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https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-17 10:08:05 +00:00
Class optimization
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+14
-9
@@ -1,4 +1,4 @@
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using System;
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using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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@@ -29,6 +29,7 @@ namespace QuanTAlib;
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public class Trima : AbstractBase
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{
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private readonly Convolution _convolution;
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private readonly double[] _kernel;
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/// <param name="period">The number of data points used in the TRIMA calculation.</param>
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/// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
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@@ -36,9 +37,10 @@ public class Trima : AbstractBase
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{
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if (period < 1)
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{
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throw new ArgumentException("Period must be greater than or equal to 1.", nameof(period));
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throw new System.ArgumentException("Period must be greater than or equal to 1.", nameof(period));
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}
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_convolution = new Convolution(GenerateKernel(period));
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_kernel = GenerateKernel(period);
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_convolution = new Convolution(_kernel);
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Name = "Trima";
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WarmupPeriod = period;
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Init();
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@@ -57,33 +59,38 @@ public class Trima : AbstractBase
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/// </summary>
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/// <param name="period">The period for which to generate the kernel.</param>
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/// <returns>An array of normalized triangular weights for the convolution operation.</returns>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static double[] GenerateKernel(int period)
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{
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double[] kernel = new double[period];
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int halfPeriod = (period + 1) / 2;
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double weightSum = 0;
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// Calculate weights and sum in one pass
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for (int i = 0; i < period; i++)
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{
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kernel[i] = i < halfPeriod ? i + 1 : period - i;
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weightSum += kernel[i];
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}
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// Normalize the kernel
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// Normalize using multiplication instead of division
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double invWeightSum = 1.0 / weightSum;
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for (int i = 0; i < period; i++)
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{
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kernel[i] /= weightSum;
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kernel[i] *= invWeightSum;
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}
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return kernel;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private new void Init()
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{
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base.Init();
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_convolution.Init();
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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@@ -98,11 +105,9 @@ public class Trima : AbstractBase
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ManageState(Input.IsNew);
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// Use Convolution for calculation
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TValue convolutionResult = _convolution.Calc(Input);
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double result = convolutionResult.Value;
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var convolutionResult = _convolution.Calc(Input);
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IsHot = _index >= WarmupPeriod;
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return result;
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return convolutionResult.Value;
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}
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}
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