diff --git a/Include/MyIncludes/Laguerre_Adaptive_Filter_Calculator.mqh b/Include/MyIncludes/Laguerre_Adaptive_Filter_Calculator.mqh new file mode 100644 index 0000000..41c8694 --- /dev/null +++ b/Include/MyIncludes/Laguerre_Adaptive_Filter_Calculator.mqh @@ -0,0 +1,361 @@ +//+------------------------------------------------------------------+ +//| Laguerre_Adaptive_Filter_Calculator.mqh | +//| Copyright 2026, xxxxxxxx| +//+------------------------------------------------------------------+ +#property copyright "Copyright 2026, xxxxxxxx" +#property version "1.20" // Integrated Standard Deviation (StDev) adaptive mode and DRY Normalize helper +#property description "Stateful calculator implementing adaptive Laguerre Filtering via ER, ATR, or StDev." + +#ifndef LAGUERRE_ADAPTIVE_FILTER_CALCULATOR_MQH +#define LAGUERRE_ADAPTIVE_FILTER_CALCULATOR_MQH + +#include +#include +#include + +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) + }; + +//+==================================================================+ +//| CLASS: CLaguerreAdaptiveFilterCalculator | +//+==================================================================+ +class CLaguerreAdaptiveFilterCalculator + { +private: + ENUM_ADAPTIVE_METHOD m_method; + int m_adaptive_period; + double m_gamma_min; + double m_gamma_max; + bool m_is_ha; + + CEfficiencyRatioCalculator *m_er_calc; + CATRCalculator *m_atr_calc; + + //--- Persistent State Registers + double m_price[]; + double m_L0[], m_L1[], m_L2[], m_L3[]; + double m_adaptive_metric[]; + double m_temp_atr[]; + double m_temp_stdev[]; + + bool PreparePriceSeries(int rates_total, int start_index, ENUM_APPLIED_PRICE price_type, + const double &open[], const double &high[], const double &low[], const double &close[]); + + //--- DRY Helper: Sliding Min-Max Normalization to map raw volatility to [0.0, 1.0] + void NormalizeMetric(int rates_total, int prev_calculated, const double &src_array[]); + +public: + CLaguerreAdaptiveFilterCalculator(void); + ~CLaguerreAdaptiveFilterCalculator(void); + + bool Init(ENUM_ADAPTIVE_METHOD method, int adaptive_period, double gamma_min, double gamma_max, bool is_ha); + void Calculate(int rates_total, int prev_calculated, ENUM_APPLIED_PRICE price_type, + const double &open[], const double &high[], const double &low[], const double &close[], + double &filter_buffer[]); + }; + +//+------------------------------------------------------------------+ +//| Constructor | +//+------------------------------------------------------------------+ +CLaguerreAdaptiveFilterCalculator::CLaguerreAdaptiveFilterCalculator(void) + : m_er_calc(NULL), + m_atr_calc(NULL), + m_is_ha(false) + { + } + +//+------------------------------------------------------------------+ +//| Destructor | +//+------------------------------------------------------------------+ +CLaguerreAdaptiveFilterCalculator::~CLaguerreAdaptiveFilterCalculator(void) + { + if(CheckPointer(m_er_calc) != POINTER_INVALID) + delete m_er_calc; + if(CheckPointer(m_atr_calc) != POINTER_INVALID) + delete m_atr_calc; + } + +//+------------------------------------------------------------------+ +//| Init | +//+------------------------------------------------------------------+ +bool CLaguerreAdaptiveFilterCalculator::Init(ENUM_ADAPTIVE_METHOD method, int adaptive_period, double gamma_min, double gamma_max, bool is_ha) + { + m_method = method; + m_adaptive_period = (adaptive_period < 2) ? 2 : adaptive_period; + m_gamma_min = fmax(0.0, fmin(1.0, gamma_min)); + m_gamma_max = fmax(0.0, fmin(1.0, gamma_max)); + m_is_ha = is_ha; + + 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; + } + +//+------------------------------------------------------------------+ +//| Calculate | +//+------------------------------------------------------------------+ +void CLaguerreAdaptiveFilterCalculator::Calculate(int rates_total, int prev_calculated, ENUM_APPLIED_PRICE price_type, + 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; + +//--- Resize state buffers & coerce strict chronological indexing + if(ArraySize(m_price) != rates_total) + { + ArrayResize(m_price, rates_total); + ArrayResize(m_L0, rates_total); + ArrayResize(m_L1, rates_total); + ArrayResize(m_L2, rates_total); + ArrayResize(m_L3, rates_total); + ArrayResize(m_adaptive_metric, rates_total); + + ArraySetAsSeries(m_price, false); + ArraySetAsSeries(m_L0, false); + ArraySetAsSeries(m_L1, false); + ArraySetAsSeries(m_L2, false); + ArraySetAsSeries(m_L3, false); + ArraySetAsSeries(m_adaptive_metric, false); + } + +//--- Prepare