cgnealg.hh

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// cgnealg.H
// created by ADP 1/8/04
// last modified 06/16/04

// Much code is shamelessly stolen from the umin cgne.H
// originally written by WWS, with his permission

/*************************************************************************

Copyright Rice University, 2004.
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#ifndef __RVLALG_UMIN_CGNE_H
#define __RVLALG_UMIN_CGNE_H

#include "alg.hh"
#include "terminator.hh"
#include "linop.hh"
#include "table.hh"

using namespace RVLAlg;

namespace RVLUmin {

  using namespace RVL;
  using namespace RVLAlg;    

  // forward declaration
  template<typename Scalar>
  class CGNEAlg;

  template<typename Scalar>
  class CGNEStep : public Algorithm {

    friend class CGNEAlg<Scalar>;

    typedef typename ScalarFieldTraits<Scalar>::AbsType atype;

  public:

    CGNEStep(LinearOp<Scalar> const & _A,
         Vector<Scalar> & _x,
         Vector<Scalar> const & _b,
         atype & _rnorm, 
         atype & _nrnorm)
      : A(_A), x(_x), b(_b), rnorm(_rnorm), nrnorm(_nrnorm), r(A.getRange()), g(A.getDomain()),
    q(A.getRange()), p(A.getDomain()) { 
      // NOTE: initial x assumed to be zero vector
      //      cerr<<"cg initialize\n";
      r.copy(b);
      rnorm=r.norm();
      A.applyAdjOp(r,g);
      p.copy(g);
      nrnorm=g.norm();
      gamma = nrnorm*nrnorm;
    }
      
    void run() {
      try {
    //          cerr<<"CGSTEP::run 0\n";
    A.applyOp(p,q);
    //  cerr<<"CGSTEP::run 1\n";
    atype qtq = q.normsq();
    atype absalpha;
    if (ProtectedDivision<atype>(gamma,qtq,absalpha)) {
      RVLException e;
      e<<"Error: CGNEStep::run() from ProtectedDivision: alpha\n";
      throw e;
    }
    // can use q for workspace since it is not needed again until
    // reinitialized
    //  cerr<<"CGSTEP::update x\n";

    Scalar alpha=absalpha;
    x.linComb(alpha,p);
    r.linComb(-alpha,q);
    //  cerr<<"CGSTEP::run 3\n";

    A.applyAdjOp(r,g);
    //  cerr<<"CGSTEP::run 4\n";

    atype newgamma = g.normsq();
    atype absbeta;
    if (ProtectedDivision<atype>(newgamma,gamma,absbeta)) {
      RVLException e;
      e<<"Error: CGNEStep::run() from ProtectedDivision: beta\n";
      throw e;
    }
    //  cerr<<"CGSTEP::run 5\n";

    Scalar beta = absbeta;
    p.linComb(ScalarFieldTraits<Scalar>::One(),g,beta);
    gamma=newgamma;
    rnorm=r.norm();
    nrnorm=sqrt(gamma);
    //  cerr<<"CGSTEP::run 6\n";

      }
      catch (RVLException & e) {
    e<<"\ncalled from CGNEStep::run()\n";
    throw e;
      }
     
    }

    ~CGNEStep() {}

  protected:

    // references to external objects
    LinearOp<Scalar> const & A;
    Vector<Scalar> & x;
    Vector<Scalar> const & b;
    atype & rnorm;
    atype & nrnorm;

  private:

    // need four work vectors and one scalar as persistent object data
    Vector<Scalar> r;    // residual
    Vector<Scalar> g;    // gradient
    Vector<Scalar> q;    // image of search direction
    Vector<Scalar> p;    // search direction
    atype gamma;         // ||g||^2
  };
  
  template<typename Scalar>
  class PCGNEStep : public Algorithm {

    friend class CGNEAlg<Scalar>;

    typedef typename ScalarFieldTraits<Scalar>::AbsType atype;

  public:

