#property indicator_separate_window
#property indicator_buffers    3
#property indicator_color1     clrGreen
#property indicator_width1     2
#property indicator_color2     clrRed
#property indicator_width2     2
#property indicator_color3     clrGold
#property indicator_width3     1
#property indicator_minimum    0.0

//
//
//
//
//

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
   pr_habclose,   // Heiken ashi (better formula) close
   pr_habopen ,   // Heiken ashi (better formula) open
   pr_habhigh,    // Heiken ashi (better formula) high
   pr_hablow,     // Heiken ashi (better formula) low
   pr_habmedian,  // Heiken ashi (better formula) median
   pr_habtypical, // Heiken ashi (better formula) typical
   pr_habweighted,// Heiken ashi (better formula) weighted
   pr_habaverage, // Heiken ashi (better formula) average
   pr_habmedianb, // Heiken ashi (better formula) median body
   pr_habtbiased, // Heiken ashi (better formula) trend biased price
   pr_habtbiased2 // Heiken ashi (better formula) 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
   ma_slwma,   // Smoothed LWMA
   ma_dsema,   // Double Smoothed Exponential average
   ma_tema,    // Triple exponential moving average - TEMA
   ma_lsma     // Linear regression value (lsma)
};
enum enCalcType
{
   st_ste, // Use standard error
   st_sam, // Custom standard deviation - with sample correction
   st_nos  // Custom standard deviation - without sample correction
};

extern string    TimeFrame      = "Current time frame";
extern enPrices  Price          = pr_median;        // Price to use
extern int       FastMa         = 20;
extern int       SlowMa         = 40;
extern int       BandsLength    = 21;
extern enMaTypes MaMethod       = ma_sma;           // Moving average method    
extern enCalcType BolDevType    = st_sam;             // Deviation calculation type      
extern double    BandsDeviation = 2.0;
extern int       Sensitive      = 50;
extern bool      Interpolate    = true;

string names[] = {"SMA","EMA","SMMA","LWMA","SLWMA","DSEMA","TEMA","LSMA"};

double buffer1[];
double buffer2[];
double buffer3[]; 
double macd[];
double avgs[];
double avgUp[];
double avgDn[];

string indicatorFileName;
bool   returnBars;
bool   calculateValue;
int    timeFrame;

//+------------------------------------------------------------------+
//|                                                                  |
//+------------------------------------------------------------------+
//
//
//
//
//

int init()
{

   IndicatorBuffers(7);
   SetIndexBuffer(0,buffer1); SetIndexStyle(0, DRAW_HISTOGRAM);
   SetIndexBuffer(1,buffer2); SetIndexStyle(1, DRAW_HISTOGRAM);
   SetIndexBuffer(2,buffer3);
   SetIndexBuffer(3,macd);
   SetIndexBuffer(4,avgs);
   SetIndexBuffer(5,avgUp);
   SetIndexBuffer(6,avgDn);
   
      //
      //
      //
      //
      //
      //
   
      indicatorFileName = WindowExpertName();
      returnBars        = (TimeFrame == "returnBars");     if (returnBars)     return(0);
      calculateValue    = (TimeFrame == "calculateValue"); if (calculateValue) return(0);
      timeFrame         = stringToTimeFrame(TimeFrame);   

      //
      //
      //
      //
      //
      
      
      IndicatorShortName(timeFrameToString(timeFrame)+"   WaddahAttarExplosion of  "+names[MaMethod]+" ("+FastMa+","+SlowMa+","+BandsLength+")");
   return(0);
}
             
//
//
//
//
//

int deinit() {  return(0); }

//+------------------------------------------------------------------+
//|                                                                  |
//+------------------------------------------------------------------+
//
//
//
//
//

int start()
{
   int counted_bars=IndicatorCounted();
   int i,limit;
   
   
   if(counted_bars < 0) return(-1);
   if(counted_bars > 0) counted_bars--;
           limit = MathMin(Bars-counted_bars,Bars-1); 
           if (returnBars) { buffer1[0] = limit+1; return(0); }

