Complete Test Linear Regression and Required to Apply Works on Real Project ...

2025-09-21 17:49:39 +03:30
parent 84dc311c72
commit 7a4f1aa48b
6 changed files with 1688 additions and 258 deletions
@@ -6641,22 +6641,22 @@ int GetPriceBoundary(

 /**
 * Get Applied Price Buffer ...
- * 
+ *
 * @param  mType: ENUM_X_PRICE, Specified Price Type ...
 * @param  dest: double, Holds Destination Prices ...
 * @param  mOpen: double collection, Open Prices ...
 * @param  mHigh: double collection, High Prices ...
 * @param  mLow: double collection, Low Prices ...
 * @param  mClose: double collection, Close Prices ...
- * 
+ *
 * @return ( int )
 */
 int GetAppliedPrice(
    ENUM_X_PRICE mType,
    double &dest[],
-    const double &mOpen[],  // Open Prices
-    const double &mHigh[],  // High Preices
-    const double &mLow[],   // Low Prices
+    const double &mOpen[], // Open Prices
+    const double &mHigh[], // High Preices
+    const double &mLow[],  // Low Prices
    const double &mClose[] // Close Prices
 )
 {
@@ -7061,3 +7061,135 @@ bool SetChartVolumesColor(
 //

 //
+// START Linear Regression ...
+//
+
+/**
+ * Linear Regression Based Calculate Data ...
+ * int this Senario X Axis is Buffer Index ...
+ *
+ * @param  _slope: double, refrence for Calculated Slope ...
+ * @param  _intercept: double, reference for Calculated Intercept ...
+ * @param  _source: double, Y Axis Valus Collection ...
+ * @param  _start: int, start Index ...
+ * @param  _count: int, number of Calculations ...
+ *
+ * @return ( bool )
+ */
+bool CalculateLinearRegression(
+    double &_slope,
+    double &_intercept,
+    double &_source[],
+    int _start = 0,
+    int _count = 0 //
+)
+{
+    //
+    bool result = false;
+
+    //
+    // Prepare ...
+    _slope = EMPTY_VALUE;
+    _intercept = EMPTY_VALUE;
+
+    //
+    // Validate ...
+    int count = ArraySize(_source);
+    result = IsValidSize(count);
+    if (!result)
+    {
+        return result;
+    }
+
+    //
+    // Normalize ...
+    _start = NormalizeInt(_start, 0, count - 1);
+    if (_count == 0 || _count + _start >= count)
+    {
+        //
+        // Get Whole Array ...
+        _count = count - 1 - _start;
+    }
+    int _end = _start + _count;
+
+    //
+    // Define Requirements ...
+    double sumX = 0;
+    double sumY = 0;
+    double sumXY = 0;
+    double sumX2 = 0;
+
+    //
+    // Looping Through Source Buffer to Cellect Data ...
+    for (int i = _start; i < _end; i++)
+    {
+        //
+        double x = i + 1;
+        double y = _source[i];
+
+        //
+        sumX += x;
+        sumY += y;
+        sumXY += x * y;
+        sumX2 += x * x;
+    }
+
+    //
+    // Calculate Slope and Intercept ...
+    int n = _count;
+    _slope = ((n * sumXY) - (sumX * sumY)) / ((n * sumX2) - (sumX * sumX));
+    _intercept = ((sumY - _slope) * sumX) / n;
+
+    //
+    result = sumX > 0 &&
+             sumY > 0 &&
+             sumXY > 0 &&
+             sumX2 > 0 &&
+             NotEmpty(_slope) &&
+             NotEmpty(_intercept);
+    if (!result)
+    {
+        //
+        _slope = EMPTY_VALUE;
+        _intercept = EMPTY_VALUE;
+    }
+
+    //
+    return result;
+}
+
+double CalculateValueBySlopeIntercept(
+    double _slope,
+    double _intercept,
+    int _index //
+)
+{
+    //
+    double result = EMPTY_VALUE;
+
+    //
+    // Normalize Index ...
+    _index = NormalizeInt(_index, 1);
+
+    //
+    // Validate ...
+    if (
+        !NotEmpty(_slope) ||
+        !NotEmpty(_intercept) ||
+        !IsValidIndex(_index))
+    {
+        return result;
+    }
+
+    //
+    result = (_intercept + _slope * _index);
+
+    //
+    return result;
+}
+
+//
+// END Linear Regression ...
+//
+
+//