New version merge

lib/averages/Sinema.cs

@@ -0,0 +1,75 @@
+namespace QuanTAlib;
+
+public class Sinema : AbstractBase
+{
+    private readonly int _period;
+    private readonly Convolution _convolution;
+
+    public Sinema(int period)
+    {
+        if (period < 1)
+        {
+            throw new ArgumentException("Period must be greater than or equal to 1.", nameof(period));
+        }
+        _period = period;
+        _convolution = new Convolution(GenerateKernel(_period));
+        Name = "Sinema";
+        WarmupPeriod = period;
+        Init();
+    }
+
+    public Sinema(object source, int period) : this(period)
+    {
+        var pubEvent = source.GetType().GetEvent("Pub");
+        pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
+    }
+
+    private new void Init()
+    {
+        base.Init();
+        _convolution.Init();
+    }
+
+    protected override void ManageState(bool isNew)
+    {
+        if (isNew)
+        {
+            _lastValidValue = Input.Value;
+            _index++;
+        }
+    }
+
+    protected override double Calculation()
+    {
+        ManageState(Input.IsNew);
+
+        // Use Convolution for calculation
+        TValue convolutionResult = _convolution.Calc(Input);
+
+        double result = convolutionResult.Value;
+        IsHot = _index >= WarmupPeriod;
+
+        return result;
+    }
+
+    public static double[] GenerateKernel(int period)
+    {
+        double[] kernel = new double[period];
+        double weightSum = 0;
+
+        for (int i = 0; i < period; i++)
+        {
+            // Use sine function to generate weights
+            kernel[i] = Math.Sin((i + 1) * Math.PI / (period + 1));
+            weightSum += kernel[i];
+        }
+
+        // Normalize the kernel
+        for (int i = 0; i < period; i++)
+        {
+            kernel[i] /= weightSum;
+        }
+
+        return kernel;
+    }
+}