/* $Id: unitTest.cpp 2531 2019-10-03 13:48:16Z stefan $ */
// Copyright (C) 2002, International Business Machines
// Corporation and others.  All Rights Reserved.
// This code is licensed under the terms of the Eclipse Public License (EPL).

#ifdef NDEBUG
#undef NDEBUG
#endif

#include "ClpConfig.h"
#include "CoinPragma.hpp"
#include <cassert>
#include <cstdio>
#include <cstdlib>
#include <cmath>
#include <cfloat>
#include <string>
#include <iostream>

#include "CoinMpsIO.hpp"
#include "CoinPackedMatrix.hpp"
#include "CoinPackedVector.hpp"
#include "CoinStructuredModel.hpp"
#include "CoinHelperFunctions.hpp"
#include "CoinTime.hpp"
#include "CoinFloatEqual.hpp"

#if CLP_HAS_ABC
#include "CoinAbcCommon.hpp"
#endif
#ifdef ABC_INHERIT
#include "CoinAbcFactorization.hpp"
#endif
#include "ClpFactorization.hpp"
#include "ClpSimplex.hpp"
#include "ClpSimplexOther.hpp"
#include "ClpSimplexNonlinear.hpp"
#include "ClpInterior.hpp"
#include "ClpLinearObjective.hpp"
#include "ClpDualRowSteepest.hpp"
#include "ClpDualRowDantzig.hpp"
#include "ClpPrimalColumnSteepest.hpp"
#include "ClpPrimalColumnDantzig.hpp"
#include "ClpParameters.hpp"
#include "ClpNetworkMatrix.hpp"
#include "ClpPlusMinusOneMatrix.hpp"
#include "MyMessageHandler.hpp"
#include "MyEventHandler.hpp"

#include "ClpPresolve.hpp"
#include "Idiot.hpp"
#if FACTORIZATION_STATISTICS
extern double ftranTwiddleFactor1X;
extern double ftranTwiddleFactor2X;
extern double ftranFTTwiddleFactor1X;
extern double ftranFTTwiddleFactor2X;
extern double btranTwiddleFactor1X;
extern double btranTwiddleFactor2X;
extern double ftranFullTwiddleFactor1X;
extern double ftranFullTwiddleFactor2X;
extern double btranFullTwiddleFactor1X;
extern double btranFullTwiddleFactor2X;
extern double denseThresholdX;
extern double twoThresholdX;
extern double minRowsSparse;
extern double largeRowsSparse;
extern double mediumRowsDivider;
extern double mediumRowsMinCount;
extern double largeRowsCount;
#endif

//#############################################################################

// Function Prototypes. Function definitions is in this file.
static void testingMessage(const char *const msg);
#if defined(COIN_HAS_AMD) || defined(COIN_HAS_CHOLMOD) || defined(COIN_HAS_GLPK)
static int barrierAvailable = 1;
static std::string nameBarrier = "barrier-UFL";
#elif COIN_HAS_WSMP
static int barrierAvailable = 2;
static std::string nameBarrier = "barrier-WSSMP";
#elif defined(COIN_HAS_MUMPS)
static int barrierAvailable = 3;
static std::string nameBarrier = "barrier-MUMPS";
#else
static int barrierAvailable = 0;
static std::string nameBarrier = "barrier-slow";
#endif
#define NUMBER_ALGORITHMS 12
// If you just want a subset then set some to 1
static int switchOff[NUMBER_ALGORITHMS] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
// shortName - 0 no , 1 yes
ClpSolve setupForSolve(int algorithm, std::string &nameAlgorithm,
  int shortName)
{
  ClpSolve solveOptions;
  /* algorithms are
        0 barrier
        1 dual with volumne crash
        2,3 dual with and without crash
        4,5 primal with and without
        6,7 automatic with and without
        8,9 primal with idiot 1 and 5
        10,11 primal with 70, dual with volume
     */
  switch (algorithm) {
  case 0:
    if (shortName)
      nameAlgorithm = "ba";
    else
      nameAlgorithm = "nameBarrier";
    solveOptions.setSolveType(ClpSolve::useBarrier);
    if (barrierAvailable == 1)
      solveOptions.setSpecialOption(4, 4);
    else if (barrierAvailable == 2)
      solveOptions.setSpecialOption(4, 2);
    break;
  case 1:
#ifdef COIN_HAS_VOL
    if (shortName)
      nameAlgorithm = "du-vol-50";
    else
      nameAlgorithm = "dual-volume-50";
    solveOptions.setSolveType(ClpSolve::useDual);
    solveOptions.setSpecialOption(0, 2, 50); // volume
#else
    solveOptions.setSolveType(ClpSolve::notImplemented);
#endif
    break;
  case 2:
    if (shortName)
      nameAlgorithm = "du-cr";
    else
      nameAlgorithm = "dual-crash";
    solveOptions.setSolveType(ClpSolve::useDual);
    solveOptions.setSpecialOption(0, 1);
    break;
  case 3:
    if (shortName)
      nameAlgorithm = "du";
    else
      nameAlgorithm = "dual";
    solveOptions.setSolveType(ClpSolve::useDual);
    break;
  case 4:
    if (shortName)
      nameAlgorithm = "pr-cr";
    else
      nameAlgorithm = "primal-crash";
    solveOptions.setSolveType(ClpSolve::usePrimal);
    solveOptions.setSpecialOption(1, 1);
    break;
  case 5:
    if (shortName)
      nameAlgorithm = "pr";
    else
      nameAlgorithm = "primal";
    solveOptions.setSolveType(ClpSolve::usePrimal);
    break;
  case 6:
    if (shortName)
      nameAlgorithm = "au-cr";
    else
      nameAlgorithm = "either-crash";
    solveOptions.setSolveType(ClpSolve::automatic);
    solveOptions.setSpecialOption(1, 1);
    break;
  case 7:
    if (shortName)
      nameAlgorithm = "au";
    else
      nameAlgorithm = "either";
    solveOptions.setSolveType(ClpSolve::automatic);
    break;
  case 8:
    if (shortName)
      nameAlgorithm = "pr-id-1";
    else
      nameAlgorithm = "primal-idiot-1";
    solveOptions.setSolveType(ClpSolve::usePrimalorSprint);
    solveOptions.setSpecialOption(1, 2, 1); // idiot
    break;
  case 9:
    if (shortName)
      nameAlgorithm = "pr-id-5";
    else
      nameAlgorithm = "primal-idiot-5";
    solveOptions.setSolveType(ClpSolve::usePrimalorSprint);
    solveOptions.setSpecialOption(1, 2, 5); // idiot
    break;
  case 10:
    if (shortName)
      nameAlgorithm = "pr-id-70";
    else
      nameAlgorithm = "primal-idiot-70";
    solveOptions.setSolveType(ClpSolve::usePrimalorSprint);
    solveOptions.setSpecialOption(1, 2, 70); // idiot
    break;
  case 11:
#ifdef COIN_HAS_VOL
    if (shortName)
      nameAlgorithm = "du-vol";
    else
      nameAlgorithm = "dual-volume";
    solveOptions.setSolveType(ClpSolve::useDual);
    solveOptions.setSpecialOption(0, 2, 3000); // volume
#else
    solveOptions.setSolveType(ClpSolve::notImplemented);
#endif
    break;
  default:
    abort();
  }
  if (shortName) {
    // can switch off
    if (switchOff[algorithm])
      solveOptions.setSolveType(ClpSolve::notImplemented);
  }
  return solveOptions;
}
static void printSol(ClpSimplex &model)
{
  int numberRows = model.numberRows();
  int numberColumns = model.numberColumns();

  double *rowPrimal = model.primalRowSolution();
  double *rowDual = model.dualRowSolution();
  double *rowLower = model.rowLower();
  double *rowUpper = model.rowUpper();

  int iRow;
  double objValue = model.getObjValue();
  printf("Objvalue %g Rows (%d)\n", objValue, numberRows);
  for (iRow = 0; iRow < numberRows; iRow++) {
    printf("%d primal %g dual %g low %g up %g\n",
      iRow, rowPrimal[iRow], rowDual[iRow],
      rowLower[iRow], rowUpper[iRow]);
  }
  double *columnPrimal = model.primalColumnSolution();
  double *columnDual = model.dualColumnSolution();
  double *columnLower = model.columnLower();
  double *columnUpper = model.columnUpper();
  double offset;
  //const double * gradient = model.objectiveAsObject()->gradient(&model,
  //                                                       columnPrimal,offset,true,1);
  const double *gradient = model.objective(columnPrimal, offset);
  int iColumn;
  objValue = -offset - model.objectiveOffset();
  printf("offset %g (%g)\n", offset, model.objectiveOffset());
  printf("Columns (%d)\n", numberColumns);
  for (iColumn = 0; iColumn < numberColumns; iColumn++) {
    printf("%d primal %g dual %g low %g up %g\n",
      iColumn, columnPrimal[iColumn], columnDual[iColumn],
      columnLower[iColumn], columnUpper[iColumn]);
    objValue += columnPrimal[iColumn] * gradient[iColumn];
    if (fabs(columnPrimal[iColumn] * gradient[iColumn]) > 1.0e-8)
      printf("obj -> %g gradient %g\n", objValue, gradient[iColumn]);
  }
  printf("Computed objective %g\n", objValue);
}

void usage(const std::string &key)
{
  std::cerr
    << "Undefined parameter \"" << key << "\".\n"
    << "Correct usage: \n"
    << "  clp [-dirSample=V1] [-dirNetlib=V2] [-netlib]\n"
    << "  where:\n"
    << "    -dirSample: directory containing mps test files\n"
    << "        Default value V1=\"../../Data/Sample\"\n"
    << "    -dirNetlib: directory containing netlib files\"\n"
    << "        Default value V2=\"../../Data/Netlib\"\n"
    << "    -netlib\n"
    << "        If specified, then netlib testset run as well as the nitTest.\n";
}
#if FACTORIZATION_STATISTICS
int loSizeX = -1;
int hiSizeX = 1000000;
#endif
//----------------------------------------------------------------
#ifndef ABC_INHERIT
#define AnySimplex ClpSimplex
#else
#include "AbcSimplex.hpp"
#define AnySimplex AbcSimplex
#endif
int mainTest(int argc, const char *argv[], int algorithm,
  AnySimplex empty, ClpSolve solveOptionsIn,
  int switchOffValue, bool doVector)
{
  int i;

  if (switchOffValue > 0) {
    // switch off some
    int iTest;
    for (iTest = 0; iTest < NUMBER_ALGORITHMS; iTest++) {
#ifndef NDEBUG
      int bottom = switchOffValue % 10;
      assert(bottom == 0 || bottom == 1);
#endif
      switchOffValue /= 10;
      switchOff[iTest] = 0;
    }
  }
  int numberFailures = 0;
  // define valid parameter keywords
  std::set< std::string > definedKeyWords;
  definedKeyWords.insert("-dirSample");
  definedKeyWords.insert("-dirNetlib");
  definedKeyWords.insert("-netlib");

  // Create a map of parameter keys and associated data
  std::map< std::string, std::string > parms;
  for (i = 1; i < argc; i++) {
    std::string parm(argv[i]);
    std::string key, value;
    std::string::size_type eqPos = parm.find('=');

    // Does parm contain and '='
    if (eqPos == std::string::npos) {
      //Parm does not contain '='
      key = parm;
    } else {
      key = parm.substr(0, eqPos);
      value = parm.substr(eqPos + 1);
    }

    // Is specifed key valid?
    if (definedKeyWords.find(key) == definedKeyWords.end()) {
      // invalid key word.
      // Write help text
      usage(key);
      return 1;
    }
    parms[key] = value;
  }

  const char dirsep = CoinFindDirSeparator();
  // Set directory containing mps data files.
  std::string dirSample;
  if (parms.find("-dirSample") != parms.end())
    dirSample = parms["-dirSample"];
  else
    dirSample = dirsep == '/' ? "../../Data/Sample/" : "..\\..\\Data\\Sample\\";

