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QuanTAlib/lib/trends_IIR/hema/tests/Hema.Validation.Tests.cs
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using System;
namespace QuanTAlib.Tests;
public class HemaValidationTests
{
[Fact]
public void Hema_Streaming_MatchesReference()
{
int period = 20;
TSeries series = BuildSeries(300, seed: 5);
double[] reference = new double[series.Count];
ReferenceHema(series.Values, reference, period);
var hema = new Hema(period);
for (int i = 0; i < series.Count; i++)
{
double actual = hema.Update(series[i]).Value;
Assert.Equal(reference[i], actual, precision: 10);
}
}
[Fact]
public void Hema_Batch_MatchesReference()
{
int period = 14;
TSeries series = BuildSeries(250, seed: 9);
double[] reference = new double[series.Count];
ReferenceHema(series.Values, reference, period);
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TSeries batch = Hema.Batch(series, period);
for (int i = 0; i < series.Count; i++)
{
Assert.Equal(reference[i], batch[i].Value, precision: 10);
}
}
[Fact]
public void Hema_Span_MatchesReference()
{
int period = 30;
TSeries series = BuildSeries(200, seed: 12);
double[] values = series.Values.ToArray();
var output = new double[values.Length];
var reference = new double[values.Length];
ReferenceHema(values, reference, period);
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Hema.Batch(values, output, period);
for (int i = 0; i < values.Length; i++)
{
Assert.Equal(reference[i], output[i], precision: 10);
}
}
private static void ReferenceHema(ReadOnlySpan<double> source, Span<double> output, int period)
{
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int n = Math.Max(period, 2);
int halfN = n / 2; // integer floor, same as HMA
int sqrtN = Math.Max((int)Math.Sqrt(n), 1); // integer floor, same as HMA
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double aS = AlphaFromWmaLag(n);
double aF = AlphaFromWmaLag(Math.Max(halfN, 1));
double aM = AlphaFromWmaLag(Math.Max(sqrtN, 1));
double bS = 1.0 - aS;
double bF = 1.0 - aF;
double bM = 1.0 - aM;
double lagS = bS / aS;
double lagF = bF / aF;
double ratio = Math.Clamp(lagF / lagS, 0.0, 0.999999);
double invOneMinusRatio = 1.0 / Math.Max(1.0 - ratio, 1e-12);
bool warmup = true;
double decayS = 1.0;
double decayF = 1.0;
double decayM = 1.0;
double eSraw = 0.0;
double eFraw = 0.0;
double eMraw = 0.0;
double lastValid = double.NaN;
for (int i = 0; i < source.Length; i++)
{
double val = source[i];
if (double.IsFinite(val))
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{
lastValid = val;
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}
else
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{
val = lastValid;
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}
if (double.IsNaN(val))
{
output[i] = double.NaN;
continue;
}
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eSraw = Math.FusedMultiplyAdd(eSraw, bS, aS * val);
eFraw = Math.FusedMultiplyAdd(eFraw, bF, aF * val);
if (warmup)
{
decayS *= bS;
decayF *= bF;
decayM *= bM;
double invS = 1.0 / Math.Max(1.0 - decayS, 1e-12);
double invF = 1.0 / Math.Max(1.0 - decayF, 1e-12);
double invM = 1.0 / Math.Max(1.0 - decayM, 1e-12);
double eS = eSraw * invS;
double eF = eFraw * invF;
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double deLag = Math.FusedMultiplyAdd(-ratio, eS, eF) * invOneMinusRatio;
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eMraw = Math.FusedMultiplyAdd(eMraw, bM, aM * deLag);
output[i] = eMraw * invM;
double maxDecay = Math.Max(decayS, Math.Max(decayF, decayM));
warmup = maxDecay > 1e-10;
}
else
{
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double deLag = Math.FusedMultiplyAdd(-ratio, eSraw, eFraw) * invOneMinusRatio;
eMraw = Math.FusedMultiplyAdd(eMraw, bM, aM * deLag);
output[i] = eMraw;
}
}
}
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private static double AlphaFromWmaLag(int p)
{
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// WMA-lag-matched alpha: EMA lag = (1-α)/α = (P-1)/3
// Solving: α = 3/(P+2)
return 3.0 / (Math.Max(p, 1) + 2.0);
}
private static TSeries BuildSeries(int count, int seed)
{
var series = new TSeries();
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: seed);
for (int i = 0; i < count; i++)
{
var bar = gbm.Next(isNew: true);
series.Add(bar.Time, bar.Close);
}
return series;
}
}