C++ VectorKKStr::size方法代码示例

void  KKJob::ProcessStatusStr (const KKStr&  statusStr)
{
  log.Level (30) << "KKJob::ProcessStatusStr[" << statusStr << "]" << endl;
  KKStr  fieldName;
  KKStr  fieldValue;

  VectorKKStr fields = statusStr.Split ('\t');
  kkuint32  fieldNum = 0;

  while  (fieldNum < fields.size ())
  {
    fieldName = fields[fieldNum];
    fieldNum++;
    if  (fieldNum < fields.size ())
    {
      fieldValue = fields[fieldNum];
      fieldNum++;
    }
    else
    {
      fieldValue = "";
    }

    fieldName.Upper ();
    fieldValue.TrimLeft ("\n\r\t ");
    fieldValue.TrimRight ("\n\r\t ");

    if  (fieldName.CompareIgnoreCase ("JOBID") == 0)
      jobId = atoi (fieldValue.Str ());

    else  if  (fieldName.CompareIgnoreCase ("PARENTID") == 0)
      parentId = atoi (fieldValue.Str ());

    else  if  (fieldName.CompareIgnoreCase ("STATUS") == 0)
      status = JobStatusFromStr (fieldValue);
   
    else  if  (fieldName.CompareIgnoreCase ("NumProcessors") == 0)
      numProcessors = fieldValue.ToInt ();

    else  if  (fieldName.CompareIgnoreCase ("NumPorcessesAllowed") == 0)
      numPorcessesAllowed = fieldValue.ToInt ();

    else  if  (fieldName.CompareIgnoreCase ("Prerequisites") == 0)
      PrerequisitesFromStr (fieldValue);
      
    else
    {
      ProcessStatusField (fieldName, fieldValue);
    }
  }
}  /* ProcessStatusStr */

void  DataBaseServer::ParseParameterStr (const  KKStr&  parameterStr)
{
  VectorKKStr  parameterPairs = parameterStr.Split ("\t");

  VectorKKStr::iterator  idx;
  for  (idx = parameterPairs.begin ();  idx != parameterPairs.end ();  idx++)
  {
    VectorKKStr  fields = (*idx).Split (":=");   // Split by either ':'  or  '='
    if  (fields.size () < 2)
    {
      // Should be two fields;  line must be malformed.
      continue;
    }

    KKStr  parameterName = fields[0].ToUpper ();

    if      ((parameterName == "EMBEDDED")      ||  (parameterName == "EMB")       ||  (parameterName == "E"))   embedded     = fields[1].ToBool ();
    else if ((parameterName == "MYSQLDATADIR")  ||  (parameterName == "MYSQL")     ||  (parameterName == "MDD")) mySqlDataDir = fields[1];
    else if ((parameterName == "DESCRIPTION")   ||  (parameterName == "DESC")      ||  (parameterName == "D"))   description  = fields[1];
    else if ((parameterName == "HOSTNAME")      ||  (parameterName == "HOST")      ||  (parameterName == "H"))   hostName     = fields[1];
    else if ((parameterName == "USERNAME")      ||  (parameterName == "USER")      ||  (parameterName == "U"))   userName     = fields[1];
    else if ((parameterName == "PASSWORD")      ||  (parameterName == "PW")        ||  (parameterName == "P"))   passWord     = fields[1];
    else if ((parameterName == "PORTNUM")       ||  (parameterName == "PN"))                                     portNum      = fields[1].ToUint32 ();
    else if ((parameterName == "DATABASENAME")  ||  (parameterName == "DATABASE")  ||  (parameterName == "DB"))  dataBaseName = fields[1];
  }

  if  (description.EqualIgnoreCase ("Embedded"))
    embedded = true;
}  /* ParseParameterStr */

void  InstrumentDataPitchAndRoll::ProcessData (const KKStr&  txt)
{
  VectorKKStr  fields = txt.Split (" \t\n\r");
  if  (fields.size () < 4)
     return;

  float  pitch = -999.99f;
  float  roll  = -999.99f;