  // Set directory containing netlib data files.
  std::string dirNetlib;
  if (parms.find("-dirNetlib") != parms.end())
    dirNetlib = parms["-dirNetlib"];
  else
    dirNetlib = dirsep == '/' ? "../../Data/Netlib/" : "..\\..\\Data\\Netlib\\";
#if FACTORIZATION_STATISTICS == 0
  if (!empty.numberRows()) {
    testingMessage("Testing ClpSimplex\n");
    ClpSimplexUnitTest(dirSample);
  }
#endif
  if (parms.find("-netlib") != parms.end() || empty.numberRows()) {
    unsigned int m;
    std::string sizeLoHi;
#if FACTORIZATION_STATISTICS
    double ftranTwiddleFactor1XChoice[3] = { 0.9, 1.0, 1.1 };
    double ftranTwiddleFactor2XChoice[3] = { 0.9, 1.0, 1.1 };
    double ftranFTTwiddleFactor1XChoice[3] = { 0.9, 1.0, 1.1 };
    double ftranFTTwiddleFactor2XChoice[3] = { 0.9, 1.0, 1.1 };
    double btranTwiddleFactor1XChoice[3] = { 0.9, 1.0, 1.1 };
    double btranTwiddleFactor2XChoice[3] = { 0.9, 1.0, 1.1 };
    double ftranFullTwiddleFactor1XChoice[3] = { 0.9, 1.0, 1.1 };
    double ftranFullTwiddleFactor2XChoice[3] = { 0.9, 1.0, 1.1 };
    double btranFullTwiddleFactor1XChoice[3] = { 0.9, 1.0, 1.1 };
    double btranFullTwiddleFactor2XChoice[3] = { 0.9, 1.0, 1.1 };
    double denseThresholdXChoice[3] = { 2, 20, 40 };
    double twoThresholdXChoice[3] = { 800, 1000, 1200 };
    double minRowsSparseChoice[3] = { 250, 300, 350 };
    double largeRowsSparseChoice[3] = { 8000, 10000, 12000 };
    double mediumRowsDividerChoice[3] = { 5, 6, 7 };
    double mediumRowsMinCountChoice[3] = { 300, 500, 600 };
    double largeRowsCountChoice[3] = { 700, 1000, 1300 };
    double times[3 * 3 * 3 * 3 * 3];
    memset(times, 0, sizeof(times));
#define whichParam(za, zname)            \
  const char *choice##za = #zname;       \
  const double *use##za = zname##Choice; \
  double *external##za = &zname
    whichParam(A, denseThresholdX);
    whichParam(B, twoThresholdX);
    whichParam(C, minRowsSparse);
    whichParam(D, mediumRowsDivider);
    whichParam(E, mediumRowsMinCount);
#endif
    // Define test problems:
    //   mps names,
    //   maximization or minimization,
    //   Number of rows and columns in problem, and
    //   objective function value
    std::vector< std::string > mpsName;
    std::vector< bool > min;
    std::vector< int > nRows;
    std::vector< int > nCols;
    std::vector< double > objValue;
    std::vector< double > objValueTol;
    // 100 added means no presolve
    std::vector< int > bestStrategy;
    if (empty.numberRows()) {
      std::string alg;
      for (int iTest = 0; iTest < NUMBER_ALGORITHMS; iTest++) {
        ClpSolve solveOptions = setupForSolve(iTest, alg, 0);
        printf("%d %s ", iTest, alg.c_str());
        if (switchOff[iTest])
          printf("skipped by user\n");
        else if (solveOptions.getSolveType() == ClpSolve::notImplemented)
          printf("skipped as not available\n");
        else
          printf("will be tested\n");
      }
    }
    if (!empty.numberRows()) {
      mpsName.push_back("25fv47");
      min.push_back(true);
      nRows.push_back(822);
      nCols.push_back(1571);
      objValueTol.push_back(1.e-8);
      objValue.push_back(5.5018458883E+03);
      bestStrategy.push_back(0);
      mpsName.push_back("80bau3b");
      min.push_back(true);
      nRows.push_back(2263);
      nCols.push_back(9799);
      objValueTol.push_back(1.e-8);
      objValue.push_back(9.8722419241E+05);
      bestStrategy.push_back(3);
      mpsName.push_back("blend");
      min.push_back(true);
      nRows.push_back(75);
      nCols.push_back(83);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-3.0812149846e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("pilotnov");
      min.push_back(true);
      nRows.push_back(976);
      nCols.push_back(2172);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-4.4972761882e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("maros-r7");
      min.push_back(true);
      nRows.push_back(3137);
      nCols.push_back(9408);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4971851665e+06);
      bestStrategy.push_back(2);
      mpsName.push_back("pilot");
      min.push_back(true);
      nRows.push_back(1442);
      nCols.push_back(3652);
      objValueTol.push_back(1.e-5);
      objValue.push_back(/*-5.5740430007e+02*/ -557.48972927292);
      bestStrategy.push_back(3);
      mpsName.push_back("pilot4");
      min.push_back(true);
      nRows.push_back(411);
      nCols.push_back(1000);
      objValueTol.push_back(5.e-5);
      objValue.push_back(-2.5811392641e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("pilot87");
      min.push_back(true);
      nRows.push_back(2031);
      nCols.push_back(4883);
      objValueTol.push_back(1.e-4);
      objValue.push_back(3.0171072827e+02);
      bestStrategy.push_back(0);
      mpsName.push_back("adlittle");
      min.push_back(true);
      nRows.push_back(57);
      nCols.push_back(97);
      objValueTol.push_back(1.e-8);
      objValue.push_back(2.2549496316e+05);
      bestStrategy.push_back(3);
      mpsName.push_back("afiro");
      min.push_back(true);
      nRows.push_back(28);
      nCols.push_back(32);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-4.6475314286e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("agg");
      min.push_back(true);
      nRows.push_back(489);
      nCols.push_back(163);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-3.5991767287e+07);
      bestStrategy.push_back(3);
      mpsName.push_back("agg2");
      min.push_back(true);
      nRows.push_back(517);
      nCols.push_back(302);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-2.0239252356e+07);
      bestStrategy.push_back(3);
      mpsName.push_back("agg3");
      min.push_back(true);
      nRows.push_back(517);
      nCols.push_back(302);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.0312115935e+07);
      bestStrategy.push_back(4);
      mpsName.push_back("bandm");
      min.push_back(true);
      nRows.push_back(306);
      nCols.push_back(472);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.5862801845e+02);
      bestStrategy.push_back(2);
      mpsName.push_back("beaconfd");
      min.push_back(true);
      nRows.push_back(174);
      nCols.push_back(262);
      objValueTol.push_back(1.e-8);
      objValue.push_back(3.3592485807e+04);
      bestStrategy.push_back(0);
      mpsName.push_back("bnl1");
      min.push_back(true);
      nRows.push_back(644);
      nCols.push_back(1175);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.9776295615E+03);
      bestStrategy.push_back(3);
      mpsName.push_back("bnl2");
      min.push_back(true);
      nRows.push_back(2325);
      nCols.push_back(3489);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.8112365404e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("boeing1");
      min.push_back(true);
      nRows.push_back(/*351*/ 352);
      nCols.push_back(384);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-3.3521356751e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("boeing2");
      min.push_back(true);
      nRows.push_back(167);
      nCols.push_back(143);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-3.1501872802e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("bore3d");
      min.push_back(true);
      nRows.push_back(234);
      nCols.push_back(315);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.3730803942e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("brandy");
      min.push_back(true);
      nRows.push_back(221);
      nCols.push_back(249);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.5185098965e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("capri");
      min.push_back(true);
      nRows.push_back(272);
      nCols.push_back(353);
      objValueTol.push_back(1.e-8);
      objValue.push_back(2.6900129138e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("cycle");
      min.push_back(true);
      nRows.push_back(1904);
      nCols.push_back(2857);
      objValueTol.push_back(1.e-9);
      objValue.push_back(-5.2263930249e+00);
      bestStrategy.push_back(3);
      mpsName.push_back("czprob");
      min.push_back(true);
      nRows.push_back(930);
      nCols.push_back(3523);
      objValueTol.push_back(1.e-8);
      objValue.push_back(2.1851966989e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("d2q06c");
      min.push_back(true);
      nRows.push_back(2172);
      nCols.push_back(5167);
      objValueTol.push_back(1.e-7);
      objValue.push_back(122784.21557456);
      bestStrategy.push_back(0);
      mpsName.push_back("d6cube");
      min.push_back(true);
      nRows.push_back(416);
      nCols.push_back(6184);
      objValueTol.push_back(1.e-7);
      objValue.push_back(3.1549166667e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("degen2");
      min.push_back(true);
      nRows.push_back(445);
      nCols.push_back(534);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.4351780000e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("degen3");
      min.push_back(true);
      nRows.push_back(1504);
      nCols.push_back(1818);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-9.8729400000e+02);
      bestStrategy.push_back(2);
      mpsName.push_back("dfl001");
      min.push_back(true);
      nRows.push_back(6072);
      nCols.push_back(12230);
      objValueTol.push_back(1.e-5);
      objValue.push_back(1.1266396047E+07);
      bestStrategy.push_back(5);
      mpsName.push_back("e226");
      min.push_back(true);
      nRows.push_back(224);
      nCols.push_back(282);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.8751929066e+01 + 7.113);
      bestStrategy.push_back(3); // The correct answer includes -7.113 term. This is a constant in the objective function. See line 1683 of the mps file.
      mpsName.push_back("etamacro");
      min.push_back(true);
      nRows.push_back(401);
      nCols.push_back(688);
      objValueTol.push_back(1.e-6);
      objValue.push_back(-7.5571521774e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("fffff800");
      min.push_back(true);
      nRows.push_back(525);
      nCols.push_back(854);
      objValueTol.push_back(1.e-6);
      objValue.push_back(5.5567961165e+05);
      bestStrategy.push_back(3);
      mpsName.push_back("finnis");
      min.push_back(true);
      nRows.push_back(498);
      nCols.push_back(614);
      objValueTol.push_back(1.e-6);
      objValue.push_back(1.7279096547e+05);
      bestStrategy.push_back(3);
      mpsName.push_back("fit1d");
      min.push_back(true);
      nRows.push_back(25);
      nCols.push_back(1026);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-9.1463780924e+03);
      bestStrategy.push_back(3 + 100);
      mpsName.push_back("fit1p");
      min.push_back(true);
      nRows.push_back(628);
      nCols.push_back(1677);
      objValueTol.push_back(1.e-8);
      objValue.push_back(9.1463780924e+03);
      bestStrategy.push_back(5 + 100);
      mpsName.push_back("fit2d");
      min.push_back(true);
      nRows.push_back(26);
      nCols.push_back(10500);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-6.8464293294e+04);
      bestStrategy.push_back(3 + 100);
      mpsName.push_back("fit2p");
      min.push_back(true);
      nRows.push_back(3001);
      nCols.push_back(13525);
      objValueTol.push_back(1.e-9);
      objValue.push_back(6.8464293232e+04);
      bestStrategy.push_back(5 + 100);
      mpsName.push_back("forplan");
      min.push_back(true);
      nRows.push_back(162);
      nCols.push_back(421);
      objValueTol.push_back(1.e-6);
      objValue.push_back(-6.6421873953e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("ganges");
      min.push_back(true);
      nRows.push_back(1310);
      nCols.push_back(1681);
      objValueTol.push_back(1.e-5);
      objValue.push_back(-1.0958636356e+05);
      bestStrategy.push_back(3);
      mpsName.push_back("gfrd-pnc");
      min.push_back(true);
      nRows.push_back(617);
      nCols.push_back(1092);
      objValueTol.push_back(1.e-8);
      objValue.push_back(6.9022359995e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("greenbea");
      min.push_back(true);
      nRows.push_back(2393);
      nCols.push_back(5405);
      objValueTol.push_back(1.e-8);
      objValue.push_back(/*-7.2462405908e+07*/ -72555248.129846);
      bestStrategy.push_back(3);
      mpsName.push_back("greenbeb");
      min.push_back(true);
      nRows.push_back(2393);
      nCols.push_back(5405);
      objValueTol.push_back(1.e-8);
      objValue.push_back(/*-4.3021476065e+06*/ -4302260.2612066);
      bestStrategy.push_back(3);
      mpsName.push_back("grow15");
      min.push_back(true);
      nRows.push_back(301);
      nCols.push_back(645);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.0687094129e+08);
      bestStrategy.push_back(4 + 100);
      mpsName.push_back("grow22");
      min.push_back(true);
      nRows.push_back(441);
      nCols.push_back(946);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.6083433648e+08);
      bestStrategy.push_back(4 + 100);
      mpsName.push_back("grow7");
      min.push_back(true);
      nRows.push_back(141);
      nCols.push_back(301);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-4.7787811815e+07);
      bestStrategy.push_back(4 + 100);
      mpsName.push_back("israel");
      min.push_back(true);
      nRows.push_back(175);
      nCols.push_back(142);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-8.9664482186e+05);
      bestStrategy.push_back(2);
      mpsName.push_back("kb2");
      min.push_back(true);
      nRows.push_back(44);
      nCols.push_back(41);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.7499001299e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("lotfi");
      min.push_back(true);
      nRows.push_back(154);
      nCols.push_back(308);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-2.5264706062e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("maros");
      min.push_back(true);
      nRows.push_back(847);
      nCols.push_back(1443);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-5.8063743701e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("modszk1");
      min.push_back(true);
      nRows.push_back(688);
      nCols.push_back(1620);
      objValueTol.push_back(1.e-8);
      objValue.push_back(3.2061972906e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("nesm");
      min.push_back(true);
      nRows.push_back(663);
      nCols.push_back(2923);
      objValueTol.push_back(1.e-5);
      objValue.push_back(1.4076073035e+07);
      bestStrategy.push_back(2);
      mpsName.push_back("perold");
      min.push_back(true);
      nRows.push_back(626);
      nCols.push_back(1376);
      objValueTol.push_back(1.e-6);
      objValue.push_back(-9.3807580773e+03);
      bestStrategy.push_back(3);
      //mpsName.push_back("qap12");min.push_back(true);nRows.push_back(3193);nCols.push_back(8856);objValueTol.push_back(1.e-6);objValue.push_back(5.2289435056e+02);bestStrategy.push_back(3);
      //mpsName.push_back("qap15");min.push_back(true);nRows.push_back(6331);nCols.push_back(22275);objValueTol.push_back(1.e-8);objValue.push_back(1.0409940410e+03);bestStrategy.push_back(3);
      mpsName.push_back("recipe");
      min.push_back(true);
      nRows.push_back(92);
      nCols.push_back(180);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-2.6661600000e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("sc105");
      min.push_back(true);
      nRows.push_back(106);
      nCols.push_back(103);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-5.2202061212e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("sc205");
      min.push_back(true);
      nRows.push_back(206);
      nCols.push_back(203);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-5.2202061212e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("sc50a");
      min.push_back(true);
      nRows.push_back(51);
      nCols.push_back(48);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-6.4575077059e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("sc50b");
      min.push_back(true);
      nRows.push_back(51);
      nCols.push_back(48);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-7.0000000000e+01);
      bestStrategy.push_back(3);
      mpsName.push_back("scagr25");
      min.push_back(true);
      nRows.push_back(472);
      nCols.push_back(500);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-1.4753433061e+07);
      bestStrategy.push_back(3);
      mpsName.push_back("scagr7");
      min.push_back(true);
      nRows.push_back(130);
      nCols.push_back(140);
      objValueTol.push_back(1.e-6);
      objValue.push_back(-2.3313892548e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("scfxm1");
      min.push_back(true);
      nRows.push_back(331);
      nCols.push_back(457);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.8416759028e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("scfxm2");
      min.push_back(true);
      nRows.push_back(661);
      nCols.push_back(914);
      objValueTol.push_back(1.e-8);
      objValue.push_back(3.6660261565e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("scfxm3");
      min.push_back(true);
      nRows.push_back(991);
      nCols.push_back(1371);
      objValueTol.push_back(1.e-8);
      objValue.push_back(5.4901254550e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("scorpion");
      min.push_back(true);
      nRows.push_back(389);
      nCols.push_back(358);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.8781248227e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("scrs8");
      min.push_back(true);
      nRows.push_back(491);
      nCols.push_back(1169);
      objValueTol.push_back(1.e-5);
      objValue.push_back(9.0429998619e+02);
      bestStrategy.push_back(2);
      mpsName.push_back("scsd1");
      min.push_back(true);
      nRows.push_back(78);
      nCols.push_back(760);
      objValueTol.push_back(1.e-8);
      objValue.push_back(8.6666666743e+00);
      bestStrategy.push_back(3 + 100);
      mpsName.push_back("scsd6");
      min.push_back(true);
      nRows.push_back(148);
      nCols.push_back(1350);
      objValueTol.push_back(1.e-8);
      objValue.push_back(5.0500000078e+01);
      bestStrategy.push_back(3 + 100);
      mpsName.push_back("scsd8");
      min.push_back(true);
      nRows.push_back(398);
      nCols.push_back(2750);
      objValueTol.push_back(1.e-7);
      objValue.push_back(9.0499999993e+02);
      bestStrategy.push_back(1 + 100);
      mpsName.push_back("sctap1");
      min.push_back(true);
      nRows.push_back(301);
      nCols.push_back(480);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4122500000e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("sctap2");
      min.push_back(true);
      nRows.push_back(1091);
      nCols.push_back(1880);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.7248071429e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("sctap3");
      min.push_back(true);
      nRows.push_back(1481);
      nCols.push_back(2480);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4240000000e+03);
      bestStrategy.push_back(3);
      mpsName.push_back("seba");
      min.push_back(true);
      nRows.push_back(516);
      nCols.push_back(1028);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.5711600000e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("share1b");
      min.push_back(true);
      nRows.push_back(118);
      nCols.push_back(225);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-7.6589318579e+04);
      bestStrategy.push_back(3);
      mpsName.push_back("share2b");
      min.push_back(true);
      nRows.push_back(97);
      nCols.push_back(79);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-4.1573224074e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("shell");
      min.push_back(true);
      nRows.push_back(537);
      nCols.push_back(1775);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.2088253460e+09);
      bestStrategy.push_back(3);
      mpsName.push_back("ship04l");
      min.push_back(true);
      nRows.push_back(403);
      nCols.push_back(2118);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.7933245380e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("ship04s");
      min.push_back(true);
      nRows.push_back(403);
      nCols.push_back(1458);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.7987147004e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("ship08l");
      min.push_back(true);
      nRows.push_back(779);
      nCols.push_back(4283);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.9090552114e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("ship08s");
      min.push_back(true);
      nRows.push_back(779);
      nCols.push_back(2387);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.9200982105e+06);
      bestStrategy.push_back(2);
      mpsName.push_back("ship12l");
      min.push_back(true);
      nRows.push_back(1152);
      nCols.push_back(5427);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4701879193e+06);
      bestStrategy.push_back(3);
      mpsName.push_back("ship12s");
      min.push_back(true);
      nRows.push_back(1152);
      nCols.push_back(2763);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4892361344e+06);
      bestStrategy.push_back(2);
      mpsName.push_back("sierra");
      min.push_back(true);
      nRows.push_back(1228);
      nCols.push_back(2036);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.5394362184e+07);
      bestStrategy.push_back(3);
      mpsName.push_back("stair");
      min.push_back(true);
      nRows.push_back(357);
      nCols.push_back(467);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-2.5126695119e+02);
      bestStrategy.push_back(3);
      mpsName.push_back("standata");
      min.push_back(true);
      nRows.push_back(360);
      nCols.push_back(1075);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.2576995000e+03);
      bestStrategy.push_back(3);
      //mpsName.push_back("standgub");min.push_back(true);nRows.push_back(362);nCols.push_back(1184);objValueTol.push_back(1.e-8);objValue.push_back(1257.6995); bestStrategy.push_back(3);
      mpsName.push_back("standmps");
      min.push_back(true);
      nRows.push_back(468);
      nCols.push_back(1075);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.4060175000E+03);
      bestStrategy.push_back(3);
      mpsName.push_back("stocfor1");
      min.push_back(true);
      nRows.push_back(118);
      nCols.push_back(111);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-4.1131976219E+04);
      bestStrategy.push_back(3);
      mpsName.push_back("stocfor2");
      min.push_back(true);
      nRows.push_back(2158);
      nCols.push_back(2031);
      objValueTol.push_back(1.e-8);
      objValue.push_back(-3.9024408538e+04);
      bestStrategy.push_back(3);
      //mpsName.push_back("stocfor3");min.push_back(true);nRows.push_back(16676);nCols.push_back(15695);objValueTol.push_back(1.e-8);objValue.push_back(-3.9976661576e+04);bestStrategy.push_back(3);
      //mpsName.push_back("truss");min.push_back(true);nRows.push_back(1001);nCols.push_back(8806);objValueTol.push_back(1.e-8);objValue.push_back(4.5881584719e+05);bestStrategy.push_back(3);
      mpsName.push_back("tuff");
      min.push_back(true);
      nRows.push_back(334);
      nCols.push_back(587);
      objValueTol.push_back(1.e-8);
      objValue.push_back(2.9214776509e-01);
      bestStrategy.push_back(3);
      mpsName.push_back("vtpbase");
      min.push_back(true);
      nRows.push_back(199);
      nCols.push_back(203);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.2983146246e+05);
      bestStrategy.push_back(3);
      mpsName.push_back("wood1p");
      min.push_back(true);
      nRows.push_back(245);
      nCols.push_back(2594);
      objValueTol.push_back(5.e-5);
      objValue.push_back(1.4429024116e+00);
      bestStrategy.push_back(3);
      mpsName.push_back("woodw");
      min.push_back(true);
      nRows.push_back(1099);
      nCols.push_back(8405);
      objValueTol.push_back(1.e-8);
      objValue.push_back(1.3044763331E+00);
      bestStrategy.push_back(3);
    } else {
      // Just testing one
      mpsName.push_back(empty.problemName());
      min.push_back(true);
      nRows.push_back(-1);
      nCols.push_back(-1);
      objValueTol.push_back(1.e-8);
      objValue.push_back(0.0);
      bestStrategy.push_back(0);
      int iTest;
      std::string alg;
      for (iTest = 0; iTest < NUMBER_ALGORITHMS; iTest++) {
        ClpSolve solveOptions = setupForSolve(iTest, alg, 0);
        printf("%d %s ", iTest, alg.c_str());
        if (switchOff[iTest])
          printf("skipped by user\n");
        else if (solveOptions.getSolveType() == ClpSolve::notImplemented)
          printf("skipped as not available\n");
        else
          printf("will be tested\n");
      }
    }

