Averages_rainbow

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#property copyright   "© mladen, 2017, mladenfx@gmail.com"

#property link        "www.forex-station.com"

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#property indicator_chart_window

#property indicator_buffers 512

#property indicator_plots   256



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enum enPrices

{

   pr_close,      // Close

   pr_open,       // Open

   pr_high,       // High

   pr_low,        // Low

   pr_median,     // Median

   pr_typical,    // Typical

   pr_weighted,   // Weighted

   pr_average,    // Average (high+low+open+close)/4

   pr_medianb,    // Average median body (open+close)/2

   pr_tbiased,    // Trend biased price

   pr_tbiased2,   // Trend biased (extreme) price

   pr_haclose,    // Heiken ashi close

   pr_haopen ,    // Heiken ashi open

   pr_hahigh,     // Heiken ashi high

   pr_halow,      // Heiken ashi low

   pr_hamedian,   // Heiken ashi median

   pr_hatypical,  // Heiken ashi typical

   pr_haweighted, // Heiken ashi weighted

   pr_haaverage,  // Heiken ashi average

   pr_hamedianb,  // Heiken ashi median body

   pr_hatbiased,  // Heiken ashi trend biased price

   pr_hatbiased2  // Heiken ashi trend biased (extreme) price

};

enum enMaTypes

{

   ma_sma,    // Simple moving average

   ma_ema,    // Exponential moving average

   ma_smma,   // Smoothed MA

   ma_lwma    // Linear weighted MA

};



input enMaTypes       AvgMethod        = ma_ema;         // Average method

input int             AvgAverages      = 50;             // Averages No.

input int             AvgPeriodStart   = 10;             // Starting average period

input int             AvgStep          = 2;              // Step to increase consecutive averages

input enPrices        AvgPrice         = pr_close;       // Price

input color           ColorUp          = clrDeepSkyBlue; // Color for slope up

input color           ColorDn          = clrSandyBrown;  // Color for slope down

input int             LinesWidth       = 0;              // Averages lines width

input ENUM_LINE_STYLE LinesStyle       = STYLE_SOLID;    // Averages lines style



int totalAvgs;



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struct simpleBuff 

{ 

   double buffer[]; 

   double bufferColor[]; 

};

simpleBuff wbuffer[256];



int OnInit()

{

   totalAvgs = MathMax(MathMin(AvgAverages,256),1);

   for (int i=0; i<totalAvgs; i++)

   {

      SetIndexBuffer(i*2  ,wbuffer[i].buffer     ,INDICATOR_DATA);

      SetIndexBuffer(i*2+1,wbuffer[i].bufferColor,INDICATOR_COLOR_INDEX);

         PlotIndexSetInteger(i,PLOT_DRAW_TYPE,DRAW_COLOR_LINE);

         PlotIndexSetInteger(i,PLOT_COLOR_INDEXES,2);

         PlotIndexSetInteger(i,PLOT_LINE_COLOR,0,ColorUp);

         PlotIndexSetInteger(i,PLOT_LINE_COLOR,1,ColorDn);

         PlotIndexSetInteger(i,PLOT_LINE_WIDTH,LinesWidth);

         PlotIndexSetInteger(i,PLOT_LINE_STYLE,LinesStyle);

         PlotIndexSetString(i,PLOT_LABEL,"Average ("+(string)(AvgPeriodStart+AvgStep*i)+")");

   }

   return(0);

}



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int OnCalculate(const int rates_total,

                const int prev_calculated,

                const datetime& time[],

                const double& open[],

                const double& high[],

                const double& low[],

                const double& close[],

                const long& tick_volume[],

                const long& volume[],

                const int& spread[])

{ 

   if (Bars(_Symbol,_Period)<rates_total) return(-1);

   

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   int i=(int)MathMax(prev_calculated-1,0); for (; i<rates_total && !IsStopped(); i++)

   {

      double price = getPrice(AvgPrice,open,close,high,low,i,rates_total);

      for (int k=0; k<totalAvgs; k++)

      {

         wbuffer[k].buffer[i]      = iCustomMa(AvgMethod,price,AvgPeriodStart+k*AvgStep,i,rates_total,k);

         wbuffer[k].bufferColor[i] = (i>0) ? (wbuffer[k].buffer[i]>wbuffer[k].buffer[i-1]) ? 0 : (wbuffer[k].buffer[i]<wbuffer[k].buffer[i-1]) ? 1 : wbuffer[k].bufferColor[i-1] : 0;

      }         

   }

   return(i);

}



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#define _maInstances 256

#define _maWorkBufferx1 1*_maInstances

double iCustomMa(int mode, double price, double length, int r, int bars, int instanceNo=0)

{

   switch (mode)

   {

      case ma_sma   : return(iSma(price,(int)length,r,bars,instanceNo));

      case ma_ema   : return(iEma(price,length,r,bars,instanceNo));

      case ma_smma  : return(iSmma(price,(int)length,r,bars,instanceNo));

      case ma_lwma  : return(iLwma(price,(int)length,r,bars,instanceNo));

      default       : return(price);

   }

}



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double workSma[][_maWorkBufferx1];

double iSma(double price, int period, int r, int _bars, int instanceNo=0)

