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feat: Adaptive SuperSmoother & UltimateSmoother Engine via ER/ATR/StDev
This commit is contained in:
Toh4iem9
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//+------------------------------------------------------------------+
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//| Ehlers_Adaptive_Smoother_Calculator.mqh |
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//| Copyright 2026, xxxxxxxx|
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//+------------------------------------------------------------------+
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#property copyright "Copyright 2026, xxxxxxxx"
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#property version "1.00" // Adaptive SuperSmoother & UltimateSmoother Engine via ER/ATR/StDev
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#property description "Stateful calculator implementing adaptive Ehlers smoothing via dynamic cutoff period scaling."
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#ifndef EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
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#define EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
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#include <MyIncludes\EfficiencyRatio_Calculator.mqh>
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#include <MyIncludes\ATR_Calculator.mqh>
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#include <MyIncludes\HeikinAshi_Tools.mqh>
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#include <MyIncludes\Ehlers_Smoother_Calculator.mqh> // Share smoother enums
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#ifndef ENUM_ADAPTIVE_METHOD_DEFINED
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#define ENUM_ADAPTIVE_METHOD_DEFINED
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enum ENUM_ADAPTIVE_METHOD
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{
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METHOD_EFFICIENCY_RATIO, // Kaufman's Efficiency Ratio (ER)
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METHOD_ATR, // Average True Range (ATR Volatility)
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METHOD_STAND_DEV // Standard Deviation (StDev Volatility)
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};
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#endif
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//+==================================================================+
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//| CLASS: CEhlersAdaptiveSmootherCalculator |
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//+==================================================================+
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class CEhlersAdaptiveSmootherCalculator
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{
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private:
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ENUM_SMOOTHER_TYPE m_smoother_type;
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ENUM_ADAPTIVE_METHOD m_method;
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int m_adaptive_period;
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int m_period_min;
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int m_period_max;
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int m_period_range; // Precalculated (period_max - period_min)
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ENUM_APPLIED_PRICE_HA_ALL m_source_price;
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bool m_is_ha;
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CEfficiencyRatioCalculator *m_er_calc;
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CATRCalculator *m_atr_calc;
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CHeikinAshi_Calculator m_ha_engine;
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//--- Persistent State Registers (Strict Instance Isolation)
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double m_price[];
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double m_adaptive_metric[];
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double m_temp_atr[];
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double m_temp_stdev[];
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double m_ha_open[], m_ha_high[], m_ha_low[], m_ha_close[];
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bool PreparePriceSeries(int rates_total, int start_index,
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const double &open[], const double &high[],
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const double &low[], const double &close[]);
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void NormalizeMetric(int rates_total, int prev_calculated, const double &src_array[]);
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public:
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CEhlersAdaptiveSmootherCalculator(void);
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~CEhlersAdaptiveSmootherCalculator(void);
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bool Init(const ENUM_SMOOTHER_TYPE smoother_type,
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const ENUM_ADAPTIVE_METHOD method,
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const int adaptive_period,
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const int period_min,
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const int period_max,
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const ENUM_APPLIED_PRICE_HA_ALL price_source);
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void Calculate(const int rates_total, const int prev_calculated,
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const double &open[], const double &high[],
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const double &low[], const double &close[],
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double &filter_buffer[]);
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};
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//+------------------------------------------------------------------+
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//| Constructor |
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//+------------------------------------------------------------------+
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CEhlersAdaptiveSmootherCalculator::CEhlersAdaptiveSmootherCalculator(void) :
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m_smoother_type(SUPERSMOOTHER),
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m_method(METHOD_EFFICIENCY_RATIO),
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m_adaptive_period(10),
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m_period_min(5),
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m_period_max(30),
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m_period_range(25),
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m_source_price(PRICE_CLOSE_STD),
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m_is_ha(false),
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m_er_calc(NULL),
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m_atr_calc(NULL)
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{
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ArraySetAsSeries(m_price, false);
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ArraySetAsSeries(m_adaptive_metric, false);
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ArraySetAsSeries(m_temp_atr, false);
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ArraySetAsSeries(m_temp_stdev, false);
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ArraySetAsSeries(m_ha_open, false);
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ArraySetAsSeries(m_ha_high, false);
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ArraySetAsSeries(m_ha_low, false);
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ArraySetAsSeries(m_ha_close, false);
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}
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//+------------------------------------------------------------------+