    double timeTaken = 0.0;
    if (!barrierAvailable)
      switchOff[0] = 1;
    // Loop once for each Mps File
    for (m = 0; m < mpsName.size(); m++) {
#if FACTORIZATION_STATISTICS
      if (nRows[m] < loSizeX || nRows[m] >= hiSizeX) {
        std::cerr << "  skipping mps file: " << mpsName[m]
                  << " as " << nRows[m]
                  << " (" << m + 1 << " out of " << mpsName.size() << ")" << std::endl;
        continue;
      }
#endif
      std::cerr << "  processing mps file: " << mpsName[m]
                << " (" << m + 1 << " out of " << mpsName.size() << ")" << std::endl;
      AnySimplex solutionBase = empty;
      std::string fn = dirNetlib + mpsName[m];
      if (!empty.numberRows() || algorithm < 6) {
        // Read data mps file,
        CoinMpsIO mps;
        int nerrors = mps.readMps(fn.c_str(), "mps");
        if (nerrors) {
          std::cerr << "Error " << nerrors << " when reading model from "
                    << fn.c_str() << "! Aborting tests.\n";
          return 1;
        }
        solutionBase.loadProblem(*mps.getMatrixByCol(), mps.getColLower(),
          mps.getColUpper(),
          mps.getObjCoefficients(),
          mps.getRowLower(), mps.getRowUpper());