prices first (Needed for ER, StDev and final filter calculation) + int start_index = (prev_calculated > 0) ? prev_calculated - 1 : 0; + if(!PreparePriceSeries(rates_total, start_index, price_type, open, high, low, close)) + return; + +//--- 1. Calculate Adaptive Metric [0.0 to 1.0] + if(m_method == METHOD_EFFICIENCY_RATIO) + { + m_er_calc.Calculate(rates_total, prev_calculated, price_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 + { + 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; + } + + // Compute raw standard deviations + 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 / m_adaptive_period; + + double sum_sq = 0.0; + for(int j = 0; j < m_adaptive_period; j++) + sum_sq += pow(m_price[i - j] - mean, 2); + + m_temp_stdev[i] = sqrt(sum_sq / m_adaptive_period); + } + + NormalizeMetric(rates_total, prev_calculated, m_temp_stdev); + } + +//--- 2. Calculate Stateful Adaptive Laguerre + if(start_index == 0) + { + m_L0[0] = m_price[0]; + m_L1[0] = m_price[0]; + m_L2[0] = m_price[0]; + m_L3[0] = m_price[0]; + filter_buffer[0] = m_price[0]; + start_index = 1; + } + + for(int i = start_index; i < rates_total; i++) + { + double metric = m_adaptive_metric[i]; + metric = fmax(0.0, fmin(1.0, metric)); // Safe clamp + + // Scale dynamic Gamma: higher volatility/efficiency -> lower Gamma (faster tracking) + double gamma = m_gamma_max - metric * (m_gamma_max - m_gamma_min); + gamma = fmax(0.0, fmin(1.0, gamma)); + + m_L0[i] = (1.0 - gamma) * m_price[i] + gamma * m_L0[i - 1]; + m_L1[i] = -gamma * m_L0[i] + m_L0[i - 1] + gamma * m_L1[i - 1]; + m_L2[i] = -gamma * m_L1[i] + m_L1[i - 1] + gamma * m_L2[i - 1]; + m_L3[i] = -gamma * m_L2[i] + m_L2[i - 1] + gamma * m_L3[i - 1]; + + filter_buffer[i] = (m_L0[i] + 2.0 * m_L1[i] + 2.0 * m_L2[i] + m_L3[i]) / 6.0; + } + } + +//+------------------------------------------------------------------+ +//| Sliding Min-Max Normalization (DRY Helper) | +//+------------------------------------------------------------------+ +void CLaguerreAdaptiveFilterCalculator::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 | +//+------------------------------------------------------------------+ +bool CLaguerreAdaptiveFilterCalculator::PreparePriceSeries(int rates_total, int start_index, ENUM_APPLIED_PRICE price_type, + const double &open[], const double &high[], const double &low[], const double &close[]) + { + if(m_is_ha) + { + static CHeikinAshi_Calculator ha_calc; + static double ha_open[], ha_high[], ha_low[], ha_close[]; + if(ArraySize(ha_open) != rates_total) + { + ArrayResize(ha_open, rates_total); + ArrayResize(ha_high, rates_total); + ArrayResize(ha_low, rates_total); + ArrayResize(ha_close, rates_total); + ArraySetAsSeries(ha_open, false); + ArraySetAsSeries(ha_high, false); + ArraySetAsSeries(ha_low, false); + ArraySetAsSeries(ha_close, false); + } + + ha_calc.Calculate(rates_total, start_index, open, high, low, close, ha_open, ha_high, ha_low, ha_close); + + for(int i = start_index; i < rates_total; i++) + { + switch(price_type) + { + case PRICE_OPEN: + m_price[i] = ha_open[i]; + break; + case PRICE_HIGH: + m_price[i] = ha_high[i]; + break; + case PRICE_LOW: + m_price[i] = ha_low[i]; + break; + case PRICE_MEDIAN: + m_price[i] = (ha_high[i] + ha_low[i]) * 0.5; + break; + case PRICE_TYPICAL: + m_price[i] = (ha_high[i] + ha_low[i] + ha_close[i]) / 3.0; + break; + case PRICE_WEIGHTED: + m_price[i] = (ha_high[i] + ha_low[i] + ha_close[i] * 2.0) * 0.25; + break; + default: + m_price[i] = ha_close[i]; + break; + } + } + } + else + { + for(int i = start_index; i < rates_total; i++) + { + switch(price_type) + { + case PRICE_OPEN: + m_price[i] = open[i]; + break; + case PRICE_HIGH: + m_price[i] = high[i]; + break; + case PRICE_LOW: + m_price[i] = low[i]; + break; + case PRICE_MEDIAN: + m_price[i] = (high[i] + low[i]) * 0.5; + break; + case PRICE_TYPICAL: + m_price[i] = (high[i] + low[i] + close[i]) / 3.0; + break; + case PRICE_WEIGHTED: + m_price[i] = (high[i] + low[i] + close[i] * 2.0) * 0.25; + break; + default: + m_price[i] = close[i]; + break; + } + } + } + return true; + } + +#endif // LAGUERRE_ADAPTIVE_FILTER_CALCULATOR_MQH +//+------------------------------------------------------------------+