refactor: Supports both Moving and Static Channels

Include/MyIncludes/LinearRegression_Calculator.mqh

@@ -1,21 +1,20 @@
 //+------------------------------------------------------------------+
 //|                                 LinearRegression_Calculator.mqh  |
-//|      VERSION 2.00: Optimized for incremental calculation.        |
+//|      VERSION 3.10: Supports both Moving and Static Channels.     |
 //|                                        Copyright 2025, xxxxxxxx  |
 //+------------------------------------------------------------------+
 #property copyright "Copyright 2025, xxxxxxxx"
 
 #include <MyIncludes\HeikinAshi_Tools.mqh>
 
-//--- Enum for Channel Calculation Mode ---
 enum ENUM_CHANNEL_MODE
   {
-   DEVIATION_STANDARD, // Channel width based on Standard Deviation
+   DEVIATION_STANDARD,
-   DEVIATION_MAXIMUM   // Channel width based on Maximum Deviation
+   DEVIATION_MAXIMUM
   };
 
 //+==================================================================+
-//|         CLASS 1: CLinearRegressionCalculator (Base Class)        |
+//|         CLASS: CLinearRegressionCalculator                       |
 //+==================================================================+
 class CLinearRegressionCalculator
   {
@@ -24,10 +23,9 @@ protected:
    ENUM_CHANNEL_MODE m_channel_mode;
    double            m_deviations;
 
-   //--- Persistent Buffer for Incremental Calculation
+   //--- Persistent Buffer
    double            m_price[];
 
-   //--- 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:
@@ -36,9 +34,13 @@ public:
 
    bool              Init(int period, ENUM_CHANNEL_MODE mode, double deviations);
 
-   //--- Updated: Accepts prev_calculated
+   //--- Method 1: Moving Regression (The "Wavy" line)
-   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,
+   void              CalculateMoving(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[]);
+                                     double &middle_buffer[], double &upper_buffer[], double &lower_buffer[]);
+
+   //--- Method 2: Static Channel (The "Straight" segment for current bars)
+   void              CalculateStaticChannel(int rates_total, 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[]);
   };
 
 //+------------------------------------------------------------------+
@@ -53,93 +55,162 @@ bool CLinearRegressionCalculator::Init(int period, ENUM_CHANNEL_MODE mode, doubl
   }
 
 //+------------------------------------------------------------------+
-//| Main Calculation (Optimized)                                     |
+//| Method 1: Moving Regression (Wavy)                               |
 //+------------------------------------------------------------------+
-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,
+void CLinearRegressionCalculator::CalculateMoving(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;
 
-//--- 1. Determine Start Index
+   int start_index = (prev_calculated == 0) ? 0 : prev_calculated - 1;
-   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;
 
-//--- 4. Calculate Linear Regression (Always recalculate for the window)
+// Pre-calc X sums
-   int regression_start_index = rates_total - m_period;
+   double sum_x = 0, sum_x2 = 0;
-// Calculate Sums
+   for(int k = 0; k < m_period; k++)
-   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[regression_start_index + i];
+      sum_x += k;
-      double x = i;
+      sum_x2 += k * k;
-      sum_x += x;
-      sum_y += y;
-      sum_xy += x * y;
-      sum_x2 += x * x;
      }
+   double denominator = m_period * sum_x2 - sum_x * sum_x;
 
-   double b = (m_period * sum_xy - sum_x * sum_y) / (m_period * sum_x2 - sum_x * sum_x);
+   int loop_start = MathMax(m_period - 1, start_index);
-   double a = (sum_y - b * sum_x) / m_period;
 
-   double deviation_offset = 0;
+   for(int i = loop_start; i < rates_total; i++)
-   double regression_values[];
-   ArrayResize(regression_values, m_period);
-
-   if(m_channel_mode == DEVIATION_STANDARD)
      {
-      double dev_sum_sq = 0;
+      double sum_y = 0, sum_xy = 0;
-      for(int i = 0; i < m_period; i++)
+      for(int k = 0; k < m_period; k++)
         {
-         regression_values[i] = a + b * i;
+         double price = m_price[i - m_period + 1 + k];
-         dev_sum_sq += MathPow(m_price[regression_start_index + i] - regression_values[i], 2);
+         sum_y += price;
+         sum_xy += k * price;
         }
-      deviation_offset = m_deviations * MathSqrt(dev_sum_sq / m_period);
-     }
-   else // DEVIATION_MAXIMUM
-     {
-      double max_dev = 0;
-      for(int i = 0; i < m_period; i++)
-        {
-         regression_values[i] = a + b * i;
-         max_dev = MathMax(max_dev, MathAbs(m_price[regression_start_index + i] - regression_values[i]));
-        }
-      deviation_offset = max_dev;
-     }
 
