MatrixInd_1

//+------------------------------------------------------------------+
//|                                                  MatrixInd_1.mq4 |
//|                      Copyright © 2008, MetaQuotes Software Corp. |
//|                                        http://www.metaquotes.net |
//+------------------------------------------------------------------+
#property copyright "Copyright © 2008, MetaQuotes Software Corp."
#property link      "http://www.metaquotes.net"

#property indicator_separate_window
//#property indicator_chart_window
#property indicator_buffers 3
#property indicator_color1 Yellow
#property indicator_color2 Red
#property indicator_color3 LightSeaGreen
#property indicator_level1 0.0

#define LIN1 100 //sample lines
#define LIN2 100 //test lines
#define COL 3  //attributes


extern bool normalize_bufers = true;
extern   int normalize_type=1;


double M_test_attr[LIN2][COL]; 
double M_sample_attr[LIN1][COL];  

double Buffer1[];
double Buffer2[];
double Buffer3[];


//+------------------------------------------------------------------+
//| Custom indicator initialization function                         |
//+------------------------------------------------------------------+
int init()
  {
//---- indicators
   SetIndexStyle(0,DRAW_LINE);
   SetIndexBuffer(0,Buffer1);
   SetIndexStyle(1,DRAW_LINE);
   SetIndexBuffer(1,Buffer2);
   SetIndexStyle(2,DRAW_LINE);
   SetIndexBuffer(2,Buffer3);
//----
   return(0);
  }
//+------------------------------------------------------------------+
//| Custom indicator deinitialization function                       |
//+------------------------------------------------------------------+
int deinit()
  {
//----
   
//----
   return(0);
  }
//+------------------------------------------------------------------+
//| Custom indicator iteration function                              |
//+------------------------------------------------------------------+
int start()
  {
   int    counted_bars=IndicatorCounted();
//----
if(isNewBar1(PERIOD_M1))
{
  main();
}    
//----
   return(0);
  }
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+
//| Custom indicator iteration function                              |
//+------------------------------------------------------------------+
int myBars1;

bool isNewBar1(int tf1)
  {
//----
   bool res=false;
   if (myBars1!=iBars(Symbol(),tf1))
   {
      res=true;
      myBars1=iBars(Symbol(),tf1);
   }  
  
//----
   return(res);
  }
  
void main()
{
  int i,j;
  
  for(i=0;i<LIN1;i++)
    for(j=0;j<COL;j++)
      M_sample_attr[i][j]=MathRand();   
  
  for(i=0;i<LIN2;i++)
    for(j=0;j<COL;j++)
      M_test_attr[i][j]=MathRand(); 
      
      
  if(normalize_bufers)    
    svm_normalize_test(M_sample_attr,M_test_attr,normalize_type);	      
  for(i=0; i < LIN2;i++)
  {      
     Buffer1[i]=M_test_attr[i][0];    
     Buffer2[i]=M_test_attr[i][1];    
     Buffer3[i]=M_test_attr[i][2];    
  }
}  


/////////////////////////////////////////////////////////////////
#define DBL_MAX 99999999999999999999
//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
double MAX(double x, double y)
{
  if(x>y)
    return(x);
  else
    return(y);  
}

//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
double MIN(double x, double y)
{
  if(x<y)
    return(x);
  else
    return(y);  
}

//+------------------------------------------------------------------+
//| Normalize matrix 'fmx' using precomputed 'xmean', 'std'. The                                                                  
//| normalization is: for each column, subtract 'xmean' and, if the
//| column 'std' is non-zero, divide by 'std'.
//| d=nr_of_attrib
//| nv=nr_of_sample_lines 
//| double **x --> double **svm_samples_attrib_scaled_dyn_
//| double *xmean = fmx_mean(x2, nv, d);
//| double *std = fmx_std(x2, nv, d);
//| fmx_prenorm(x, nv, d, xmean, std);
//|       X  - mean
//|        i
//|   S = ---------
//|    i     std
//+------------------------------------------------------------------+
void fmx_prenorm(
                 double &fmx[][], 
                 double xmean[], //  double *xmean = fmx_mean(x2, nv, d);
                 double std[]   //  double *std = fmx_std(x2, nv, d);
                 )
{
  int    i;
  int    j;
  double  f;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);

    for (i = 0; i < columns; i++)
      for (j = 0; j < rows; j++)
	  {
	    f = fmx[j][i];
	      if (std[i] != 0)
		     fmx[j][i] = (f-xmean[i])/std[i];
	      else
		     fmx[j][i] = f-xmean[i];
	 }
	 