   //
   //
   //
   //
   //
   
   if (calculateValue || timeFrame == Period())
   {
   
       for(i=limit; i>=0; i--)
       {
           double price = getPrice(Price,Open,Close,High,Low,i,Bars);
           macd[i] = iCustomMa(MaMethod,price,FastMa,i,Bars,0)-iCustomMa(MaMethod,price,SlowMa,i,Bars,1);  
           double Trend1 = (macd[i] - macd[i+1]) * Sensitive;
           avgs[i]       = iCustomMa(price,BandsLength,i,Bars,2);
           double sDev=0;
           switch (BolDevType)
           {
             case st_ste : sDev = iStdError(price, BandsLength,i,Bars);  break;
             default :     sDev = iDeviation(price,BandsLength,BolDevType==st_sam,i,Bars);
           }            
           avgUp[i]      = avgs[i] + BandsDeviation * sDev;
           avgDn[i]      = avgs[i] - BandsDeviation * sDev;
           double Explo1 = avgUp[i] - avgDn[i];   
               buffer1[i] = EMPTY_VALUE;
               buffer2[i] = EMPTY_VALUE;
               buffer3[i] = EMPTY_VALUE;
                    
               if(Trend1  > 0) buffer1[i] = Trend1;   
               if(Trend1  < 0) buffer2[i] = (-1*Trend1);
                               buffer3[i] = Explo1;           
   }
  return(0);
  }
  
  //
  //
  //
  //
  //
   
  limit = MathMax(limit,MathMin(Bars-1,iCustom(NULL,timeFrame,indicatorFileName,"returnBars",0,0)*timeFrame/Period()));
      
      for(i=limit; i>=0; i--)
      {
        int y = iBarShift(NULL,timeFrame,Time[i]);
            buffer1[i] = iCustom(NULL,timeFrame,indicatorFileName,"calculateValue",Price,FastMa,SlowMa,BandsLength,MaMethod,BandsDeviation,BolDevType,Sensitive,0,y);
            buffer2[i] = iCustom(NULL,timeFrame,indicatorFileName,"calculateValue",Price,FastMa,SlowMa,BandsLength,MaMethod,BandsDeviation,BolDevType,Sensitive,1,y);
            buffer3[i] = iCustom(NULL,timeFrame,indicatorFileName,"calculateValue",Price,FastMa,SlowMa,BandsLength,MaMethod,BandsDeviation,BolDevType,Sensitive,2,y);
            
            //
            //
            //
            //
            //
       
            if (timeFrame <= Period() || y==iBarShift(NULL,timeFrame,Time[i-1])) continue;
            if (!Interpolate) continue;

            //
            //
            //
            //
            //

            datetime time = iTime(NULL,timeFrame,y);
               for(int n = 1; i+n < Bars && Time[i+n] >= time; n++) continue;	
               for(int x = 1; x < n; x++)
               {
               
                  buffer3[i+x] = buffer3[i] + (buffer3[i+n] - buffer3[i]) * x/n;
                  
               }               
   }
   return(0);
}

//
//
//
//
//

string sTfTable[] = {"M1","M5","M15","M30","H1","H4","D1","W1","MN"};
int    iTfTable[] = {1,5,15,30,60,240,1440,10080,43200};

//
//
//
//
//

int stringToTimeFrame(string tfs)
{
   tfs = stringUpperCase(tfs);
   for (int i=ArraySize(iTfTable)-1; i>=0; i--)
         if (tfs==sTfTable[i] || tfs==""+iTfTable[i]) return(MathMax(iTfTable[i],Period()));
                                                      return(Period());
}

//
//
//
//
//

string timeFrameToString(int tf)
{
   for (int i=ArraySize(iTfTable)-1; i>=0; i--) 
         if (tf==iTfTable[i]) return(sTfTable[i]);
                              return("");
}

//
//
//
//
//

string stringUpperCase(string str)
{
   string   s = str;

   for (int length=StringLen(str)-1; length>=0; length--)
   {
      int tchar = StringGetChar(s, length);
         if((tchar > 96 && tchar < 123) || (tchar > 223 && tchar < 256))
                     s = StringSetChar(s, length, tchar - 32);
         else if(tchar > -33 && tchar < 0)
                     s = StringSetChar(s, length, tchar + 224);
   }
   return(s);
}
   
//------------------------------------------------------------------
//                                                                  
//------------------------------------------------------------------
//
//
//
//
//

#define _maInstances 3
#define _maWorkBufferx1 1*_maInstances
#define _maWorkBufferx2 2*_maInstances
#define _maWorkBufferx3 3*_maInstances

double iCustomMa(int mode, double price, double length, int r, int bars, int instanceNo=0)
{
   r = bars-r-1;
   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));
      case ma_slwma : return(iSlwma(price,(int)length,r,bars,instanceNo));
      case ma_dsema : return(iDsema(price,length,r,bars,instanceNo));
      case ma_tema  : return(iTema(price,(int)length,r,bars,instanceNo));
      case ma_lsma  : return(iLinr(price,(int)length,r,bars,instanceNo));
      default       : return(price);
   }
}

