// Copyright (C) 2003, International Business Machines
// Corporation and others.  All Rights Reserved.
#ifndef ClpHelperFunctions_H
#define ClpHelperFunctions_H

/**
    Note (JJF) I have added some operations on arrays even though they may
    duplicate CoinDenseVector.  I think the use of templates was a mistake
    as I don't think inline generic code can take as much advantage of
    parallelism or machine architectures or memory hierarchies.

*/

double maximumAbsElement(const double * region, int size);
void setElements(double * region, int size, double value);
void multiplyAdd(const double * region1, int size, double multiplier1,
		 double * region2, double multiplier2);
double innerProduct(const double * region1, int size, const double * region2);
void getNorms(const double * region, int size, double & norm1, double & norm2);

/// Following only included if ClpPdco defined
#ifdef ClpPdco_H


inline double pdxxxmerit(int nlow, int nupp, int *low, int *upp, CoinDenseVector <double> &r1,
		CoinDenseVector <double> &r2, CoinDenseVector <double> &rL,
		CoinDenseVector <double> &rU, CoinDenseVector <double> &cL,
		CoinDenseVector <double> &cU ){

// Evaluate the merit function for Newton's method.
// It is the 2-norm of the three sets of residuals.
  double sum1, sum2;
  CoinDenseVector <double> f(6);
  f[0] = r1.twoNorm();
  f[1] = r2.twoNorm();
  sum1 = sum2 = 0.0;
  for (int k=0; k<nlow; k++){
    sum1 += rL[low[k]]*rL[low[k]];
    sum2 += cL[low[k]]*cL[low[k]];
  }
  f[2] = sqrt(sum1);
  f[4] = sqrt(sum2);
  sum1 = sum2 = 0.0;
  for (int k=0; k<nupp; k++){
    sum1 += rL[upp[k]]*rL[upp[k]];
    sum2 += cL[upp[k]]*cL[upp[k]];
  }
  f[3] = sqrt(sum1);
  f[5] = sqrt(sum2);

  return f.twoNorm();
}

//-----------------------------------------------------------------------
// End private function pdxxxmerit
//-----------------------------------------------------------------------


//function [r1,r2,rL,rU,Pinf,Dinf] =    ...
//      pdxxxresid1( Aname,fix,low,upp, ...
//                   b,bl,bu,d1,d2,grad,rL,rU,x,x1,x2,y,z1,z2 )

inline void pdxxxresid1(ClpPdco *model, const int nlow, const int nupp, const int nfix,
		 int *low, int *upp, int *fix,
		 CoinDenseVector <double> &b, double *bl, double *bu, double d1, double d2,
		 CoinDenseVector <double> &grad, CoinDenseVector <double> &rL,
		 CoinDenseVector <double> &rU, CoinDenseVector <double> &x,
		 CoinDenseVector <double> &x1, CoinDenseVector <double> &x2,
		 CoinDenseVector <double> &y,  CoinDenseVector <double> &z1,
		 CoinDenseVector <double> &z2, CoinDenseVector <double> &r1,
		 CoinDenseVector <double> &r2, double *Pinf, double *Dinf){

// Form residuals for the primal and dual equations.
// rL, rU are output, but we input them as full vectors
// initialized (permanently) with any relevant zeros.

// Get some element pointers for efficiency
  double *x_elts  = x.getElements();
  double *r2_elts = r2.getElements();
  
  for (int k=0; k<nfix; k++)
    x_elts[fix[k]]  = 0;

  r1.clear();
  r2.clear();   
  model->matVecMult( 1, r1, x );
  model->matVecMult( 2, r2, y );
  for (int k=0; k<nfix; k++)
    r2_elts[fix[k]]  = 0;


  r1      = b    - r1 - d2*d2*y;
  r2      = grad - r2 - z1;              // grad includes d1*d1*x
  if(nupp > 0)       
    r2    = r2 + z2;   

  for (int k=0; k<nlow; k++)
    rL[low[k]] = bl[low[k]] - x[low[k]] + x1[low[k]];
  for (int k=0; k<nupp; k++)
    rU[upp[k]] = - bu[upp[k]] + x[upp[k]] + x2[upp[k]];

  double normL = 0.0;
  double normU = 0.0;
  for (int k=0; k<nlow; k++)
    if (rL[low[k]] > normL) normL = rL[low[k]];
  for (int k=0; k<nupp; k++)
    if (rU[upp[k]] > normU) normU = rU[upp[k]];