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//| Destructor |
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//+------------------------------------------------------------------+
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CEhlersAdaptiveSmootherCalculator::~CEhlersAdaptiveSmootherCalculator(void)
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{
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if(CheckPointer(m_er_calc) != POINTER_INVALID)
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{
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delete m_er_calc;
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m_er_calc = NULL;
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}
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if(CheckPointer(m_atr_calc) != POINTER_INVALID)
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{
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delete m_atr_calc;
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m_atr_calc = NULL;
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}
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}
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//+------------------------------------------------------------------+
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//| Initialization |
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//+------------------------------------------------------------------+
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bool CEhlersAdaptiveSmootherCalculator::Init(const ENUM_SMOOTHER_TYPE smoother_type,
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const ENUM_ADAPTIVE_METHOD method,
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const int adaptive_period,
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const int period_min,
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const int period_max,
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const ENUM_APPLIED_PRICE_HA_ALL price_source)
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{
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m_smoother_type = smoother_type;
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m_method = method;
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m_adaptive_period = (adaptive_period < 2) ? 2 : adaptive_period;
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m_period_min = (period_min < 2) ? 2 : period_min;
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m_period_max = (period_max < m_period_min) ? (m_period_min + 1) : period_max;
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m_period_range = m_period_max - m_period_min;
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m_source_price = price_source;
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m_is_ha = (m_source_price <= PRICE_HA_CLOSE);
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if(CheckPointer(m_er_calc) != POINTER_INVALID)
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{
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delete m_er_calc;
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m_er_calc = NULL;
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}
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if(CheckPointer(m_atr_calc) != POINTER_INVALID)
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{
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delete m_atr_calc;
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m_atr_calc = NULL;
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}
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if(m_method == METHOD_EFFICIENCY_RATIO)
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{
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m_er_calc = new CEfficiencyRatioCalculator();
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if(CheckPointer(m_er_calc) == POINTER_INVALID || !m_er_calc.Init(m_adaptive_period))
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return false;
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}
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else
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if(m_method == METHOD_ATR)
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{
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if(m_is_ha)
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m_atr_calc = new CATRCalculator_HA();
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else
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m_atr_calc = new CATRCalculator();
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if(CheckPointer(m_atr_calc) == POINTER_INVALID || !m_atr_calc.Init(m_adaptive_period, ATR_POINTS))
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return false;
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}
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return true;
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}
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//+------------------------------------------------------------------+
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//| Main Calculation Loop (Incremental O(1)) |
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//+------------------------------------------------------------------+
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void CEhlersAdaptiveSmootherCalculator::Calculate(const int rates_total, const int prev_calculated,
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const double &open[], const double &high[],
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const double &low[], const double &close[],
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double &filter_buffer[])
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{
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int required_bars = m_adaptive_period * 2 + 5;
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if(rates_total < required_bars)
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return;
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// Safe array sizing
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if(ArraySize(m_price) != rates_total)
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{
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ArrayResize(m_price, rates_total);
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ArraySetAsSeries(m_price, false);
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ArrayResize(m_adaptive_metric, rates_total);
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ArraySetAsSeries(m_adaptive_metric, false);
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}
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if(ArraySize(filter_buffer) != rates_total)
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{
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ArrayResize(filter_buffer, rates_total);
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ArraySetAsSeries(filter_buffer, false);
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}
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int start_index = (prev_calculated > 0) ? prev_calculated - 1 : 0;
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if(!PreparePriceSeries(rates_total, start_index, open, high, low, close))
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return;
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// 1. Calculate Adaptive Metric [0.0 to 1.0]
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if(m_method == METHOD_EFFICIENCY_RATIO)
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{
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ENUM_APPLIED_PRICE p_type = (m_source_price <= PRICE_HA_CLOSE) ? PRICE_CLOSE : (ENUM_APPLIED_PRICE)m_source_price;
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m_er_calc.Calculate(rates_total, prev_calculated, p_type, open, high, low, close, m_adaptive_metric);
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}
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else
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if(m_method == METHOD_ATR)
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{
