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  //  If you do not agree to this license, do not download, install,
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  #include "old_ml_precomp.hpp"
  #include <ctype.h>
  
  #define MISS_VAL    FLT_MAX
  #define CV_VAR_MISS    0
  
  CvTrainTestSplit::CvTrainTestSplit()
  {
      train_sample_part_mode = CV_COUNT;
      train_sample_part.count = -1;
      mix = false;
  }
  
  CvTrainTestSplit::CvTrainTestSplit( int _train_sample_count, bool _mix )
  {
      train_sample_part_mode = CV_COUNT;
      train_sample_part.count = _train_sample_count;
      mix = _mix;
  }
  
  CvTrainTestSplit::CvTrainTestSplit( float _train_sample_portion, bool _mix )
  {
      train_sample_part_mode = CV_PORTION;
      train_sample_part.portion = _train_sample_portion;
      mix = _mix;
  }
  
  ////////////////
  
  CvMLData::CvMLData()
  {
      values = missing = var_types = var_idx_mask = response_out = var_idx_out = var_types_out = 0;
      train_sample_idx = test_sample_idx = 0;
      header_lines_number = 0;
      sample_idx = 0;
      response_idx = -1;
  
      train_sample_count = -1;
  
      delimiter = ',';
      miss_ch = '?';
      //flt_separator = '.';
  
      rng = &cv::theRNG();
  }
  
  CvMLData::~CvMLData()
  {
      clear();
  }
  
  void CvMLData::free_train_test_idx()
  {
      cvReleaseMat( &train_sample_idx );
      cvReleaseMat( &test_sample_idx );
      sample_idx = 0;
  }
  
  void CvMLData::clear()
  {
      class_map.clear();
  
      cvReleaseMat( &values );
      cvReleaseMat( &missing );
      cvReleaseMat( &var_types );
      cvReleaseMat( &var_idx_mask );
  
      cvReleaseMat( &response_out );
      cvReleaseMat( &var_idx_out );
      cvReleaseMat( &var_types_out );
  
      free_train_test_idx();
  
      total_class_count = 0;
  
      response_idx = -1;
  
      train_sample_count = -1;
  }
  
  
  void CvMLData::set_header_lines_number( int idx )
  {
      header_lines_number = std::max(0, idx);
  }
  
  int CvMLData::get_header_lines_number() const
  {
      return header_lines_number;
  }
  
  static char *fgets_chomp(char *str, int n, FILE *stream)
  {
      char *head = fgets(str, n, stream);
      if( head )
      {
          for(char *tail = head + strlen(head) - 1; tail >= head; --tail)
          {
              if( *tail != '\r'  && *tail != '\n' )
                  break;
              *tail = '\0';
          }
      }
      return head;
  }
  
  
  int CvMLData::read_csv(const char* filename)
  {
      const int M = 1000000;
      const char str_delimiter[3] = { ' ', delimiter, '\0' };
      FILE* file = 0;
      CvMemStorage* storage;
      CvSeq* seq;
      char *ptr;
      float* el_ptr;
      CvSeqReader reader;
      int cols_count = 0;
      uchar *var_types_ptr = 0;
  
      clear();
  
      file = fopen( filename, "rt" );
  
      if( !file )
          return -1;
  
      std::vector<char> _buf(M);
      char* buf = &_buf[0];
  
      // skip header lines
      for( int i = 0; i < header_lines_number; i++ )
      {
          if( fgets( buf, M, file ) == 0 )
          {
              fclose(file);
              return -1;
          }
      }
  
      // read the first data line and determine the number of variables
      if( !fgets_chomp( buf, M, file ))
      {
          fclose(file);
          return -1;
      }
  
      ptr = buf;
      while( *ptr == ' ' )
          ptr++;
      for( ; *ptr != '\0'; )
      {
          if(*ptr == delimiter || *ptr == ' ')
          {
              cols_count++;
              ptr++;
              while( *ptr == ' ' ) ptr++;
          }
          else
              ptr++;
      }
  
      cols_count++;
  
      if ( cols_count == 0)
      {
          fclose(file);
          return -1;
      }
  
