/*
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   SLEPc - Scalable Library for Eigenvalue Problem Computations
   Copyright (c) 2002-2021, Universitat Politecnica de Valencia, Spain

   This file is part of SLEPc.
   SLEPc is distributed under a 2-clause BSD license (see LICENSE).
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*/

static char help[] = "Singular value decomposition of the Lauchli matrix.\n"
  "The command line options are:\n"
  "  -n <n>, where <n> = matrix dimension.\n"
  "  -mu <mu>, where <mu> = subdiagonal value.\n\n";

#include <slepcsvd.h>

int main(int argc,char **argv)
{
  Mat            A;               /* operator matrix */
  Vec            u,v;             /* left and right singular vectors */
  SVD            svd;             /* singular value problem solver context */
  SVDType        type;
  PetscReal      error,tol,sigma,mu=PETSC_SQRT_MACHINE_EPSILON;
  PetscInt       n=100,i,j,Istart,Iend,nsv,maxit,its,nconv;
  PetscErrorCode ierr;

  ierr = SlepcInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;

  ierr = PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL);CHKERRQ(ierr);
  ierr = PetscOptionsGetReal(NULL,NULL,"-mu",&mu,NULL);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD,"\nLauchli singular value decomposition, (%D x %D) mu=%g\n\n",n+1,n,(double)mu);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                          Build the Lauchli matrix
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  ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
  ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,n+1,n);CHKERRQ(ierr);
  ierr = MatSetFromOptions(A);CHKERRQ(ierr);
  ierr = MatSetUp(A);CHKERRQ(ierr);

  ierr = MatGetOwnershipRange(A,&Istart,&Iend);CHKERRQ(ierr);
  for (i=Istart;i<Iend;i++) {
    if (i == 0) {
      for (j=0;j<n;j++) {
        ierr = MatSetValue(A,0,j,1.0,INSERT_VALUES);CHKERRQ(ierr);
      }
    } else {
      ierr = MatSetValue(A,i,i-1,mu,INSERT_VALUES);CHKERRQ(ierr);
    }
  }

  ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatCreateVecs(A,&v,&u);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
          Create the singular value solver and set various options
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  /*
     Create singular value solver context
  */
  ierr = SVDCreate(PETSC_COMM_WORLD,&svd);CHKERRQ(ierr);

  /*
     Set operators and problem type
  */
  ierr = SVDSetOperators(svd,A,NULL);CHKERRQ(ierr);
  ierr = SVDSetProblemType(svd,SVD_STANDARD);CHKERRQ(ierr);

  /*
     Use thick-restart Lanczos as default solver
  */
  ierr = SVDSetType(svd,SVDTRLANCZOS);CHKERRQ(ierr);

  /*
     Set solver parameters at runtime
  */
  ierr = SVDSetFromOptions(svd);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                      Solve the singular value system
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  ierr = SVDSolve(svd);CHKERRQ(ierr);
  ierr = SVDGetIterationNumber(svd,&its);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD," Number of iterations of the method: %D\n",its);CHKERRQ(ierr);

  /*
     Optional: Get some information from the solver and display it
  */
  ierr = SVDGetType(svd,&type);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type);CHKERRQ(ierr);
  ierr = SVDGetDimensions(svd,&nsv,NULL,NULL);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD," Number of requested singular values: %D\n",nsv);CHKERRQ(ierr);
  ierr = SVDGetTolerances(svd,&tol,&maxit);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD," Stopping condition: tol=%.4g, maxit=%D\n",(double)tol,maxit);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
                    Display solution and clean up
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  /*
     Get number of converged singular triplets
  */
  ierr = SVDGetConverged(svd,&nconv);CHKERRQ(ierr);
  ierr = PetscPrintf(PETSC_COMM_WORLD," Number of converged approximate singular triplets: %D\n\n",nconv);CHKERRQ(ierr);

  if (nconv>0) {
    /*
       Display singular values and relative errors
    */
    ierr = PetscPrintf(PETSC_COMM_WORLD,
         "          sigma           relative error\n"
         "  --------------------- ------------------\n");CHKERRQ(ierr);
    for (i=0;i<nconv;i++) {
      /*
         Get converged singular triplets: i-th singular value is stored in sigma
      */
      ierr = SVDGetSingularTriplet(svd,i,&sigma,u,v);CHKERRQ(ierr);

      /*
         Compute the error associated to each singular triplet
      */
      ierr = SVDComputeError(svd,i,SVD_ERROR_RELATIVE,&error);CHKERRQ(ierr);

      ierr = PetscPrintf(PETSC_COMM_WORLD,"       % 6f      ",(double)sigma);CHKERRQ(ierr);
      ierr = PetscPrintf(PETSC_COMM_WORLD," % 12g\n",(double)error);CHKERRQ(ierr);
    }
    ierr = PetscPrintf(PETSC_COMM_WORLD,"\n");CHKERRQ(ierr);
  }

  /*
     Free work space
  */
  ierr = SVDDestroy(&svd);CHKERRQ(ierr);
  ierr = MatDestroy(&A);CHKERRQ(ierr);
  ierr = VecDestroy(&u);CHKERRQ(ierr);
  ierr = VecDestroy(&v);CHKERRQ(ierr);
  ierr = SlepcFinalize();
  return ierr;
}

/*TEST

   testset:
      filter: sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
      requires: double
      test:
         suffix: 1
      test:
         suffix: 1_scalapack
         nsize: {{1 2}}
         args: -svd_type scalapack
         requires: scalapack

TEST*/
