libtrilinos-rol-dev 12.12.1-5 / usr / include / trilinos / ROL_PoissonInversion.hpp

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/** \file
    \brief  Contains definitions for Poisson material inversion.
    \author Created by D. Ridzal and D. Kouri.
 */

#ifndef USE_HESSVEC 
#define USE_HESSVEC 1
#endif

#ifndef ROL_POISSONINVERSION_HPP
#define ROL_POISSONINVERSION_HPP

#include "ROL_StdVector.hpp"
#include "ROL_Objective.hpp"
#include "ROL_HelperFunctions.hpp"

#include "Teuchos_LAPACK.hpp"

namespace ROL {
namespace ZOO {

/** \brief Poisson material inversion.
 */
template<class Real>
class Objective_PoissonInversion : public Objective<Real> {

  typedef std::vector<Real> vector;
  typedef Vector<Real>      V;
  typedef StdVector<Real>   SV;

  typedef typename vector::size_type uint;

private:
  uint nu_;
  uint nz_;

  Real hu_;
  Real hz_;

  Real alpha_;

  Real eps_;
  int  reg_type_;

  Teuchos::RCP<const vector> getVector( const V& x ) {
    using Teuchos::dyn_cast;
    return dyn_cast<const SV>(x).getVector();
  }
  
  Teuchos::RCP<vector> getVector( V& x ) {
    using Teuchos::dyn_cast;
    return dyn_cast<SV>(x).getVector();
  }

public:

  /* CONSTRUCTOR */
  Objective_PoissonInversion(uint nz = 32, Real alpha = 1.e-4)
    : nu_(nz-1), nz_(nz), hu_(1./((Real)nu_+1.)), hz_(hu_),
      alpha_(alpha), eps_(1.e-4), reg_type_(2) {}

  /* REGULARIZATION DEFINITIONS */
  Real reg_value(const Vector<Real> &z) {
    using Teuchos::RCP;

    RCP<const vector> zp = getVector(z);

    Real val = 0.0;
    for (uint i = 0; i < nz_; i++) {
      if ( reg_type_ == 2 ) {
        val += alpha_/2.0 * hz_ * (*zp)[i]*(*zp)[i];
      }
      else if ( reg_type_ == 1 ) {
        val += alpha_ * hz_ * std::sqrt((*zp)[i]*(*zp)[i] + eps_);
      }
      else if ( reg_type_ == 0 ) {
        if ( i < nz_-1 ) {
          val += alpha_ * std::sqrt(std::pow((*zp)[i]-(*zp)[i+1],2.0)+eps_);
        }
      }
    }
    return val;
  }

  void reg_gradient(Vector<Real> &g, const Vector<Real> &z) {
    using Teuchos::RCP;     

    if ( reg_type_ == 2 ) {
      g.set(z);
      g.scale(alpha_*hz_);    
    } 
    else if ( reg_type_ == 1 ) {
      RCP<const vector> zp = getVector(z);
      RCP<vector >      gp = getVector(g);

      for (uint i = 0; i < nz_; i++) {
        (*gp)[i] = alpha_ * hz_ * (*zp)[i]/std::sqrt(std::pow((*zp)[i],2.0)+eps_);
      }
    }
    else if ( reg_type_ == 0 ) {
      RCP<const vector> zp = getVector(z);
      RCP<vector>       gp = getVector(g);

      Real diff = 0.0;
      for (uint i = 0; i < nz_; i++) {
        if ( i == 0 ) {
          diff     = (*zp)[i]-(*zp)[i+1];
          (*gp)[i] = alpha_ * diff/std::sqrt(std::pow(diff,2.0)+eps_);
        }
        else if ( i == nz_-1 ) {
          diff     = (*zp)[i-1]-(*zp)[i];
          (*gp)[i] = -alpha_ * diff/std::sqrt(std::pow(diff,2.0)+eps_);
        }
        else {
          diff      = (*zp)[i]-(*zp)[i+1];
          (*gp)[i]  = alpha_ * diff/std::sqrt(std::pow(diff,2.0)+eps_);
          diff      = (*zp)[i-1]-(*zp)[i];
          (*gp)[i] -= alpha_ * diff/std::sqrt(std::pow(diff,2.0)+eps_);
        }
      }
    }
  }

