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mql5/Include/MyIncludes/Ehlers_Adaptive_Smoother_Calculator.mqh
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//+------------------------------------------------------------------+
//| Ehlers_Adaptive_Smoother_Calculator.mqh |
//| Copyright 2026, xxxxxxxx|
//+------------------------------------------------------------------+
#property copyright "Copyright 2026, xxxxxxxx"
#property version "1.00" // Adaptive SuperSmoother & UltimateSmoother Engine via ER/ATR/StDev
#property description "Stateful calculator implementing adaptive Ehlers smoothing via dynamic cutoff period scaling."
#ifndef EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
#define EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
#include <MyIncludes\EfficiencyRatio_Calculator.mqh>
#include <MyIncludes\ATR_Calculator.mqh>
#include <MyIncludes\HeikinAshi_Tools.mqh>
#include <MyIncludes\Ehlers_Smoother_Calculator.mqh> // Share smoother enums
#ifndef ENUM_ADAPTIVE_METHOD_DEFINED
#define ENUM_ADAPTIVE_METHOD_DEFINED
enum ENUM_ADAPTIVE_METHOD
{
METHOD_EFFICIENCY_RATIO, // Kaufman's Efficiency Ratio (ER)
METHOD_ATR, // Average True Range (ATR Volatility)
METHOD_STAND_DEV // Standard Deviation (StDev Volatility)
};
#endif
//+==================================================================+
//| CLASS: CEhlersAdaptiveSmootherCalculator |
//+==================================================================+
class CEhlersAdaptiveSmootherCalculator
{
private:
ENUM_SMOOTHER_TYPE m_smoother_type;
ENUM_ADAPTIVE_METHOD m_method;
int m_adaptive_period;
int m_period_min;
int m_period_max;
int m_period_range; // Precalculated (period_max - period_min)
ENUM_APPLIED_PRICE_HA_ALL m_source_price;
bool m_is_ha;
CEfficiencyRatioCalculator *m_er_calc;
CATRCalculator *m_atr_calc;
CHeikinAshi_Calculator m_ha_engine;
//--- Persistent State Registers (Strict Instance Isolation)
double m_price[];
double m_adaptive_metric[];
double m_temp_atr[];
double m_temp_stdev[];
double m_ha_open[], m_ha_high[], m_ha_low[], m_ha_close[];
bool PreparePriceSeries(int rates_total, int start_index,
const double &open[], const double &high[],
const double &low[], const double &close[]);
void NormalizeMetric(int rates_total, int prev_calculated, const double &src_array[]);
public:
CEhlersAdaptiveSmootherCalculator(void);
~CEhlersAdaptiveSmootherCalculator(void);
bool Init(const ENUM_SMOOTHER_TYPE smoother_type,
const ENUM_ADAPTIVE_METHOD method,
const int adaptive_period,
const int period_min,
const int period_max,
const ENUM_APPLIED_PRICE_HA_ALL price_source);
void Calculate(const int rates_total, const int prev_calculated,
const double &open[], const double &high[],
const double &low[], const double &close[],
double &filter_buffer[]);
};
//+------------------------------------------------------------------+
//| Constructor |
//+------------------------------------------------------------------+
CEhlersAdaptiveSmootherCalculator::CEhlersAdaptiveSmootherCalculator(void) :
m_smoother_type(SUPERSMOOTHER),
m_method(METHOD_EFFICIENCY_RATIO),
m_adaptive_period(10),
m_period_min(5),
m_period_max(30),
m_period_range(25),
m_source_price(PRICE_CLOSE_STD),
m_is_ha(false),
m_er_calc(NULL),
m_atr_calc(NULL)
{
ArraySetAsSeries(m_price, false);
ArraySetAsSeries(m_adaptive_metric, false);
ArraySetAsSeries(m_temp_atr, false);
ArraySetAsSeries(m_temp_stdev, false);
ArraySetAsSeries(m_ha_open, false);
ArraySetAsSeries(m_ha_high, false);
ArraySetAsSeries(m_ha_low, false);
ArraySetAsSeries(m_ha_close, false);
}
//+------------------------------------------------------------------+
//| Destructor |
//+------------------------------------------------------------------+
CEhlersAdaptiveSmootherCalculator::~CEhlersAdaptiveSmootherCalculator(void)
{
if(CheckPointer(m_er_calc) != POINTER_INVALID)
{
delete m_er_calc;
m_er_calc = NULL;
}
if(CheckPointer(m_atr_calc) != POINTER_INVALID)
{
delete m_atr_calc;
m_atr_calc = NULL;
}
}
//+------------------------------------------------------------------+
//| Initialization |
//+------------------------------------------------------------------+