      // create temporary memory storage to store the whole database
      el_ptr = new float[cols_count];
      storage = cvCreateMemStorage();
      seq = cvCreateSeq( 0, sizeof(*seq), cols_count*sizeof(float), storage );
  
      var_types = cvCreateMat( 1, cols_count, CV_8U );
      cvZero( var_types );
      var_types_ptr = var_types->data.ptr;
  
      for(;;)
      {
          char *token = NULL;
          int type;
          token = strtok(buf, str_delimiter);
          if (!token)
              break;
          for (int i = 0; i < cols_count-1; i++)
          {
              str_to_flt_elem( token, el_ptr[i], type);
              var_types_ptr[i] |= type;
              token = strtok(NULL, str_delimiter);
              if (!token)
              {
                  fclose(file);
                  delete [] el_ptr;
                  return -1;
              }
          }
          str_to_flt_elem( token, el_ptr[cols_count-1], type);
          var_types_ptr[cols_count-1] |= type;
          cvSeqPush( seq, el_ptr );
          if( !fgets_chomp( buf, M, file ) )
              break;
      }
      fclose(file);
  
      values = cvCreateMat( seq->total, cols_count, CV_32FC1 );
      missing = cvCreateMat( seq->total, cols_count, CV_8U );
      var_idx_mask = cvCreateMat( 1, values->cols, CV_8UC1 );
      cvSet( var_idx_mask, cvRealScalar(1) );
      train_sample_count = seq->total;
  
      cvStartReadSeq( seq, &reader );
      for(int i = 0; i < seq->total; i++ )
      {
          const float* sdata = (float*)reader.ptr;
          float* ddata = values->data.fl + cols_count*i;
          uchar* dm = missing->data.ptr + cols_count*i;
  
          for( int j = 0; j < cols_count; j++ )
          {
              ddata[j] = sdata[j];
              dm[j] = ( fabs( MISS_VAL - sdata[j] ) <= FLT_EPSILON );
          }
          CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
      }
  
      if ( cvNorm( missing, 0, CV_L1 ) <= FLT_EPSILON )
          cvReleaseMat( &missing );
  
      cvReleaseMemStorage( &storage );
      delete []el_ptr;
      return 0;
  }
  
  const CvMat* CvMLData::get_values() const
  {
      return values;
  }
  
  const CvMat* CvMLData::get_missing() const
  {
      CV_FUNCNAME( "CvMLData::get_missing" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      __END__;
  
      return missing;
  }
  
  const std::map<cv::String, int>& CvMLData::get_class_labels_map() const
  {
      return class_map;
  }
  
  void CvMLData::str_to_flt_elem( const char* token, float& flt_elem, int& type)
  {
  
      char* stopstring = NULL;
      flt_elem = (float)strtod( token, &stopstring );
      assert( stopstring );
      type = CV_VAR_ORDERED;
      if ( *stopstring == miss_ch && strlen(stopstring) == 1 ) // missed value
      {
          flt_elem = MISS_VAL;
          type = CV_VAR_MISS;
      }
      else
      {
          if ( (*stopstring != 0) && (*stopstring != '\n') && (strcmp(stopstring, "\r\n") != 0) ) // class label
          {
              int idx = class_map[token];
              if ( idx == 0)
              {
                  total_class_count++;
                  idx = total_class_count;
                  class_map[token] = idx;
              }
              flt_elem = (float)idx;
              type = CV_VAR_CATEGORICAL;
          }
      }
  }
  
  void CvMLData::set_delimiter(char ch)
  {
      CV_FUNCNAME( "CvMLData::set_delimited" );
      __BEGIN__;
  
      if (ch == miss_ch /*|| ch == flt_separator*/)
          CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
  
      delimiter = ch;
  
      __END__;
  }
  
  char CvMLData::get_delimiter() const
  {
      return delimiter;
  }
  
  void CvMLData::set_miss_ch(char ch)
  {
      CV_FUNCNAME( "CvMLData::set_miss_ch" );
      __BEGIN__;
  
      if (ch == delimiter/* || ch == flt_separator*/)
          CV_ERROR(CV_StsBadArg, "delimited, miss_character and flt_separator must be different");
  
      miss_ch = ch;
  