  void reg_hessVec(Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &z) {

    using Teuchos::RCP;

    if ( reg_type_ == 2 ) {
      hv.set(v);
      hv.scale(alpha_*hz_);
    }
    else if ( reg_type_ == 1 ) {
      RCP<const vector> zp  = getVector(z);
      RCP<const vector> vp  = getVector(v);
      RCP<vector>       hvp = getVector(hv);

      for (uint i = 0; i < nz_; i++) {
        (*hvp)[i] = alpha_*hz_*(*vp)[i]*eps_/std::pow(std::pow((*zp)[i],2.0)+eps_,3.0/2.0);
      }
    }
    else if ( reg_type_ == 0 ) {
      RCP<const vector> zp  = getVector(z);
      RCP<const vector> vp  = getVector(v);
      RCP<vector>       hvp = getVector(hv);

      Real diff1 = 0.0;
      Real diff2 = 0.0;
      for (uint i = 0; i < nz_; i++) {
        if ( i == 0 ) {
          diff1 = (*zp)[i]-(*zp)[i+1];
          diff1 = eps_/std::pow(std::pow(diff1,2.0)+eps_,3.0/2.0);
          (*hvp)[i] = alpha_* ((*vp)[i]*diff1 - (*vp)[i+1]*diff1);
        }
        else if ( i == nz_-1 ) {
          diff2 = (*zp)[i-1]-(*zp)[i];
          diff2 = eps_/std::pow(std::pow(diff2,2.0)+eps_,3.0/2.0);
          (*hvp)[i] = alpha_* (-(*vp)[i-1]*diff2 + (*vp)[i]*diff2);
        }
        else {
          diff1 = (*zp)[i]-(*zp)[i+1];
          diff1 = eps_/std::pow(std::pow(diff1,2.0)+eps_,3.0/2.0);
          diff2 = (*zp)[i-1]-(*zp)[i];
          diff2 = eps_/std::pow(std::pow(diff2,2.0)+eps_,3.0/2.0);
          (*hvp)[i] = alpha_* (-(*vp)[i-1]*diff2 + (*vp)[i]*(diff1 + diff2) - (*vp)[i+1]*diff1);
        }
      }
    }
  }

  /* FINITE ELEMENT DEFINTIONS */
  void apply_mass(Vector<Real> &Mf, const Vector<Real> &f ) {

    using Teuchos::RCP;
    RCP<const vector> fp  = getVector(f);
    RCP<vector>       Mfp = getVector(Mf);

    for (uint i = 0; i < nu_; i++) {
      if ( i == 0 ) {
        (*Mfp)[i] = hu_/6.0*(4.0*(*fp)[i] + (*fp)[i+1]);
      }
      else if ( i == nu_-1 ) {
        (*Mfp)[i] = hu_/6.0*((*fp)[i-1] + 4.0*(*fp)[i]);
      }
      else {
        (*Mfp)[i] = hu_/6.0*((*fp)[i-1] + 4.0*(*fp)[i] + (*fp)[i+1]);
      }
    }
  }

  void solve_poisson(Vector<Real> &u, const Vector<Real> &z, Vector<Real> &b) {

    using Teuchos::RCP;
    RCP<const vector> zp = getVector(z);
    RCP<vector>       up = getVector(u);
    RCP<vector>       bp = getVector(b);

    // Get Diagonal and Off-Diagonal Entries of PDE Jacobian
    vector d(nu_,1.0);
    vector o(nu_-1,1.0);
    for ( uint i = 0; i < nu_; i++ ) {
      d[i] = (std::exp((*zp)[i]) + std::exp((*zp)[i+1]))/hu_;
      if ( i < nu_-1 ) {
        o[i] *= -std::exp((*zp)[i+1])/hu_;
      }
    }

    // Solve Tridiagonal System Using LAPACK's SPD Tridiagonal Solver
    Teuchos::LAPACK<int,Real> lp;
    int info;
    int ldb  = nu_;
    int nhrs = 1;
    lp.PTTRF(nu_,&d[0],&o[0],&info);
    lp.PTTRS(nu_,nhrs,&d[0],&o[0],&(*bp)[0],ldb,&info);
    u.set(b);
  }