  KKStr  fieldName  = "";
  KKStr  fieldValue = "";
  kkuint32 fieldNum   = 0;

  while  (fieldNum < fields.size ())
  {
    fieldName  = fields[fieldNum];
    fieldName.Upper ();
    fieldNum++;

    if  (fieldNum < fields.size ())
    {
      fieldValue = fields[fieldNum];  
      fieldNum++;
    }
    else
    {
      fieldValue = "";
    }

    if  (fieldName == "R")
    {
      roll = fieldValue.ToFloat ();
    }
    else if  (fieldName == "P")
    {
      pitch = fieldValue.ToFloat ();
    }
  } 

  manager->PitchAndRollData (curTextLineStartScanLine, pitch, roll);
}  /* ProcessData */

void  KKJob::PrerequisitesFromStr (const KKStr&  s)
{
  prerequisites.clear ();

  if  (s.CompareIgnoreCase ("None") != 0)
  {
    VectorKKStr fields = s.Split (',');
    for  (kkuint32 x = 0;  x < fields.size ();  ++x)
    {
      kkint32 p = fields[x].ToInt ();
      prerequisites.push_back (p);
    }
  }
}  /* PrerequisitesFromStr */

void  InstrumentDataBatteryMeter::ProcessBatteryData (const KKStr&  txt)
{
  // We will be expecting 5 fields;  
  // <Current battery> <\t> <Bat 0 Voltage>  <\t> .... <\t> <Bat-3 Voltage>
    
  VectorKKStr  fields = txt.Split (',');
  if  (fields.size () < (1 + numOfBatteries))
    return;
      
  // activeBattery is '1' based  that is batteries '1' - '4';  so 
  // batteryLevels[0] = battery level for battery 1.
  kkint32  activeBattery = fields[0].ToInt ();
  if  ((activeBattery < 1)  ||  ((kkuint32)activeBattery > numOfBatteries))
    return;

  kkuint32  x;
  for  (x = 0;  x < numOfBatteries;  x++)
    batteryLevels[x] = fields[x + 1].ToFloat ();

  manager->BatteryData (curTextLineStartScanLine, activeBattery, batteryLevels);
}  /* ProcessBatteryData */

void  ImportGPSDataGPGGA (const KKStr&  fileName)
{
  RunLog  log;

  DataBasePtr  dbConn = new DataBase (log);

  ifstream  i (fileName.Str ());
  if  (!i.is_open ())
  {
    log.Level (-1) << endl << endl 
       << "ImpotrtGPSData  Could not open file[" << fileName << "]" << endl
       << endl;
    return;
  }
  log.Level (10) << endl << endl << endl << endl << endl
    << "ImpotrtGPSData   FileName[" << fileName << "]" << endl << endl
    << endl;

  char  buff[20480];
  bool  firstPass = true;

  int  lastMinute = 0;
  int  linesRead = 0;

  KKStr  ln (256);

  DateTime  lastDateTime;
  while  (i.getline (buff, sizeof (buff)))
  {
    linesRead++;
    ln = buff;
    ln.TrimLeft ();
     
    if  (!ln.LocateStr ("GPGGA"))
      continue;

    VectorKKStr  fields = ln.Parse (",");
    if  (fields.size () < 8)
      continue;

    if  (!fields[2].EqualIgnoreCase ("$GPGGA"))
      continue;


    /*
    0           1             2        3         4      5       6       7   8  
06/01/2010, 23:59:59.818,  $GPGGA,  235958,  2840.927,  N,  08828.458,  W,  2,  09,22.10,0,M,,,14,0000*12
06/02/2010, 00:00:10.818,  $GPGGA,  000009,  2840.931,  N,  08828.482,  W,  1,  09,0.89,0,M,,,,*2D
06/02/2010, 00:00:21.802,  $GPGGA,  000020,  2840.929,  N,  08828.505,  W,  1,  09,0.89,0,M,,,,*21
06/02/2010, 00:00:31.818,  $GPGGA,  000030,  2840.924,  N,  08828.526,  W,  1,  09,0.89,0,M,,,,*2C
06/02/2010, 00:00:42.818,  $GPGGA,  000041,  2840.917,  N,  08828.547,  W,  1,  09,0.89,0,M,,,,*2D
06/02/2010, 00:00:53.802,  $GPGGA,  000052,  2840.906,  N,  08828.568,  W,  1,  09,1.00,0,M,,,,*22
06/02/2010, 00:01:03.802,  $GPGGA,  000102,  2840.895,  N,  08828.585,  W,  1,  09,0.89,0,M,,,,*2E
06/02/2010, 00:01:13.818,  $GPGGA,  000112,  2840.883,  N,  08828.600,  W,  1,  09,0.89,0,M,,,,*26
   */