      __END__;
  }
  
  char CvMLData::get_miss_ch() const
  {
      return miss_ch;
  }
  
  void CvMLData::set_response_idx( int idx )
  {
      CV_FUNCNAME( "CvMLData::set_response_idx" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      if ( idx >= values->cols)
          CV_ERROR( CV_StsBadArg, "idx value is not correct" );
  
      if ( response_idx >= 0 )
          chahge_var_idx( response_idx, true );
      if ( idx >= 0 )
          chahge_var_idx( idx, false );
      response_idx = idx;
  
      __END__;
  }
  
  int CvMLData::get_response_idx() const
  {
      CV_FUNCNAME( "CvMLData::get_response_idx" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
       __END__;
      return response_idx;
  }
  
  void CvMLData::change_var_type( int var_idx, int type )
  {
      CV_FUNCNAME( "CvMLData::change_var_type" );
      __BEGIN__;
  
      int var_count = 0;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
       var_count = values->cols;
  
      if ( var_idx < 0 || var_idx >= var_count)
          CV_ERROR( CV_StsBadArg, "var_idx is not correct" );
  
      if ( type != CV_VAR_ORDERED && type != CV_VAR_CATEGORICAL)
           CV_ERROR( CV_StsBadArg, "type is not correct" );
  
      assert( var_types );
      if ( var_types->data.ptr[var_idx] == CV_VAR_CATEGORICAL && type == CV_VAR_ORDERED)
          CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
      var_types->data.ptr[var_idx] = (uchar)type;
  
      __END__;
  
      return;
  }
  
  void CvMLData::set_var_types( const char* str )
  {
      CV_FUNCNAME( "CvMLData::set_var_types" );
      __BEGIN__;
  
      const char* ord = 0, *cat = 0;
      int var_count = 0, set_var_type_count = 0;
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      var_count = values->cols;
  
      assert( var_types );
  
      ord = strstr( str, "ord" );
      cat = strstr( str, "cat" );
      if ( !ord && !cat )
          CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
      if ( !ord && strlen(cat) == 3 ) // str == "cat"
      {
          cvSet( var_types, cvScalarAll(CV_VAR_CATEGORICAL) );
          return;
      }
  
      if ( !cat && strlen(ord) == 3 ) // str == "ord"
      {
          cvSet( var_types, cvScalarAll(CV_VAR_ORDERED) );
          return;
      }
  
      if ( ord ) // parse ord str
      {
          char* stopstring = NULL;
          if ( ord[3] != '[')
              CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
          ord += 4; // pass "ord["
          do
          {
              int b1 = (int)strtod( ord, &stopstring );
              if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
                  CV_ERROR( CV_StsBadArg, "types string is not correct" );
              ord = stopstring + 1;
              if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
              {
                  if ( var_types->data.ptr[b1] == CV_VAR_CATEGORICAL)
                      CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
                  var_types->data.ptr[b1] = CV_VAR_ORDERED;
                  set_var_type_count++;
              }
              else
              {
                  if ( stopstring[0] == '-')
                  {
                      int b2 = (int)strtod( ord, &stopstring);
                      if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
                          CV_ERROR( CV_StsBadArg, "types string is not correct" );
                      ord = stopstring + 1;
                      for (int i = b1; i <= b2; i++)
                      {
                          if ( var_types->data.ptr[i] == CV_VAR_CATEGORICAL)
                              CV_ERROR( CV_StsBadArg, "it`s impossible to assign CV_VAR_ORDERED type to categorical variable" );
                          var_types->data.ptr[i] = CV_VAR_ORDERED;
                      }
                      set_var_type_count += b2 - b1 + 1;
                  }
                  else
                      CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
              }
          }
          while (*stopstring != ']');
  
          if ( stopstring[1] != '\0' && stopstring[1] != ',')
              CV_ERROR( CV_StsBadArg, "types string is not correct" );
      }
  