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if(ArraySize(m_temp_atr) != rates_total)
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{
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ArrayResize(m_temp_atr, rates_total);
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ArraySetAsSeries(m_temp_atr, false);
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}
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m_atr_calc.Calculate(rates_total, prev_calculated, open, high, low, close, m_temp_atr);
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NormalizeMetric(rates_total, prev_calculated, m_temp_atr);
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}
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else // METHOD_STAND_DEV (MathPow-Free Accelerated StDev)
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{
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if(ArraySize(m_temp_stdev) != rates_total)
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{
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ArrayResize(m_temp_stdev, rates_total);
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ArraySetAsSeries(m_temp_stdev, false);
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}
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int start_sync = (prev_calculated > 0) ? prev_calculated - 1 : 0;
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int loop_start = MathMax(m_adaptive_period - 1, start_sync);
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if(loop_start == m_adaptive_period - 1)
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{
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for(int i = 0; i < loop_start; i++)
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m_temp_stdev[i] = 0.0;
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}
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double inv_p = 1.0 / (double)m_adaptive_period;
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for(int i = loop_start; i < rates_total; i++)
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{
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double sum = 0.0;
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for(int j = 0; j < m_adaptive_period; j++)
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sum += m_price[i - j];
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double mean = sum * inv_p;
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double sum_sq = 0.0;
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for(int j = 0; j < m_adaptive_period; j++)
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{
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double diff = m_price[i - j] - mean;
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sum_sq += diff * diff;
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}
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m_temp_stdev[i] = MathSqrt(sum_sq * inv_p);
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}
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NormalizeMetric(rates_total, prev_calculated, m_temp_stdev);
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}
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// 2. Deterministic Seeding on Initial Pass
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int loop_start_filter = MathMax(3, start_index);
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if(prev_calculated == 0)
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{
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filter_buffer[0] = m_price[0];
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filter_buffer[1] = m_price[1];
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filter_buffer[2] = m_price[2];
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loop_start_filter = 3;
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}
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// 3. Dynamic Adaptive 2-Pole Difference Equation
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for(int i = loop_start_filter; i < rates_total; i++)
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{
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double metric = m_adaptive_metric[i];
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if(metric < 0.0)
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metric = 0.0;
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else
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if(metric > 1.0)
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metric = 1.0;
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// Higher metric (high efficiency/volatility) -> shorter period (faster tracking)
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double dyn_period = (double)m_period_max - (metric * (double)m_period_range);
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if(dyn_period < (double)m_period_min)
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dyn_period = (double)m_period_min;
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if(dyn_period > (double)m_period_max)
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dyn_period = (double)m_period_max;
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// Solve 2-Pole Butterworth Transfer Function for the dynamic period
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double omega = M_SQRT2 * M_PI / dyn_period;
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double a1 = MathExp(-omega);
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double b1 = 2.0 * a1 * MathCos(omega);
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double c2 = b1;
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double c3 = -a1 * a1;
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double f1 = filter_buffer[i - 1];
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double f2 = filter_buffer[i - 2];
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if(m_smoother_type == SUPERSMOOTHER)
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{
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double c1_half = (1.0 - c2 - c3) * 0.5;
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filter_buffer[i] = c1_half * (m_price[i] + m_price[i - 1]) + c2 * f1 + c3 * f2;
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}
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else // ULTIMATESMOOTHER
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{
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double c1 = (1.0 + c2 - c3) * 0.25;
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double u0 = 1.0 - c1;
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double u1 = 2.0 * c1 - c2;
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double u2 = -(c1 + c3);
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filter_buffer[i] = u0 * m_price[i] + u1 * m_price[i - 1] + u2 * m_price[i - 2] + c2 * f1 + c3 * f2;
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}
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}
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}
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//+------------------------------------------------------------------+
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//| Sliding Min-Max Normalization (DRY Helper) |
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//+------------------------------------------------------------------+
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void CEhlersAdaptiveSmootherCalculator::NormalizeMetric(int rates_total, int prev_calculated, const double &src_array[])
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{
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int start_sync = (prev_calculated > 0) ? prev_calculated - 1 : 0;
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int min_lookback = m_adaptive_period;
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int loop_start = MathMax(min_lookback * 2, start_sync);
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if(loop_start == min_lookback * 2)
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{
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for(int i = 0; i < loop_start; i++)
