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Miha Kralj 060649192f docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files
- Remove 'C# Implementation Considerations' sections from 34 indicator .md files
- Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.)
- Move test files into tests/ subdirectories for consistent project structure
- Add trader-focused bullet points to indicator documentation
2026-03-12 12:34:16 -07:00

204 lines
6.1 KiB
C#

using System;
using OoplesFinance.StockIndicators;
using OoplesFinance.StockIndicators.Models;
namespace QuanTAlib.Tests;
public class FramaValidationTests
{
[Fact]
public void Frama_Streaming_MatchesReference()
{
int period = 16;
TBarSeries series = BuildSeries(200, seed: 5);
double[] reference = new double[series.Count];
ReferenceFrama(series.High.Values, series.Low.Values, period, reference);
var frama = new Frama(period);
for (int i = 0; i < series.Count; i++)
{
double actual = frama.Update(series[i], isNew: true).Value;
Assert.Equal(reference[i], actual, precision: 10);
}
}
[Fact]
public void Frama_Batch_MatchesReference()
{
int period = 20;
TBarSeries series = BuildSeries(180, seed: 7);
double[] reference = new double[series.Count];
ReferenceFrama(series.High.Values, series.Low.Values, period, reference);
TSeries batch = Frama.Batch(series, period);
for (int i = 0; i < series.Count; i++)
{
Assert.Equal(reference[i], batch[i].Value, precision: 10);
}
}
[Fact]
public void Frama_Span_MatchesReference()
{
int period = 24;
TBarSeries series = BuildSeries(160, seed: 11);
double[] output = new double[series.Count];
double[] reference = new double[series.Count];
ReferenceFrama(series.High.Values, series.Low.Values, period, reference);
Frama.Batch(series.High.Values, series.Low.Values, period, output);
for (int i = 0; i < series.Count; i++)
{
Assert.Equal(reference[i], output[i], precision: 10);
}
}
private static void ReferenceFrama(ReadOnlySpan<double> high, ReadOnlySpan<double> low, int period, Span<double> output)
{
int pe = (period % 2 == 0) ? period : period + 1;
int h = pe / 2;
double lastHigh = double.NaN;
double lastLow = double.NaN;
double fr = double.NaN;
bool hasValue = false;
for (int i = 0; i < high.Length; i++)
{
double highVal = high[i];
double lowVal = low[i];
if (!double.IsFinite(highVal) || !double.IsFinite(lowVal))
{
if (!double.IsFinite(lastHigh) || !double.IsFinite(lastLow))
{
output[i] = double.NaN;
continue;
}
highVal = lastHigh;
lowVal = lastLow;
}
lastHigh = highVal;
lastLow = lowVal;
if (i < pe - 1)
{
output[i] = double.NaN;
continue;
}
double maxRecent = double.MinValue;
double minRecent = double.MaxValue;
double maxPrev = double.MinValue;
double minPrev = double.MaxValue;
double maxFull = double.MinValue;
double minFull = double.MaxValue;
int startFull = i - pe + 1;
int startRecent = i - h + 1;
for (int j = startFull; j <= i; j++)
{
double hv = high[j];
double lv = low[j];
if (!double.IsFinite(hv) || !double.IsFinite(lv))
{
hv = lastHigh;
lv = lastLow;
}
if (hv > maxFull)
{
maxFull = hv;
}
if (lv < minFull)
{
minFull = lv;
}
if (j >= startRecent)
{
if (hv > maxRecent)
{
maxRecent = hv;
}
if (lv < minRecent)
{
minRecent = lv;
}
}
else
{
if (hv > maxPrev)
{
maxPrev = hv;
}
if (lv < minPrev)
{
minPrev = lv;
}
}
}
double n1 = (maxRecent - minRecent) / h;
double n2 = (maxPrev - minPrev) / h;
double n3 = (maxFull - minFull) / pe;
double alpha = 1.0;
if (n1 > 0.0 && n2 > 0.0 && n3 > 0.0)
{
double dimen = (Math.Log(n1 + n2) - Math.Log(n3)) / 0.693147180559945309417232121458176568;
alpha = Math.Exp(-4.6 * (dimen - 1.0));
if (alpha < 0.01)
{
alpha = 0.01;
}
if (alpha > 1.0)
{
alpha = 1.0;
}
}
double price = (highVal + lowVal) * 0.5;
double prev = hasValue && double.IsFinite(fr) ? fr : price;
fr = Math.FusedMultiplyAdd(prev, 1.0 - alpha, alpha * price);
hasValue = true;
output[i] = fr;
}
}
private static TBarSeries BuildSeries(int count, int seed)
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: seed);
return gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
}
[Fact]
public void Frama_MatchesOoples_Structural()
{
var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.15, seed: 42);
var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var ooplesData = bars.Select(b => new TickerData
{
Date = new DateTime(b.Time, DateTimeKind.Utc),
Open = b.Open, High = b.High, Low = b.Low,
Close = b.Close, Volume = b.Volume
}).ToList();
var result = new StockData(ooplesData).CalculateEhlersFractalAdaptiveMovingAverage();
var values = result.CustomValuesList;
int finiteCount = values.Count(v => double.IsFinite(v));
Assert.True(finiteCount > 100, $"Expected >100 finite values, got {finiteCount}");
}
}