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Refactor and expand unit tests for TBarSeries, TSeries, and TValue classes

Browse Source 
- Enhanced TBarSeriesTests with additional constructors, methods, and assertions for better coverage.
- Improved TSeriesTests to include new constructors, methods, and edge cases.
- Expanded TValueTests to cover constructors, implicit conversions, equality checks, and hash codes.
- Updated project file to target .NET 10.0 and include internal visibility for tests.
- Added Codacy configuration for code quality checks.
This commit is contained in:
Miha Kralj
2025-11-29 16:08:45 -08:00
parent 6cdebb984d
commit 8d8e60098e
12 changed files with 2514 additions and 813 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.codacy/codacy.yaml
+15
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@@ -0,0 +1,15 @@
runtimes:
- dart@3.7.2
- go@1.22.3
- java@17.0.10
- node@22.2.0
- python@3.11.11
tools:
- dartanalyzer@3.7.2
- eslint@8.57.0
- lizard@1.17.31
- pmd@7.11.0
- pylint@3.3.6
- revive@1.7.0
- semgrep@1.78.0
- trivy@0.66.0
.gitignore
+4
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@@ -405,3 +405,7 @@ memory-bank/
.DS_Store
.AppleDouble
.LSOverride
#Ignore insiders AI rules
.github/instructions/codacy.instructions.md
lib/averages/ema/Ema.Validation.Tests.cs
+1 -1
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@@ -86,7 +86,7 @@ public class EmaValidationTests : IDisposable
var qResult = ema.Update(_data);
// Calculate TA-Lib EMA
var retCode = TALib.Functions.Ema(tData, 0..^0, output, out var outRange, period);
var retCode = TALib.Functions.Ema<double>(tData, 0..^0, output, out var outRange, period);
// Check success
Assert.Equal(Core.RetCode.Success, retCode);
lib/averages/ema/Ema.cs
-1
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@@ -1,4 +1,3 @@
using System;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
lib/averages/ema/EmaVector.Tests.cs
+382 -280
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@@ -1,280 +1,382 @@
using System;
using System.Linq;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class EmaVectorTests
{
[Fact]
public void Initialization_WithPeriods_SetsCorrectAlphas()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
// We can't check private fields directly, but we can check results after 1 step
// Alpha = 2 / (P + 1)
// P=10 -> A=2/11
// P=20 -> A=2/21
var res = emaVector.Update(new TValue(DateTime.Now, 100.0));
// First value should be 100.0 due to compensation
Assert.Equal(100.0, res[0].Value, 1e-9);
Assert.Equal(100.0, res[1].Value, 1e-9);
}
[Fact]
public void Calc_Streaming_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
var values = new double[] { 10, 20, 30, 40, 50, 40, 30, 20, 10 };
var time = DateTime.Now;
foreach (var val in values)
{
var tVal = new TValue(time, val);
var multiRes = emaVector.Update(tVal);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(tVal);
Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
Assert.Equal(singleRes.Time, multiRes[i].Time);
}
time = time.AddMinutes(1);
}
}
[Fact]
public void Calc_Series_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
int len = 100;
var t = new System.Collections.Generic.List<long>(len);
var v = new System.Collections.Generic.List<double>(len);
var now = DateTime.Now;
for (int i = 0; i < len; i++)
{
t.Add(now.AddMinutes(i).Ticks);
v.Add(Math.Sin(i * 0.1) * 100);
}
var series = new TSeries(t, v);
var multiRes = emaVector.Calculate(series);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(series);
Assert.Equal(singleRes.Count, multiRes[i].Count);
for (int j = 0; j < len; j++)
{
Assert.Equal(singleRes.Values[j], multiRes[i].Values[j], 1e-8);
}
}
}
[Fact]
public void Calc_Series_MatchesStreaming()
{
int[] periods = { 5, 10, 20 };