        solutionBase.setDblParam(ClpObjOffset, mps.objectiveOffset());
      }

      // Runs through strategies
      if (algorithm == 6 || algorithm == 7) {
        // algorithms tested are at top of file
        double testTime[NUMBER_ALGORITHMS];
        std::string alg[NUMBER_ALGORITHMS];
        int iTest;
        for (iTest = 0; iTest < NUMBER_ALGORITHMS; iTest++) {
          ClpSolve solveOptions = setupForSolve(iTest, alg[iTest], 1);
          if (solveOptions.getSolveType() != ClpSolve::notImplemented) {
            double time1 = CoinCpuTime();
            ClpSimplex solution = solutionBase;
            if (solution.maximumSeconds() < 0.0)
              solution.setMaximumSeconds(120.0);
            if (doVector) {
              ClpMatrixBase *matrix = solution.clpMatrix();
              if (dynamic_cast< ClpPackedMatrix * >(matrix)) {
                ClpPackedMatrix *clpMatrix = dynamic_cast< ClpPackedMatrix * >(matrix);
                clpMatrix->makeSpecialColumnCopy();
              }
            }
            solution.initialSolve(solveOptions);
            double time2 = CoinCpuTime() - time1;
            testTime[iTest] = time2;
            printf("Finished %s Took %g seconds (%d iterations) - status %d\n",
              mpsName[m].c_str(), time2, solution.problemStatus(), solution.numberIterations());
            if (solution.problemStatus())
              testTime[iTest] = 1.0e20;
          } else {
            testTime[iTest] = 1.0e30;
          }
        }
        int iBest = -1;
        double dBest = 1.0e10;
        printf("%s", fn.c_str());
        for (iTest = 0; iTest < NUMBER_ALGORITHMS; iTest++) {
          if (testTime[iTest] < 1.0e30) {
            printf(" %s %g",
              alg[iTest].c_str(), testTime[iTest]);
            if (testTime[iTest] < dBest) {
              dBest = testTime[iTest];
              iBest = iTest;
            }
          }
        }
        printf("\n");
        if (iBest >= 0)
          printf("Best strategy for %s is %s (%d) which takes %g seconds\n",
            fn.c_str(), alg[iBest].c_str(), iBest, testTime[iBest]);
        else
          printf("No strategy finished in time limit\n");
        continue;
      }
      double time1 = CoinCpuTime();
      AnySimplex solution = solutionBase;
#if 0
               solution.setOptimizationDirection(-1);
               {
                    int j;
                    double * obj = solution.objective();
                    int n = solution.numberColumns();
                    for (j = 0; j < n; j++)
                         obj[j] *= -1.0;
               }
#endif
      ClpSolve::SolveType method;
      ClpSolve solveOptions = solveOptionsIn;
      std::string nameAlgorithm;
      if (algorithm != 5) {
        if (algorithm == 0) {
          method = ClpSolve::useDual;
          nameAlgorithm = "dual";
        } else if (algorithm == 1) {
          method = ClpSolve::usePrimalorSprint;
          nameAlgorithm = "primal";
        } else if (algorithm == 3) {
          method = ClpSolve::automatic;
          nameAlgorithm = "either";
        } else {
          nameAlgorithm = "barrier-slow";
#if defined(COIN_HAS_AMD) || defined(COIN_HAS_CHOLMOD) || defined(COIN_HAS_GLPK)
          solveOptions.setSpecialOption(4, 4);
          nameAlgorithm = "barrier-UFL";
#endif
#ifdef COIN_HAS_WSMP
          solveOptions.setSpecialOption(4, 2);
          nameAlgorithm = "barrier-WSSMP";
#endif
#ifdef COIN_HAS_MUMPS
          solveOptions.setSpecialOption(4, 6);
          nameAlgorithm = "barrier-MUMPS";
#endif
          method = ClpSolve::useBarrier;
        }
        solveOptions.setSolveType(method);
      } else {
        int iAlg = bestStrategy[m];
        int presolveOff = iAlg / 100;
        iAlg = iAlg % 100;
        if (!barrierAvailable && iAlg == 0) {
          if (nRows[m] != 2172)
            iAlg = 5; // try primal
          else
            iAlg = 3; // d2q06c
        }
        solveOptions = setupForSolve(iAlg, nameAlgorithm, 0);
        if (presolveOff)
          solveOptions.setPresolveType(ClpSolve::presolveOff);
      }
      if (doVector) {
        ClpMatrixBase *matrix = solution.clpMatrix();
        if (dynamic_cast< ClpPackedMatrix * >(matrix)) {
          ClpPackedMatrix *clpMatrix = dynamic_cast< ClpPackedMatrix * >(matrix);
          clpMatrix->makeSpecialColumnCopy();
        }
      }
#if FACTORIZATION_STATISTICS
      double timesOne[3 * 3 * 3 * 3 * 3];
      memset(timesOne, 0, sizeof(timesOne));
      int iterationsOne[3 * 3 * 3 * 3 * 3];
      memset(iterationsOne, 0, sizeof(iterationsOne));
      AnySimplex saveModel(solution);
      double time2;
#if 0
               solution.initialSolve(solveOptions);
               time2 = CoinCpuTime() - time1;
               timeTaken += time2;
               printf("%s took %g seconds using algorithm %s\n", fn.c_str(), time2, nameAlgorithm.c_str());
#endif
#define loA 1
#define loB 0
#define loC 0
#define loD 1
#define loE 1
#define hiA 2
#define hiB 1
#define hiC 1
#define hiD 2
#define hiE 2
      time2 = CoinCpuTime();
      for (int iA = loA; iA < hiA; iA++) {
        *externalA = useA[iA];
        for (int iB = loB; iB < hiB; iB++) {
          *externalB = useB[iB];
          for (int iC = loC; iC < hiC; iC++) {
            *externalC = useC[iC];
            for (int iD = loD; iD < hiD; iD++) {
              *externalD = useD[iD];
              for (int iE = loE; iE < hiE; iE++) {
                *externalE = useE[iE];
                solution = saveModel;
                solution.initialSolve(solveOptions);
                double time3 = CoinCpuTime();
                printf("Finished %s Took %g seconds (%d iterations) - status %d\n",
                  mpsName[m].c_str(), time3 - time2, solution.numberIterations(), solution.problemStatus());
                iterationsOne[iA + 3 * iB + 9 * iC + 27 * iD + 81 * iE] = solution.numberIterations();
                timesOne[iA + 3 * iB + 9 * iC + 27 * iD + 81 * iE] = time3 - time2;
                times[iA + 3 * iB + 9 * iC + 27 * iD + 81 * iE] += time3 - time2;
                time2 = time3;
              }
            }
          }
        }
      }
      double bestTime = 1.0e100;
      int iBestTime = -1;
      double bestTimePer = 1.0e100;
      int iBestTimePer = -1;
      int bestIterations = 1000000;
      int iBestIterations = -1;
      printf("TTimes ");
      for (int i = 0; i < 3 * 3 * 3 * 3 * 3; i++) {
        // skip if not done
        if (!iterationsOne[i])
          continue;
        double average = timesOne[i] / static_cast< double >(iterationsOne[i]);
        if (timesOne[i] < bestTime) {
          bestTime = timesOne[i];
          iBestTime = i;
        }
        if (average < bestTimePer) {
          bestTimePer = average;
          iBestTimePer = i;
        }
        if (iterationsOne[i] < bestIterations) {
          bestIterations = iterationsOne[i];
          iBestIterations = i;
        }
        printf("%.2f ", timesOne[i]);
      }
      printf("\n");
      int iA, iB, iC, iD, iE;
      iA = iBestTime;
      iE = iA / 81;
      iA -= 81 * iE;
      iD = iA / 27;
      iA -= 27 * iD;
      iC = iA / 9;
      iA -= 9 * iC;
      iB = iA / 3;
      iA -= 3 * iB;
      printf("Best time %.2f %s=%g %s=%g %s=%g %s=%g %s=%g\n", bestTime, choiceA, useA[iA],
        choiceB, useB[iB], choiceC, useC[iC], choiceD, useD[iD], choiceE, useE[iE]);
      iA = iBestTimePer;
      iE = iA / 81;
      iA -= 81 * iE;
      iD = iA / 27;
      iA -= 27 * iD;
      iC = iA / 9;
      iA -= 9 * iC;
      iB = iA / 3;
      iA -= 3 * iB;
      printf("Best time per iteration %g %s=%g %s=%g %s=%g %s=%g %s=%g\n", bestTimePer, choiceA, useA[iA],
        choiceB, useB[iB], choiceC, useC[iC], choiceD, useD[iD], choiceE, useE[iE]);
      iA = iBestIterations;
      iE = iA / 81;
      iA -= 81 * iE;
      iD = iA / 27;
      iA -= 27 * iD;
      iC = iA / 9;
      iA -= 9 * iC;
      iB = iA / 3;
      iA -= 3 * iB;
      printf("Best iterations %d %s=%g %s=%g %s=%g %s=%g %s=%g\n", bestIterations, choiceA, useA[iA],
        choiceB, useB[iB], choiceC, useC[iC], choiceD, useD[iD], choiceE, useE[iE]);
#else
      solution.initialSolve(solveOptions);
      double time2 = CoinCpuTime() - time1;
      timeTaken += time2;
      printf("%s took %g seconds using algorithm %s\n", fn.c_str(), time2, nameAlgorithm.c_str());
#endif
      // Test objective solution value
      {
        if (!solution.isProvenOptimal()) {
          std::cerr << "** NOT OPTIMAL ";
          numberFailures++;
        }
        double soln = solution.objectiveValue();
        CoinRelFltEq eq(objValueTol[m]);
        std::cerr << soln << ",  " << objValue[m] << " diff " << soln - objValue[m] << std::endl;
        if (!eq(soln, objValue[m])) {
          printf("** difference fails\n");
          numberFailures++;
        }
      }
    }
    printf("Total time %g seconds\n", timeTaken);
#if FACTORIZATION_STATISTICS
    double bestTime = 1.0e100;
    int iBestTime = -1;
    for (int i = 0; i < 3 * 3 * 3 * 3 * 3; i++) {
      if (times[i] && times[i] < bestTime) {
        bestTime = times[i];
        iBestTime = i;
      }
    }
    for (int iA = 0; iA < hiA; iA++) {
      for (int iB = 0; iB < hiB; iB++) {
        for (int iC = 0; iC < hiC; iC++) {
          for (int iD = loD; iD < hiD; iD++) {
            for (int iE = loE; iE < hiE; iE++) {
              int k = iA + 3 * iB + 9 * iC + 27 * iD + 81 * iE;
              double thisTime = times[k];
              if (thisTime) {
                if (k == iBestTime)
                  printf("** ");
                printf("%s=%g %s=%g %s=%g %s=%g %s=%g - time %.2f\n",
                  choiceA, useA[iA],
                  choiceB, useB[iB], choiceC, useC[iC],
                  choiceD, useD[iD], choiceE, useE[iE], thisTime);
              }
            }
          }
        }
      }
    }
    //exit(0);
#endif
  } else {
    testingMessage("***Skipped Testing on netlib    ***\n");
    testingMessage("***use -netlib to test class***\n");
  }
  if (!numberFailures)
    testingMessage("All tests completed successfully\n");
  else
    testingMessage("Some tests failed\n");
  return 0;
}

