Actual source code: cgls.c

petsc-master 2020-07-14
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  1: /*
  2:     This file implements CGLS, the Conjugate Gradient method for Least-Squares problems.
  3: */
  4:  #include <petsc/private/kspimpl.h>

  6: typedef struct {
  7:   PetscInt  nwork_n,nwork_m;
  8:   Vec       *vwork_m;   /* work vectors of length m, where the system is size m x n */
  9:   Vec       *vwork_n;   /* work vectors of length n */
 10: } KSP_CGLS;

 12: static PetscErrorCode KSPSetUp_CGLS(KSP ksp)
 13: {
 15:   KSP_CGLS       *cgls = (KSP_CGLS*)ksp->data;

 18:   cgls->nwork_m = 2;
 19:   if (cgls->vwork_m) {
 20:     VecDestroyVecs(cgls->nwork_m,&cgls->vwork_m);
 21:   }

 23:   cgls->nwork_n = 2;
 24:   if (cgls->vwork_n) {
 25:     VecDestroyVecs(cgls->nwork_n,&cgls->vwork_n);
 26:   }
 27:   KSPCreateVecs(ksp,cgls->nwork_n,&cgls->vwork_n,cgls->nwork_m,&cgls->vwork_m);
 28:   return(0);
 29: }

 31: static PetscErrorCode KSPSolve_CGLS(KSP ksp)
 32: {
 34:   KSP_CGLS       *cgls = (KSP_CGLS*)ksp->data;
 35:   Mat            A;
 36:   Vec            x,b,r,p,q,ss;
 37:   PetscScalar    beta;
 38:   PetscReal      alpha,gamma,oldgamma;

 41:   KSPGetOperators(ksp,&A,NULL); /* Matrix of the system */

 43:   /* vectors of length n, where system size is mxn */
 44:   x  = ksp->vec_sol; /* Solution vector */
 45:   p  = cgls->vwork_n[0];
 46:   ss  = cgls->vwork_n[1];

 48:   /* vectors of length m, where system size is mxn */
 49:   b  = ksp->vec_rhs; /* Right-hand side vector */
 50:   r  = cgls->vwork_m[0];
 51:   q  = cgls->vwork_m[1];

 53:   /* Minimization with the CGLS method */
 54:   ksp->its = 0;
 55:   ksp->rnorm = 0;
 56:   MatMult(A,x,r);
 57:   VecAYPX(r,-1,b);         /* r_0 = b - A * x_0  */
 58:   MatMultTranspose(A,r,p); /* p_0 = A^T * r_0    */
 59:   VecCopy(p,ss);           /* s_0 = p_0          */
 60:   VecNorm(ss,NORM_2,&gamma);
 61:   KSPCheckNorm(ksp,gamma);
 62:   if (ksp->normtype != KSP_NORM_NONE) ksp->rnorm = gamma;
 63:   (*ksp->converged)(ksp,ksp->its,ksp->rnorm,&ksp->reason,ksp->cnvP);
 64:   if (ksp->reason) return(0);
 65:   gamma = gamma*gamma;                          /* gamma = norm2(s)^2 */

 67:   do {
 68:     MatMult(A,p,q);           /* q = A * p               */
 69:     VecNorm(q,NORM_2,&alpha);
 70:     KSPCheckNorm(ksp,alpha);
 71:     alpha = alpha*alpha;                           /* alpha = norm2(q)^2      */
 72:     alpha = gamma / alpha;                         /* alpha = gamma / alpha   */
 73:     VecAXPY(x,alpha,p);       /* x += alpha * p          */
 74:     VecAXPY(r,-alpha,q);      /* r -= alpha * q          */
 75:     MatMultTranspose(A,r,ss); /* ss = A^T * r            */
 76:     oldgamma = gamma;                              /* oldgamma = gamma        */
 77:     VecNorm(ss,NORM_2,&gamma);
 78:     KSPCheckNorm(ksp,gamma);
 79:     ksp->its++;
 80:     if (ksp->normtype != KSP_NORM_NONE) ksp->rnorm = gamma;
 81:     KSPMonitor(ksp,ksp->its,ksp->rnorm);
 82:     (*ksp->converged)(ksp,ksp->its,ksp->rnorm,&ksp->reason,ksp->cnvP);
 83:     if (ksp->reason) return(0);
 84:     gamma = gamma*gamma;                           /* gamma = norm2(s)^2      */
 85:     beta = gamma/oldgamma;                         /* beta = gamma / oldgamma */
 86:     VecAYPX(p,beta,ss);       /* p = s + beta * p        */
 87:   } while (ksp->its<ksp->max_it);

 89:   if (ksp->its >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
 90:   return(0);
 91: }

 93: static PetscErrorCode KSPDestroy_CGLS(KSP ksp)
 94: {
 95:   KSP_CGLS       *cgls = (KSP_CGLS*)ksp->data;

 99:   /* Free work vectors */
100:   if (cgls->vwork_n) {
101:     VecDestroyVecs(cgls->nwork_n,&cgls->vwork_n);
102:   }
103:   if (cgls->vwork_m) {
104:     VecDestroyVecs(cgls->nwork_m,&cgls->vwork_m);
105:   }
106:   PetscFree(ksp->data);
107:   return(0);
108: }

110: /*MC
111:      KSPCGLS - Conjugate Gradient method for Least-Squares problems

113:    Level: beginner

115:    Supports non-square (rectangular) matrices.

117:    Notes:
118:     This does not use the preconditioner, so one should probably use KSPLSQR instead.

120: .seealso:  KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP,
121:            KSPCGSetType(), KSPCGUseSingleReduction(), KSPPIPECG, KSPGROPPCG

123: M*/
124: PETSC_EXTERN PetscErrorCode KSPCreate_CGLS(KSP ksp)
125: {
127:   KSP_CGLS       *cgls;

130:   PetscNewLog(ksp,&cgls);
131:   ksp->data                = (void*)cgls;
132:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,3);
133:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);
134:   ksp->ops->setup          = KSPSetUp_CGLS;
135:   ksp->ops->solve          = KSPSolve_CGLS;
136:   ksp->ops->destroy        = KSPDestroy_CGLS;
137:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
138:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
139:   ksp->ops->setfromoptions = NULL;
140:   ksp->ops->view           = NULL;
141: #if defined(PETSC_USE_COMPLEX)
142:   SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"This is not supported for complex numbers");
143: #endif
144:   return(0);
145: }