//
//
//
//
//

double workSma[][_maWorkBufferx1];
double iSma(double price, int period, int r, int _bars, int instanceNo=0)
{
   if (ArrayRange(workSma,0)!= _bars) ArrayResize(workSma,_bars);

   workSma[r][instanceNo+0] = price;
   double avg = price; int k=1;  for(; k<period && (r-k)>=0; k++) avg += workSma[r-k][instanceNo+0];  
   return(avg/(double)k);
}

//
//
//
//
//

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]);
}

//
//
//
//
//

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]);
}

//
//
//
//
//

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);
}

//
//
//
//
//


double workSlwma[][_maWorkBufferx2];
double iSlwma(double price, double period, int r, int _bars, int instanceNo=0)
{
   if (ArrayRange(workSlwma,0)!= _bars) ArrayResize(workSlwma,_bars); 

   //
   //
   //
   //
   //

      int SqrtPeriod = (int)MathFloor(MathSqrt(period)); instanceNo *= 2;
         workSlwma[r][instanceNo] = 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*workSlwma[r-k][instanceNo];  
         }             
         workSlwma[r][instanceNo+1] = (sum/sumw);

         //
         //
         //
         //
         //
         
         sumw = SqrtPeriod;
         sum  = SqrtPeriod*workSlwma[r][instanceNo+1];
            for(k=1; k<SqrtPeriod && (r-k)>=0; k++)
            {
               weight = SqrtPeriod-k;
               sumw += weight;
               sum  += weight*workSlwma[r-k][instanceNo+1];  
            }
   return(sum/sumw);
}

//
//
//
//
//

double workDsema[][_maWorkBufferx2];
#define _ema1 0
#define _ema2 1

double iDsema(double price, double period, int r, int _bars, int instanceNo=0)
{
   if (ArrayRange(workDsema,0)!= _bars) ArrayResize(workDsema,_bars); instanceNo*=2;

   //
   //
   //
   //
   //
   
   workDsema[r][_ema1+instanceNo] = price;
   workDsema[r][_ema2+instanceNo] = price;
   if (r>0 && period>1)
   {
      double alpha = 2.0 /(1.0+MathSqrt(period));
          workDsema[r][_ema1+instanceNo] = workDsema[r-1][_ema1+instanceNo]+alpha*(price                         -workDsema[r-1][_ema1+instanceNo]);
          workDsema[r][_ema2+instanceNo] = workDsema[r-1][_ema2+instanceNo]+alpha*(workDsema[r][_ema1+instanceNo]-workDsema[r-1][_ema2+instanceNo]); }
   return(workDsema[r][_ema2+instanceNo]);
}

//
//
//
//
//

double workTema[][_maWorkBufferx3];
#define _tema1 0
#define _tema2 1
#define _tema3 2

double iTema(double price, double period, int r, int bars, int instanceNo=0)
{
   if (ArrayRange(workTema,0)!= bars) ArrayResize(workTema,bars); instanceNo*=3;

   //
   //
   //
   //
   //
      
   workTema[r][_tema1+instanceNo] = price;
   workTema[r][_tema2+instanceNo] = price;
   workTema[r][_tema3+instanceNo] = price;
   if (r>0 && period>1)
   {
      double alpha = 2.0 / (1.0+period);
          workTema[r][_tema1+instanceNo] = workTema[r-1][_tema1+instanceNo]+alpha*(price                         -workTema[r-1][_tema1+instanceNo]);
          workTema[r][_tema2+instanceNo] = workTema[r-1][_tema2+instanceNo]+alpha*(workTema[r][_tema1+instanceNo]-workTema[r-1][_tema2+instanceNo]);
          workTema[r][_tema3+instanceNo] = workTema[r-1][_tema3+instanceNo]+alpha*(workTema[r][_tema2+instanceNo]-workTema[r-1][_tema3+instanceNo]); }
   return(workTema[r][_tema3+instanceNo]+3.0*(workTema[r][_tema1+instanceNo]-workTema[r][_tema2+instanceNo]));
}

//
//
//
//
//

double workLinr[][_maWorkBufferx1];
double iLinr(double price, int period, int r, int bars, int instanceNo=0)
{
   if (ArrayRange(workLinr,0)!= bars) ArrayResize(workLinr,bars);

   //
   //
   //
   //
   //
   
      period = MathMax(period,1);
      workLinr[r][instanceNo] = price;
      if (r<period) return(price);
         double lwmw = period; double lwma = lwmw*price;
         double sma  = price;
         for(int k=1; k<period && (r-k)>=0; k++)
         {
            double weight = period-k;
                   lwmw  += weight;
                   lwma  += weight*workLinr[r-k][instanceNo];  
                   sma   +=        workLinr[r-k][instanceNo];
         }             
   
   return(3.0*lwma/lwmw-2.0*sma/period);
}

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

#define _prHABF(_prtype) (_prtype>=pr_habclose && _prtype<=pr_habtbiased2)
#define _priceInstances     1
#define _priceInstancesSize 4
double workHa[][_priceInstances*_priceInstancesSize];
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*=_priceInstancesSize; int r = bars-i-1;
         