    PCGNEStep(LinearOp<Scalar> const & _A,
          LinearOp<Scalar> const & _M,
          Vector<Scalar> & _x,
          Vector<Scalar> const & _b,
          atype & _rnorm, 
          atype & _nrnorm)
      : A(_A), M(_M), x(_x), b(_b), rnorm(_rnorm), nrnorm(_nrnorm), 
    r(A.getRange()), ng(A.getDomain()), g(A.getDomain()),
    q(A.getRange()), p(A.getDomain()) { 
      // sanity tests - cannot sensibly test M for SPD, but 
      // at least get domain right
      if ((M.getDomain() != A.getDomain()) ||
      (M.getRange()  != A.getDomain())) {
    RVLException e;
    e<<"Error PCGNEStep constructor\n";
    e<<"  preconditioning operator does not have domain, range\n";
    e<<"  same as domain of system operator\n";
    e<<"  preconditioning operator:\n";
    M.write(e);
    e<<"  system operator:\n";
    A.write(e);
    throw e;
      }
      // NOTE: initial x assumed to be zero vector
      r.copy(b);
      rnorm=r.norm();
      A.applyAdjOp(r,ng);
      M.applyOp(ng,g);
      p.copy(g);
      gamma = abs(g.inner(ng));
      nrnorm=sqrt(gamma);
    }
      
    void run() {
      try {
    A.applyOp(p,q);
    atype qtq = q.normsq();
    atype absalpha;
    if (ProtectedDivision<atype>(gamma,qtq,absalpha)) {
      RVLException e;
      e<<"Error: PCGNEStep::run() from ProtectedDivision: alpha\n";
      throw e;
    }
    // can use q for workspace since it is not needed again until
    // reinitialized

    Scalar alpha=absalpha;
    x.linComb(alpha,p);
    r.linComb(-alpha,q);

    A.applyAdjOp(r,ng);
    M.applyOp(ng,g);

    atype newgamma = abs(g.inner(ng));
    atype absbeta;
    if (ProtectedDivision<atype>(newgamma,gamma,absbeta)) {
      RVLException e;
      e<<"Error: PCGNEStep::run() from ProtectedDivision: beta\n";
      throw e;
    }

    Scalar beta = absbeta;
    p.linComb(ScalarFieldTraits<Scalar>::One(),g,beta);
    gamma=newgamma;
    rnorm=r.norm();
    nrnorm=sqrt(gamma);
      }
      catch (RVLException & e) {
    e<<"\ncalled from PCGNEStep::run()\n";
    throw e;
      }
     
    }

    ~PCGNEStep() {}

  protected:

    // references to external objects
    LinearOp<Scalar> const & A;
    LinearOp<Scalar> const & M;
    Vector<Scalar> & x;
    Vector<Scalar> const & b;
    atype & rnorm;
    atype & nrnorm;

  private:

    // need four work vectors and one scalar as persistent object data
    Vector<Scalar> r;    // residual
    Vector<Scalar> ng;   // normal residual
    Vector<Scalar> g;    // gradient = preconditioned normal residual
    Vector<Scalar> q;    // image of search direction
    Vector<Scalar> p;    // search direction
    atype gamma;         // gradient norm, inner product defined by inverse of M
  };
  
  template<typename Scalar>
  class CGNEAlg: public Algorithm, public Terminator {

    typedef typename ScalarFieldTraits<Scalar>::AbsType atype;

  public:

