10 PetscFunctionReturn(PETSC_SUCCESS);
914 }
915
916 393 static PetscErrorCode PEPLinearGetEPS_Linear(PEP pep,EPS *eps)
917 {
918 393 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
919
920
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 393 PetscFunctionBegin;
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 393 if (!ctx->eps) {
922
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 393 PetscCall(EPSCreate(PetscObjectComm((PetscObject)pep),&ctx->eps));
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 393 PetscCall(PetscObjectIncrementTabLevel((PetscObject)ctx->eps,(PetscObject)pep,1));
924
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 393 PetscCall(EPSSetOptionsPrefix(ctx->eps,((PetscObject)pep)->prefix));
925
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 393 PetscCall(EPSAppendOptionsPrefix(ctx->eps,"pep_linear_"));
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 393 PetscCall(PetscObjectSetOptions((PetscObject)ctx->eps,((PetscObject)pep)->options));
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 393 PetscCall(EPSMonitorSet(ctx->eps,EPSMonitor_Linear,pep,NULL));
928 }
929 393 *eps = ctx->eps;
930
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 393 PetscFunctionReturn(PETSC_SUCCESS);
931 }
932
933 /*@
934 PEPLinearGetEPS - Retrieve the linear eigensolver object (`EPS`) associated
935 to the polynomial eigenvalue solver.
936
937 Collective
938
939 Input Parameter:
940 . pep - the polynomial eigensolver context
941
942 Output Parameter:
943 . eps - the linear eigensolver context
944
945 Level: advanced
946
947 .seealso: [](ch:pep), `PEPLINEAR`, `PEPLinearSetEPS()`
948 @*/
949 393 PetscErrorCode PEPLinearGetEPS(PEP pep,EPS *eps)
950 {
951
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 393 PetscFunctionBegin;
952
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 393 PetscValidHeaderSpecific(pep,PEP_CLASSID,1);
953
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 393 PetscAssertPointer(eps,2);
954
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 393 PetscUseMethod(pep,"PEPLinearGetEPS_C",(PEP,EPS*),(pep,eps));
955
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 393 PetscFunctionReturn(PETSC_SUCCESS);
956 }
957
958 ✗ static PetscErrorCode PEPView_Linear(PEP pep,PetscViewer viewer)
959 {
960 ✗ PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
961 ✗ PetscBool isascii;
962
963 ✗ PetscFunctionBegin;
964 ✗ PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
965 ✗ if (isascii) {
966 ✗ if (!ctx->eps) PetscCall(PEPLinearGetEPS(pep,&ctx->eps));
967 ✗ PetscCall(PetscViewerASCIIPrintf(viewer," %s matrices\n",ctx->explicitmatrix? "explicit": "implicit"));
968 ✗ PetscCall(PetscViewerASCIIPrintf(viewer," linearization parameters: alpha=%g beta=%g\n",(double)ctx->alpha,(double)ctx->beta));
969 ✗ PetscCall(PetscViewerASCIIPushTab(viewer));
970 ✗ PetscCall(EPSView(ctx->eps,viewer));
971 ✗ PetscCall(PetscViewerASCIIPopTab(viewer));
972 }
973 ✗ PetscFunctionReturn(PETSC_SUCCESS);
974 }
975
976 413 static PetscErrorCode PEPReset_Linear(PEP pep)
977 {
978 413 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
979
980
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 413 PetscFunctionBegin;
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 413 if (!ctx->eps) PetscCall(EPSReset(ctx->eps));
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 413 PetscCall(MatDestroy(&ctx->A));
983
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 413 PetscCall(MatDestroy(&ctx->B));
984
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 413 PetscCall(VecDestroy(&ctx->w[0]));
985
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 413 PetscCall(VecDestroy(&ctx->w[1]));
986
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 413 PetscCall(VecDestroy(&ctx->w[2]));
987
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 413 PetscCall(VecDestroy(&ctx->w[3]));
988
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 413 PetscCall(VecDestroy(&ctx->w[4]));
989
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 413 PetscCall(VecDestroy(&ctx->w[5]));
990
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 81 PetscFunctionReturn(PETSC_SUCCESS);
991 }
992
993 403 static PetscErrorCode PEPDestroy_Linear(PEP pep)
994 {
995 403 PEP_LINEAR *ctx = (PEP_LINEAR*)pep->data;
996
997
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 403 PetscFunctionBegin;
998
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 403 PetscCall(EPSDestroy(&ctx->eps));
999
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 403 PetscCall(PetscFree(pep->data));
1000
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetLinearization_C",NULL));
1001
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetLinearization_C",NULL));
1002
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetEPS_C",NULL));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetEPS_C",NULL));
1004
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetExplicitMatrix_C",NULL));
1005
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetExplicitMatrix_C",NULL));
1006
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 79 PetscFunctionReturn(PETSC_SUCCESS);
1007 }
1008
1009 /*MC
1010 PEPLINEAR - PEPLINEAR = "linear" - A linearization-based solver that
1011 uses `EPS` to solve the resulting linear eigenproblem.
1012
1013 Notes:
1014 A linear eigenvalue problem is obtained by linearization, as described
1015 in section [](#sec:linearization), where the linearization parameters
1016 can be set via `PEPLinearSetLinearization()`. Note that the linearization
1017 is done differently depending on `PEPProblemType`. Then the matrices of
1018 the linearization are passed to an `EPS` object. Use `PEPLinearGetEPS()`
1019 to configure this solver.
1020
1021 By default, the matrices of the linearization are handled implicitly via
1022 shell matrices, but this can be changed with `PEPLinearSetExplicitMatrix()`.
1023
1024 Level: beginner
1025
1026 .seealso: [](ch:pep), [](#sec:linearization), `PEP`, `PEPType`, `PEPProblemType`, `PEPSetType()`, `PEPLinearSetLinearization()`, `PEPLinearGetEPS()`, `PEPLinearSetExplicitMatrix()`
1027 M*/
1028 403 SLEPC_EXTERN PetscErrorCode PEPCreate_Linear(PEP pep)
1029 {
1030 403 PEP_LINEAR *ctx;
1031
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 403 PetscFunctionBegin;
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 403 PetscCall(PetscNew(&ctx));
1034 403 pep->data = (void*)ctx;
1035
1036 403 pep->lineariz = PETSC_TRUE;
1037 403 ctx->explicitmatrix = PETSC_FALSE;
1038 403 ctx->alpha = 1.0;
1039 403 ctx->beta = 0.0;
1040
1041 403 pep->ops->solve = PEPSolve_Linear;
1042 403 pep->ops->setup = PEPSetUp_Linear;
1043 403 pep->ops->setfromoptions = PEPSetFromOptions_Linear;
1044 403 pep->ops->destroy = PEPDestroy_Linear;
1045 403 pep->ops->reset = PEPReset_Linear;
1046 403 pep->ops->view = PEPView_Linear;
1047 403 pep->ops->backtransform = PEPBackTransform_Default;
1048 403 pep->ops->computevectors = PEPComputeVectors_Default;
1049 403 pep->ops->extractvectors = PEPExtractVectors_Linear;
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetLinearization_C",PEPLinearSetLinearization_Linear));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetLinearization_C",PEPLinearGetLinearization_Linear));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetEPS_C",PEPLinearSetEPS_Linear));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetEPS_C",PEPLinearGetEPS_Linear));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearSetExplicitMatrix_C",PEPLinearSetExplicitMatrix_Linear));
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 403 PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPLinearGetExplicitMatrix_C",PEPLinearGetExplicitMatrix_Linear));
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 79 PetscFunctionReturn(PETSC_SUCCESS);
1058 }
1059