  Real evaluate_target(Real x) {
    return x*(1.0-x);
  }

  void apply_linearized_control_operator( Vector<Real> &Bd, const Vector<Real> &z, 
                                    const Vector<Real> &d,  const Vector<Real> &u ) {

    using Teuchos::RCP;
    
    RCP<const vector> zp  = getVector(z);
    RCP<const vector> up  = getVector(u);
    RCP<const vector> dp  = getVector(d);
    RCP<vector>       Bdp = getVector(Bd);

    for (uint i = 0; i < nu_; i++) {
      if ( i == 0 ) {
        (*Bdp)[i] = 1.0/hu_*( std::exp((*zp)[i])*(*up)[i]*(*dp)[i] 
                                  + std::exp((*zp)[i+1])*((*up)[i]-(*up)[i+1])*(*dp)[i+1] );
      }
      else if ( i == nu_-1 ) {
        (*Bdp)[i] = 1.0/hu_*( std::exp((*zp)[i])*((*up)[i]-(*up)[i-1])*(*dp)[i] 
                                  + std::exp((*zp)[i+1])*(*up)[i]*(*dp)[i+1] );
      }
      else {
        (*Bdp)[i] = 1.0/hu_*( std::exp((*zp)[i])*((*up)[i]-(*up)[i-1])*(*dp)[i] 
                                  + std::exp((*zp)[i+1])*((*up)[i]-(*up)[i+1])*(*dp)[i+1] );
      }
    }
  }

  void apply_transposed_linearized_control_operator( Vector<Real> &Bd, const Vector<Real> &z,
                                               const Vector<Real> &d,  const Vector<Real> &u ) {
    using Teuchos::RCP;

    RCP<const vector> zp  = getVector(z);
    RCP<const vector> up  = getVector(u);
    RCP<const vector> dp  = getVector(d);
    RCP<vector>       Bdp = getVector(Bd);

    for (uint i = 0; i < nz_; i++) {
      if ( i == 0 ) {
        (*Bdp)[i] = std::exp((*zp)[i])/hu_*(*up)[i]*(*dp)[i];
      }
      else if ( i == nz_-1 ) {
        (*Bdp)[i] = std::exp((*zp)[i])/hu_*(*up)[i-1]*(*dp)[i-1];
      }
      else {
        (*Bdp)[i] = std::exp((*zp)[i])/hu_*( ((*up)[i]-(*up)[i-1])*((*dp)[i]-(*dp)[i-1]) );
      }
    }
  }
  
  void apply_transposed_linearized_control_operator_2( Vector<Real> &Bd, const Vector<Real> &z, const Vector<Real> &v,
                                                 const Vector<Real> &d,  const Vector<Real> &u ) {
    using Teuchos::RCP;
    RCP<const vector> zp  = getVector(z);
    RCP<const vector> vp  = getVector(v);
    RCP<const vector> up  = getVector(u);
    RCP<const vector> dp  = getVector(d);
    RCP<vector>       Bdp = getVector(Bd);

    for (uint i = 0; i < nz_; i++) {
      if ( i == 0 ) {
        (*Bdp)[i] = (*vp)[i]*std::exp((*zp)[i])/hu_*(*up)[i]*(*dp)[i];
      }
      else if ( i == nz_-1 ) {
        (*Bdp)[i] = (*vp)[i]*std::exp((*zp)[i])/hu_*(*up)[i-1]*(*dp)[i-1];
      }
      else {
        (*Bdp)[i] = (*vp)[i]*std::exp((*zp)[i])/hu_*( ((*up)[i]-(*up)[i-1])*((*dp)[i]-(*dp)[i-1]) );
      }
    }
  }

  /* STATE AND ADJOINT EQUATION DEFINTIONS */
  void solve_state_equation(Vector<Real> &u, const Vector<Real> &z) {

    using Teuchos::RCP;
    using Teuchos::rcp;

    Real k1 = 1.0;
    Real k2 = 2.0;
    // Right Hand Side
    RCP<vector> bp = rcp( new vector(nu_, 0.0) );
    for ( uint i = 0; i < nu_; i++ ) {
      if ( (Real)(i+1)*hu_ < 0.5 ) {
       (*bp)[i] = 2.0*k1*hu_;
      }
      else if ( std::abs((Real)(i+1)*hu_ - 0.5) < ROL_EPSILON<Real>() ) {
       (*bp)[i] = (k1+k2)*hu_;
      }
      else if ( (Real)(i+1)*hu_ > 0.5 ) {
       (*bp)[i] = 2.0*k2*hu_;
      }
    }
   