var emaVectorBatch = new EmaVector(periods);
var emaVectorStream = new EmaVector(periods);
int len = 100;
var t = new System.Collections.Generic.List<long>(len);
var v = new System.Collections.Generic.List<double>(len);
var now = DateTime.Now;
for (int i = 0; i < len; i++)
{
t.Add(now.AddMinutes(i).Ticks);
v.Add(Math.Sin(i * 0.1) * 100);
}
var series = new TSeries(t, v);
// Batch calculation
var batchRes = emaVectorBatch.Calculate(series);
// Streaming calculation
for (int i = 0; i < len; i++)
{
var tVal = new TValue(new DateTime(t[i]), v[i]);
var streamRes = emaVectorStream.Update(tVal);
for (int j = 0; j < periods.Length; j++)
{
Assert.Equal(batchRes[j].Values[i], streamRes[j].Value, 1e-9);
}
}
}
[Fact]
public void Reset_ClearsState()
{
int[] periods = { 10 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Reset();
// After reset, next calculation should treat it as first value (warmup)
var res = emaVector.Update(new TValue(DateTime.Now, 200.0));
Assert.Equal(200.0, res[0].Value, 1e-9);
}
[Fact]
public void Update_NaN_Input_UsesLastValidValue()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
// Feed some valid values
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
// Feed NaN - should use last valid value (110)
var resultAfterNaN = emaVector.Update(new TValue(DateTime.Now, double.NaN));
// All results should be finite (not NaN)
foreach (var result in resultAfterNaN)
{
Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
}
}
[Fact]
public void Update_Infinity_Input_UsesLastValidValue()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
// Feed some valid values
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
// Feed positive infinity - should use last valid value
var resultAfterPosInf = emaVector.Update(new TValue(DateTime.Now, double.PositiveInfinity));
foreach (var result in resultAfterPosInf)
{
Assert.True(double.IsFinite(result.Value));
}
// Feed negative infinity - should use last valid value
var resultAfterNegInf = emaVector.Update(new TValue(DateTime.Now, double.NegativeInfinity));
foreach (var result in resultAfterNegInf)
{
Assert.True(double.IsFinite(result.Value));
}
}
[Fact]
public void Update_MultipleNaN_ContinuesWithLastValid()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
// Feed valid values
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
emaVector.Update(new TValue(DateTime.Now, 120.0));
// Feed multiple NaN values
var r1 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
var r2 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
var r3 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
// All results should be finite
foreach (var result in r1) Assert.True(double.IsFinite(result.Value));
foreach (var result in r2) Assert.True(double.IsFinite(result.Value));
foreach (var result in r3) Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Calculate_Series_HandlesNaN()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
// Create series with NaN values interspersed
var t = new System.Collections.Generic.List<long>();
var v = new System.Collections.Generic.List<double>();
var now = DateTime.Now;
t.Add(now.Ticks); v.Add(100.0);
t.Add(now.AddMinutes(1).Ticks); v.Add(110.0);
t.Add(now.AddMinutes(2).Ticks); v.Add(double.NaN);
t.Add(now.AddMinutes(3).Ticks); v.Add(120.0);
t.Add(now.AddMinutes(4).Ticks); v.Add(double.PositiveInfinity);
t.Add(now.AddMinutes(5).Ticks); v.Add(130.0);
var series = new TSeries(t, v);
var results = emaVector.Calculate(series);
// All results should be finite for all periods
foreach (var periodResults in results)
{
foreach (var val in periodResults.Values)
{
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
}
}
}
[Fact]
public void Reset_ClearsLastValidValue()
{
int[] periods = { 10 };
var emaVector = new EmaVector(periods);