    KKStr  dateStr = fields[0];
    KKStr  timeStr = fields[1];

    KKStr  latStr = fields[4];
    KKStr  logStr = fields[6];

    auto  x = latStr.LocateCharacter ('.');
    if  (!x) 
      continue;

    KKStr latMinStr = latStr.SubStrPart (x - 2);
    KKStr latDegStr = latStr.SubStrSeg (0, x - 2);

    double latitude = latDegStr.ToDouble () + latMinStr.ToDouble () / 60.0;
    if  (fields[5].EqualIgnoreCase ("S"))
      latitude = 0.0 - latitude;

    x = logStr.LocateCharacter ('.');
    if  (!x) 
      continue;

    KKStr logMinStr = logStr.SubStrPart (x - 2);
    KKStr logDegStr = logStr.SubStrSeg (0, x - 2);

    double longitude = logDegStr.ToDouble () + logMinStr.ToDouble () / 60.0;
    if  (fields[7].EqualIgnoreCase ("W"))
      longitude = 0.0 - longitude;

    DateType  gmtDate (dateStr);
    TimeType  gmtTime (timeStr);

    DateTime  gmtDateTime (gmtDate, gmtTime);
    DateTime  localTime = gmtDateTime;
    localTime.HoursAdd (-4);

    DateTime  startDT = localTime;
    DateTime  endDT   = localTime;

    if  (firstPass)
    {
      firstPass = false;
      startDT.SecondsAdd (-180);
    }
//.........这里部分代码省略.........

void  RandomSplitJobManager::GenerateFinalResultsReport ()
{
  KKStr reportFileName = osGetRootName (ManagerName ()) + "_Results.html;";

  ofstream f (reportFileName.Str ());

  f << "Run Time Parameters" << endl
    << "Run Time"          << "\t" << osGetLocalDateTime ()  << endl
    << "configFileName"    << "\t" << configFileName         << endl
    << "DataFileName"      << "\t" << dataFileName           << endl
    << "Format"            << "\t" << format->DriverName ()  << endl
    << "DataIndexFileName" << "\t" << dataIndexFileName      << endl
    << "NumFolds"          << "\t" << numFolds               << endl
    << "NumSplits"         << "\t" << numSplits              << endl
    << "splitFraction"     << "\t" << splitFraction          << endl
    << endl;


  KKJobList::const_iterator  idx;

  ConfusionMatrix2  avgResults (*(this->MLClasses ()));
  KKB::uint  x = 0;

  for  (idx = Jobs ()->begin ();  idx != Jobs ()->end ();  idx++)
  {
    RandomSplitJobPtr j = dynamic_cast<RandomSplitJobPtr> (*idx);
    if  (j->RandomSplitsResults () != NULL)
    {
      f << endl
        << "Random Split[" << j->SplitNum () << "]" << endl;
      j->RandomSplitsResults ()->PrintConfusionMatrixTabDelimited (f);
      f << endl << endl;

      j->PrintClassCounts (f);
      f << endl << endl;

      avgResults.AddIn (*(j->RandomSplitsResults ()), log);
      x++;
    }
  }

  f << endl << "Mean Average of all random Splits." << endl;
  avgResults.FactorCounts (1.0 / (double)x);
  avgResults.PrintConfusionMatrixTabDelimited (f);
  f << endl 
    << endl
    << endl
    << endl
    << "Class Counts" << endl
    << endl;

  kkuint32  numClasses = (kkuint32)mlClasses->size ();

  VectorFloat   classAccs;
  VectorDouble  knownCounts;
  VectorDouble  predCounts;
  VectorDouble  adjCounts;
  VectorDouble  adjCountsStdError;
  VectorDouble  predDelta;       
  VectorDouble  adjDelta;
  
  KKStr l1, l2, l3;
  mlClasses->ExtractThreeTitleLines (l1, l2, l3);

  VectorKKStr  knownCountLines;
  VectorKKStr  predCountLines;
  VectorKKStr  adjCountLines;
  VectorKKStr  deltaPredCountLines;
  VectorKKStr  deltaAdjCountLines;
  VectorKKStr  accLines;