    CGNEAlg(RVL::Vector<Scalar> & x, 
        RVL::LinearOp<Scalar> const & A, 
        RVL::Vector<Scalar> const & rhs, 
        atype & _rnorm,
        atype & _nrnorm,
        atype _rtol = 100.0*numeric_limits<atype>::epsilon(),
        atype _nrtol = 100.0*numeric_limits<atype>::epsilon(),
        int _maxcount = 10,
        atype _maxstep = numeric_limits<atype>::max(),
        ostream & _str = cout)
    : rnorm(_rnorm), 
      nrnorm(_nrnorm), 
      rtol(_rtol), 
      nrtol(_nrtol), 
      maxstep(_maxstep), 
      maxcount(_maxcount), 
      count(0), 
      proj(false), 
      str(_str)
    {
      try {
    x.zero(); 
    step = new CGNEStep<Scalar>(A,x,rhs,rnorm,nrnorm);
      }
      catch (RVLException & e) {
    e<<"\ncalled from CGNEAlg constructor (not preconditioned)\n";
    throw e;
      }
    }

    CGNEAlg(RVL::Vector<Scalar> & x, 
        LinearOp<Scalar> const & A, 
        LinearOp<Scalar> const & M, 
        Vector<Scalar> const & rhs, 
        atype & _rnorm,
        atype & _nrnorm,
        atype _rtol = 100.0*numeric_limits<atype>::epsilon(),
        atype _nrtol = 100.0*numeric_limits<atype>::epsilon(),
        int _maxcount = 10,
        atype _maxstep = numeric_limits<atype>::max(),
        ostream & _str = cout)
    : rnorm(_rnorm), 
      nrnorm(_nrnorm), 
      rtol(_rtol), 
      nrtol(_nrtol), 
      maxstep(_maxstep), 
      maxcount(_maxcount), 
      count(0), 
      proj(false), 
      str(_str)
    { 
      try {
    x.zero(); 
    step = new PCGNEStep<Scalar>(A,M,x,rhs,rnorm,nrnorm);
      }
      catch (RVLException & e) {
    e<<"\ncalled from CGNEAlg constructor (preconditioned)\n";
    throw e;
      }
    }

    ~CGNEAlg() {
      delete step;
    }

    bool query() { return proj; }

    void run() { 
      try {
    //  cerr<<"cg::run\n";
    // access to internals
    CGNEStep<Scalar>  * cg  = dynamic_cast<CGNEStep<Scalar> *>(step);
    PCGNEStep<Scalar> * pcg = dynamic_cast<PCGNEStep<Scalar> *>(step);
    if ((!cg && !pcg) || (cg && pcg)) {
      RVLException e;
      e<<"Error: CGNEAlg::run\n";
      e<<"  unable to determine whether step data member\n";
      e<<"  is preconditioned or not. PANIC!\n";
      throw e;
    }
    
    // terminator for CGNE iteration
    vector<string> names(2);
    vector<atype *> nums(2);
    vector<atype> tols(2);
    atype rnorm0=rnorm;
    atype nrnorm0=nrnorm;
          
    names[0]="Residual Norm"; nums[0]=&rnorm; tols[0]=rtol*rnorm0;
    names[1]="Gradient Norm"; nums[1]=&nrnorm; tols[1]=nrtol*nrnorm0;
    if (pcg) str<<"========================== BEGIN PCGNE =========================\n";
    else    str<<"========================== BEGIN CGNE =========================\n";
    VectorCountingThresholdIterationTable<atype> stop1(maxcount,names,nums,tols,str);
    stop1.init();
    // terminator for Trust Region test and projection
    //      BallProjTerminator<Scalar> stop2(x,maxstep,str);

