Files
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

690 lines
22 KiB
C#

using Xunit;
namespace QuanTAlib.Tests;
public class WeibulldistTests
{
private const double Tolerance = 1e-10;
// ─── A) Constructor validation ────────────────────────────────────────────
[Fact]
public void Constructor_DefaultParameters_SetsProperties()
{
var indicator = new Weibulldist();
Assert.Equal("Weibulldist(1.50,1.00,14)", indicator.Name);
Assert.Equal(14, indicator.WarmupPeriod);
Assert.False(indicator.IsHot);
}
[Fact]
public void Constructor_CustomParameters_SetsName()
{
var indicator = new Weibulldist(k: 2.0, lambda: 0.5, period: 20);
Assert.Equal("Weibulldist(2.00,0.50,20)", indicator.Name);
Assert.Equal(20, indicator.WarmupPeriod);
}
[Fact]
public void Constructor_ZeroK_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(k: 0.0));
Assert.Equal("k", ex.ParamName);
}
[Fact]
public void Constructor_NegativeK_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(k: -1.0));
Assert.Equal("k", ex.ParamName);
}
[Fact]
public void Constructor_ZeroLambda_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(lambda: 0.0));
Assert.Equal("lambda", ex.ParamName);
}
[Fact]
public void Constructor_NegativeLambda_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(lambda: -1.0));
Assert.Equal("lambda", ex.ParamName);
}
[Fact]
public void Constructor_PeriodOne_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(period: 1));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_PeriodZero_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(period: 0));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Constructor_NegativePeriod_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() => new Weibulldist(period: -1));
Assert.Equal("period", ex.ParamName);
}
// ─── B) Basic calculation ─────────────────────────────────────────────────
[Fact]
public void Update_ReturnsValidTValue()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
var input = new TValue(time, 100.0);
var result = indicator.Update(input);
Assert.Equal(input.Time, result.Time);
Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Update_OutputInRange()
{
var indicator = new Weibulldist(k: 1.5, lambda: 1.0, period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
Assert.True(indicator.Last.Value >= 0.0, "Output must be >= 0");
Assert.True(indicator.Last.Value <= 1.0, "Output must be <= 1");
}
[Fact]
public void Last_IsAccessible_AfterUpdate()
{
var indicator = new Weibulldist(period: 3);
var time = DateTime.UtcNow;
indicator.Update(new TValue(time, 50.0));
Assert.NotEqual(default, indicator.Last);
}
[Fact]
public void IsHot_Property_ReflectsWarmup()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
for (int i = 0; i < 4; i++)
{
indicator.Update(new TValue(time.AddMinutes(i), 100.0 + i));
Assert.False(indicator.IsHot);
}
indicator.Update(new TValue(time.AddMinutes(4), 104.0));
Assert.True(indicator.IsHot);
}
[Fact]
public void Update_AtMaxOfWindow_ReturnsNearOne()
{
// When current value equals window max, x=1.0 → high CDF value
var indicator = new Weibulldist(k: 2.0, lambda: 1.0, period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 101.0, 110.0 }; // 110 is max
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
// CDF(1.0, k=2, λ=1) = 1 - exp(-1) ≈ 0.6321
Assert.True(indicator.Last.Value > 0.5, $"Expected > 0.5 but got {indicator.Last.Value}");
}
[Fact]
public void Update_AtMinOfWindow_ReturnsZero()
{
// When current value equals window min, x=0.0 → CDF(0, k, λ) = 0
var indicator = new Weibulldist(k: 2.0, lambda: 1.0, period: 5);
var time = DateTime.UtcNow;
double[] prices = { 110.0, 102.0, 98.0, 101.0, 90.0 }; // 90 is min
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
Assert.Equal(0.0, indicator.Last.Value, Tolerance);
}
// ─── C) State + bar correction ────────────────────────────────────────────
[Fact]
public void Update_IsNewTrue_AdvancesState()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
