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refactor: Optimized for incremental calculation

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Toh4iem9
2025-12-17 20:07:02 +01:00
parent cb0e7986ba
commit b47dd02fb0
1 changed files with 116 additions and 83 deletions
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Include/MyIncludes/LinearRegression_Calculator.mqh
+116 -83
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@@ -1,6 +1,6 @@
//+------------------------------------------------------------------+
//| LinearRegression_Calculator.mqh |
//| Calculation engine for Standard and Heikin Ashi LinReg Channels. |
//| VERSION 2.00: Optimized for incremental calculation. |
//| Copyright 2025, xxxxxxxx |
//+------------------------------------------------------------------+
#property copyright "Copyright 2025, xxxxxxxx"
@@ -15,9 +15,7 @@ enum ENUM_CHANNEL_MODE
};
//+==================================================================+
//| |
//| CLASS 1: CLinearRegressionCalculator (Base Class) |
//| |
//+==================================================================+
class CLinearRegressionCalculator
{
@@ -25,21 +23,26 @@ protected:
int m_period;
ENUM_CHANNEL_MODE m_channel_mode;
double m_deviations;
//--- Persistent Buffer for Incremental Calculation
double m_price[];
virtual bool PreparePriceSeries(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type);
//--- Updated: Accepts start_index
virtual 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[]);
public:
CLinearRegressionCalculator(void) {};
virtual ~CLinearRegressionCalculator(void) {};
bool Init(int period, ENUM_CHANNEL_MODE mode, double deviations);
void Calculate(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
//--- Updated: Accepts prev_calculated
void Calculate(int rates_total, int prev_calculated, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
double &middle_buffer[], double &upper_buffer[], double &lower_buffer[]);
};
//+------------------------------------------------------------------+
//| CLinearRegressionCalculator: Initialization |
//| Init |
//+------------------------------------------------------------------+
bool CLinearRegressionCalculator::Init(int period, ENUM_CHANNEL_MODE mode, double deviations)
{
@@ -50,21 +53,36 @@ bool CLinearRegressionCalculator::Init(int period, ENUM_CHANNEL_MODE mode, doubl
}
//+------------------------------------------------------------------+
//| CLinearRegressionCalculator: Main Calculation Method |
//| Main Calculation (Optimized) |
//+------------------------------------------------------------------+
void CLinearRegressionCalculator::Calculate(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
void CLinearRegressionCalculator::Calculate(int rates_total, int prev_calculated, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
double &middle_buffer[], double &upper_buffer[], double &lower_buffer[])
{
if(rates_total < m_period)
return;
if(!PreparePriceSeries(rates_total, open, high, low, close, price_type))
//--- 1. Determine Start Index
int start_index;
if(prev_calculated == 0)
start_index = 0;
else
start_index = prev_calculated - 1;
//--- 2. Resize Buffer
if(ArraySize(m_price) != rates_total)
ArrayResize(m_price, rates_total);
//--- 3. Prepare Price (Optimized)
if(!PreparePriceSeries(rates_total, start_index, price_type, open, high, low, close))
return;
int start_index = rates_total - m_period;
//--- 4. Calculate Linear Regression (Always recalculate for the window)
int regression_start_index = rates_total - m_period;
// Calculate Sums
double sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
for(int i = 0; i < m_period; i++)
{
double y = m_price[start_index + i];
double y = m_price[regression_start_index + i];
double x = i;
sum_x += x;
sum_y += y;
@@ -85,7 +103,7 @@ void CLinearRegressionCalculator::Calculate(int rates_total, const double &open[
for(int i = 0; i < m_period; i++)
{
regression_values[i] = a + b * i;
dev_sum_sq += MathPow(m_price[start_index + i] - regression_values[i], 2);
dev_sum_sq += MathPow(m_price[regression_start_index + i] - regression_values[i], 2);
}
deviation_offset = m_deviations * MathSqrt(dev_sum_sq / m_period);
}
@@ -95,114 +113,129 @@ void CLinearRegressionCalculator::Calculate(int rates_total, const double &open[
for(int i = 0; i < m_period; i++)
{
regression_values[i] = a + b * i;
max_dev = MathMax(max_dev, MathAbs(m_price[start_index + i] - regression_values[i]));
max_dev = MathMax(max_dev, MathAbs(m_price[regression_start_index + i] - regression_values[i]));
}
deviation_offset = max_dev;
}
// Fill Buffers
for(int i = 0; i < m_period; i++)
{
int buffer_index = start_index + i;
int buffer_index = regression_start_index + i;
middle_buffer[buffer_index] = regression_values[i];
upper_buffer[buffer_index] = regression_values[i] + deviation_offset;
lower_buffer[buffer_index] = regression_values[i] - deviation_offset;
}
PlotIndexSetInteger(0, PLOT_DRAW_BEGIN, start_index);
PlotIndexSetInteger(1, PLOT_DRAW_BEGIN, start_index);