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m_adaptive_metric[i] = 0.0;
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}
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for(int i = loop_start; i < rates_total; i++)
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{
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double min_val = src_array[i];
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double max_val = src_array[i];
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for(int j = 1; j < m_adaptive_period; j++)
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{
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double val = src_array[i - j];
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if(val < min_val)
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min_val = val;
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if(val > max_val)
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max_val = val;
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}
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double diff = max_val - min_val;
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if(diff > 1.0e-9)
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m_adaptive_metric[i] = (src_array[i] - min_val) / diff;
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else
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m_adaptive_metric[i] = 0.0;
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}
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}
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//+------------------------------------------------------------------+
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//| Prepare Price Series (Instance Isolated Caches - Zero Static!) |
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//+------------------------------------------------------------------+
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bool CEhlersAdaptiveSmootherCalculator::PreparePriceSeries(int rates_total, int start_index,
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const double &open[], const double &high[],
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const double &low[], const double &close[])
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{
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if(m_is_ha)
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{
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if(ArraySize(m_ha_open) != rates_total)
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{
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ArrayResize(m_ha_open, rates_total);
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ArraySetAsSeries(m_ha_open, false);
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ArrayResize(m_ha_high, rates_total);
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ArraySetAsSeries(m_ha_high, false);
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ArrayResize(m_ha_low, rates_total);
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ArraySetAsSeries(m_ha_low, false);
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ArrayResize(m_ha_close, rates_total);
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ArraySetAsSeries(m_ha_close, false);
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}
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m_ha_engine.Calculate(rates_total, start_index, open, high, low, close,
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m_ha_open, m_ha_high, m_ha_low, m_ha_close);
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for(int i = start_index; i < rates_total; i++)
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{
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switch(m_source_price)
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{
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case PRICE_HA_OPEN:
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m_price[i] = m_ha_open[i];
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break;
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case PRICE_HA_HIGH:
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m_price[i] = m_ha_high[i];
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break;
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case PRICE_HA_LOW:
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m_price[i] = m_ha_low[i];
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break;
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case PRICE_HA_MEDIAN:
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m_price[i] = (m_ha_high[i] + m_ha_low[i]) * 0.5;
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break;
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case PRICE_HA_TYPICAL:
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m_price[i] = (m_ha_high[i] + m_ha_low[i] + m_ha_close[i]) / 3.0;
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break;
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case PRICE_HA_WEIGHTED:
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m_price[i] = (m_ha_high[i] + m_ha_low[i] + 2.0 * m_ha_close[i]) * 0.25;
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break;
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case PRICE_HA_CLOSE:
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default:
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m_price[i] = m_ha_close[i];
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break;
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}
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}
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}
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else
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{
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for(int i = start_index; i < rates_total; i++)
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{
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switch(m_source_price)
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{
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case PRICE_OPEN_STD:
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m_price[i] = open[i];
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break;
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case PRICE_HIGH_STD:
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m_price[i] = high[i];
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break;
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case PRICE_LOW_STD:
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m_price[i] = low[i];
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break;
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case PRICE_MEDIAN_STD:
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m_price[i] = (high[i] + low[i]) * 0.5;
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break;
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case PRICE_TYPICAL_STD:
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m_price[i] = (high[i] + low[i] + close[i]) / 3.0;
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break;
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case PRICE_WEIGHTED_STD:
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m_price[i] = (high[i] + low[i] + 2.0 * close[i]) * 0.25;
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break;
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case PRICE_CLOSE_STD:
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default:
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m_price[i] = close[i];
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break;
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}
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}
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}
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return true;
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}
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#endif // EHLERS_ADAPTIVE_SMOOTHER_CALCULATOR_MQH
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//+------------------------------------------------------------------+
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