         //
         //
         //
         //
         //
         
         double haOpen  = (r>0) ? (workHa[r-1][instanceNo+2] + workHa[r-1][instanceNo+3])/2.0 : (open[i]+close[i])/2;;
         double haClose = (open[i]+high[i]+low[i]+close[i]) / 4.0;
         if (_prHABF(tprice))
               if (high[i]!=low[i])
                     haClose = (open[i]+close[i])/2.0+(((close[i]-open[i])/(high[i]-low[i]))*MathAbs((close[i]-open[i])/2.0));
               else  haClose = (open[i]+close[i])/2.0; 
         double haHigh  = fmax(high[i], fmax(haOpen,haClose));
         double haLow   = fmin(low[i] , fmin(haOpen,haClose));

         //
         //
         //
         //
         //
         
         if(haOpen<haClose) { workHa[r][instanceNo+0] = haLow;  workHa[r][instanceNo+1] = haHigh; } 
         else               { workHa[r][instanceNo+0] = haHigh; workHa[r][instanceNo+1] = haLow;  } 
                              workHa[r][instanceNo+2] = haOpen;
                              workHa[r][instanceNo+3] = haClose;
         //
         //
         //
         //
         //
         
         switch (tprice)
         {
            case pr_haclose:
            case pr_habclose:    return(haClose);
            case pr_haopen:   
            case pr_habopen:     return(haOpen);
            case pr_hahigh: 
            case pr_habhigh:     return(haHigh);
            case pr_halow:    
            case pr_hablow:      return(haLow);
            case pr_hamedian:
            case pr_habmedian:   return((haHigh+haLow)/2.0);
            case pr_hamedianb:
            case pr_habmedianb:  return((haOpen+haClose)/2.0);
            case pr_hatypical:
            case pr_habtypical:  return((haHigh+haLow+haClose)/3.0);
            case pr_haweighted:
            case pr_habweighted: return((haHigh+haLow+haClose+haClose)/4.0);
            case pr_haaverage:  
            case pr_habaverage:  return((haHigh+haLow+haClose+haOpen)/4.0);
            case pr_hatbiased:
            case pr_habtbiased:
               if (haClose>haOpen)
                     return((haHigh+haClose)/2.0);
               else  return((haLow+haClose)/2.0);        
            case pr_hatbiased2:
            case pr_habtbiased2:
               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);
}

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

#define _devInstances 1
double workDev[][_devInstances];
double iDeviation(double values, int length, bool isSample, int i, int bars, int instanceNo=0)
{
   if (ArrayRange(workDev,0)!=bars) ArrayResize(workDev,bars); i=bars-i-1; workDev[i][instanceNo] = values;
                 
   //
   //
   //
   //
   //
   
      double oldMean   = values;
      double newMean   = values;
      double squares   = 0; int k;
      for (k=1; k<length && (i-k)>=0; k++)
      {
         newMean  = (workDev[i-k][instanceNo]-oldMean)/(k+1)+oldMean;
         squares += (workDev[i-k][instanceNo]-oldMean)*(workDev[i-k][instanceNo]-newMean);
         oldMean  = newMean;
      }
      return(MathSqrt(squares/fmax(k-isSample,1)));
}

//
//
//
//
//

double workErr[][_devInstances];
double iStdError(double values, int length,int i, int bars, int instanceNo=0)
{
   if (ArrayRange(workErr,0)!=bars) ArrayResize(workErr,bars); i = bars-i-1; workErr[i][instanceNo] = values;
                        
      //
      //
      //
      //
      //
                              
      double avgY     = workErr[i][instanceNo]; int j; for (j=1; j<length && (i-j)>=0; j++) avgY += workErr[i-j][instanceNo]; avgY /= j;
      double avgX     = length * (length-1) * 0.5 / length;
      double sumDxSqr = 0.00;
      double sumDySqr = 0.00;
      double sumDxDy  = 0.00;
   
      for (int k=0; k<length && (i-k)>=0; k++)
      {
         double dx = k-avgX;
         double dy = workErr[i-k][instanceNo]-avgY;
            sumDxSqr += (dx*dx);
            sumDySqr += (dy*dy);
            sumDxDy  += (dx*dy);
      }
      double err2 = (sumDySqr-(sumDxDy*sumDxDy)/sumDxSqr)/(length-2); 
      
   //
   //
   //
   //
   //
         
   if (err2 > 0)
         return(MathSqrt(err2));
   else  return(0.00);       
}