  ConfusionMatrix2  totalCM (*MLClasses ());
  int  totalCmCount = 0;


  // Known Counts
  for  (idx = Jobs ()->begin ();  idx != Jobs ()->end ();  idx++)
  {
    RandomSplitJobPtr j = dynamic_cast<RandomSplitJobPtr> (*idx);
    if  (j->RandomSplitsResults () != NULL)
    {
      KKStr splitNumStr = StrFormatInt (j->SplitNum (), "ZZZ0");
      j->GetClassCounts (classAccs, knownCounts, predCounts, adjCounts, adjCountsStdError, predDelta, adjDelta);

      totalCM.AddIn (*(j->RandomSplitsResults ()), log);
      totalCmCount++;
      KKStr accLine        = "Acc By Class\t" + splitNumStr;
      KKStr knownLine      = "Known\t"        + splitNumStr;
      KKStr predLine       = "Predicted\t"    + splitNumStr;
      KKStr adjLine        = "Adjusted\t"     + splitNumStr;
      KKStr deltaPredLine  = "Delta Pred\t"   + splitNumStr;
      KKStr deltaAdjLine   = "Delta Adj\t"    + splitNumStr;


      double  totalAcc       = 0.0;
      double  totalDeltaPred = 0.0;
      double  totalDeltaAdj  = 0.0;

      for  (x = 0;  x < numClasses;  x++)
//.........这里部分代码省略.........

void  CmdLineExpander::BuildCmdLineParameters (const VectorKKStr&  argv)
{
  kkuint32  x = 0;

  while  (x < argv.size ())
  {
    KKStr  s = argv[x];
    x++;

    KKStr  sUpper = s.ToUpper();
    if  ((sUpper == "-L")  ||  (sUpper == "-LOGFILE"))
    {
      if  (x < argv.size ())
      {
        if  (argv[x][(kkint16)0] != '-')
        {
          logFileName = argv[x];
          if  (!logFileName.Empty ())
            log.AttachFile (logFileName);
          x++;
        }
      }

      if  (logFileName.Empty ())
      {
        log.Level (-1) << std::endl << std::endl;
        log.Level (-1) << applicationName   << " - Invalid Log File Parameter (-L)." << endl;
        log.Level (-1) << "                 Name of log file required."              << endl;
        log.Level (-1) << endl;
        parmsGood = false;
      }

    }

    else if  (sUpper == "-CMDFILE")
    {
      KKStr  cmdFileName = "";

      if  (x < argv.size ())
      {
        if  (argv[x][(kkint16)0] != '-')
        {
          cmdFileName = argv[x];
          x++;
        }
      }

      if  (cmdFileName.Empty ())
      {
        log.Level (-1) << endl << endl << endl
             << applicationName  << "  "  << "BuildCmdLineParameters             *** ERROR ***"  << endl << endl
             << "-CMDFILE option did not define a file name." << endl
             << endl;

        parmsGood = false;
      }

      else
      {
        if  (FileInStack (cmdFileName, cmdFileStack))
        {
          log.Level (-1) << endl << endl << endl
               << applicationName  << "  BuildCmdLineParameters             *** ERROR ***"  << endl 
               << endl
               << "-CMDFILE [" << cmdFileName << "]  is being called recursively."  << endl
               << endl;
 
          parmsGood = false;
        }
        else
        {
          bool  validFile = true;
          cmdFileStack.push_back (cmdFileName);
          VectorKKStr  cmdFileParameters;
          ExtractParametersFromFile (cmdFileName, cmdFileParameters, validFile);
          BuildCmdLineParameters (cmdFileParameters);
          cmdFileStack.pop_back ();
          if  (!validFile)
            parmsGood = false;
        }
      }
    }

    else
    {
      expandedParameters.push_back (s);
    }
  }
}  /* BuildCmdLineParameters */

//.........这里部分代码省略.........
  {
    LLoydsEntryListPtr  allClassesLLoydsEntries = DeriveAllLLoydsBins (images);

