Laguerre stripped 1.01

Author: © mladen, 2017
Price Data Components
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Laguerre stripped 1.01
ÿþ//------------------------------------------------------------------

#property copyright "© mladen, 2017"

#property link      "mladenfx@gmail.com"

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

//------------------------------------------------------------------

#property indicator_chart_window

#property indicator_buffers 10

#property indicator_plots   7

#property indicator_label1  "Fill 1"

#property indicator_type1   DRAW_FILLING

#property indicator_color1  C'0,205,126',C'155,0,126'

#property indicator_label2  "Fill 2"

#property indicator_type2   DRAW_FILLING

#property indicator_color2  C'0,180,126',C'180,0,126'

#property indicator_label3  "Fill 3"

#property indicator_type3   DRAW_FILLING

#property indicator_color3  C'0,155,126',C'205,0,126'

#property indicator_label4  "Laguerre 1"

#property indicator_type4   DRAW_LINE

#property indicator_color4  clrGray

#property indicator_label5  "Laguerre 2"

#property indicator_type5   DRAW_LINE

#property indicator_color5  clrGray

#property indicator_label6  "Laguerre 3"

#property indicator_type6   DRAW_LINE

#property indicator_color6  clrGray

#property indicator_label7  "Laguerre 4"

#property indicator_type7   DRAW_LINE

#property indicator_color7  clrGray



//

//

//

//

//



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   Gamma = 0.75;      // Gamma

input enPrices Price = pr_close;  // Price



double lagg1u[],lagg1d[],lagg2u[],lagg2d[],lagg3u[],lagg3d[],lagg1[],lagg2[],lagg3[],lagg4[];



//------------------------------------------------------------------

//

//------------------------------------------------------------------

//

//

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//

//



int OnInit()

{

   SetIndexBuffer(0,lagg1u ,INDICATOR_DATA);

   SetIndexBuffer(1,lagg1d ,INDICATOR_DATA);

   SetIndexBuffer(2,lagg2u ,INDICATOR_DATA);

   SetIndexBuffer(3,lagg2d ,INDICATOR_DATA);

   SetIndexBuffer(4,lagg3u ,INDICATOR_DATA);

   SetIndexBuffer(5,lagg3d ,INDICATOR_DATA);

   SetIndexBuffer(6,lagg1  ,INDICATOR_DATA);

   SetIndexBuffer(7,lagg2  ,INDICATOR_DATA);

   SetIndexBuffer(8,lagg3  ,INDICATOR_DATA);

   SetIndexBuffer(9,lagg4  ,INDICATOR_DATA);

   return(0);

}



//------------------------------------------------------------------

//

//------------------------------------------------------------------

//

//

//

//

//



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);

   

   //

   //

   //

   //

   //



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

   {

      double laga,lagb,lagc,lagd; 

         iLaGuerre(getPrice(Price,open,close,high,low,i,rates_total),Gamma,laga,lagb,lagc,lagd,i,rates_total,0);

            lagg1[i]  = laga;

            lagg2[i]  = lagb;

            lagg3[i]  = lagc;

            lagg4[i]  = lagd;

            lagg1u[i] = laga;

            lagg1d[i] = lagb;

            lagg2u[i] = lagb;

            lagg2d[i] = lagc;

            lagg3u[i] = lagc;

            lagg3d[i] = lagd;

   }

   return(i);

}



//------------------------------------------------------------------

//

//------------------------------------------------------------------

//

//

//

//

//



double workLag[][4];

void iLaGuerre(double price, double gamma, double& val1, double& val2, double& val3, double& val4, int i, int bars, int instanceNo=0)

{

   if (ArrayRange(workLag,0)!=bars) ArrayResize(workLag,bars); instanceNo*=4;



   //

   //

   //

   //

   //



   gamma = MathMax(MathMin(gamma,0.99),0.01);

   if (i>0)

   {      

      workLag[i][instanceNo+0] = (1.0 - gamma)*price                                          + gamma*workLag[i-1][instanceNo+0];

	   workLag[i][instanceNo+1] = -gamma*workLag[i][instanceNo+0] + workLag[i-1][instanceNo+0] + gamma*workLag[i-1][instanceNo+1];

	   workLag[i][instanceNo+2] = -gamma*workLag[i][instanceNo+1] + workLag[i-1][instanceNo+1] + gamma*workLag[i-1][instanceNo+2];

	   workLag[i][instanceNo+3] = -gamma*workLag[i][instanceNo+2] + workLag[i-1][instanceNo+2] + gamma*workLag[i-1][instanceNo+3];

   }	   

   else for (int k=0; k<4; k++) workLag[i][instanceNo+k] = price;

   val1 = workLag[i][instanceNo+0];

   val2 = workLag[i][instanceNo+1];

   val3 = workLag[i][instanceNo+2];

   val4 = workLag[i][instanceNo+3];

}

//------------------------------------------------------------------

//

//------------------------------------------------------------------

//

//

//

//

//

//



#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;

         

         //

         //

         //

         //

         //

         

         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;

         //

         //

         //

         //

         //

         

         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);        

         }

   }

   

   //

   //

   //

   //

   //

   

   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);

}

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