// Display message on stdout and stderr
static void testingMessage(const char *const msg)
{
  std::cerr << msg;
  //cout <<endl <<"*****************************************"
  //     <<endl <<msg <<endl;
}

//--------------------------------------------------------------------------
// test factorization methods and simplex method and simple barrier
void ClpSimplexUnitTest(const std::string &dirSample)
{

  CoinRelFltEq eq(0.000001);

  {
    ClpSimplex solution;

    // matrix data
    //deliberate hiccup of 2 between 0 and 1
    CoinBigIndex start[5] = { 0, 4, 7, 8, 9 };
    int length[5] = { 2, 3, 1, 1, 1 };
    int rows[11] = { 0, 2, -1, -1, 0, 1, 2, 0, 1, 2 };
    double elements[11] = { 7.0, 2.0, 1.0e10, 1.0e10, -2.0, 1.0, -2.0, 1, 1, 1 };
    CoinPackedMatrix matrix(true, 3, 5, 8, elements, rows, start, length);

    // rim data
    double objective[7] = { -4.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
    double rowLower[5] = { 14.0, 3.0, 3.0, 1.0e10, 1.0e10 };
    double rowUpper[5] = { 14.0, 3.0, 3.0, -1.0e10, -1.0e10 };
    double colLower[7] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
    double colUpper[7] = { 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0 };

    // basis 1
    int rowBasis1[3] = { -1, -1, -1 };
    int colBasis1[5] = { 1, 1, -1, -1, 1 };
    solution.loadProblem(matrix, colLower, colUpper, objective,
      rowLower, rowUpper);
    int i;
    solution.createStatus();
    for (i = 0; i < 3; i++) {
      if (rowBasis1[i] < 0) {
        solution.setRowStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution.setRowStatus(i, ClpSimplex::basic);
      }
    }
    for (i = 0; i < 5; i++) {
      if (colBasis1[i] < 0) {
        solution.setColumnStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution.setColumnStatus(i, ClpSimplex::basic);
      }
    }
    solution.setLogLevel(3 + 4 + 8 + 16 + 32);
    solution.primal();
    for (i = 0; i < 3; i++) {
      if (rowBasis1[i] < 0) {
        solution.setRowStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution.setRowStatus(i, ClpSimplex::basic);
      }
    }
    for (i = 0; i < 5; i++) {
      if (colBasis1[i] < 0) {
        solution.setColumnStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution.setColumnStatus(i, ClpSimplex::basic);
      }
    }
    // intricate stuff does not work with scaling
    solution.scaling(0);
#ifndef NDEBUG
    int returnCode = solution.factorize();
    assert(!returnCode);
#else
    solution.factorize();
#endif
    const double *colsol = solution.primalColumnSolution();
    const double *rowsol = solution.primalRowSolution();
    solution.getSolution(rowsol, colsol);
#ifndef NDEBUG
    double colsol1[5] = { 20.0 / 7.0, 3.0, 0.0, 0.0, 23.0 / 7.0 };
    for (i = 0; i < 5; i++) {
      assert(eq(colsol[i], colsol1[i]));
    }
    // now feed in again without actually doing factorization
#endif
    ClpFactorization factorization2 = *solution.factorization();
    ClpSimplex solution2 = solution;
    solution2.setFactorization(factorization2);
    solution2.createStatus();
    for (i = 0; i < 3; i++) {
      if (rowBasis1[i] < 0) {
        solution2.setRowStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution2.setRowStatus(i, ClpSimplex::basic);
      }
    }
    for (i = 0; i < 5; i++) {
      if (colBasis1[i] < 0) {
        solution2.setColumnStatus(i, ClpSimplex::atLowerBound);
      } else {
        solution2.setColumnStatus(i, ClpSimplex::basic);
      }
    }
    // intricate stuff does not work with scaling
    solution2.scaling(0);
    solution2.getSolution(rowsol, colsol);
    colsol = solution2.primalColumnSolution();
    rowsol = solution2.primalRowSolution();
    for (i = 0; i < 5; i++) {
      assert(eq(colsol[i], colsol1[i]));
    }
    solution2.setDualBound(0.1);
    solution2.dual();
    objective[2] = -1.0;
    objective[3] = -0.5;
    objective[4] = 10.0;
    solution.dual();
    for (i = 0; i < 3; i++) {
      rowLower[i] = -1.0e20;
      colUpper[i + 2] = 0.0;
    }
    solution.setLogLevel(3);
    solution.dual();
    double rowObjective[] = { 1.0, 0.5, -10.0 };
    solution.loadProblem(matrix, colLower, colUpper, objective,
      rowLower, rowUpper, rowObjective);
    solution.dual();
    solution.loadProblem(matrix, colLower, colUpper, objective,
      rowLower, rowUpper, rowObjective);
    solution.primal();
  }
#ifndef COIN_NO_CLP_MESSAGE
  {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      solution.dual();
      // Test event handling
      MyEventHandler handler;
      solution.passInEventHandler(&handler);
      int numberRows = solution.numberRows();
      // make sure values pass has something to do
      for (int i = 0; i < numberRows; i++)
        solution.setRowStatus(i, ClpSimplex::basic);
      solution.objective()[1] = -2.0;
      solution.primal(1);
      assert(solution.secondaryStatus() == 102); // Came out at end of pass
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
  }
  // Test Message handler
  {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    //fn = "Test/subGams4";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex model;
      model.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      // Message handler
      MyMessageHandler messageHandler(&model);
      std::cout << "Testing derived message handler" << std::endl;
      model.passInMessageHandler(&messageHandler);
      model.messagesPointer()->setDetailMessage(1, 102);
      model.setFactorizationFrequency(10);
      model.primal();
      model.primal(0, 3);
      model.setObjCoeff(3, -2.9473684210526314);
      model.primal(0, 3);
      // Write saved solutions
      int nc = model.getNumCols();
      size_t s;
      std::deque< StdVectorDouble > fep = messageHandler.getFeasibleExtremePoints();
      size_t numSavedSolutions = fep.size();
      for (s = 0; s < numSavedSolutions; ++s) {
        const StdVectorDouble &solnVec = fep[s];
        for (int c = 0; c < nc; ++c) {
          if (fabs(solnVec[c]) > 1.0e-8)
            std::cout << "Saved Solution: " << s << " ColNum: " << c << " Value: " << solnVec[c] << std::endl;
        }
      }
      // Solve again without scaling
      // and maximize then minimize
      messageHandler.clearFeasibleExtremePoints();
      model.scaling(0);
      model.setOptimizationDirection(-1);
      model.primal();
      model.setOptimizationDirection(1);
      model.primal();
      fep = messageHandler.getFeasibleExtremePoints();
      numSavedSolutions = fep.size();
      for (s = 0; s < numSavedSolutions; ++s) {
        const StdVectorDouble &solnVec = fep[s];
        for (int c = 0; c < nc; ++c) {
          if (fabs(solnVec[c]) > 1.0e-8)
            std::cout << "Saved Solution: " << s << " ColNum: " << c << " Value: " << solnVec[c] << std::endl;
        }
      }
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
  }
#endif
  // Test dual ranging
  {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex model;
      model.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      model.primal();
      int which[13] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 };
      double costIncrease[13];
      int sequenceIncrease[13];
      double costDecrease[13];
      int sequenceDecrease[13];
      // ranging
      model.dualRanging(13, which, costIncrease, sequenceIncrease,
        costDecrease, sequenceDecrease);
      int i;
      for (i = 0; i < 13; i++)
        printf("%d increase %g %d, decrease %g %d\n",
          i, costIncrease[i], sequenceIncrease[i],
          costDecrease[i], sequenceDecrease[i]);
      assert(fabs(costDecrease[3]) < 1.0e-4);
      assert(fabs(costIncrease[7] - 1.0) < 1.0e-4);
      model.setOptimizationDirection(-1);
      {
        int j;
        double *obj = model.objective();
        int n = model.numberColumns();
        for (j = 0; j < n; j++)
          obj[j] *= -1.0;
      }
      double costIncrease2[13];
      int sequenceIncrease2[13];
      double costDecrease2[13];
      int sequenceDecrease2[13];
      // ranging
      model.dualRanging(13, which, costIncrease2, sequenceIncrease2,
        costDecrease2, sequenceDecrease2);
      for (i = 0; i < 13; i++) {
        assert(fabs(costIncrease[i] - costDecrease2[i]) < 1.0e-6);
        assert(fabs(costDecrease[i] - costIncrease2[i]) < 1.0e-6);
        assert(sequenceIncrease[i] == sequenceDecrease2[i]);
        assert(sequenceDecrease[i] == sequenceIncrease2[i]);
      }
      // Now delete all rows and see what happens
      model.deleteRows(model.numberRows(), which);
      model.primal();
      // ranging
      if (!model.dualRanging(8, which, costIncrease, sequenceIncrease,
            costDecrease, sequenceDecrease)) {
        for (i = 0; i < 8; i++) {
          printf("%d increase %g %d, decrease %g %d\n",
            i, costIncrease[i], sequenceIncrease[i],
            costDecrease[i], sequenceDecrease[i]);
        }
      }
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
  }
  // Test primal ranging
  {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex model;
      model.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      model.primal();
      int which[13] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 };
      double valueIncrease[13];
      int sequenceIncrease[13];
      double valueDecrease[13];
      int sequenceDecrease[13];
      // ranging
      model.primalRanging(13, which, valueIncrease, sequenceIncrease,
        valueDecrease, sequenceDecrease);
      int i;
      for (i = 0; i < 13; i++)
        printf("%d increase %g %d, decrease %g %d\n",
          i, valueIncrease[i], sequenceIncrease[i],
          valueDecrease[i], sequenceDecrease[i]);
      assert(fabs(valueIncrease[3] - 0.642857) < 1.0e-4);
      assert(fabs(valueIncrease[8] - 2.95113) < 1.0e-4);
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
#if 0
          // out until I find optimization bug
          // Test parametrics
          ClpSimplexOther * model2 = (ClpSimplexOther *) (&model);
          double rhs[] = { 1.0, 2.0, 3.0, 4.0, 5.0};
          double endingTheta = 1.0;
          model2->scaling(0);
          model2->setLogLevel(63);
          model2->parametrics(0.0, endingTheta, 0.1,
                              NULL, NULL, rhs, rhs, NULL);
#endif
  }
  // Test binv etc
  {
    /*
             Wolsey : Page 130
             max 4x1 -  x2
             7x1 - 2x2    <= 14
             x2    <= 3
             2x1 - 2x2    <= 3
             x1 in Z+, x2 >= 0

             note slacks are -1 in Clp so signs may be different
          */

    int n_cols = 2;
    int n_rows = 3;

    double obj[2] = { -4.0, 1.0 };
    double collb[2] = { 0.0, 0.0 };
    double colub[2] = { COIN_DBL_MAX, COIN_DBL_MAX };
    double rowlb[3] = { -COIN_DBL_MAX, -COIN_DBL_MAX, -COIN_DBL_MAX };
    double rowub[3] = { 14.0, 3.0, 3.0 };

    int rowIndices[5] = { 0, 2, 0, 1, 2 };
    int colIndices[5] = { 0, 0, 1, 1, 1 };
    double elements[5] = { 7.0, 2.0, -2.0, 1.0, -2.0 };
    CoinPackedMatrix M(true, rowIndices, colIndices, elements, 5);

    ClpSimplex model;
    model.loadProblem(M, collb, colub, obj, rowlb, rowub);
    model.dual(0, 1); // keep factorization

