xml doc rewrite

lib/averages/Gma.cs

@@ -1,9 +1,35 @@
+using System;
 namespace QuanTAlib;
 
+/// <summary>
+/// GMA: Gaussian Moving Average
+/// A moving average that uses weights based on the Gaussian (normal) distribution curve.
+/// This creates a smooth, bell-shaped weighting scheme that gives maximum weight to the
+/// center of the period and gradually decreasing weights towards the edges.
+/// </summary>
+/// <remarks>
+/// The GMA calculation process:
+/// 1. Creates a Gaussian distribution of weights centered on the period
+/// 2. Normalizes the weights to sum to 1
+/// 3. Applies the weights through convolution
+///
+/// Key characteristics:
+/// - Smooth, symmetric weight distribution
+/// - Natural bell curve weighting
+/// - Reduces noise while preserving signal characteristics
+/// - Less sensitive to outliers than simple moving averages
+/// - Implemented using efficient convolution operations
+///
+/// Implementation:
+///     Based on Gaussian distribution principles from statistics
+/// </remarks>
+
 public class Gma : AbstractBase
 {
     private readonly Convolution _convolution;
 
+    /// <param name="period">The number of data points used in the GMA calculation.</param>
+    /// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
     public Gma(int period)
     {
         if (period < 1)
@@ -16,12 +42,20 @@ public class Gma : AbstractBase
         Init();
     }
 
+    /// <param name="source">The data source object that publishes updates.</param>
+    /// <param name="period">The number of data points used in the GMA calculation.</param>
     public Gma(object source, int period) : this(period)
     {
         var pubEvent = source.GetType().GetEvent("Pub");
         pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
     }
 
+    /// <summary>
+    /// Generates the Gaussian-based convolution kernel for the GMA calculation.
+    /// </summary>
+    /// <param name="period">The period for which to generate the kernel.</param>
+    /// <param name="sigma">The standard deviation parameter controlling the spread of the Gaussian curve. Default is 1.0.</param>
+    /// <returns>An array of normalized Gaussian-based weights for the convolution operation.</returns>
     public static double[] GenerateKernel(int period, double sigma = 1.0)
     {
         double[] kernel = new double[period];
@@ -71,4 +105,4 @@ public class Gma : AbstractBase
 
         return result;
     }
-}
+}