bool CEhlersAdaptiveSmootherCalculator::Init(const ENUM_SMOOTHER_TYPE smoother_type,
const ENUM_ADAPTIVE_METHOD method,
const int adaptive_period,
const int period_min,
const int period_max,
const ENUM_APPLIED_PRICE_HA_ALL price_source)
{
m_smoother_type = smoother_type;
m_method = method;
m_adaptive_period = (adaptive_period < 2) ? 2 : adaptive_period;
m_period_min = (period_min < 2) ? 2 : period_min;
m_period_max = (period_max < m_period_min) ? (m_period_min + 1) : period_max;
m_period_range = m_period_max - m_period_min;
m_source_price = price_source;
m_is_ha = (m_source_price <= PRICE_HA_CLOSE);
if(CheckPointer(m_er_calc) != POINTER_INVALID)
{
delete m_er_calc;
m_er_calc = NULL;
}
if(CheckPointer(m_atr_calc) != POINTER_INVALID)
{
delete m_atr_calc;
m_atr_calc = NULL;
}
if(m_method == METHOD_EFFICIENCY_RATIO)
{
m_er_calc = new CEfficiencyRatioCalculator();
if(CheckPointer(m_er_calc) == POINTER_INVALID || !m_er_calc.Init(m_adaptive_period))
return false;
}
else
if(m_method == METHOD_ATR)
{
if(m_is_ha)
m_atr_calc = new CATRCalculator_HA();
else
m_atr_calc = new CATRCalculator();
if(CheckPointer(m_atr_calc) == POINTER_INVALID || !m_atr_calc.Init(m_adaptive_period, ATR_POINTS))
return false;
}
return true;
}
//+------------------------------------------------------------------+
//| Main Calculation Loop (Incremental O(1)) |
//+------------------------------------------------------------------+
void CEhlersAdaptiveSmootherCalculator::Calculate(const int rates_total, const int prev_calculated,
const double &open[], const double &high[],
const double &low[], const double &close[],
double &filter_buffer[])
{
int required_bars = m_adaptive_period * 2 + 5;
if(rates_total < required_bars)
return;
// Safe array sizing
if(ArraySize(m_price) != rates_total)
{
ArrayResize(m_price, rates_total);
ArraySetAsSeries(m_price, false);
ArrayResize(m_adaptive_metric, rates_total);
ArraySetAsSeries(m_adaptive_metric, false);
}
if(ArraySize(filter_buffer) != rates_total)
{
ArrayResize(filter_buffer, rates_total);
ArraySetAsSeries(filter_buffer, false);
}
int start_index = (prev_calculated > 0) ? prev_calculated - 1 : 0;
if(!PreparePriceSeries(rates_total, start_index, open, high, low, close))
return;
// 1. Calculate Adaptive Metric [0.0 to 1.0]
if(m_method == METHOD_EFFICIENCY_RATIO)
{
ENUM_APPLIED_PRICE p_type = (m_source_price <= PRICE_HA_CLOSE) ? PRICE_CLOSE : (ENUM_APPLIED_PRICE)m_source_price;
m_er_calc.Calculate(rates_total, prev_calculated, p_type, open, high, low, close, m_adaptive_metric);
}
else
if(m_method == METHOD_ATR)
{
if(ArraySize(m_temp_atr) != rates_total)
{
ArrayResize(m_temp_atr, rates_total);
ArraySetAsSeries(m_temp_atr, false);
}
m_atr_calc.Calculate(rates_total, prev_calculated, open, high, low, close, m_temp_atr);
NormalizeMetric(rates_total, prev_calculated, m_temp_atr);
}
else // METHOD_STAND_DEV (MathPow-Free Accelerated StDev)
{
if(ArraySize(m_temp_stdev) != rates_total)
{
ArrayResize(m_temp_stdev, rates_total);
ArraySetAsSeries(m_temp_stdev, false);
}
int start_sync = (prev_calculated > 0) ? prev_calculated - 1 : 0;
int loop_start = MathMax(m_adaptive_period - 1, start_sync);
if(loop_start == m_adaptive_period - 1)
{
for(int i = 0; i < loop_start; i++)
m_temp_stdev[i] = 0.0;
}
double inv_p = 1.0 / (double)m_adaptive_period;
for(int i = loop_start; i < rates_total; i++)
{
double sum = 0.0;
for(int j = 0; j < m_adaptive_period; j++)
sum += m_price[i - j];
double mean = sum * inv_p;
double sum_sq = 0.0;
for(int j = 0; j < m_adaptive_period; j++)
{
double diff = m_price[i - j] - mean;
sum_sq += diff * diff;
}
m_temp_stdev[i] = MathSqrt(sum_sq * inv_p);
}
NormalizeMetric(rates_total, prev_calculated, m_temp_stdev);
}
// 2. Deterministic Seeding on Initial Pass
int loop_start_filter = MathMax(3, start_index);
if(prev_calculated == 0)
{
filter_buffer[0] = m_price[0];
filter_buffer[1] = m_price[1];
filter_buffer[2] = m_price[2];
loop_start_filter = 3;
}
// 3. Dynamic Adaptive 2-Pole Difference Equation
for(int i = loop_start_filter; i < rates_total; i++)
{
double metric = m_adaptive_metric[i];
if(metric < 0.0)
metric = 0.0;
else
if(metric > 1.0)
metric = 1.0;