    //check that the tableau matches wolsey (B-1 A)
    // slacks in second part of binvA
    double *binvA = reinterpret_cast< double * >(malloc((n_cols + n_rows) * sizeof(double)));

    printf("B-1 A by row\n");
    int i;
    for (i = 0; i < n_rows; i++) {
      model.getBInvARow(i, binvA, binvA + n_cols);
      printf("row: %d -> ", i);
      for (int j = 0; j < n_cols + n_rows; j++) {
        printf("%g, ", binvA[j]);
      }
      printf("\n");
    }
    // See if can re-use factorization AND arrays
    model.primal(0, 3 + 4); // keep factorization
    // And do by column
    printf("B-1 A by column\n");
    for (i = 0; i < n_rows + n_cols; i++) {
      model.getBInvACol(i, binvA);
      printf("column: %d -> ", i);
      for (int j = 0; j < n_rows; j++) {
        printf("%g, ", binvA[j]);
      }
      printf("\n");
    }
    /* Do twice -
             without and with scaling
          */
    // set scaling off
    model.scaling(0);
    for (int iPass = 0; iPass < 2; iPass++) {
      model.primal(0, 3 + 4); // keep factorization
      const double *rowScale = model.rowScale();
      const double *columnScale = model.columnScale();
      if (!iPass)
        assert(!rowScale);
      else
        assert(rowScale); // only true for this example
      /* has to be exactly correct as in OsiClpsolverInterface.cpp
                  (also redo each pass as may change
               */
      printf("B-1 A");
      for (i = 0; i < n_rows; i++) {
        model.getBInvARow(i, binvA, binvA + n_cols);
        printf("\nrow: %d -> ", i);
        int j;
        // First columns
        for (j = 0; j < n_cols; j++) {
          if (binvA[j]) {
            printf("(%d %g), ", j, binvA[j]);
          }
        }
        // now rows
        for (j = 0; j < n_rows; j++) {
          if (binvA[j + n_cols]) {
            printf("(%d %g), ", j + n_cols, binvA[j + n_cols]);
          }
        }
      }
      printf("\n");
      printf("And by column (trickier)");
      const int *pivotVariable = model.pivotVariable();
      for (i = 0; i < n_cols + n_rows; i++) {
        model.getBInvACol(i, binvA);
        printf("\ncolumn: %d -> ", i);
        for (int j = 0; j < n_rows; j++) {
          if (binvA[j]) {
            // need to know pivot variable for +1/-1 (slack) and row/column scaling
            int pivot = pivotVariable[j];
            if (pivot < n_cols) {
              // scaled coding is in just in case
              if (!columnScale) {
                printf("(%d %g), ", j, binvA[j]);
              } else {
                printf("(%d %g), ", j, binvA[j] * columnScale[pivot]);
              }
            } else {
              if (!rowScale) {
                printf("(%d %g), ", j, binvA[j]);
              } else {
                printf("(%d %g), ", j, binvA[j] / rowScale[pivot - n_cols]);
              }
            }
          }
        }
      }
      printf("\n");
      printf("binvrow");
      for (i = 0; i < n_rows; i++) {
        model.getBInvRow(i, binvA);
        printf("\nrow: %d -> ", i);
        int j;
        for (j = 0; j < n_rows; j++) {
          if (binvA[j])
            printf("(%d %g), ", j, binvA[j]);
        }
      }
      printf("\n");
      printf("And by column ");
      for (i = 0; i < n_rows; i++) {
        model.getBInvCol(i, binvA);
        printf("\ncol: %d -> ", i);
        int j;
        for (j = 0; j < n_rows; j++) {
          if (binvA[j])
            printf("(%d %g), ", j, binvA[j]);
        }
      }
      printf("\n");
      // now deal with next pass
      if (!iPass) {
        // get scaling for testing
        model.scaling(1);
      }
    }
    free(binvA);
    model.setColUpper(1, 2.0);
    model.dual(0, 2 + 4); // use factorization and arrays
    model.dual(0, 2); // hopefully will not use factorization
    model.primal(0, 3 + 4); // keep factorization
    // but say basis has changed
    model.setWhatsChanged(model.whatsChanged() & (~512));
    model.dual(0, 2); // hopefully will not use factorization
  }
  // test steepest edge
  {
    CoinMpsIO m;
    std::string fn = dirSample + "finnis";
    int returnCode = m.readMps(fn.c_str(), "mps");
    if (returnCode) {
      // probable cause is that gz not there
      fprintf(stderr, "Unable to open finnis.mps in %s\n", dirSample.c_str());
      fprintf(stderr, "Most probable cause is that sample data is not available, or finnis.mps is gzipped i.e. finnis.mps.gz and libz has not been activated\n");
      fprintf(stderr, "Either gunzip files or edit Makefiles/Makefile.location to get libz\n");
    } else {
      ClpModel model;
      model.loadProblem(*m.getMatrixByCol(), m.getColLower(),
        m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      ClpSimplex solution(model);

      solution.scaling(1);
      solution.setDualBound(1.0e8);
      //solution.factorization()->maximumPivots(1);
      //solution.setLogLevel(3);
      solution.setDualTolerance(1.0e-7);
      // set objective sense,
      ClpDualRowSteepest steep;
      solution.setDualRowPivotAlgorithm(steep);
      solution.setDblParam(ClpObjOffset, m.objectiveOffset());
      solution.dual();
    }
  }
  // test normal solution
  {
    CoinMpsIO m;
    std::string fn = dirSample + "afiro";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      ClpModel model;
      // do twice - without and with scaling
      int iPass;
      for (iPass = 0; iPass < 2; iPass++) {
        // explicit row objective for testing
        int nr = m.getNumRows();
        double *rowObj = new double[nr];
        CoinFillN(rowObj, nr, 0.0);
        model.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
          m.getObjCoefficients(),
          m.getRowLower(), m.getRowUpper(), rowObj);
        delete[] rowObj;
        solution = ClpSimplex(model);
        if (iPass) {
          solution.scaling();
        }
        solution.dual();
        solution.dual();
        // test optimal
        assert(solution.status() == 0);
        int numberColumns = solution.numberColumns();
        int numberRows = solution.numberRows();
        CoinPackedVector colsol(numberColumns, solution.primalColumnSolution());
        double *objective = solution.objective();
#ifndef NDEBUG
        double objValue = colsol.dotProduct(objective);
#endif
        CoinRelFltEq eq(1.0e-8);
        assert(eq(objValue, -4.6475314286e+02));
        solution.dual();
        assert(eq(solution.objectiveValue(), -4.6475314286e+02));
        double *lower = solution.columnLower();
        double *upper = solution.columnUpper();
        double *sol = solution.primalColumnSolution();
        double *result = new double[numberColumns];
        CoinFillN(result, numberColumns, 0.0);
        solution.matrix()->transposeTimes(solution.dualRowSolution(), result);
        int iRow, iColumn;
        // see if feasible and dual feasible
        for (iColumn = 0; iColumn < numberColumns; iColumn++) {
          double value = sol[iColumn];
          assert(value < upper[iColumn] + 1.0e-8);
          assert(value > lower[iColumn] - 1.0e-8);
          value = objective[iColumn] - result[iColumn];
          assert(value > -1.0e-5);
          if (sol[iColumn] > 1.0e-5)
            assert(value < 1.0e-5);
        }
        delete[] result;
        result = new double[numberRows];
        CoinFillN(result, numberRows, 0.0);
        solution.matrix()->times(colsol, result);
        lower = solution.rowLower();
        upper = solution.rowUpper();
        sol = solution.primalRowSolution();
#ifndef NDEBUG
        for (iRow = 0; iRow < numberRows; iRow++) {
          double value = result[iRow];
          assert(eq(value, sol[iRow]));
          assert(value < upper[iRow] + 1.0e-8);
          assert(value > lower[iRow] - 1.0e-8);
        }
#endif
        delete[] result;
        // test row objective
        double *rowObjective = solution.rowObjective();
        CoinDisjointCopyN(solution.dualRowSolution(), numberRows, rowObjective);
        CoinDisjointCopyN(solution.dualColumnSolution(), numberColumns, objective);
        // this sets up all slack basis
        solution.createStatus();
        solution.dual();
        CoinFillN(rowObjective, numberRows, 0.0);
        CoinDisjointCopyN(m.getObjCoefficients(), numberColumns, objective);
        solution.dual();
      }
    } else {
      std::cerr << "Error reading afiro from sample data. Skipping test." << std::endl;
    }
  }
  // test unbounded
  {
    CoinMpsIO m;
    std::string fn = dirSample + "brandy";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      // do twice - without and with scaling
      int iPass;
      for (iPass = 0; iPass < 2; iPass++) {
        solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
          m.getObjCoefficients(),
          m.getRowLower(), m.getRowUpper());
        if (iPass)
          solution.scaling();
        solution.setOptimizationDirection(-1);
        // test unbounded and ray
#ifdef DUAL
        solution.setDualBound(100.0);
        solution.dual();
#else
        solution.primal();
#endif
        assert(solution.status() == 2);
        int numberColumns = solution.numberColumns();
        int numberRows = solution.numberRows();
        double *lower = solution.columnLower();
        double *upper = solution.columnUpper();
        double *sol = solution.primalColumnSolution();
        double *ray = solution.unboundedRay();
        double *objective = solution.objective();
        double objChange = 0.0;
        int iRow, iColumn;
        // make sure feasible and columns form ray
        for (iColumn = 0; iColumn < numberColumns; iColumn++) {
          double value = sol[iColumn];
          assert(value < upper[iColumn] + 1.0e-8);
          assert(value > lower[iColumn] - 1.0e-8);
          value = ray[iColumn];
          if (value > 0.0)
            assert(upper[iColumn] > 1.0e30);
          else if (value < 0.0)
            assert(lower[iColumn] < -1.0e30);
          objChange += value * objective[iColumn];
        }
        // make sure increasing objective
        assert(objChange > 0.0);
        double *result = new double[numberRows];
        CoinFillN(result, numberRows, 0.0);
        solution.matrix()->times(sol, result);
        lower = solution.rowLower();
        upper = solution.rowUpper();
        sol = solution.primalRowSolution();
#ifndef NDEBUG
        for (iRow = 0; iRow < numberRows; iRow++) {
          double value = result[iRow];
          assert(eq(value, sol[iRow]));
          assert(value < upper[iRow] + 2.0e-8);
          assert(value > lower[iRow] - 2.0e-8);
        }
#endif
        CoinFillN(result, numberRows, 0.0);
        solution.matrix()->times(ray, result);
        // there may be small differences (especially if scaled)
        for (iRow = 0; iRow < numberRows; iRow++) {
          double value = result[iRow];
          if (value > 1.0e-8)
            assert(upper[iRow] > 1.0e30);
          else if (value < -1.0e-8)
            assert(lower[iRow] < -1.0e30);
        }
        delete[] result;
        delete[] ray;
      }
    } else {
      std::cerr << "Error reading brandy from sample data. Skipping test." << std::endl;
    }
  }
  // test infeasible
  {
    CoinMpsIO m;
    std::string fn = dirSample + "brandy";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      // do twice - without and with scaling
      int iPass;
      for (iPass = 0; iPass < 2; iPass++) {
        solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
          m.getObjCoefficients(),
          m.getRowLower(), m.getRowUpper());
        if (iPass)
          solution.scaling();
        // test infeasible and ray
        solution.columnUpper()[0] = 0.0;
#if 1 //def DUAL
        solution.setDualBound(100.0);
        solution.dual();
#else
        solution.primal();
#endif
        assert(solution.status() == 1);
        int numberColumns = solution.numberColumns();
        int numberRows = solution.numberRows();
        double *lower = solution.rowLower();
        double *upper = solution.rowUpper();
        double *ray = solution.infeasibilityRay();
        assert(ray);
        // construct proof of infeasibility
        int iRow, iColumn;
        double lo = 0.0, up = 0.0;
        int nl = 0, nu = 0;
        for (iRow = 0; iRow < numberRows; iRow++) {
          if (lower[iRow] > -1.0e20) {
            lo += ray[iRow] * lower[iRow];
          } else {
            if (ray[iRow] > 1.0e-8)
              nl++;
          }
          if (upper[iRow] < 1.0e20) {
            up += ray[iRow] * upper[iRow];
          } else {
            if (ray[iRow] > 1.0e-8)
              nu++;
          }
        }
        if (nl)
          lo = -1.0e100;
        if (nu)
          up = 1.0e100;
        double *result = new double[numberColumns];
        double lo2 = 0.0, up2 = 0.0;
        CoinFillN(result, numberColumns, 0.0);
        solution.matrix()->transposeTimes(ray, result);
        lower = solution.columnLower();
        upper = solution.columnUpper();
        nl = nu = 0;
        for (iColumn = 0; iColumn < numberColumns; iColumn++) {
          if (result[iColumn] > 1.0e-8) {
            if (lower[iColumn] > -1.0e20)
              lo2 += result[iColumn] * lower[iColumn];
            else
              nl++;
            if (upper[iColumn] < 1.0e20)
              up2 += result[iColumn] * upper[iColumn];
            else
              nu++;
          } else if (result[iColumn] < -1.0e-8) {
            if (lower[iColumn] > -1.0e20)
              up2 += result[iColumn] * lower[iColumn];
            else
              nu++;
            if (upper[iColumn] < 1.0e20)
              lo2 += result[iColumn] * upper[iColumn];
            else
              nl++;
          }
        }
        if (nl)
          lo2 = -1.0e100;
        if (nu)
          up2 = 1.0e100;
        // make sure inconsistency
        assert(lo2 > up || up2 < lo);
        delete[] result;
        delete[] ray;
      }
    } else {
      std::cerr << "Error reading brandy from sample data. Skipping test." << std::endl;
    }
  }
  // test delete and add
  {
    CoinMpsIO m;
    std::string fn = dirSample + "brandy";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      solution.dual();
      CoinRelFltEq eq(1.0e-8);
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));