    SV b(bp);
    // Solve Equation
    solve_poisson(u,z,b);
  }

  void solve_adjoint_equation(Vector<Real> &p, const Vector<Real> &u, const Vector<Real> &z) {

    using Teuchos::RCP;
    using Teuchos::rcp;

    RCP<const vector> up = getVector(u);
    RCP<vector> rp = rcp( new vector(nu_,0.0) );
    SV res(rp);

    for ( uint i = 0; i < nu_; i++) {
      (*rp)[i] = -((*up)[i]-evaluate_target((Real)(i+1)*hu_));
    }
    StdVector<Real> Mres( Teuchos::rcp( new std::vector<Real>(nu_,0.0) ) );
    apply_mass(Mres,res);
    solve_poisson(p,z,Mres);
  }

  void solve_state_sensitivity_equation(Vector<Real> &w, const Vector<Real> &v, 
                                        const Vector<Real> &u, const Vector<Real> &z) {

    using Teuchos::rcp;
    SV b( rcp( new vector(nu_,0.0) ) );
    apply_linearized_control_operator(b,z,v,u);
    solve_poisson(w,z,b);
  }

  void solve_adjoint_sensitivity_equation(Vector<Real> &q, const Vector<Real> &w, const Vector<Real> &v,
                                          const Vector<Real> &p, const Vector<Real> &u, const Vector<Real> &z) {

    using Teuchos::rcp;

    SV res( rcp( new vector(nu_,0.0) ) );
    apply_mass(res,w);
    SV res1( rcp( new vector(nu_,0.0) ) );
    apply_linearized_control_operator(res1,z,v,p);
    res.axpy(-1.0,res1);
    solve_poisson(q,z,res);
  }

  /* OBJECTIVE FUNCTION DEFINITIONS */
  Real value( const Vector<Real> &z, Real &tol ) {

    using Teuchos::RCP;
    using Teuchos::rcp;

    // SOLVE STATE EQUATION
    RCP<vector> up = rcp( new vector(nu_,0.0) );
    SV u( up );

    solve_state_equation(u,z);

    // COMPUTE MISFIT
    RCP<vector> rp = rcp( new vector(nu_,0.0) );
    SV res( rp );

    for ( uint i = 0; i < nu_; i++) {
      (*rp)[i] = ((*up)[i]-evaluate_target((Real)(i+1)*hu_));
    }

    RCP<V> Mres = res.clone();
    apply_mass(*Mres,res);
    return 0.5*Mres->dot(res) + reg_value(z);
  } 

  void gradient( Vector<Real> &g, const Vector<Real> &z, Real &tol ) {

    using Teuchos::rcp; 

    // SOLVE STATE EQUATION
    SV u( rcp( new vector(nu_,0.0) ) );
    solve_state_equation(u,z);

    // SOLVE ADJOINT EQUATION
    SV p( Teuchos::rcp( new std::vector<Real>(nu_,0.0) ) );
    solve_adjoint_equation(p,u,z);

    // Apply Transpose of Linearized Control Operator
    apply_transposed_linearized_control_operator(g,z,p,u);
   
    // Regularization gradient
    SV g_reg( rcp( new vector(nz_,0.0) ) );
    reg_gradient(g_reg,z); 

    // Build Gradient
    g.plus(g_reg);
  }
#if USE_HESSVEC
  void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &z, Real &tol ) {

    using Teuchos::rcp;

    // SOLVE STATE EQUATION
    SV u( rcp( new vector(nu_,0.0) ) );
    solve_state_equation(u,z);

    // SOLVE ADJOINT EQUATION
    SV p( rcp( new vector(nu_,0.0) ) );
    solve_adjoint_equation(p,u,z);

    // SOLVE STATE SENSITIVITY EQUATION
    SV w( rcp( new vector(nu_,0.0) ) );
    solve_state_sensitivity_equation(w,v,u,z);