    Terminator * stop2 = NULL;
    if (cg)  stop2 = new BallProjTerminator<Scalar>( cg->x,maxstep,str);  
    if (pcg) stop2 = new BallProjTerminator<Scalar>(pcg->x,maxstep,str); 
    // terminate if either
    OrTerminator stop(stop1,*stop2);
    // loop
    LoopAlg doit(*step,stop);
    //  cerr<<"stop1="<<stop1.query()<<" stop2="<<stop2->query()<<endl;
    //  cerr<<"rtol="<<rtol<<" nrtol="<<nrtol<<" maxcount="<<maxcount<<endl;
    doit.run();
    // must recompute residual if scaling occured 
    //  cerr<<"stop1="<<stop1.query()<<" stop2="<<stop2->query()<<" xnorm="<<cg->x.norm()<<" maxstep="<<maxstep<<"\n";
    proj = stop2->query();
    if (proj) {
      if (cg) {
        //      cerr<<"adjust\n";
        Vector<Scalar> temp((cg->A).getRange());
        (cg->A).applyOp((cg->x),temp);
        temp.linComb(-1.0,(cg->b));
        rnorm=temp.norm();
        Vector<Scalar> temp1((cg->A).getDomain());
        (cg->A).applyAdjOp(temp,temp1);
        nrnorm=temp1.norm();
      }
      if (pcg) {
        Vector<Scalar> temp((pcg->A).getRange());
        (pcg->A).applyOp((pcg->x),temp);
        temp.linComb(-1.0,(pcg->b));
        rnorm=temp.norm();
        Vector<Scalar> temp1((pcg->A).getDomain());
        Vector<Scalar> temp2((pcg->A).getDomain());
        (pcg->A).applyAdjOp(temp,temp1);
        (pcg->M).applyOp(temp1,temp2);
        atype tmpgamma = abs(temp1.inner(temp2));
        nrnorm=sqrt(tmpgamma);
      }
    }

    count = stop1.getCount();
    if (pcg) str<<"=========================== END PCGNE ==========================\n";
    else str<<"=========================== END CGNE ==========================\n";
          // display results
          str<<"\n ****************** CGNE summary *****************  "<<endl;
          str<<"initial residual norm      = "<<rnorm0<<endl;
          str<<"residual norm              = "<<rnorm<<endl;
          str<<"residual redn              = "<<rnorm/rnorm0<<endl;
          str<<"initial gradient norm      = "<<nrnorm0<<endl;
          str<<"gradient norm              = "<<nrnorm<<endl;
          str<<"gradient redn              = "<<nrnorm/nrnorm0<<endl;
      }
      catch (RVLException & e) {
    e<<"\ncalled from CGNEAlg::run\n";
    throw e;
      }
    }

    int getCount() const { return count; }

  private:

    atype & rnorm;                 // residual norm
    atype & nrnorm;                // gradient norm
    atype rtol;                    // tolerance residual norm
    atype nrtol;                   // tolerance gradient norm 
    atype maxstep;                 // upper bound for net step x-x0
    int maxcount;                  // upper bound for iteration count
    int count;                     // actual iteration count
    mutable bool proj;             // whether step is projected onto TR boundary
    ostream & str;                 // stream for report output
    Algorithm * step;              // CGNE or PCGNE step

    // disable default, copy constructors
    CGNEAlg();
    CGNEAlg(CGNEAlg<Scalar> const &);

  };

  template<typename Scalar>
  class CGNEPolicyData {

    typedef typename ScalarFieldTraits<Scalar>::AbsType atype;
  
  public:

    atype rtol;
    atype nrtol;
    atype Delta;
    int maxcount;
    bool verbose;

    CGNEPolicyData(atype _rtol = numeric_limits<atype>::max(),
           atype _nrtol = numeric_limits<atype>::max(),
           atype _Delta = numeric_limits<atype>::max(),
           int _maxcount = 0,
           bool _verbose = false)
      : rtol(_rtol), nrtol(_nrtol), Delta(_Delta), maxcount(_maxcount), verbose(_verbose) {}
      
    CGNEPolicyData(CGNEPolicyData<Scalar> const & a) 
      : rtol(a.rtol), nrtol(a.nrtol), Delta(a.Delta), maxcount(a.maxcount), verbose(a.verbose) {}

    ostream & write(ostream & str) const {
      str<<"\n";
      str<<"==============================================\n";
      str<<"CGNEPolicyData: \n";
      str<<"rtol      = "<<rtol<<"\n";
      str<<"nrtol     = "<<nrtol<<"\n";
      str<<"Delta     = "<<Delta<<"\n";
      str<<"maxcount  = "<<maxcount<<"\n";
      str<<"verbose   = "<<verbose<<"\n";
      str<<"==============================================\n";
      return str;
    }
  };