      int numberColumns = solution.numberColumns();
      int numberRows = solution.numberRows();
      double *saveObj = new double[numberColumns];
      double *saveLower = new double[numberRows + numberColumns];
      double *saveUpper = new double[numberRows + numberColumns];
      int *which = new int[numberRows + numberColumns];

      CoinBigIndex numberElements = m.getMatrixByCol()->getNumElements();
      CoinBigIndex *starts = new CoinBigIndex[numberRows + numberColumns];
      int *index = new int[numberElements];
      double *element = new double[numberElements];

      const CoinBigIndex *startM;
      const int *lengthM;
      const int *indexM;
      const double *elementM;

      int n, nel;

      // delete non basic columns
      n = 0;
      nel = 0;
      int iRow, iColumn;
      const double *lower = m.getColLower();
      const double *upper = m.getColUpper();
      const double *objective = m.getObjCoefficients();
      startM = m.getMatrixByCol()->getVectorStarts();
      lengthM = m.getMatrixByCol()->getVectorLengths();
      indexM = m.getMatrixByCol()->getIndices();
      elementM = m.getMatrixByCol()->getElements();
      starts[0] = 0;
      for (iColumn = 0; iColumn < numberColumns; iColumn++) {
        if (solution.getColumnStatus(iColumn) != ClpSimplex::basic) {
          saveObj[n] = objective[iColumn];
          saveLower[n] = lower[iColumn];
          saveUpper[n] = upper[iColumn];
          CoinBigIndex j;
          for (j = startM[iColumn]; j < startM[iColumn] + lengthM[iColumn]; j++) {
            index[nel] = indexM[j];
            element[nel++] = elementM[j];
          }
          which[n++] = iColumn;
          starts[n] = nel;
        }
      }
      solution.deleteColumns(n, which);
      solution.dual();
      // Put back
      solution.addColumns(n, saveLower, saveUpper, saveObj,
        starts, index, element);
      solution.dual();
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));
      // Delete all columns and add back
      n = 0;
      nel = 0;
      starts[0] = 0;
      lower = m.getColLower();
      upper = m.getColUpper();
      objective = m.getObjCoefficients();
      for (iColumn = 0; iColumn < numberColumns; iColumn++) {
        saveObj[n] = objective[iColumn];
        saveLower[n] = lower[iColumn];
        saveUpper[n] = upper[iColumn];
        CoinBigIndex j;
        for (j = startM[iColumn]; j < startM[iColumn] + lengthM[iColumn]; j++) {
          index[nel] = indexM[j];
          element[nel++] = elementM[j];
        }
        which[n++] = iColumn;
        starts[n] = nel;
      }
      solution.deleteColumns(n, which);
      solution.dual();
      // Put back
      solution.addColumns(n, saveLower, saveUpper, saveObj,
        starts, index, element);
      solution.dual();
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));

      // reload with original
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      // delete half rows
      n = 0;
      nel = 0;
      lower = m.getRowLower();
      upper = m.getRowUpper();
      startM = m.getMatrixByRow()->getVectorStarts();
      lengthM = m.getMatrixByRow()->getVectorLengths();
      indexM = m.getMatrixByRow()->getIndices();
      elementM = m.getMatrixByRow()->getElements();
      starts[0] = 0;
      for (iRow = 0; iRow < numberRows; iRow++) {
        if ((iRow & 1) == 0) {
          saveLower[n] = lower[iRow];
          saveUpper[n] = upper[iRow];
          CoinBigIndex j;
          for (j = startM[iRow]; j < startM[iRow] + lengthM[iRow]; j++) {
            index[nel] = indexM[j];
            element[nel++] = elementM[j];
          }
          which[n++] = iRow;
          starts[n] = nel;
        }
      }
      solution.deleteRows(n, which);
      solution.dual();
      // Put back
      solution.addRows(n, saveLower, saveUpper,
        starts, index, element);
      solution.dual();
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));
      solution.writeMps("yy.mps");
      // Delete all rows
      n = 0;
      nel = 0;
      lower = m.getRowLower();
      upper = m.getRowUpper();
      starts[0] = 0;
      for (iRow = 0; iRow < numberRows; iRow++) {
        saveLower[n] = lower[iRow];
        saveUpper[n] = upper[iRow];
        CoinBigIndex j;
        for (j = startM[iRow]; j < startM[iRow] + lengthM[iRow]; j++) {
          index[nel] = indexM[j];
          element[nel++] = elementM[j];
        }
        which[n++] = iRow;
        starts[n] = nel;
      }
      solution.deleteRows(n, which);
      solution.dual();
      // Put back
      solution.addRows(n, saveLower, saveUpper,
        starts, index, element);
      solution.dual();
      solution.writeMps("xx.mps");
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));
      // Zero out status array to give some interest
      memset(solution.statusArray() + numberColumns, 0, numberRows);
      solution.primal(1);
      assert(eq(solution.objectiveValue(), 1.5185098965e+03));
      // Delete all columns and rows
      n = 0;
      for (iColumn = 0; iColumn < numberColumns; iColumn++) {
        which[n++] = iColumn;
        starts[n] = nel;
      }
      solution.deleteColumns(n, which);
      n = 0;
      for (iRow = 0; iRow < numberRows; iRow++) {
        which[n++] = iRow;
        starts[n] = nel;
      }
      solution.deleteRows(n, which);

      delete[] saveObj;
      delete[] saveLower;
      delete[] saveUpper;
      delete[] which;
      delete[] starts;
      delete[] index;
      delete[] element;
    } else {
      std::cerr << "Error reading brandy from sample data. Skipping test." << std::endl;
    }
  }
#if 1
  // Test barrier
  {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpInterior solution;
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      solution.primalDual();
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
  }
#endif
#if COIN_BIG_INDEX == 0
  // test network
#define QUADRATIC
  if (1) {
    std::string fn = dirSample + "input.130";
    int numberColumns;
    int numberRows;

    FILE *fp = fopen(fn.c_str(), "r");
    if (!fp) {
      // Try in Data/Sample
      fn = "Data/Sample/input.130";
      fp = fopen(fn.c_str(), "r");
    }
    if (!fp) {
      fprintf(stderr, "Unable to open file input.130 in dirSample or Data/Sample directory\n");
    } else {
      int problem;
      char temp[100];
      // read and skip
      int x = fscanf(fp, "%s", temp);
      if (x < 0)
        throw("bad fscanf");
      assert(!strcmp(temp, "BEGIN"));
      x = fscanf(fp, "%*s %*s %d %d %*s %*s %d %*s", &problem, &numberRows,
        &numberColumns);
      if (x < 0)
        throw("bad fscanf");
      // scan down to SUPPLY
      while (fgets(temp, 100, fp)) {
        if (!strncmp(temp, "SUPPLY", 6))
          break;
      }
      if (strncmp(temp, "SUPPLY", 6)) {
        fprintf(stderr, "Unable to find SUPPLY\n");
        exit(2);
      }
      // get space for rhs
      double *lower = new double[numberRows];
      double *upper = new double[numberRows];
      int i;
      for (i = 0; i < numberRows; i++) {
        lower[i] = 0.0;
        upper[i] = 0.0;
      }
      // ***** Remember to convert to C notation
      while (fgets(temp, 100, fp)) {
        int row;
        int value;
        if (!strncmp(temp, "ARCS", 4))
          break;
        sscanf(temp, "%d %d", &row, &value);
        upper[row - 1] = -value;
        lower[row - 1] = -value;
      }
      if (strncmp(temp, "ARCS", 4)) {
        fprintf(stderr, "Unable to find ARCS\n");
        exit(2);
      }
      // number of columns may be underestimate
      int *head = new int[2 * numberColumns];
      int *tail = new int[2 * numberColumns];
      int *ub = new int[2 * numberColumns];
      int *cost = new int[2 * numberColumns];
      // ***** Remember to convert to C notation
      numberColumns = 0;
      while (fgets(temp, 100, fp)) {
        int iHead;
        int iTail;
        int iUb;
        int iCost;
        if (!strncmp(temp, "DEMAND", 6))
          break;
        sscanf(temp, "%d %d %d %d", &iHead, &iTail, &iCost, &iUb);
        iHead--;
        iTail--;
        head[numberColumns] = iHead;
        tail[numberColumns] = iTail;
        ub[numberColumns] = iUb;
        cost[numberColumns] = iCost;
        numberColumns++;
      }
      if (strncmp(temp, "DEMAND", 6)) {
        fprintf(stderr, "Unable to find DEMAND\n");
        exit(2);
      }
      // ***** Remember to convert to C notation
      while (fgets(temp, 100, fp)) {
        int row;
        int value;
        if (!strncmp(temp, "END", 3))
          break;
        sscanf(temp, "%d %d", &row, &value);
        upper[row - 1] = value;
        lower[row - 1] = value;
      }
      if (strncmp(temp, "END", 3)) {
        fprintf(stderr, "Unable to find END\n");
        exit(2);
      }
      printf("Problem %d has %d rows and %d columns\n", problem,
        numberRows, numberColumns);
      fclose(fp);
      ClpSimplex model;
      // now build model

      double *objective = new double[numberColumns];
      double *lowerColumn = new double[numberColumns];
      double *upperColumn = new double[numberColumns];

      double *element = new double[2 * numberColumns];
      CoinBigIndex *start = new CoinBigIndex[numberColumns + 1];
      int *row = new int[2 * numberColumns];
      start[numberColumns] = 2 * numberColumns;
      for (i = 0; i < numberColumns; i++) {
        start[i] = 2 * i;
        element[2 * i] = -1.0;
        element[2 * i + 1] = 1.0;
        row[2 * i] = head[i];
        row[2 * i + 1] = tail[i];
        lowerColumn[i] = 0.0;
        upperColumn[i] = ub[i];
        objective[i] = cost[i];
      }
      // Create Packed Matrix
      CoinPackedMatrix matrix;
      int *lengths = NULL;
      matrix.assignMatrix(true, numberRows, numberColumns,
        2 * numberColumns, element, row, start, lengths);
      // load model
      model.loadProblem(matrix,
        lowerColumn, upperColumn, objective,
        lower, upper);
      model.factorization()->maximumPivots(200 + model.numberRows() / 100);
      model.createStatus();
      double time1 = CoinCpuTime();
      model.dual();
      std::cout << "Network problem, ClpPackedMatrix took " << CoinCpuTime() - time1 << " seconds" << std::endl;
      ClpPlusMinusOneMatrix *plusMinus = new ClpPlusMinusOneMatrix(matrix);
      assert(plusMinus->getIndices()); // would be zero if not +- one
      //ClpPlusMinusOneMatrix *plusminus_matrix;