// Higher metric (high efficiency/volatility) -> shorter period (faster tracking)
double dyn_period = (double)m_period_max - (metric * (double)m_period_range);
if(dyn_period < (double)m_period_min)
dyn_period = (double)m_period_min;
if(dyn_period > (double)m_period_max)
dyn_period = (double)m_period_max;
// Solve 2-Pole Butterworth Transfer Function for the dynamic period
double omega = M_SQRT2 * M_PI / dyn_period;
double a1 = MathExp(-omega);
double b1 = 2.0 * a1 * MathCos(omega);
double c2 = b1;
double c3 = -a1 * a1;
double f1 = filter_buffer[i - 1];
double f2 = filter_buffer[i - 2];
if(m_smoother_type == SUPERSMOOTHER)
{
double c1_half = (1.0 - c2 - c3) * 0.5;
filter_buffer[i] = c1_half * (m_price[i] + m_price[i - 1]) + c2 * f1 + c3 * f2;
}
else // ULTIMATESMOOTHER
{
double c1 = (1.0 + c2 - c3) * 0.25;
double u0 = 1.0 - c1;
double u1 = 2.0 * c1 - c2;
double u2 = -(c1 + c3);
filter_buffer[i] = u0 * m_price[i] + u1 * m_price[i - 1] + u2 * m_price[i - 2] + c2 * f1 + c3 * f2;
}
}
}
//+------------------------------------------------------------------+
//| Sliding Min-Max Normalization (DRY Helper) |
//+------------------------------------------------------------------+
void CEhlersAdaptiveSmootherCalculator::NormalizeMetric(int rates_total, int prev_calculated, const double &src_array[])
{
int start_sync = (prev_calculated > 0) ? prev_calculated - 1 : 0;
int min_lookback = m_adaptive_period;
int loop_start = MathMax(min_lookback * 2, start_sync);
if(loop_start == min_lookback * 2)
{
for(int i = 0; i < loop_start; i++)
m_adaptive_metric[i] = 0.0;
}
for(int i = loop_start; i < rates_total; i++)
{
double min_val = src_array[i];
double max_val = src_array[i];
for(int j = 1; j < m_adaptive_period; j++)
{
double val = src_array[i - j];
if(val < min_val)
min_val = val;
if(val > max_val)
max_val = val;
}
double diff = max_val - min_val;
if(diff > 1.0e-9)
m_adaptive_metric[i] = (src_array[i] - min_val) / diff;
else
m_adaptive_metric[i] = 0.0;
}
}
//+------------------------------------------------------------------+
//| Prepare Price Series (Instance Isolated Caches - Zero Static!) |
//+------------------------------------------------------------------+
bool CEhlersAdaptiveSmootherCalculator::PreparePriceSeries(int rates_total, int start_index,
const double &open[], const double &high[],
const double &low[], const double &close[])
{
if(m_is_ha)
{
if(ArraySize(m_ha_open) != rates_total)
{
ArrayResize(m_ha_open, rates_total);
ArraySetAsSeries(m_ha_open, false);
ArrayResize(m_ha_high, rates_total);
ArraySetAsSeries(m_ha_high, false);
ArrayResize(m_ha_low, rates_total);
ArraySetAsSeries(m_ha_low, false);
ArrayResize(m_ha_close, rates_total);
ArraySetAsSeries(m_ha_close, false);
}
m_ha_engine.Calculate(rates_total, start_index, open, high, low, close,
m_ha_open, m_ha_high, m_ha_low, m_ha_close);
for(int i = start_index; i < rates_total; i++)
{
switch(m_source_price)
{
case PRICE_HA_OPEN:
m_price[i] = m_ha_open[i];
break;
case PRICE_HA_HIGH:
m_price[i] = m_ha_high[i];
break;
case PRICE_HA_LOW:
m_price[i] = m_ha_low[i];
break;
case PRICE_HA_MEDIAN:
m_price[i] = (m_ha_high[i] + m_ha_low[i]) * 0.5;
break;
case PRICE_HA_TYPICAL:
m_price[i] = (m_ha_high[i] + m_ha_low[i] + m_ha_close[i]) / 3.0;
break;
case PRICE_HA_WEIGHTED:
m_price[i] = (m_ha_high[i] + m_ha_low[i] + 2.0 * m_ha_close[i]) * 0.25;
break;
case PRICE_HA_CLOSE:
default:
m_price[i] = m_ha_close[i];
break;
}
}
}
else
{
for(int i = start_index; i < rates_total; i++)
{
switch(m_source_price)
{
case PRICE_OPEN_STD:
m_price[i] = open[i];
break;
case PRICE_HIGH_STD:
m_price[i] = high[i];
break;
case PRICE_LOW_STD:
m_price[i] = low[i];
break;
case PRICE_MEDIAN_STD:
m_price[i] = (high[i] + low[i]) * 0.5;
break;
case PRICE_TYPICAL_STD:
m_price[i] = (high[i] + low[i] + close[i]) / 3.0;
break;
case PRICE_WEIGHTED_STD:
m_price[i] = (high[i] + low[i] + 2.0 * close[i]) * 0.25;
break;
case PRICE_CLOSE_STD:
default:
m_price[i] = close[i];
break;
}
}
}
return true;
}
#endif // EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
//+------------------------------------------------------------------+
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