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# /home/coin/svn-release/Alps-1.5.0/Clp/src/ClpHelperFunctions.hpp

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    00001 /* $Id: ClpHelperFunctions.hpp 2034 2014-06-12 16:10:26Z stefan $ */
    00002 // Copyright (C) 2003, International Business Machines
    00003 // Corporation and others.  All Rights Reserved.
    00004 // This code is licensed under the terms of the Eclipse Public License (EPL).
    00005
    00006 #ifndef ClpHelperFunctions_H
    00007 #define ClpHelperFunctions_H
    00008
    00009 #include "ClpConfig.h"
    00010 #ifdef HAVE_CMATH
    00011 # include <cmath>
    00012 #else
    00013 # ifdef HAVE_MATH_H
    00014 #  include <math.h>
    00015 # else
    00016 #  error "don't have header file for math"
    00017 # endif
    00018 #endif
    00019
    00028 double maximumAbsElement(const double * region, int size);
    00029 void setElements(double * region, int size, double value);
    00030 void multiplyAdd(const double * region1, int size, double multiplier1,
    00031                  double * region2, double multiplier2);
    00032 double innerProduct(const double * region1, int size, const double * region2);
    00033 void getNorms(const double * region, int size, double & norm1, double & norm2);
    00034 #if COIN_LONG_WORK
    00035 // For long double versions
    00036 CoinWorkDouble maximumAbsElement(const CoinWorkDouble * region, int size);
    00037 void setElements(CoinWorkDouble * region, int size, CoinWorkDouble value);
    00038 void multiplyAdd(const CoinWorkDouble * region1, int size, CoinWorkDouble multiplier1,
    00039                  CoinWorkDouble * region2, CoinWorkDouble multiplier2);
    00040 CoinWorkDouble innerProduct(const CoinWorkDouble * region1, int size, const CoinWorkDouble * region2);
    00041 void getNorms(const CoinWorkDouble * region, int size, CoinWorkDouble & norm1, CoinWorkDouble & norm2);
    00042 inline void
    00043 CoinMemcpyN(const double * from, const int size, CoinWorkDouble * to)
    00044 {
    00045      for (int i = 0; i < size; i++)
    00046           to[i] = from[i];
    00047 }
    00048 inline void
    00049 CoinMemcpyN(const CoinWorkDouble * from, const int size, double * to)
    00050 {
    00051      for (int i = 0; i < size; i++)
    00052           to[i] = static_cast<double>(from[i]);
    00053 }
    00054 inline CoinWorkDouble
    00055 CoinMax(const CoinWorkDouble x1, const double x2)
    00056 {
    00057      return (x1 > x2) ? x1 : x2;
    00058 }
    00059 inline CoinWorkDouble
    00060 CoinMax(double x1, const CoinWorkDouble x2)
    00061 {
    00062      return (x1 > x2) ? x1 : x2;
    00063 }
    00064 inline CoinWorkDouble
    00065 CoinMin(const CoinWorkDouble x1, const double x2)
    00066 {
    00067      return (x1 < x2) ? x1 : x2;
    00068 }
    00069 inline CoinWorkDouble
    00070 CoinMin(double x1, const CoinWorkDouble x2)
    00071 {
    00072      return (x1 < x2) ? x1 : x2;
    00073 }
    00074 inline CoinWorkDouble CoinSqrt(CoinWorkDouble x)
    00075 {
    00076      return sqrtl(x);
    00077 }
    00078 #else
    00079 inline double CoinSqrt(double x)
    00080 {
    00081      return sqrt(x);
    00082 }
    00083 #endif
    00085 #   ifdef NDEBUG
    00086 #      define ClpTraceDebug(expression)         {}
    00087 #   else
    00088 void ClpTracePrint(std::string fileName, std::string message, int line);
    00089 #      define ClpTraceDebug(expression) { \
    00090        if (!(expression)) { ClpTracePrint(__FILE__,__STRING(expression),__LINE__); } \
    00091   }
    00092 #   endif
    00094 #ifdef ClpPdco_H
    00095
    00096
    00097 inline double pdxxxmerit(int nlow, int nupp, int *low, int *upp, CoinDenseVector <double> &r1,
    00098                          CoinDenseVector <double> &r2, CoinDenseVector <double> &rL,
    00099                          CoinDenseVector <double> &rU, CoinDenseVector <double> &cL,
    00100                          CoinDenseVector <double> &cU )
    00101 {
    00102
    00103 // Evaluate the merit function for Newton's method.
    00104 // It is the 2-norm of the three sets of residuals.
