Nema

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#property copyright "© mladen, 2016, MetaQuotes Software Corp."

#property link      "www.forex-tsd.com, www.mql5.com"

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#property indicator_chart_window

#property indicator_buffers 2

#property indicator_plots   1

#property indicator_label1  "nema"

#property indicator_type1   DRAW_COLOR_LINE

#property indicator_color1  clrGray,clrDodgerBlue,clrSandyBrown

#property indicator_width1  2



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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

};

input double   NemaPeriod  = 14;       // NEMA period

input int      NemaDepth   = 1;        // NEMA depth

input enPrices NemaPrice   = pr_close; // Price



double nema[],nemac[];



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int OnInit()

{

   SetIndexBuffer(0,nema ,INDICATOR_DATA); 

   SetIndexBuffer(1,nemac,INDICATOR_COLOR_INDEX); 

   return(0);

}



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double x[],xp[],xf[];

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(0);

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

      {

         nema[i]  = iNema(getPrice(NemaPrice,open,close,high,low,i,rates_total),NemaPeriod,NemaDepth,i,rates_total); 

         nemac[i] = (i>0) ? (nema[i]>nema[i-1]) ? 1 : (nema[i]<nema[i-1]) ? 2 : nemac[i-1] : 0;

      }      

   return(i);

}



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#define _nemaInstances     1

#define _nemaInstancesSize 51

#define _nemcInstancesSize 51

#define _nema              50

double  _workNema[][_nemaInstances*_nemaInstancesSize];

double  _workNemc[][               _nemcInstancesSize];



double iNema(double value, double period, int depth, int i, int bars, int instanceNo=0)

{

   depth = MathMax(MathMin(depth,_nemcInstancesSize-1),1); 

      int cInstance = instanceNo; instanceNo *= _nemaInstancesSize;

         if (ArrayRange(_workNema,0) != bars)         ArrayResize(_workNema,bars);         

         if (ArrayRange(_workNemc,0) < cInstance+1) { ArrayResize(_workNemc,cInstance+1); _workNemc[cInstance][0]=-1; }

         if (_workNemc[cInstance][0] != depth)

            {_workNemc[cInstance][0]  = depth; for(int k=1; k<=depth; k++) _workNemc[cInstance][k] = factorial(depth)/(factorial(depth-k)*factorial(k)); }

      

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   _workNema[i][instanceNo+_nema] = value;

      if (period>1)

      {

         double alpha = 2.0/(1.0+period), sign=1; _workNema[i][instanceNo+_nema] = 0;

         for (int k=0; k<depth; k++, sign *= -1)

         {

            _workNema[i][instanceNo+k    ]  = (i>0) ? _workNema[i-1][instanceNo+k]+alpha*(value-_workNema[i-1][instanceNo+k]) : value; value = _workNema[i][instanceNo+k];

            _workNema[i][instanceNo+_nema] += value*sign*_workNemc[cInstance][k+1];

         }  

      }     

   return(_workNema[i][instanceNo+_nema]);

}

double factorial(int n) { double a=1; for(int i=1; i<=n; i++) a*=i; return(a); }



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#define priceInstances 1

double workHa[][priceInstances*4];

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*=4;

         

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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);

}