    // SOLVE ADJOINT SENSITIVITY EQUATION
    SV q( rcp( new vector(nu_,0.0) ) );
    solve_adjoint_sensitivity_equation(q,w,v,p,u,z);

    // Apply Transpose of Linearized Control Operator
    apply_transposed_linearized_control_operator(hv,z,q,u);
  
    // Apply Transpose of Linearized Control Operator
    SV tmp( rcp( new vector(nz_,0.0) ) );
    apply_transposed_linearized_control_operator(tmp,z,w,p);
    hv.axpy(-1.0,tmp); 

    // Apply Transpose of 2nd Derivative of Control Operator
    tmp.zero();
    apply_transposed_linearized_control_operator_2(tmp,z,v,p,u);
    hv.plus(tmp);

    // Regularization hessVec
    SV hv_reg( rcp( new vector(nz_,0.0) ) );
    reg_hessVec(hv_reg,v,z);

    // Build hessVec
    hv.plus(hv_reg);
  }
#endif

  void invHessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {

    using Teuchos::RCP;
    using Teuchos::rcp;

    // Cast hv and v vectors to std::vector.
    RCP<vector> hvp       = getVector(hv);

    std::vector<Real> vp(*getVector(v));

    int dim = static_cast<int>(vp.size());


    // Compute dense Hessian.
    Teuchos::SerialDenseMatrix<int, Real> H(dim, dim);
    Objective_PoissonInversion<Real> & obj = *this; 
    H = computeDenseHessian<Real>(obj, x);

    // Compute eigenvalues, sort real part.
    std::vector<vector> eigenvals = computeEigenvalues<Real>(H);
    std::sort((eigenvals[0]).begin(), (eigenvals[0]).end());

    // Perform 'inertia' correction.
    Real inertia = (eigenvals[0])[0];
    Real correction = 0.0;
    if ( inertia <= 0.0 ) {
      correction = 2.0*std::abs(inertia);
      if ( inertia == 0.0 ) {
        int cnt = 0;
        while ( eigenvals[0][cnt] == 0.0 ) {
          cnt++;
        }
        correction = 0.5*eigenvals[0][cnt];
        if ( cnt == dim-1 ) {
          correction = 1.0;
        }
      }
      for (int i=0; i<dim; i++) {
        H(i,i) += correction;
      }
    }

    // Compute dense inverse Hessian.
    Teuchos::SerialDenseMatrix<int, Real> invH = computeInverse<Real>(H);

    // Apply dense inverse Hessian.
    Teuchos::SerialDenseVector<int, Real> hv_teuchos(Teuchos::View, &((*hvp)[0]), dim);
    const Teuchos::SerialDenseVector<int, Real> v_teuchos(Teuchos::View, &(vp[0]), dim);
    hv_teuchos.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, invH, v_teuchos, 0.0);
  }

};

template<class Real>
void getPoissonInversion( Teuchos::RCP<Objective<Real> > &obj,
                          Teuchos::RCP<Vector<Real> >    &x0,
                          Teuchos::RCP<Vector<Real> >    &x ) {
  // Problem dimension
  int n = 128;

  // Get Initial Guess
  Teuchos::RCP<std::vector<Real> > x0p = Teuchos::rcp(new std::vector<Real>(n,0.0));
  for ( int i = 0; i < n; i++ ) {
    (*x0p)[i] = 1.5;
  }
  x0 = Teuchos::rcp(new StdVector<Real>(x0p));

  // Get Solution
  Teuchos::RCP<std::vector<Real> > xp = Teuchos::rcp(new std::vector<Real>(n,0.0));
  Real h = 1.0/((Real)n+1), pt = 0.0, k1 = 1.0, k2 = 2.0;
  for( int i = 0; i < n; i++ ) {
    pt = (Real)(i+1)*h;
    if ( pt >= 0.0 && pt < 0.5 ) {
      (*xp)[i] = std::log(k1);
    }
    else if ( pt >= 0.5 && pt < 1.0 ) {
      (*xp)[i] = std::log(k2); 
    }
  }
  x = Teuchos::rcp(new StdVector<Real>(xp));

  // Instantiate Objective Function
  obj = Teuchos::rcp(new Objective_PoissonInversion<Real>(n,1.e-6));
}

} // End ZOO Namespace
} // End ROL Namespace

#endif