Add Support For ZigZag Swing Prediction to TestRegression Expert ...

Libraries/x-saherelm.common.extensions.lib.mq5

@@ -7065,67 +7065,54 @@ bool SetChartVolumesColor(
 //
 
 /**
- * Linear Regression Based Calculate Data ...
- * int this Senario X Axis is Buffer Index ...
+ * Calculate Slope and Intercept for Linear Regression Predictions ...
  *
- * @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 ...
+ * @param  _slope: double, refrence to Hold Calculated Slope ...
+ * @param  _intercept: double, reference to Hold Calculated Intercept ...
+ * @param  xData: double, reference Collection to Provides X-Axis Data for Calculations ...
+ * @param  yData: double, reference Collection to Provides Y-Axis Data for Calculations ...
  *
- * @return ( bool )
+ * @return ( int )
  */
-bool CalculateLinearRegression(
+int CalculateSlopeAndIntercept(
     double &_slope,
     double &_intercept,
-    double &_source[],
-    int _start = 0,
-    int _count = 0 //
+    double &xData[],
+    double &yData[] //
 )
 {
     //
-    bool result = false;
+    int result = 0;
 
     //
-    // Prepare ...
-    _slope = EMPTY_VALUE;
-    _intercept = EMPTY_VALUE;
+    bool has = false;
 
     //
-    // Validate ...
-    int count = ArraySize(_source);
-    result = IsValidSize(count);
-    if (!result)
+    _slope = 0;
+    _intercept = 0;
+
+    //
+    if (!HasChild(xData) ||
+        !HasChild(yData))
     {
         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 = 0;
+    double y = 0;
+    int end = MathMin(ArraySize(xData), ArraySize(yData));
+    for (int i = 0; i < end; i++)
     {
         //
-        double x = i + 1;
-        double y = _source[i];
+        double x = xData[i];
+        double y = yData[i];
 
         //
         sumX += x;
@@ -7135,54 +7122,46 @@ bool CalculateLinearRegression(
     }
 
     //
-    // Calculate Slope and Intercept ...
-    int n = _count;
-    _slope = ((n * sumXY) - (sumX * sumY)) / ((n * sumX2) - (sumX * sumX));
-    _intercept = ((sumY - _slope) * sumX) / n;
+    int n = end;
+    _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;
-    }
+    result = n;
 
     //
     return result;
 }
 
-double CalculateValueBySlopeIntercept(
+/**
+ * Predict Value for Specified X ...
+ *
+ * @param  _sllope: double, Provided Slope ...
+ * @param  _intercept: double, Provided Intercept ...
+ * @param  _forX: double, Specified XValue ...
+ *
+ * @return ( double )
+ */
+double PredictValue(
     double _slope,
     double _intercept,
-    int _index //
+    double _forX //
 )
 {
     //
-    double result = EMPTY_VALUE;
-
-    //
-    // Normalize Index ...
-    _index = NormalizeInt(_index, 1);
+    double result = 0;
 
     //
     // Validate ...
-    if (
+    if (!NotEmpty(_forX) ||
         !NotEmpty(_slope) ||
-        !NotEmpty(_intercept) ||
-        !IsValidIndex(_index))
+        !NotEmpty(_intercept))
     {
         return result;
     }
 
     //
-    result = (_intercept + _slope * _index);
+    result = (_intercept + (_slope * _forX));
 
     //
     return result;