double first = indicator.Last.Value;
indicator.Update(new TValue(time, 110.0));
double second = indicator.Last.Value;
Assert.NotEqual(first, second, Tolerance);
}
[Fact]
public void Update_IsNewFalse_RewritesLastBar()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
// New bar with value A
indicator.Update(new TValue(time, 110.0), true);
double valueA = indicator.Last.Value;
// Correct same bar with value B
indicator.Update(new TValue(time, 90.0), false);
double valueB = indicator.Last.Value;
Assert.NotEqual(valueA, valueB, Tolerance);
}
[Fact]
public void Update_IterativeCorrection_RestoresState()
{
var time = DateTime.UtcNow;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 72001);
var bars = gbm.Fetch(20, time.Ticks, TimeSpan.FromMinutes(1));
// Streaming without corrections
var straight = new Weibulldist(period: 5);
for (int i = 0; i < bars.Close.Count; i++)
{
straight.Update(bars.Close[i]);
}
double finalStraight = straight.Last.Value;
// With corrections (wrong → corrected)
var corrected = new Weibulldist(period: 5);
for (int i = 0; i < bars.Close.Count; i++)
{
corrected.Update(new TValue(bars.Close[i].Time, 999.0), true);
corrected.Update(bars.Close[i], false);
}
Assert.Equal(finalStraight, corrected.Last.Value, Tolerance);
}
[Fact]
public void Reset_ClearsState()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
Assert.True(indicator.IsHot);
indicator.Reset();
Assert.False(indicator.IsHot);
Assert.Equal(default, indicator.Last);
}
// ─── D) Warmup / convergence ──────────────────────────────────────────────
[Fact]
public void IsHot_FlipsAtPeriod()
{
int period = 10;
var indicator = new Weibulldist(period: period);
var time = DateTime.UtcNow;
for (int i = 0; i < period - 1; i++)
{
indicator.Update(new TValue(time.AddMinutes(i), 100.0 + i));
Assert.False(indicator.IsHot, $"Should not be hot at bar {i + 1}");
}
indicator.Update(new TValue(time.AddMinutes(period - 1), 100.0 + period));
Assert.True(indicator.IsHot, "Should be hot after period bars");
}
// ─── E) Robustness ────────────────────────────────────────────────────────
[Fact]
public void Update_NaN_UsesLastValidValue()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
double before = indicator.Last.Value;
indicator.Update(new TValue(time, double.NaN));
Assert.Equal(before, indicator.Last.Value, Tolerance);
}
[Fact]
public void Update_PositiveInfinity_UsesLastValidValue()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
double before = indicator.Last.Value;
indicator.Update(new TValue(time, double.PositiveInfinity));
Assert.Equal(before, indicator.Last.Value, Tolerance);
}
[Fact]
public void Update_NegativeInfinity_UsesLastValidValue()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
double before = indicator.Last.Value;
indicator.Update(new TValue(time, double.NegativeInfinity));
Assert.Equal(before, indicator.Last.Value, Tolerance);
}
[Fact]
public void Update_BatchNaN_Stable()
{
var indicator = new Weibulldist(period: 5);
var time = DateTime.UtcNow;
double[] prices = { 100.0, double.NaN, 102.0, double.NaN, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
var result = indicator.Update(new TValue(time, p));
Assert.True(double.IsFinite(result.Value), "Output must always be finite");
time = time.AddMinutes(1);
}
}
[Fact]
public void Update_FlatRange_ReturnsCdfAtHalf()
{
// When all values in window are identical, range=0 → x=0.5
var indicator = new Weibulldist(k: 2.0, lambda: 1.0, period: 5);
var time = DateTime.UtcNow;
for (int i = 0; i < 10; i++)
{
indicator.Update(new TValue(time.AddMinutes(i), 100.0));
}
// CDF(0.5/1.0, k=2, λ=1) = 1 - exp(-0.5^2) = 1 - exp(-0.25)
double expected = 1.0 - Math.Exp(-Math.Pow(0.5, 2.0));
Assert.Equal(expected, indicator.Last.Value, 1e-6);
}
// ─── F) Consistency: batch == streaming == span == eventing ──────────────
[Fact]
public void AllModes_ConsistencyCheck()