	 
}

//+------------------------------------------------------------------+
//|              max X  +  min X
//|               i   i     i   i
//|   midrange = ----------------
//|                     2
//|   range = max X  -  min X
//|            i   i     i   i
//|    
//|       X  - midrange
//|        i
//|   S = -------------
//|    i     range / 2                                                                     
//+------------------------------------------------------------------+
void fmx_prenorm_range(
                       double &fmx[][], 
                       double xrange[], 
                       double xmidrange[] 
                       )
{
  int    i;
  int    j;
  double  f;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);

  for (i = 0; i < columns; i++)
    for (j = 0; j < rows; j++)
    {
	    f = fmx[j][i];
	      if (xrange[i] != 0)
		    fmx[j][i] = (f-xmidrange[i])/(xrange[i]/2);
	      else
		    fmx[j][i] = f-xmidrange[i];

	  }
}

//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
void fmx_midrange(double  &xmidrange[],double fmx[][])
{
  int    i;
  int    j;
  double smax = -DBL_MAX;
  double smin = DBL_MAX;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);
  ArrayResize(xmidrange,columns);
  for (i = 0; i < columns; i++)
  {
     smax = -DBL_MAX;
     smin = DBL_MAX;
     for (j = 0; j < rows; j++)
	  {
	      smax=MAX(fmx[j][i],smax);
         smin=MIN(fmx[j][i],smin);
     }  
	  xmidrange[i] = (smax+smin)/2;
  }
}
//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
void fmx_range(double  &xrange[], double fmx[][])
{
  int    i;
  int    j;
  double smax = -DBL_MAX;
  double smin = DBL_MAX;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);
  ArrayResize(xrange,columns);
  for (i = 0; i < columns; i++)
  {
     smax = -DBL_MAX;
     smin = DBL_MAX;
     for (j = 0; j < rows; j++)
	  {
	     smax=MAX(fmx[j][i],smax);
        smin=MIN(fmx[j][i],smin);
     }  
	  xrange[i] = smax-smin;
   }

}


//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
void fmx_max(double &xrange[],double fmx[][])
{
  int    i;
  int    j;
  double smax = -DBL_MAX;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);

  ArrayResize(xrange,columns);
  for (i = 0; i < columns; i++)
  {
    smax = -DBL_MAX;
	 for (j = 0; j < rows; j++)
	 {
	   smax=MAX(fmx[j][i],smax);
    }  
    xrange[i] = smax;
  }
}

//+------------------------------------------------------------------+
//|                                                                  
//+------------------------------------------------------------------+
void fmx_min(double &xrange[],double fmx[][])
{
  int    i;
  int    j;
  double smin = DBL_MAX;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);

  ArrayResize(xrange,columns);
  for (i = 0; i < columns; i++)
  {
    smin = DBL_MAX;
    for (j = 0; j < rows; j++)
	 {
      smin=MIN(fmx[j][i],smin);
    }  
    xrange[i] = smin;
  }
}

//+------------------------------------------------------------------+
//| Return mean values of columns in 'fmx'.                                                                  
//+------------------------------------------------------------------+
void fmx_mean(double &xmean[], double fmx[][])
{
  int    i;
  int    j;
  double s;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);

  ArrayResize(xmean,columns);
  if (rows > 1)
  {
    for (i = 0; i < columns; i++)
	 {
	   s = 0.0;
	   for (j = 0; j < rows; j++)
	     s += fmx[j][i];
		  xmean[i] = s/rows;
	 }
  }
  else
  {
    for (i = 0; i < columns; i++)
	   xmean[i] = fmx[0][i];
  }
}

//+------------------------------------------------------------------+
//| Set elements of 'vec' to 'value'.                                                                  
//+------------------------------------------------------------------+
void fvec_set(double &vec[], int len, double value)
{
  int i;
  ArrayResize(vec,len);  
  for (i = 0; i < len; i++)
    vec[i] = value;
}

