Trend noise balance (from tos)

I am moving here from thinkorswim (trying to anyways).  I wrote a "strategy" I used pretty successfully there which I would eventually try to get set up as an EA over here, 
but first I obviously need my indicators set up.  Below is what I have for trendnoisebalance indicator thus far, and below the ### signs is the thinkorswim code for (just for your reference).
I have not finished adding in the portion where the value resets when the EMA's cross yet because there is a simple error in here somewhere I can't get past.  I have tried plotting all of the variables
individually and all work w/ exception to the "trend".  Please let me know if where I am making my error (or errors,  in all likelihood). 

TNB is a great indicator to keep you out of choppy areas, feel free to try it out.

Thanks




//+------------------------------------------------------------------+
//|                                          Trend Noise Balance.mq4 |
//|                                                              TCC |
//|                                                                  |
//+------------------------------------------------------------------+
#property copyright "TCC"

#property indicator_separate_window
#property indicator_buffers 1
#property indicator_color1 Red
//--- input parameters
extern int    fastlength=7;
extern int    slowlength=15;
extern int    trendlength=7;
extern int    noiselength=250;
extern int    correctionfactor=2;
//--- buffers
double   TNB[];
//+------------------------------------------------------------------+
//| Custom indicator initialization function                         |
//+------------------------------------------------------------------+
int init()
  {
//---- indicators
   SetIndexBuffer(0,TNB);   
   SetIndexStyle(0,DRAW_LINE);
   string short_name = "TrendNoiseBalance";
   IndicatorShortName(short_name);
//----
   return(0);
  }
//+------------------------------------------------------------------+
//| Custom indicator deinitialization function                       |
//+------------------------------------------------------------------+
int deinit()
  {
//----
   
//----
   return(0);
  }
//+------------------------------------------------------------------+
//| Custom indicator iteration function                              |
//+------------------------------------------------------------------+
  int start()
    {
     int limit;
     int counted_bars=IndicatorCounted();
  //---- check for possible errors
     if(counted_bars<0) return(-1);
  //---- the last counted bar will be recounted
     if(counted_bars>0) counted_bars--;
     limit=Bars-counted_bars;
  //---- main loop
     double cpc=0;
     double smf = 2 / (1 + trendlength);
     for(int i=0; i<limit; i++)
     {
      double rel=Close[i]-Close[i+1];
      cpc=cpc+rel;
      double trend=cpc*smf;
      trend=trend*(1 - smf)+cpc*smf;     
      double   diff=MathAbs(cpc-trend);
      double   noise = correctionfactor * (diff+noiselength)/2;
      double   denom = MathAbs(trend) + MathAbs(noise);
      if(denom==0)
         {
         TNB[i]=0;
         }else
         {
         TNB[i]=  100*(MathAbs(trend)/denom);
         }
      } 

##############################################
thinkorswim code:

input fastLength = 7;
input slowLength = 15;
input trendLength = 4;
input noiseType = {default linear, squared};
input noiseLength = 250;
input correctionFactor = 2;

assert(trendLength > 0, "'trend length' must be positive: " + trendLength);
assert(correctionFactor > 0, "'correction factor' must be positive: " + correctionFactor);

def smf = 2 / (1 + trendLength);

def reversal = TrendPeriods(fastLength, slowLength);

def cpc = if isNaN(reversal[1]) then 0 else if reversal[1] != reversal then 0 else cpc[1] + close - close[1];

def trend = if isNaN(reversal[1]) then 0 else if reversal[1] != reversal then 0 else trend[1] * (1 - smf) + cpc * smf;

def noise;
def diff = AbsValue(cpc - trend);
switch(noiseType) {
case linear:
    noise = correctionFactor * Average(diff, noiseLength);
case squared:
    noise = correctionFactor * Sqrt(Average(diff*diff, noiseLength));
}

def denom = AbsValue(trend) + AbsValue(noise);
plot TNB = if denom == 0 then 0 else 100 * AbsValue(trend) / denom;
plot HalfLine = 50;

TNB.SetDefaultColor(GetColor(9));
HalfLine.SetDefaultColor(GetColor(5));