{
int count = 100;
int period = 20;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 72002);
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var source = bars.Close;
// Streaming
var streaming = new Weibulldist(period: period);
for (int i = 0; i < source.Count; i++)
{
streaming.Update(source[i]);
}
// Batch (TSeries)
var batch = Weibulldist.Batch(source, period: period);
// Span
var rawValues = new double[source.Count];
for (int i = 0; i < source.Count; i++)
{
rawValues[i] = source[i].Value;
}
var spanOutput = new double[source.Count];
Weibulldist.Batch(rawValues, spanOutput, period: period);
// Eventing
var eventResults = new List<double>();
var eventSource = new TSeries();
var eventIndicator = new Weibulldist(eventSource, period: period);
eventIndicator.Pub += (object? s, in TValueEventArgs e) => eventResults.Add(e.Value.Value);
for (int i = 0; i < source.Count; i++)
{
eventSource.Add(source[i], true);
}
double streamingLast = streaming.Last.Value;
double batchLast = batch[source.Count - 1].Value;
double spanLast = spanOutput[source.Count - 1];
double eventLast = eventResults[^1];
Assert.Equal(streamingLast, batchLast, Tolerance);
Assert.Equal(streamingLast, spanLast, Tolerance);
Assert.Equal(streamingLast, eventLast, Tolerance);
}
[Fact]
public void Streaming_VsBatch_AllValues_Match()
{
int count = 80;
int period = 15;
var gbm = new GBM(startPrice: 50, mu: 0.0, sigma: 0.3, seed: 72003);
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var source = bars.Close;
var streaming = new Weibulldist(period: period);
var streamingVals = new double[count];
for (int i = 0; i < count; i++)
{
streaming.Update(source[i]);
streamingVals[i] = streaming.Last.Value;
}
var batch = Weibulldist.Batch(source, period: period);
for (int i = 0; i < count; i++)
{
Assert.Equal(streamingVals[i], batch[i].Value, Tolerance);
}
}
// ─── G) Span API tests ────────────────────────────────────────────────────
[Fact]
public void Batch_Span_EmptySource_ThrowsArgumentException()
{
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch([], Array.Empty<double>()));
Assert.Equal("source", ex.ParamName);
}
[Fact]
public void Batch_Span_OutputTooShort_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[2];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst));
Assert.Equal("output", ex.ParamName);
}
[Fact]
public void Batch_Span_InvalidK_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[3];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst, k: 0.0));
Assert.Equal("k", ex.ParamName);
}
[Fact]
public void Batch_Span_NegativeK_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[3];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst, k: -0.5));
Assert.Equal("k", ex.ParamName);
}
[Fact]
public void Batch_Span_InvalidLambda_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[3];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst, lambda: 0.0));
Assert.Equal("lambda", ex.ParamName);
}
[Fact]
public void Batch_Span_NegativeLambda_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[3];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst, lambda: -1.0));
Assert.Equal("lambda", ex.ParamName);
}
[Fact]
public void Batch_Span_InvalidPeriod_ThrowsArgumentException()
{
double[] src = { 1.0, 2.0, 3.0 };
double[] dst = new double[3];
var ex = Assert.Throws<ArgumentException>(() =>
Weibulldist.Batch(src, dst, period: 1));
Assert.Equal("period", ex.ParamName);
}
[Fact]
public void Batch_Span_OutputInRange()
{
int count = 100;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 72004);
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
double[] src = new double[count];
for (int i = 0; i < count; i++)
{
src[i] = bars.Close[i].Value;
}
double[] dst = new double[count];
Weibulldist.Batch(src, dst, period: 20);
foreach (double v in dst)
{
Assert.True(v >= 0.0 && v <= 1.0, $"Output {v} out of [0,1] range");
}
}
[Fact]