      //plusminus_matrix = new ClpPlusMinusOneMatrix;

      //plusminus_matrix->passInCopy(numberRows, numberColumns, true, plusMinus->getMutableIndices(),
      //                         plusMinus->startPositive(),plusMinus->startNegative());
      model.loadProblem(*plusMinus,
        lowerColumn, upperColumn, objective,
        lower, upper);
      //model.replaceMatrix( plusminus_matrix , true);
      delete plusMinus;
      //model.createStatus();
      //model.initialSolve();
      //model.writeMps("xx.mps");

      model.factorization()->maximumPivots(200 + model.numberRows() / 100);
      model.createStatus();
      time1 = CoinCpuTime();
      model.dual();
      std::cout << "Network problem, ClpPlusMinusOneMatrix took " << CoinCpuTime() - time1 << " seconds" << std::endl;
      ClpNetworkMatrix network(numberColumns, head, tail);
      model.loadProblem(network,
        lowerColumn, upperColumn, objective,
        lower, upper);

      model.factorization()->maximumPivots(200 + model.numberRows() / 100);
      model.createStatus();
      time1 = CoinCpuTime();
      model.dual();
      std::cout << "Network problem, ClpNetworkMatrix took " << CoinCpuTime() - time1 << " seconds" << std::endl;
      delete[] lower;
      delete[] upper;
      delete[] head;
      delete[] tail;
      delete[] ub;
      delete[] cost;
      delete[] objective;
      delete[] lowerColumn;
      delete[] upperColumn;
    }
  }
#ifdef QUADRATIC
  // Test quadratic to solve linear
  if (1) {
    CoinMpsIO m;
    std::string fn = dirSample + "exmip1";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      //solution.dual();
      // get quadratic part
      int numberColumns = solution.numberColumns();
      int *start = new int[numberColumns + 1];
      int *column = new int[numberColumns];
      double *element = new double[numberColumns];
      int i;
      start[0] = 0;
      int n = 0;
      int kk = numberColumns - 1;
      int kk2 = numberColumns - 1;
      for (i = 0; i < numberColumns; i++) {
        if (i >= kk) {
          column[n] = i;
          if (i >= kk2)
            element[n] = 1.0e-1;
          else
            element[n] = 0.0;
          n++;
        }
        start[i + 1] = n;
      }
      // Load up objective
      solution.loadQuadraticObjective(numberColumns, start, column, element);
      delete[] start;
      delete[] column;
      delete[] element;
      //solution.quadraticSLP(50,1.0e-4);
      CoinRelFltEq eq(1.0e-4);
      //assert(eq(objValue,820.0));
      //solution.setLogLevel(63);
      solution.primal();
      printSol(solution);
      //assert(eq(objValue,3.2368421));
      //exit(77);
    } else {
      std::cerr << "Error reading exmip1 from sample data. Skipping test." << std::endl;
    }
  }
  // Test quadratic
  if (1) {
    CoinMpsIO m;
    std::string fn = dirSample + "share2qp";
    //fn = "share2qpb";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex model;
      model.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      model.dual();
      // get quadratic part
      int *start = NULL;
      int *column = NULL;
      double *element = NULL;
      m.readQuadraticMps(NULL, start, column, element, 2);
      int column2[200];
      double element2[200];
      int start2[80];
      int j;
      start2[0] = 0;
      int nel = 0;
      bool good = false;
      for (j = 0; j < 79; j++) {
        if (start[j] == start[j + 1]) {
          column2[nel] = j;
          element2[nel] = 0.0;
          nel++;
        } else {
          int i;
          for (i = start[j]; i < start[j + 1]; i++) {
            column2[nel] = column[i];
            element2[nel++] = element[i];
          }
        }
        start2[j + 1] = nel;
      }
      // Load up objective
      if (good)
        model.loadQuadraticObjective(model.numberColumns(), start2, column2, element2);
      else
        model.loadQuadraticObjective(model.numberColumns(), start, column, element);
      delete[] start;
      delete[] column;
      delete[] element;
      int numberColumns = model.numberColumns();
      model.scaling(0);
#if 0
               model.nonlinearSLP(50, 1.0e-4);
#else
      // Get feasible
      ClpObjective *saveObjective = model.objectiveAsObject()->clone();
      ClpLinearObjective zeroObjective(NULL, numberColumns);
      model.setObjective(&zeroObjective);
      model.dual();
      model.setObjective(saveObjective);
      delete saveObjective;
#endif
      //model.setLogLevel(63);
      //exit(77);
      model.setFactorizationFrequency(10);
      model.primal();
      printSol(model);
#ifndef NDEBUG
      double objValue = model.getObjValue();
#endif
      CoinRelFltEq eq(1.0e-4);
      assert(eq(objValue, -400.92));
      // and again for barrier
      model.barrier(false);
      //printSol(model);
      model.allSlackBasis();
      model.primal();
      //printSol(model);
    } else {
      std::cerr << "Error reading share2qp from sample data. Skipping test." << std::endl;
    }
  }
  if (0) {
    CoinMpsIO m;
    std::string fn = "./beale";
    //fn = "./jensen";
    if (m.readMps(fn.c_str(), "mps") == 0) {
      ClpSimplex solution;
      solution.loadProblem(*m.getMatrixByCol(), m.getColLower(), m.getColUpper(),
        m.getObjCoefficients(),
        m.getRowLower(), m.getRowUpper());
      solution.setDblParam(ClpObjOffset, m.objectiveOffset());
      solution.dual();
      // get quadratic part
      int *start = NULL;
      int *column = NULL;
      double *element = NULL;
      m.readQuadraticMps(NULL, start, column, element, 2);
      // Load up objective
      solution.loadQuadraticObjective(solution.numberColumns(), start, column, element);
      delete[] start;
      delete[] column;
      delete[] element;
      solution.primal(1);
      solution.nonlinearSLP(50, 1.0e-4);
      double objValue = solution.getObjValue();
      CoinRelFltEq eq(1.0e-4);
      assert(eq(objValue, 0.5));
      solution.primal();
      objValue = solution.getObjValue();
      assert(eq(objValue, 0.5));
    } else {
      std::cerr << "Error reading beale.mps. Skipping test." << std::endl;
    }
  }
#endif
  // Test CoinStructuredModel
  {

    // Sub block
    CoinModel sub;
    {
      // matrix data
      //deliberate hiccup of 2 between 0 and 1
      CoinBigIndex start[5] = { 0, 4, 7, 8, 9 };
      int length[5] = { 2, 3, 1, 1, 1 };
      int rows[11] = { 0, 2, -1, -1, 0, 1, 2, 0, 1, 2 };
      double elements[11] = { 7.0, 2.0, 1.0e10, 1.0e10, -2.0, 1.0, -2.0, 1, 1, 1 };
      CoinPackedMatrix matrix(true, 3, 5, 8, elements, rows, start, length);
      // by row
      matrix.reverseOrdering();
      const double *element = matrix.getElements();
      const int *column = matrix.getIndices();
      const CoinBigIndex *rowStart = matrix.getVectorStarts();
      const int *rowLength = matrix.getVectorLengths();

      // rim data
      //double objective[5]={-4.0,1.0,0.0,0.0,0.0};
      double rowLower[3] = { 14.0, 3.0, 3.0 };
      double rowUpper[3] = { 14.0, 3.0, 3.0 };
      //double columnLower[5]={0.0,0.0,0.0,0.0,0.0};
      //double columnUpper[5]={100.0,100.0,100.0,100.0,100.0};

      for (int i = 0; i < 3; i++) {
        sub.addRow(rowLength[i], column + rowStart[i],
          element + rowStart[i], rowLower[i], rowUpper[i]);
      }
      //for (int i=0;i<5;i++) {
      //sub.setColumnBounds(i,columnLower[i],columnUpper[i]);
      //sub.setColumnObjective(i,objective[i]);
      //}
      sub.convertMatrix();
    }
    // Top
    CoinModel top;
    {
      // matrix data
      CoinBigIndex start[5] = { 0, 2, 4, 6, 8 };
      int length[5] = { 2, 2, 2, 2, 2 };
      int rows[10] = { 0, 1, 0, 1, 0, 1, 0, 1, 0, 1 };
      double elements[10] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
      CoinPackedMatrix matrix(true, 2, 5, 8, elements, rows, start, length);
      // by row
      matrix.reverseOrdering();
      const double *element = matrix.getElements();
      const int *column = matrix.getIndices();
      const CoinBigIndex *rowStart = matrix.getVectorStarts();
      const int *rowLength = matrix.getVectorLengths();

      // rim data
      double objective[5] = { -4.0, 1.0, 0.0, 0.0, 0.0 };
      //double rowLower[3]={14.0,3.0,3.0};
      //double rowUpper[3]={14.0,3.0,3.0};
      double columnLower[5] = { 0.0, 0.0, 0.0, 0.0, 0.0 };
      double columnUpper[5] = { 100.0, 100.0, 100.0, 100.0, 100.0 };

      for (int i = 0; i < 2; i++) {
        top.addRow(rowLength[i], column + rowStart[i],
          element + rowStart[i],
          -COIN_DBL_MAX, COIN_DBL_MAX);
      }
      for (int i = 0; i < 5; i++) {
        top.setColumnBounds(i, columnLower[i], columnUpper[i]);
        top.setColumnObjective(i, objective[i]);
      }
      top.convertMatrix();
    }
    // Create a structured model
    CoinStructuredModel structured;
    int numberBlocks = 5;
    for (int i = 0; i < numberBlocks; i++) {
      std::string topName = "row_master";
      std::string blockName = "block_";
      char bName = static_cast< char >('a' + static_cast< char >(i));
      blockName.append(1, bName);
      structured.addBlock(topName, blockName, top);
      structured.addBlock(blockName, blockName, sub);
    }
    // Set rhs on first block
    CoinModel *first = structured.coinBlock(0);
    for (int i = 0; i < 2; i++) {
      first->setRowLower(i, 0.0);
      first->setRowUpper(i, 100.0);
    }
    // Refresh whats set
    structured.refresh(0);
    // Could perturb stuff, but for first go don't bother
    ClpSimplex fullModel;
    // There is no original stuff set - think
    fullModel.loadProblem(structured, false);
    fullModel.dual();
    fullModel.dropNames();
    fullModel.writeMps("test.mps");
    // Make up very simple nested model - not realistic
    // Create a structured model
    CoinStructuredModel structured2;
    numberBlocks = 3;
    for (int i = 0; i < numberBlocks; i++) {
      std::string blockName = "block_";
      char bName = static_cast< char >('a' + static_cast< char >(i));
      blockName.append(1, bName);
      structured2.addBlock(blockName, blockName, structured);
    }
    fullModel.loadProblem(structured2, false);
    fullModel.dual();
    fullModel.dropNames();
    fullModel.writeMps("test2.mps");
  }
#endif
}

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