xml doc rewrite

lib/averages/Epma.cs

@@ -1,10 +1,35 @@
+using System;
 namespace QuanTAlib;
 
+/// <summary>
+/// EPMA: Endpoint Moving Average
+/// A moving average that uses a specialized convolution kernel to emphasize recent price movements
+/// while maintaining a connection to historical data. The weights decrease linearly with a focus
+/// on endpoints.
+/// </summary>
+/// <remarks>
+/// The EPMA uses a unique weighting scheme where:
+/// - The most recent price gets the highest weight: (2 * period - 1)
+/// - Each previous price gets a weight reduced by 3: (2 * period - 1) - 3i
+/// - Weights are normalized to sum to 1
+///
+/// Key characteristics:
+/// - Emphasizes recent price movements more than traditional moving averages
+/// - Maintains some influence from historical data
+/// - Uses convolution for efficient calculation
+/// - Provides better endpoint preservation than simple moving averages
+///
+/// Implementation:
+///     Original implementation based on convolution principles
+/// </remarks>
+
 public class Epma : AbstractBase
 {
     private readonly int _period;
     private readonly Convolution _convolution;
 
+    /// <param name="period">The number of data points used in the EPMA calculation.</param>
+    /// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
     public Epma(int period)
     {
         if (period < 1)
@@ -18,6 +43,8 @@ public class Epma : AbstractBase
         Init();
     }
 
+    /// <param name="source">The data source object that publishes updates.</param>
+    /// <param name="period">The number of data points used in the EPMA calculation.</param>
     public Epma(object source, int period) : this(period)
     {
         var pubEvent = source.GetType().GetEvent("Pub");
@@ -60,6 +87,11 @@ public class Epma : AbstractBase
         return result;
     }
 
+    /// <summary>
+    /// Generates the convolution kernel for the EPMA calculation.
+    /// </summary>
+    /// <param name="period">The period for which to generate the kernel.</param>
+    /// <returns>An array of normalized weights for the convolution operation.</returns>
     public static double[] GenerateKernel(int period)
     {
         double[] kernel = new double[period];
@@ -79,4 +111,4 @@ public class Epma : AbstractBase
 
         return kernel;
     }
-}
+}