public void Batch_Span_HandlesNaN()
{
double[] src = { 100.0, double.NaN, 102.0, 98.0, 105.0, 103.0 };
double[] dst = new double[src.Length];
Weibulldist.Batch(src, dst, period: 5);
foreach (double v in dst)
{
Assert.True(double.IsFinite(v), "Span output should always be finite");
}
}
[Fact]
public void Batch_Span_NoStackOverflow_LargeData()
{
int count = 5000;
double[] src = new double[count];
for (int i = 0; i < count; i++)
{
src[i] = 100.0 + Math.Sin(i * 0.1) * 10.0;
}
double[] dst = new double[count];
Weibulldist.Batch(src, dst, period: 300);
foreach (double v in dst)
{
Assert.True(double.IsFinite(v));
}
}
[Fact]
public void Batch_Span_MatchesStreaming()
{
int count = 60;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.25, seed: 72005);
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
double[] src = new double[count];
for (int i = 0; i < count; i++)
{
src[i] = bars.Close[i].Value;
}
double[] spanOut = new double[count];
Weibulldist.Batch(src, spanOut, period: 14);
var streaming = new Weibulldist(period: 14);
for (int i = 0; i < count; i++)
{
streaming.Update(bars.Close[i]);
Assert.Equal(streaming.Last.Value, spanOut[i], Tolerance);
}
}
// ─── H) Chainability ──────────────────────────────────────────────────────
[Fact]
public void Pub_EventFires()
{
var indicator = new Weibulldist(period: 3);
int count = 0;
indicator.Pub += (object? sender, in TValueEventArgs args) => count++;
var time = DateTime.UtcNow;
indicator.Update(new TValue(time, 100.0));
indicator.Update(new TValue(time.AddMinutes(1), 102.0));
indicator.Update(new TValue(time.AddMinutes(2), 98.0));
Assert.Equal(3, count);
}
[Fact]
public void Chaining_Constructor_Works()
{
int period = 5;
var source = new TSeries();
var indicator = new Weibulldist(source, period: period);
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
source.Add(new TValue(time, p), true);
time = time.AddMinutes(1);
}
Assert.True(indicator.IsHot);
Assert.True(indicator.Last.Value >= 0.0 && indicator.Last.Value <= 1.0);
}
[Fact]
public void Pub_EventValue_MatchesLast()
{
var indicator = new Weibulldist(period: 5);
TValue? lastEvent = null;
indicator.Pub += (object? s, in TValueEventArgs e) => lastEvent = e.Value;
var time = DateTime.UtcNow;
double[] prices = { 100.0, 102.0, 98.0, 105.0, 103.0 };
foreach (var p in prices)
{
indicator.Update(new TValue(time, p));
time = time.AddMinutes(1);
}
Assert.NotNull(lastEvent);
Assert.Equal(indicator.Last.Value, lastEvent.Value.Value, Tolerance);
}
// ─── Additional: Shape/scale parameter effects ───────────────────────────
[Fact]
public void DifferentShapes_ProduceDifferentResults()
{
// Verify at a non-boundary interior point (x=0.4, lambda=1.0) that different k values
// produce provably distinct CDF outputs — no GBM needed for this mathematical property
const double x = 0.4;
const double lambda = 1.0;
double cdf05 = Weibulldist.StaticCdf(x, k: 0.5, lambda: lambda); // concave, fast rise
double cdf15 = Weibulldist.StaticCdf(x, k: 1.5, lambda: lambda); // intermediate
double cdf50 = Weibulldist.StaticCdf(x, k: 5.0, lambda: lambda); // sigmoidal, slow rise
// All in [0,1]
Assert.InRange(cdf05, 0.0, 1.0);
Assert.InRange(cdf15, 0.0, 1.0);
Assert.InRange(cdf50, 0.0, 1.0);
// k=0.5 (concave) > k=1.5 > k=5.0 (sigmoidal) at x=0.4 < lambda: strict ordering
Assert.True(cdf05 > cdf15 + 1e-6, $"k=0.5 ({cdf05:G10}) should exceed k=1.5 ({cdf15:G10}) at x={x}");
Assert.True(cdf15 > cdf50 + 1e-6, $"k=1.5 ({cdf15:G10}) should exceed k=5.0 ({cdf50:G10}) at x={x}");
}
[Fact]
public void Calculate_StaticMethod_ReturnsTuple()
{
int count = 50;
var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 72007);
var bars = gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
var (results, instance) = Weibulldist.Calculate(bars.Close, period: 20);
Assert.Equal(count, results.Count);
Assert.True(instance.IsHot);
Assert.Equal(results[^1].Value, instance.Last.Value, Tolerance);
}
}