  template<typename Scalar> 
  class CGNEPolicy {

    typedef typename ScalarFieldTraits<Scalar>::AbsType atype;

  public:
    CGNEAlg<Scalar> * build(Vector<Scalar> & x, 
                LinearOp<Scalar> const & A,
                Vector<Scalar> const & d,
                atype & rnorm,
                atype & nrnorm,
                ostream & str) const {
      try {
    if (verbose) 
      return new CGNEAlg<Scalar>(x,A,d,rnorm,nrnorm,rtol,nrtol,maxcount,Delta,str);
    else
      return new CGNEAlg<Scalar>(x,A,d,rnorm,nrnorm,rtol,nrtol,maxcount,Delta,nullstr);
      }
      catch (RVLException & e) {
    e<<"\ncalled from CGNEPolicy::build\n";
    e<<"inputs: \n";
    e<<"**** x:\n";
    x.write(e);
    e<<"**** A:\n";
    A.write(e);
    e<<"**** d:\n";
    d.write(e);
    throw e;
      }
    }

      
    CGNEAlg<Scalar> * build(Vector<Scalar> & x,
                            LinearOp<Scalar> const & A,
                            LinearOp<Scalar> const & M,
                            Vector<Scalar> const & d,
                            atype & rnorm,
                            atype & nrnorm,
                            ostream & str) const {
    try {
        if (verbose)
            return new CGNEAlg<Scalar>(x,A,M,d,rnorm,nrnorm,rtol,nrtol,maxcount,Delta,str);
        else
            return new CGNEAlg<Scalar>(x,A,M,d,rnorm,nrnorm,rtol,nrtol,maxcount,Delta,nullstr);
        }
        catch (RVLException & e) {
            e<<"\ncalled from CGNEPolicy::build\n";
            e<<"inputs: \n";
            e<<"**** x:\n";
            x.write(e);
            e<<"**** A:\n";
            A.write(e);
            e<<"**** d:\n";
            d.write(e);
            throw e;
        }
    }
      
    void assign(atype _rtol, atype _nrtol, atype _Delta, int _maxcount, bool _verbose) {
      rtol=_rtol; nrtol=_nrtol; Delta=_Delta; maxcount=_maxcount; verbose=_verbose;
    }

    void assign(Table const & t) {
      rtol=getValueFromTable<atype>(t,"CGNE_ResTol");
      nrtol=getValueFromTable<atype>(t,"CGNE_GradTol"); 
      Delta=getValueFromTable<atype>(t,"TR_Delta");
      maxcount=getValueFromTable<int>(t,"CGNE_MaxItn"); 
      verbose=getValueFromTable<bool>(t,"CGNE_Verbose");
    }

    void assign(CGNEPolicyData<Scalar> const & s) {
      rtol=s.rtol;
      nrtol=s.nrtol;
      Delta=s.Delta;
      maxcount=s.maxcount;
      verbose=s.verbose;
    }

    mutable atype Delta;

    CGNEPolicy(atype _rtol = numeric_limits<atype>::max(),
           atype _nrtol = numeric_limits<atype>::max(),
           atype _Delta = numeric_limits<atype>::max(),
           int _maxcount = 0,
           bool _verbose = true)
      : Delta(_Delta), rtol(_rtol), nrtol(_nrtol), maxcount(_maxcount), verbose(_verbose), nullstr(0) {}

    CGNEPolicy(CGNEPolicy<Scalar> const & p)
      :     Delta(p.Delta), 
        rtol(p.rtol), 
        nrtol(p.nrtol), 
        maxcount(p.maxcount), 
        verbose(p.verbose), 
        nullstr(0) {}
      
  private:
    mutable atype rtol;
    mutable atype nrtol;
    mutable int maxcount;
    mutable bool verbose;
    mutable std::ostream nullstr;
  };
}

#endif

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