//+------------------------------------------------------------------+
//|  Return standard deviations of columns in 'fmx'.
//+------------------------------------------------------------------+
void fmx_std(double  &std[], double fmx[][])
{
  int    i;
  int    j;
  double  xmean;
  double s;
  int rows = ArrayRange(fmx,0);
  int columns = ArrayRange(fmx,1);
  
  ArrayResize(std,columns);
  if (rows > 1)
  {  
    for (i = 0; i < columns; i++)
    {
	      s = 0.0;
	      for (j = 0; j < rows; j++)
		s += fmx[j][i];
	      xmean = s/rows;
	      s = 0.0;
	      for (j = 0; j < rows; j++)
		s += (fmx[j][i]-xmean)*(fmx[j][i]-xmean);
	      std[i] = MathSqrt(s/(rows-1));
    }
  }  
  else
   fvec_set(std, columns, 0.0);
}

//+------------------------------------------------------------------+
//| 1-normalize TRAIN lines from std and mean calculated from TRAIN lines
//| 1-normalize TEST lines from std and mean calculated from TEST lines
//| ..................................................................
//| 2-normalize TRAIN lines from std and mean calculated from TRAIN lines  
//| 2-normalize TEST lines from std and mean calculated from TRAIN lines    
//| ..................................................................
//| 3-normalize TRAIN lines from range and midrange calculated from TRAIN lines   
//| 3-normalize TEST lines from range and midrange calculated from TEST lines 
//| ..................................................................
//| 4-normalize TEST lines from range and midrange calculated from TRAIN lines                                                          
//+------------------------------------------------------------------+
void svm_normalize_sample(
								double &svm_samples_attrib[][],							
								int normalize
							 )
{

  double xmean[];   
  double std[];  
  double xrange[];  
  double xmidrange[];  

  
  if(normalize==1 || normalize==2)
  { //normalize TRAIN lines from std and mean calculated from TRAIN lines
    fmx_mean(xmean,svm_samples_attrib);
    fmx_std(std,svm_samples_attrib);
    fmx_prenorm(svm_samples_attrib,xmean, std);
  } 
  else if(normalize==3)
  { //normalize TRAIN lines from range and midrange calculated from TRAIN lines
    fmx_range(xrange,svm_samples_attrib);
    fmx_midrange(xmidrange,svm_samples_attrib);       
    fmx_prenorm_range(svm_samples_attrib,xrange, xmidrange);
  }

}

//+------------------------------------------------------------------+
//| 1-normalize TEST lines from std and mean calculated from TEST lines
//| 2-normalize TEST lines from std and mean calculated from TRAIN lines     
//| 3-normalize TEST lines from range and midrange calculated from TEST lines
//| 4-normalize TEST lines from range and midrange calculated from TRAIN lines                                                             
//+------------------------------------------------------------------+
void svm_normalize_test(
	                     double svm_samples_attrib[][],
								double &svm_test_attrib[][],								
								int normalize
							)		
							
{

  if(normalize==1)
  {  //normalize TEST lines from std and mean calculated from TEST lines
    double xmean2[]; 
    fmx_mean(xmean2,svm_test_attrib);
    double std2[];
    fmx_std(std2,svm_test_attrib);
    fmx_prenorm(svm_test_attrib,xmean2, std2);
  }                 
  else if(normalize==2)
  { //normalize TEST lines from std and mean calculated from TRAIN lines
    double xmean1[];
    fmx_mean(xmean1,svm_samples_attrib);
    double std1[];
    fmx_std(std1,svm_samples_attrib);
    fmx_prenorm(svm_test_attrib, xmean1, std1);
  }
  else if(normalize==3)
  { //normalize TEST lines from range and midrange calculated from TEST lines
    double xrange2[];
    fmx_range(xrange2,svm_test_attrib);
    double xmidrange2[];
    fmx_midrange(xmidrange2,svm_test_attrib);   
    fmx_prenorm_range(svm_test_attrib, xrange2, xmidrange2);
  }
  else if(normalize==4)
  { //normalize TEST lines from range and midrange calculated from TRAIN lines
    double xrange1[];
    fmx_range(xrange1,svm_samples_attrib);
    double xmidrange1[];
    fmx_midrange(xmidrange1,svm_samples_attrib);                                       
    fmx_prenorm_range(svm_test_attrib, xrange1, xmidrange1);
  }
  
}