-// Fill Buffers
+      double b = (m_period * sum_xy - sum_x * sum_y) / denominator;
-   for(int i = 0; i < m_period; i++)
+      double a = (sum_y - b * sum_x) / m_period;
-     {
+      double regression_value = a + b * (m_period - 1); // End point
-      int buffer_index = regression_start_index + i;
+
-      middle_buffer[buffer_index] = regression_values[i];
+      middle_buffer[i] = regression_value;
-      upper_buffer[buffer_index]  = regression_values[i] + deviation_offset;
+
-      lower_buffer[buffer_index]  = regression_values[i] - deviation_offset;
+      double deviation_offset = 0;
-     }
+      if(m_channel_mode == DEVIATION_STANDARD)
-   if(regression_start_index > 0)
+        {
-     {
+         double dev_sum_sq = 0;
-      middle_buffer[regression_start_index-1] = EMPTY_VALUE;
+         for(int k = 0; k < m_period; k++)
-      upper_buffer[regression_start_index-1] = EMPTY_VALUE;
+           {
-      lower_buffer[regression_start_index-1] = EMPTY_VALUE;
+            double price = m_price[i - m_period + 1 + k];
+            double reg_val_at_k = a + b * k;
+            dev_sum_sq += MathPow(price - reg_val_at_k, 2);
+           }
+         deviation_offset = m_deviations * MathSqrt(dev_sum_sq / m_period);
+        }
+      else
+        {
+         double max_dev = 0;
+         for(int k = 0; k < m_period; k++)
+           {
+            double price = m_price[i - m_period + 1 + k];
+            double reg_val_at_k = a + b * k;
+            max_dev = MathMax(max_dev, MathAbs(price - reg_val_at_k));
+           }
+         deviation_offset = max_dev;
+        }
+
+      upper_buffer[i] = regression_value + deviation_offset;
+      lower_buffer[i] = regression_value - deviation_offset;
      }
   }
 
 //+------------------------------------------------------------------+
-//| Prepare Price (Standard - Optimized)                             |
+//| Method 2: Static Channel (Straight)                              |
+//+------------------------------------------------------------------+
+void CLinearRegressionCalculator::CalculateStaticChannel(int rates_total, 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;
+
+// Always update price buffer for the last segment
+   if(ArraySize(m_price) != rates_total)
+      ArrayResize(m_price, rates_total);
+
+// We only need to prepare the last 'm_period' prices
+   int start_prep = rates_total - m_period;
+   if(!PreparePriceSeries(rates_total, start_prep, price_type, open, high, low, close))
+      return;
+
+// 1. Clear old history (Optimization: only clear if necessary, but for visual clarity we clear all before start)
+   if(start_prep > 0)
+     {
+      middle_buffer[start_prep - 1] = EMPTY_VALUE;
+      upper_buffer[start_prep - 1]  = EMPTY_VALUE;
+      lower_buffer[start_prep - 1]  = EMPTY_VALUE;
+     }
+
+// 2. Calculate Regression for the SINGLE window [rates_total-period ... rates_total-1]
+   double sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
+
+   for(int k = 0; k < m_period; k++)
+     {
+      double x = k;
+      double y = m_price[start_prep + k];
+      sum_x += x;
+      sum_x2 += x * x;
+      sum_y += y;
+      sum_xy += x * y;
+     }
+
+   double denominator = m_period * sum_x2 - sum_x * sum_x;
+   double b = (m_period * sum_xy - sum_x * sum_y) / denominator;
+   double a = (sum_y - b * sum_x) / m_period;
+
+// 3. Calculate Deviation
+   double deviation_offset = 0;
+   if(m_channel_mode == DEVIATION_STANDARD)
+     {
+      double dev_sum_sq = 0;
+      for(int k = 0; k < m_period; k++)
+        {
+         double y = m_price[start_prep + k];
+         double reg_val = a + b * k;
+         dev_sum_sq += MathPow(y - reg_val, 2);
+        }
+      deviation_offset = m_deviations * MathSqrt(dev_sum_sq / m_period);
+     }
+   else
+     {
+      double max_dev = 0;
+      for(int k = 0; k < m_period; k++)
+        {
+         double y = m_price[start_prep + k];
+         double reg_val = a + b * k;
+         max_dev = MathMax(max_dev, MathAbs(y - reg_val));
+        }
+      deviation_offset = max_dev;
+     }
+
+// 4. Draw the Straight Line Segment
+   for(int k = 0; k < m_period; k++)
+     {
+      int bar_index = start_prep + k;
+      double reg_val = a + b * k;
+
+      middle_buffer[bar_index] = reg_val;
+      upper_buffer[bar_index]  = reg_val + deviation_offset;
+      lower_buffer[bar_index]  = reg_val - deviation_offset;
+     }
+  }
+
+//+------------------------------------------------------------------+
+//| Prepare Price (Standard)                                         |
 //+------------------------------------------------------------------+
 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[])
   {
-// Optimized copy loop
    for(int i = start_index; i < rates_total; i++)
      {
       switch(price_type)
@@ -180,19 +251,16 @@ 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, int start_index, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[]) override;
   };
 
 //+------------------------------------------------------------------+
-//| Prepare Price (Heikin Ashi - Optimized)                          |
+//|                                                                  |
 //+------------------------------------------------------------------+
 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[])
   {
-// Resize internal HA buffers
    if(ArraySize(m_ha_open) != rates_total)
      {
       ArrayResize(m_ha_open, rates_total);
@@ -200,12 +268,7 @@ bool CLinearRegressionCalculator_HA::PreparePriceSeries(int rates_total, int sta
       ArrayResize(m_ha_low, rates_total);
       ArrayResize(m_ha_close, rates_total);
      }
-
+   m_ha_calculator.Calculate(rates_total, start_index, open, high, low, close, m_ha_open, m_ha_high, m_ha_low, m_ha_close);
-//--- 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)