    00105      double sum1, sum2;
    00106      CoinDenseVector <double> f(6);
    00107      f[0] = r1.twoNorm();
    00108      f[1] = r2.twoNorm();
    00109      sum1 = sum2 = 0.0;
    00110      for (int k = 0; k < nlow; k++) {
    00111           sum1 += rL[low[k]] * rL[low[k]];
    00112           sum2 += cL[low[k]] * cL[low[k]];
    00113      }
    00114      f[2] = sqrt(sum1);
    00115      f[4] = sqrt(sum2);
    00116      sum1 = sum2 = 0.0;
    00117      for (int k = 0; k < nupp; k++) {
    00118           sum1 += rL[upp[k]] * rL[upp[k]];
    00119           sum2 += cL[upp[k]] * cL[upp[k]];
    00120      }
    00121      f[3] = sqrt(sum1);
    00122      f[5] = sqrt(sum2);
    00123
    00124      return f.twoNorm();
    00125 }
    00126
    00127 //-----------------------------------------------------------------------
    00128 // End private function pdxxxmerit
    00129 //-----------------------------------------------------------------------
    00130
    00131
    00132 //function [r1,r2,rL,rU,Pinf,Dinf] =    ...
    00133 //      pdxxxresid1( Aname,fix,low,upp, ...
    00134 //                   b,bl,bu,d1,d2,grad,rL,rU,x,x1,x2,y,z1,z2 )
    00135
    00136 inline void pdxxxresid1(ClpPdco *model, const int nlow, const int nupp, const int nfix,
    00137                         int *low, int *upp, int *fix,
    00138                         CoinDenseVector <double> &b, double *bl, double *bu, double d1, double d2,
    00139                         CoinDenseVector <double> &grad, CoinDenseVector <double> &rL,
    00140                         CoinDenseVector <double> &rU, CoinDenseVector <double> &x,
    00141                         CoinDenseVector <double> &x1, CoinDenseVector <double> &x2,
    00142                         CoinDenseVector <double> &y,  CoinDenseVector <double> &z1,
    00143                         CoinDenseVector <double> &z2, CoinDenseVector <double> &r1,
    00144                         CoinDenseVector <double> &r2, double *Pinf, double *Dinf)
    00145 {
    00146
    00147 // Form residuals for the primal and dual equations.
    00148 // rL, rU are output, but we input them as full vectors
    00149 // initialized (permanently) with any relevant zeros.
    00150
    00151 // Get some element pointers for efficiency
    00152      double *x_elts  = x.getElements();
    00153      double *r2_elts = r2.getElements();
    00154
    00155      for (int k = 0; k < nfix; k++)
    00156           x_elts[fix[k]]  = 0;
    00157
    00158      r1.clear();
    00159      r2.clear();
    00160      model->matVecMult( 1, r1, x );
    00161      model->matVecMult( 2, r2, y );
    00162      for (int k = 0; k < nfix; k++)
    00163           r2_elts[fix[k]]  = 0;
    00164
    00165
    00166      r1      = b    - r1 - d2 * d2 * y;
    00167      r2      = grad - r2 - z1;              // grad includes d1*d1*x
    00168      if (nupp > 0)
    00169           r2    = r2 + z2;
    00170
    00171      for (int k = 0; k < nlow; k++)
    00172           rL[low[k]] = bl[low[k]] - x[low[k]] + x1[low[k]];
    00173      for (int k = 0; k < nupp; k++)
    00174           rU[upp[k]] = - bu[upp[k]] + x[upp[k]] + x2[upp[k]];
    00175
    00176      double normL = 0.0;
    00177      double normU = 0.0;
    00178      for (int k = 0; k < nlow; k++)
    00179           if (rL[low[k]] > normL) normL = rL[low[k]];
    00180      for (int k = 0; k < nupp; k++)
    00181           if (rU[upp[k]] > normU) normU = rU[upp[k]];
    00182
    00183      *Pinf    = CoinMax(normL, normU);
    00184      *Pinf    = CoinMax( r1.infNorm() , *Pinf );
    00185      *Dinf    = r2.infNorm();
    00186      *Pinf    = CoinMax( *Pinf, 1e-99 );
    00187      *Dinf    = CoinMax( *Dinf, 1e-99 );
    00188 }
    00189
    00190 //-----------------------------------------------------------------------
    00191 // End private function pdxxxresid1
    00192 //-----------------------------------------------------------------------
    00193
    00194
    00195 //function [cL,cU,center,Cinf,Cinf0] = ...