    // Create a report for all classes
    KKStr  randomReportFileName;
    if  (reportFileName.Empty ())
      randomReportFileName = "RandomDistanceReport_All.txt";
    else
      randomReportFileName = osRemoveExtension  (reportFileName) + "_Random_All.txt";

    ofstream randomReport (randomReportFileName.Str ());

    randomReport << "Source Directory  [" << sourceRootDirPath  << "]" << endl;
    randomReport << "Class             [" << "All"              << "]" << endl;

    {
      // Find the mean and stddev of Nearest Neighbor regardless of class.
      NeighborList  allClassesNeighbors (images, log);
      allClassesNeighbors.FindNearestNeighbors (NeighborType::AnyPlankton, fromPlankton);

      double  allClassesMinDistAnyClass    = 0.0f;
      double  allClassesMaxDistAnyClass    = 0.0f;

      allClassesNeighbors.CalcStatistics (allClassesMeanNNDAnyClass,
                                          allClassesMeanStdDevAnyClass, 
                                          allClassesMinDistAnyClass,
                                          allClassesMaxDistAnyClass
                                         );
    }


    RandomNND  randomizeLocations (lastScanLine, 
                                   images, 
                                   numOfIterations, 
                                   numOfBuckets, 
                                   bucketSize, 
                                   randomReport, 
                                   log
                                  );

    randomizeLocations.GenerateReport ();

    // All classes Z-Score
    double  allClassesRandomMeanNND   = randomizeLocations.NND_Mean   ();
    double  allClassesRandomStdDevNND = randomizeLocations.NND_StdDev ();
    double  allClassesRealDataU2Stat  = randomizeLocations.RealDataU2Stat ();
    double  z_Score = Z_Score (allClassesMeanNNDAnyClass, allClassesRandomMeanNND, allClassesRandomStdDevNND, images.QueueSize ());

    KKStr  zScoreSummaryLine = KKStr ("All-Classes") + "\t" +
                                StrFormatDouble (allClassesMeanNNDAnyClass,     "###,##0.00")  + "\t" +
                                StrFormatDouble (allClassesMeanStdDevAnyClass,  "###,##0.00")  + "\t" +
                                StrFormatDouble (allClassesRandomMeanNND,       "###,##0.00")  + "\t" +
                                StrFormatDouble (allClassesRandomStdDevNND,     "###,##0.00")  + "\t" +
                                StrFormatDouble (z_Score,                       "###,##0.00");

    zScoreSummaryLines.push_back (zScoreSummaryLine);


    randomReport << endl << endl << endl
                 << "Z-Score" << endl
                 << "=======" << endl
                 << endl    
                 << "SampleMeanNND   " << "\t" << allClassesMeanNNDAnyClass     << endl
                 << "SampleStdDevNND " << "\t" << allClassesMeanStdDevAnyClass  << endl
                 << "RandomMeanNND   " << "\t" << allClassesRandomMeanNND       << endl
                 << "RandomStdDevNND " << "\t" << allClassesRandomStdDevNND     << endl
                 << "------- Z-Score " << "\t" << z_Score                       << endl
                 << endl;

    classSummaries.PushOnBack (new ClassSummary (MLClass::CreateNewMLClass (KKStr ("AllClasses")), 
                                                 allClassesLLoydsEntries, 
                                                 (float)allClassesRealDataU2Stat, 
                                                 (float)z_Score
                                                )
                              );
  }

  {
    // Z-Score Summary Report
    KKB::kkuint32  x;

    *report << std::endl << std::endl
      << "Z-Score Summary By Class" << std::endl
            << std::endl
            << "ClassName"  << "\t"  << "SampleMean"  << "\t"  << "SampleStdDev" << "\t" << "RandomMean" << "\t" << "RandomStdDev" << "\t" << "Z-Score" << std::endl
            << "========="  << "\t"  << "=========="  << "\t"  << "============" << "\t" << "==========" << "\t" << "============" << "\t" << "=======" << std::endl;

    for  (x = 0;  x < zScoreSummaryLines.size ();  x++)
      *report << zScoreSummaryLines[x] << std::endl;
  }

  *report << endl << endl << endl;
  classSummaries.SummaryReport (*report);

  *report << endl << endl << endl;
  classSummaries.SpatialOverlapReport (*report);

  classSummaries.SaveLLoydsBinsData (lloydsBinsFileName, sourceRootDirPath, lastScanLine, baseLLoydsBinSize);
                                           
}  /* RandomReport */