// Feed values including NaN
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, double.NaN));
// Reset
emaVector.Reset();
// After reset, first valid value should establish new baseline
var result = emaVector.Update(new TValue(DateTime.Now, 50.0));
Assert.Equal(50.0, result[0].Value, 1e-9);
}
[Fact]
public void NaN_Handling_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
// Data with NaN values
var values = new double[] { 10, 20, double.NaN, 40, double.PositiveInfinity, 60, 70 };
var time = DateTime.Now;
foreach (var val in values)
{
var tVal = new TValue(time, val);
var multiRes = emaVector.Update(tVal);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(tVal);
Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
}
time = time.AddMinutes(1);
}
}
}
using System;
using System.Linq;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class EmaVectorTests
{
[Fact]
public void Initialization_WithPeriods_SetsCorrectAlphas()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
var res = emaVector.Update(new TValue(DateTime.Now, 100.0));
Assert.Equal(100.0, res[0].Value, 1e-9);
Assert.Equal(100.0, res[1].Value, 1e-9);
}
[Fact]
public void Initialization_WithAlphas_Works()
{
double[] alphas = { 0.1, 0.2, 0.5 };
var emaVector = new EmaVector(alphas);
var res = emaVector.Update(new TValue(DateTime.Now, 100.0));
Assert.Equal(3, res.Length);
Assert.Equal(100.0, res[0].Value, 1e-9);
Assert.Equal(100.0, res[1].Value, 1e-9);
Assert.Equal(100.0, res[2].Value, 1e-9);
}
[Fact]
public void Initialization_WithZeroPeriod_ThrowsArgumentException()
{
int[] periods = { 10, 0, 20 };
Assert.Throws<ArgumentException>(() => new EmaVector(periods));
}
[Fact]
public void Initialization_WithNegativePeriod_ThrowsArgumentException()
{
int[] periods = { 10, -5, 20 };
Assert.Throws<ArgumentException>(() => new EmaVector(periods));
}
[Fact]
public void Initialization_WithZeroAlpha_ThrowsArgumentException()
{
double[] alphas = { 0.1, 0.0, 0.5 };
Assert.Throws<ArgumentException>(() => new EmaVector(alphas));
}
[Fact]
public void Initialization_WithNegativeAlpha_ThrowsArgumentException()
{
double[] alphas = { 0.1, -0.1, 0.5 };
Assert.Throws<ArgumentException>(() => new EmaVector(alphas));
}
[Fact]
public void Initialization_WithAlphaGreaterThanOne_ThrowsArgumentException()
{
double[] alphas = { 0.1, 1.5, 0.5 };
Assert.Throws<ArgumentException>(() => new EmaVector(alphas));
}
[Fact]
public void Initialization_WithAlphaEqualToOne_Works()
{
double[] alphas = { 0.1, 1.0, 0.5 };
var emaVector = new EmaVector(alphas);
var res = emaVector.Update(new TValue(DateTime.Now, 100.0));
Assert.Equal(3, res.Length);
}
[Fact]
public void Calc_Streaming_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
var values = new double[] { 10, 20, 30, 40, 50, 40, 30, 20, 10 };
var time = DateTime.Now;
foreach (var val in values)
{
var tVal = new TValue(time, val);
var multiRes = emaVector.Update(tVal);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(tVal);
Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
Assert.Equal(singleRes.Time, multiRes[i].Time);
}
time = time.AddMinutes(1);
}
}
[Fact]
public void Calc_Series_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
int len = 100;
var t = new System.Collections.Generic.List<long>(len);
var v = new System.Collections.Generic.List<double>(len);
var now = DateTime.Now;
for (int i = 0; i < len; i++)
{
t.Add(now.AddMinutes(i).Ticks);
v.Add(Math.Sin(i * 0.1) * 100);
}
var series = new TSeries(t, v);
var multiRes = emaVector.Calculate(series);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(series);
Assert.Equal(singleRes.Count, multiRes[i].Count);
for (int j = 0; j < len; j++)
{
Assert.Equal(singleRes.Values[j], multiRes[i].Values[j], 1e-8);
}
}
}
[Fact]
public void Calc_Series_MatchesStreaming()