      if ( cat ) // parse cat str
      {
          char* stopstring = NULL;
          if ( cat[3] != '[')
              CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
          cat += 4; // pass "cat["
          do
          {
              int b1 = (int)strtod( cat, &stopstring );
              if ( *stopstring == 0 || (*stopstring != ',' && *stopstring != ']' && *stopstring != '-') )
                  CV_ERROR( CV_StsBadArg, "types string is not correct" );
              cat = stopstring + 1;
              if ( (stopstring[0] == ',') || (stopstring[0] == ']'))
              {
                  var_types->data.ptr[b1] = CV_VAR_CATEGORICAL;
                  set_var_type_count++;
              }
              else
              {
                  if ( stopstring[0] == '-')
                  {
                      int b2 = (int)strtod( cat, &stopstring);
                      if ( (*stopstring == 0) || (*stopstring != ',' && *stopstring != ']') )
                          CV_ERROR( CV_StsBadArg, "types string is not correct" );
                      cat = stopstring + 1;
                      for (int i = b1; i <= b2; i++)
                          var_types->data.ptr[i] = CV_VAR_CATEGORICAL;
                      set_var_type_count += b2 - b1 + 1;
                  }
                  else
                      CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
              }
          }
          while (*stopstring != ']');
  
          if ( stopstring[1] != '\0' && stopstring[1] != ',')
              CV_ERROR( CV_StsBadArg, "types string is not correct" );
      }
  
      if (set_var_type_count != var_count)
          CV_ERROR( CV_StsBadArg, "types string is not correct" );
  
       __END__;
  }
  
  const CvMat* CvMLData::get_var_types()
  {
      CV_FUNCNAME( "CvMLData::get_var_types" );
      __BEGIN__;
  
      uchar *var_types_out_ptr = 0;
      int avcount, vt_size;
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      assert( var_idx_mask );
  
      avcount = cvFloor( cvNorm( var_idx_mask, 0, CV_L1 ) );
      vt_size = avcount + (response_idx >= 0);
  
      if ( avcount == values->cols || (avcount == values->cols-1 && response_idx == values->cols-1) )
          return var_types;
  
      if ( !var_types_out || ( var_types_out && var_types_out->cols != vt_size ) )
      {
          cvReleaseMat( &var_types_out );
          var_types_out = cvCreateMat( 1, vt_size, CV_8UC1 );
      }
  
      var_types_out_ptr = var_types_out->data.ptr;
      for( int i = 0; i < var_types->cols; i++)
      {
          if (i == response_idx || !var_idx_mask->data.ptr[i]) continue;
          *var_types_out_ptr = var_types->data.ptr[i];
          var_types_out_ptr++;
      }
      if ( response_idx >= 0 )
          *var_types_out_ptr = var_types->data.ptr[response_idx];
  
      __END__;
  
      return var_types_out;
  }
  
  int CvMLData::get_var_type( int var_idx ) const
  {
      return var_types->data.ptr[var_idx];
  }
  
  const CvMat* CvMLData::get_responses()
  {
      CV_FUNCNAME( "CvMLData::get_responses_ptr" );
      __BEGIN__;
  
      int var_count = 0;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
      var_count = values->cols;
  
      if ( response_idx < 0 || response_idx >= var_count )
         return 0;
      if ( !response_out )
          response_out = cvCreateMatHeader( values->rows, 1, CV_32FC1 );
      else
          cvInitMatHeader( response_out, values->rows, 1, CV_32FC1);
      cvGetCol( values, response_out, response_idx );
  
      __END__;
  
      return response_out;
  }
  
  void CvMLData::set_train_test_split( const CvTrainTestSplit * spl)
  {
      CV_FUNCNAME( "CvMLData::set_division" );
      __BEGIN__;
  
      int sample_count = 0;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      sample_count = values->rows;
  
      float train_sample_portion;
  
      if (spl->train_sample_part_mode == CV_COUNT)
      {
          train_sample_count = spl->train_sample_part.count;
          if (train_sample_count > sample_count)
              CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
          train_sample_count = train_sample_count<=0 ? sample_count : train_sample_count;
      }
      else // dtype.train_sample_part_mode == CV_PORTION
      {
          train_sample_portion = spl->train_sample_part.portion;
          if ( train_sample_portion > 1)
              CV_ERROR( CV_StsBadArg, "train samples count is not correct" );
          train_sample_portion = train_sample_portion <= FLT_EPSILON ||
              1 - train_sample_portion <= FLT_EPSILON ? 1 : train_sample_portion;
          train_sample_count = std::max(1, cvFloor( train_sample_portion * sample_count ));
      }
  