    00196 //      pdxxxresid2( mu,low,upp,cL,cU,x1,x2,z1,z2 )
    00197
    00198 inline void pdxxxresid2(double mu, int nlow, int nupp, int *low, int *upp,
    00199                         CoinDenseVector <double> &cL, CoinDenseVector <double> &cU,
    00200                         CoinDenseVector <double> &x1, CoinDenseVector <double> &x2,
    00201                         CoinDenseVector <double> &z1, CoinDenseVector <double> &z2,
    00202                         double *center, double *Cinf, double *Cinf0)
    00203 {
    00204
    00205 // Form residuals for the complementarity equations.
    00206 // cL, cU are output, but we input them as full vectors
    00207 // initialized (permanently) with any relevant zeros.
    00208 // Cinf  is the complementarity residual for X1 z1 = mu e, etc.
    00209 // Cinf0 is the same for mu=0 (i.e., for the original problem).
    00210
    00211      double maxXz = -1e20;
    00212      double minXz = 1e20;
    00213
    00214      double *x1_elts = x1.getElements();
    00215      double *z1_elts = z1.getElements();
    00216      double *cL_elts = cL.getElements();
    00217      for (int k = 0; k < nlow; k++) {
    00218           double x1z1    = x1_elts[low[k]] * z1_elts[low[k]];
    00219           cL_elts[low[k]] = mu - x1z1;
    00220           if (x1z1 > maxXz) maxXz = x1z1;
    00221           if (x1z1 < minXz) minXz = x1z1;
    00222      }
    00223
    00224      double *x2_elts = x2.getElements();
    00225      double *z2_elts = z2.getElements();
    00226      double *cU_elts = cU.getElements();
    00227      for (int k = 0; k < nupp; k++) {
    00228           double x2z2    = x2_elts[upp[k]] * z2_elts[upp[k]];
    00229           cU_elts[upp[k]] = mu - x2z2;
    00230           if (x2z2 > maxXz) maxXz = x2z2;
    00231           if (x2z2 < minXz) minXz = x2z2;
    00232      }
    00233
    00234      maxXz   = CoinMax( maxXz, 1e-99 );
    00235      minXz   = CoinMax( minXz, 1e-99 );
    00236      *center  = maxXz / minXz;
    00237
    00238      double normL = 0.0;
    00239      double normU = 0.0;
    00240      for (int k = 0; k < nlow; k++)
    00241           if (cL_elts[low[k]] > normL) normL = cL_elts[low[k]];
    00242      for (int k = 0; k < nupp; k++)
    00243           if (cU_elts[upp[k]] > normU) normU = cU_elts[upp[k]];
    00244      *Cinf    = CoinMax( normL, normU);
    00245      *Cinf0   = maxXz;
    00246 }
    00247 //-----------------------------------------------------------------------
    00248 // End private function pdxxxresid2
    00249 //-----------------------------------------------------------------------
    00250
    00251 inline double  pdxxxstep( CoinDenseVector <double> &x, CoinDenseVector <double> &dx )
    00252 {
    00253
    00254 // Assumes x > 0.
    00255 // Finds the maximum step such that x + step*dx >= 0.
    00256
    00257      double step     = 1e+20;
    00258
    00259      int n = x.size();
    00260      double *x_elts = x.getElements();
    00261      double *dx_elts = dx.getElements();
    00262      for (int k = 0; k < n; k++)
    00263           if (dx_elts[k] < 0)
    00264                if ((x_elts[k] / (-dx_elts[k])) < step)
    00265                     step = x_elts[k] / (-dx_elts[k]);
    00266      return step;
    00267 }
    00268 //-----------------------------------------------------------------------
    00269 // End private function pdxxxstep
    00270 //-----------------------------------------------------------------------
    00271
    00272 inline double  pdxxxstep(int nset, int *set, CoinDenseVector <double> &x, CoinDenseVector <double> &dx )
    00273 {
    00274
    00275 // Assumes x > 0.
    00276 // Finds the maximum step such that x + step*dx >= 0.
    00277
    00278      double step     = 1e+20;
    00279
    00280      int n = x.size();
    00281      double *x_elts = x.getElements();
    00282      double *dx_elts = dx.getElements();
    00283      for (int k = 0; k < n; k++)
    00284           if (dx_elts[k] < 0)
    00285                if ((x_elts[k] / (-dx_elts[k])) < step)
    00286                     step = x_elts[k] / (-dx_elts[k]);
    00287      return step;
    00288 }
    00289 //-----------------------------------------------------------------------
    00290 // End private function pdxxxstep
    00291 //-----------------------------------------------------------------------
    00292 #endif
    00293 #endif