{

   if (ArrayRange(workSma,0)!= _bars) ArrayResize(workSma,_bars); int k=1;



   workSma[r][instanceNo+0] = price;

   double avg = price; for(; k<period && (r-k)>=0; k++) avg += workSma[r-k][instanceNo+0];  avg /= (double)k;

   return(avg);

}



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double workEma[][_maWorkBufferx1];

double iEma(double price, double period, int r, int _bars, int instanceNo=0)

{

   if (ArrayRange(workEma,0)!= _bars) ArrayResize(workEma,_bars);



   workEma[r][instanceNo] = price;

   if (r>0 && period>1)

          workEma[r][instanceNo] = workEma[r-1][instanceNo]+(2.0/(1.0+period))*(price-workEma[r-1][instanceNo]);

   return(workEma[r][instanceNo]);

}



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double workSmma[][_maWorkBufferx1];

double iSmma(double price, double period, int r, int _bars, int instanceNo=0)

{

   if (ArrayRange(workSmma,0)!= _bars) ArrayResize(workSmma,_bars);



   workSmma[r][instanceNo] = price;

   if (r>1 && period>1)

          workSmma[r][instanceNo] = workSmma[r-1][instanceNo]+(price-workSmma[r-1][instanceNo])/period;

   return(workSmma[r][instanceNo]);

}



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double workLwma[][_maWorkBufferx1];

double iLwma(double price, double period, int r, int _bars, int instanceNo=0)

{

   if (ArrayRange(workLwma,0)!= _bars) ArrayResize(workLwma,_bars);

   

   workLwma[r][instanceNo] = price; if (period<1) return(price);

      double sumw = period;

      double sum  = period*price;



      for(int k=1; k<period && (r-k)>=0; k++)

      {

         double weight = period-k;

                sumw  += weight;

                sum   += weight*workLwma[r-k][instanceNo];  

      }             

      return(sum/sumw);

}



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#define _pricesInstances 1

#define _pricesSize      4

double workHa[][_pricesInstances*_pricesSize];

double getPrice(int tprice, const double& open[], const double& close[], const double& high[], const double& low[], int i,int _bars, int instanceNo=0)

{

  if (tprice>=pr_haclose)

   {

      if (ArrayRange(workHa,0)!= _bars) ArrayResize(workHa,_bars); instanceNo*=_pricesSize;

         

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         double haOpen;

         if (i>0)

                haOpen  = (workHa[i-1][instanceNo+2] + workHa[i-1][instanceNo+3])/2.0;

         else   haOpen  = (open[i]+close[i])/2;

         double haClose = (open[i] + high[i] + low[i] + close[i]) / 4.0;

         double haHigh  = MathMax(high[i], MathMax(haOpen,haClose));

         double haLow   = MathMin(low[i] , MathMin(haOpen,haClose));



         if(haOpen  <haClose) { workHa[i][instanceNo+0] = haLow;  workHa[i][instanceNo+1] = haHigh; } 

         else                 { workHa[i][instanceNo+0] = haHigh; workHa[i][instanceNo+1] = haLow;  } 

                                workHa[i][instanceNo+2] = haOpen;

                                workHa[i][instanceNo+3] = haClose;

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         switch (tprice)

         {

            case pr_haclose:     return(haClose);

            case pr_haopen:      return(haOpen);

            case pr_hahigh:      return(haHigh);

            case pr_halow:       return(haLow);

            case pr_hamedian:    return((haHigh+haLow)/2.0);

            case pr_hamedianb:   return((haOpen+haClose)/2.0);

            case pr_hatypical:   return((haHigh+haLow+haClose)/3.0);

            case pr_haweighted:  return((haHigh+haLow+haClose+haClose)/4.0);

            case pr_haaverage:   return((haHigh+haLow+haClose+haOpen)/4.0);

            case pr_hatbiased:

               if (haClose>haOpen)

                     return((haHigh+haClose)/2.0);

               else  return((haLow+haClose)/2.0);        

            case pr_hatbiased2:

               if (haClose>haOpen)  return(haHigh);

               if (haClose<haOpen)  return(haLow);

                                    return(haClose);        

         }

   }

   

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   switch (tprice)

   {

      case pr_close:     return(close[i]);

      case pr_open:      return(open[i]);

      case pr_high:      return(high[i]);

      case pr_low:       return(low[i]);

      case pr_median:    return((high[i]+low[i])/2.0);

      case pr_medianb:   return((open[i]+close[i])/2.0);

      case pr_typical:   return((high[i]+low[i]+close[i])/3.0);

      case pr_weighted:  return((high[i]+low[i]+close[i]+close[i])/4.0);

      case pr_average:   return((high[i]+low[i]+close[i]+open[i])/4.0);

      case pr_tbiased:   

               if (close[i]>open[i])

                     return((high[i]+close[i])/2.0);

               else  return((low[i]+close[i])/2.0);        

      case pr_tbiased2:   

               if (close[i]>open[i]) return(high[i]);

               if (close[i]<open[i]) return(low[i]);

                                     return(close[i]);        

   }

   return(0);

}