      if ( train_sample_count == sample_count )
      {
          free_train_test_idx();
          return;
      }
  
      if ( train_sample_idx && train_sample_idx->cols != train_sample_count )
          free_train_test_idx();
  
      if ( !sample_idx)
      {
          int test_sample_count = sample_count- train_sample_count;
          sample_idx = (int*)cvAlloc( sample_count * sizeof(sample_idx[0]) );
          for (int i = 0; i < sample_count; i++ )
              sample_idx[i] = i;
          train_sample_idx = cvCreateMatHeader( 1, train_sample_count, CV_32SC1 );
          *train_sample_idx = cvMat( 1, train_sample_count, CV_32SC1, &sample_idx[0] );
  
          CV_Assert(test_sample_count > 0);
          test_sample_idx = cvCreateMatHeader( 1, test_sample_count, CV_32SC1 );
          *test_sample_idx = cvMat( 1, test_sample_count, CV_32SC1, &sample_idx[train_sample_count] );
      }
  
      mix = spl->mix;
      if ( mix )
          mix_train_and_test_idx();
  
      __END__;
  }
  
  const CvMat* CvMLData::get_train_sample_idx() const
  {
      CV_FUNCNAME( "CvMLData::get_train_sample_idx" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
      __END__;
  
      return train_sample_idx;
  }
  
  const CvMat* CvMLData::get_test_sample_idx() const
  {
      CV_FUNCNAME( "CvMLData::get_test_sample_idx" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
      __END__;
  
      return test_sample_idx;
  }
  
  void CvMLData::mix_train_and_test_idx()
  {
      CV_FUNCNAME( "CvMLData::mix_train_and_test_idx" );
      __BEGIN__;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
      __END__;
  
      if ( !sample_idx)
          return;
  
      if ( train_sample_count > 0 && train_sample_count < values->rows )
      {
          int n = values->rows;
          for (int i = 0; i < n; i++)
          {
              int a = (*rng)(n);
              int b = (*rng)(n);
              int t;
              CV_SWAP( sample_idx[a], sample_idx[b], t );
          }
      }
  }
  
  const CvMat* CvMLData::get_var_idx()
  {
       CV_FUNCNAME( "CvMLData::get_var_idx" );
      __BEGIN__;
  
      int avcount = 0;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      assert( var_idx_mask );
  
      avcount = cvFloor( cvNorm( var_idx_mask, 0, CV_L1 ) );
      int* vidx;
  
      if ( avcount == values->cols )
          return 0;
  
      if ( !var_idx_out || ( var_idx_out && var_idx_out->cols != avcount ) )
      {
          cvReleaseMat( &var_idx_out );
          var_idx_out = cvCreateMat( 1, avcount, CV_32SC1);
          if ( response_idx >=0 )
              var_idx_mask->data.ptr[response_idx] = 0;
      }
  
      vidx = var_idx_out->data.i;
  
      for(int i = 0; i < var_idx_mask->cols; i++)
          if ( var_idx_mask->data.ptr[i] )
          {
              *vidx = i;
              vidx++;
          }
  
      __END__;
  
      return var_idx_out;
  }
  
  void CvMLData::chahge_var_idx( int vi, bool state )
  {
      change_var_idx( vi, state );
  }
  
  void CvMLData::change_var_idx( int vi, bool state )
  {
       CV_FUNCNAME( "CvMLData::change_var_idx" );
      __BEGIN__;
  
      int var_count = 0;
  
      if ( !values )
          CV_ERROR( CV_StsInternal, "data is empty" );
  
      var_count = values->cols;
  
      if ( vi < 0 || vi >= var_count)
          CV_ERROR( CV_StsBadArg, "variable index is not correct" );
  
      assert( var_idx_mask );
      var_idx_mask->data.ptr[vi] = state;
  
      __END__;
  }
  
  /* End of file. */
  