  *Pinf    = CoinMax(normL, normU);  
  *Pinf    = CoinMax( r1.infNorm() , *Pinf );
  *Dinf    = r2.infNorm();
  *Pinf    = CoinMax( *Pinf, 1e-99 );
  *Dinf    = CoinMax( *Dinf, 1e-99 );
}

//-----------------------------------------------------------------------
// End private function pdxxxresid1
//-----------------------------------------------------------------------


//function [cL,cU,center,Cinf,Cinf0] = ...
//      pdxxxresid2( mu,low,upp,cL,cU,x1,x2,z1,z2 )

inline void pdxxxresid2(double mu, int nlow, int nupp, int *low, int *upp,
		 CoinDenseVector <double> &cL, CoinDenseVector <double> &cU,
		 CoinDenseVector <double> &x1, CoinDenseVector <double> &x2,
		 CoinDenseVector <double> &z1, CoinDenseVector <double> &z2,
		 double *center, double *Cinf, double *Cinf0){

// Form residuals for the complementarity equations.
// cL, cU are output, but we input them as full vectors
// initialized (permanently) with any relevant zeros.
// Cinf  is the complementarity residual for X1 z1 = mu e, etc.
// Cinf0 is the same for mu=0 (i.e., for the original problem).

  double maxXz = -1e20;
  double minXz = 1e20;

  double *x1_elts = x1.getElements();
  double *z1_elts = z1.getElements();
  double *cL_elts = cL.getElements();
  for (int k=0; k<nlow; k++){
    double x1z1    = x1_elts[low[k]] * z1_elts[low[k]];
    cL_elts[low[k]] = mu - x1z1;
    if(x1z1 > maxXz) maxXz = x1z1;
    if(x1z1 < minXz) minXz = x1z1;
  }

  double *x2_elts = x2.getElements();
  double *z2_elts = z2.getElements();
  double *cU_elts = cU.getElements();
  for (int k=0; k<nupp; k++){
    double x2z2    = x2_elts[upp[k]] * z2_elts[upp[k]];
    cU_elts[upp[k]] = mu - x2z2;
    if(x2z2 > maxXz) maxXz = x2z2;
    if(x2z2 < minXz) minXz = x2z2;
  }

  maxXz   = CoinMax( maxXz, 1e-99 );
  minXz   = CoinMax( minXz, 1e-99 );
  *center  = maxXz / minXz;

  double normL = 0.0;
  double normU = 0.0;
  for (int k=0; k<nlow; k++)
    if (cL_elts[low[k]] > normL) normL = cL_elts[low[k]];
  for (int k=0; k<nupp; k++)
    if (cU_elts[upp[k]] > normU) normU = cU_elts[upp[k]];
  *Cinf    = CoinMax( normL, normU);
  *Cinf0   = maxXz;
}
//-----------------------------------------------------------------------
// End private function pdxxxresid2
//-----------------------------------------------------------------------

inline double  pdxxxstep( CoinDenseVector <double> &x, CoinDenseVector <double> &dx ){

// Assumes x > 0.
// Finds the maximum step such that x + step*dx >= 0.

  double step     = 1e+20;

  int n = x.size();
  double *x_elts = x.getElements();
  double *dx_elts = dx.getElements();
  for (int k=0; k<n; k++)
    if (dx_elts[k] < 0)
      if ((x_elts[k]/(-dx_elts[k])) < step)
	step = x_elts[k]/(-dx_elts[k]);
  return step;
}
//-----------------------------------------------------------------------
// End private function pdxxxstep
//-----------------------------------------------------------------------

inline double  pdxxxstep(int nset, int *set, CoinDenseVector <double> &x, CoinDenseVector <double> &dx ){

// Assumes x > 0.
// Finds the maximum step such that x + step*dx >= 0.

  double step     = 1e+20;

  int n = x.size();
  double *x_elts = x.getElements();
  double *dx_elts = dx.getElements();
  for (int k=0; k<n; k++)
    if (dx_elts[k] < 0)
      if ((x_elts[k]/(-dx_elts[k])) < step)
	step = x_elts[k]/(-dx_elts[k]);
  return step;
}
//-----------------------------------------------------------------------
// End private function pdxxxstep
//-----------------------------------------------------------------------
#endif
#endif