PlotIndexSetInteger(2, PLOT_DRAW_BEGIN, start_index);
if(regression_start_index > 0)
{
middle_buffer[regression_start_index-1] = EMPTY_VALUE;
upper_buffer[regression_start_index-1] = EMPTY_VALUE;
lower_buffer[regression_start_index-1] = EMPTY_VALUE;
}
}
//+------------------------------------------------------------------+
//| CLinearRegressionCalculator: Prepares the standard source price. |
//| Prepare Price (Standard - Optimized) |
//+------------------------------------------------------------------+
bool CLinearRegressionCalculator::PreparePriceSeries(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type)
bool CLinearRegressionCalculator::PreparePriceSeries(int rates_total, int start_index, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[])
{
ArrayResize(m_price, rates_total);
switch(price_type)
// Optimized copy loop
for(int i = start_index; i < rates_total; i++)
{
case PRICE_OPEN:
ArrayCopy(m_price, open, 0, 0, rates_total);
break;
case PRICE_HIGH:
ArrayCopy(m_price, high, 0, 0, rates_total);
break;
case PRICE_LOW:
ArrayCopy(m_price, low, 0, 0, rates_total);
break;
case PRICE_MEDIAN:
for(int i=0; i<rates_total; i++)
switch(price_type)
{
case PRICE_CLOSE:
m_price[i] = close[i];
break;
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])/2.0;
break;
case PRICE_TYPICAL:
for(int i=0; i<rates_total; i++)
break;
case PRICE_TYPICAL:
m_price[i] = (high[i]+low[i]+close[i])/3.0;
break;
case PRICE_WEIGHTED:
for(int i=0; i<rates_total; i++)
break;
case PRICE_WEIGHTED:
m_price[i] = (high[i]+low[i]+2*close[i])/4.0;
break;
default:
ArrayCopy(m_price, close, 0, 0, rates_total);
break;
break;
default:
m_price[i] = close[i];
break;
}
}
return true;
}
//+==================================================================+
//| |
//| CLASS 2: CLinearRegressionCalculator_HA (Heikin Ashi) |
//| |
//| CLASS 2: CLinearRegressionCalculator_HA |
//+==================================================================+
class CLinearRegressionCalculator_HA : public CLinearRegressionCalculator
{
private:
CHeikinAshi_Calculator m_ha_calculator;
// Internal HA buffers
double m_ha_open[], m_ha_high[], m_ha_low[], m_ha_close[];
protected:
virtual bool PreparePriceSeries(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type) override;
virtual 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[]) override;
};
//+------------------------------------------------------------------+
//| CLinearRegressionCalculator_HA: Prepares the HA source price. |
//| Prepare Price (Heikin Ashi - Optimized) |
//+------------------------------------------------------------------+
bool CLinearRegressionCalculator_HA::PreparePriceSeries(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type)
bool CLinearRegressionCalculator_HA::PreparePriceSeries(int rates_total, int start_index, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[])
{
double ha_open[], ha_high[], ha_low[], ha_close[];
ArrayResize(ha_open, rates_total);
ArrayResize(ha_high, rates_total);
ArrayResize(ha_low, rates_total);
ArrayResize(ha_close, rates_total);
m_ha_calculator.Calculate(rates_total, open, high, low, close, ha_open, ha_high, ha_low, ha_close);
ArrayResize(m_price, rates_total);
switch(price_type)
// Resize internal HA buffers
if(ArraySize(m_ha_open) != rates_total)
{
case PRICE_OPEN:
ArrayCopy(m_price, ha_open, 0, 0, rates_total);
break;
case PRICE_HIGH:
ArrayCopy(m_price, ha_high, 0, 0, rates_total);
break;
case PRICE_LOW:
ArrayCopy(m_price, ha_low, 0, 0, rates_total);
break;
case PRICE_MEDIAN:
for(int i=0; i<rates_total; i++)
m_price[i] = (ha_high[i]+ha_low[i])/2.0;
break;
case PRICE_TYPICAL:
for(int i=0; i<rates_total; i++)
m_price[i] = (ha_high[i]+ha_low[i]+ha_close[i])/3.0;
break;
case PRICE_WEIGHTED:
for(int i=0; i<rates_total; i++)
m_price[i] = (ha_high[i]+ha_low[i]+2*ha_close[i])/4.0;
break;
default:
ArrayCopy(m_price, ha_close, 0, 0, rates_total);
break;
ArrayResize(m_ha_open, rates_total);
ArrayResize(m_ha_high, rates_total);
ArrayResize(m_ha_low, rates_total);
ArrayResize(m_ha_close, rates_total);
}
//--- STRICT CALL: Use the optimized 10-param HA calculation
m_ha_calculator.Calculate(rates_total, start_index, open, high, low, close,
m_ha_open, m_ha_high, m_ha_low, m_ha_close);
//--- Copy to m_price (Optimized loop)
for(int i = start_index; i < rates_total; i++)
{
switch(price_type)
{
case PRICE_CLOSE:
m_price[i] = m_ha_close[i];
break;
case PRICE_OPEN:
m_price[i] = m_ha_open[i];
break;
case PRICE_HIGH:
m_price[i] = m_ha_high[i];
break;
case PRICE_LOW:
m_price[i] = m_ha_low[i];
break;
case PRICE_MEDIAN:
m_price[i] = (m_ha_high[i]+m_ha_low[i])/2.0;
break;
case PRICE_TYPICAL:
m_price[i] = (m_ha_high[i]+m_ha_low[i]+m_ha_close[i])/3.0;
break;
case PRICE_WEIGHTED:
m_price[i] = (m_ha_high[i]+m_ha_low[i]+2*m_ha_close[i])/4.0;
break;
default:
m_price[i] = m_ha_close[i];
break;
}
}
return true;
}
//+------------------------------------------------------------------+
//+------------------------------------------------------------------+