{
int[] periods = { 5, 10, 20 };
var emaVectorBatch = new EmaVector(periods);
var emaVectorStream = new EmaVector(periods);
int len = 100;
var t = new System.Collections.Generic.List<long>(len);
var v = new System.Collections.Generic.List<double>(len);
var now = DateTime.Now;
for (int i = 0; i < len; i++)
{
t.Add(now.AddMinutes(i).Ticks);
v.Add(Math.Sin(i * 0.1) * 100);
}
var series = new TSeries(t, v);
var batchRes = emaVectorBatch.Calculate(series);
for (int i = 0; i < len; i++)
{
var tVal = new TValue(new DateTime(t[i]), v[i]);
var streamRes = emaVectorStream.Update(tVal);
for (int j = 0; j < periods.Length; j++)
{
Assert.Equal(batchRes[j].Values[i], streamRes[j].Value, 1e-9);
}
}
}
[Fact]
public void Calculate_Static_MatchesInstanceMethod()
{
int[] periods = { 5, 10, 20 };
int len = 50;
var t = new System.Collections.Generic.List<long>(len);
var v = new System.Collections.Generic.List<double>(len);
var now = DateTime.Now;
for (int i = 0; i < len; i++)
{
t.Add(now.AddMinutes(i).Ticks);
v.Add(Math.Sin(i * 0.1) * 100);
}
var series = new TSeries(t, v);
var instanceEma = new EmaVector(periods);
var instanceRes = instanceEma.Calculate(series);
var staticRes = EmaVector.Calculate(series, periods);
for (int i = 0; i < periods.Length; i++)
{
Assert.Equal(instanceRes[i].Count, staticRes[i].Count);
for (int j = 0; j < len; j++)
{
Assert.Equal(instanceRes[i].Values[j], staticRes[i].Values[j], 1e-9);
}
}
}
[Fact]
public void Reset_ClearsState()
{
int[] periods = { 10 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Reset();
var res = emaVector.Update(new TValue(DateTime.Now, 200.0));
Assert.Equal(200.0, res[0].Value, 1e-9);
}
[Fact]
public void Update_NaN_Input_UsesLastValidValue()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
var resultAfterNaN = emaVector.Update(new TValue(DateTime.Now, double.NaN));
foreach (var result in resultAfterNaN)
{
Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
}
}
[Fact]
public void Update_Infinity_Input_UsesLastValidValue()
{
int[] periods = { 10, 20 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
var resultAfterPosInf = emaVector.Update(new TValue(DateTime.Now, double.PositiveInfinity));
foreach (var result in resultAfterPosInf)
{
Assert.True(double.IsFinite(result.Value));
}
var resultAfterNegInf = emaVector.Update(new TValue(DateTime.Now, double.NegativeInfinity));
foreach (var result in resultAfterNegInf)
{
Assert.True(double.IsFinite(result.Value));
}
}
[Fact]
public void Update_MultipleNaN_ContinuesWithLastValid()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, 110.0));
emaVector.Update(new TValue(DateTime.Now, 120.0));
var r1 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
var r2 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
var r3 = emaVector.Update(new TValue(DateTime.Now, double.NaN));
foreach (var result in r1) Assert.True(double.IsFinite(result.Value));
foreach (var result in r2) Assert.True(double.IsFinite(result.Value));
foreach (var result in r3) Assert.True(double.IsFinite(result.Value));
}
[Fact]
public void Calculate_Series_HandlesNaN()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
var t = new System.Collections.Generic.List<long>();
var v = new System.Collections.Generic.List<double>();
var now = DateTime.Now;
t.Add(now.Ticks); v.Add(100.0);
t.Add(now.AddMinutes(1).Ticks); v.Add(110.0);
t.Add(now.AddMinutes(2).Ticks); v.Add(double.NaN);
t.Add(now.AddMinutes(3).Ticks); v.Add(120.0);
t.Add(now.AddMinutes(4).Ticks); v.Add(double.PositiveInfinity);
t.Add(now.AddMinutes(5).Ticks); v.Add(130.0);
var series = new TSeries(t, v);
var results = emaVector.Calculate(series);
foreach (var periodResults in results)
{
foreach (var val in periodResults.Values)
{
Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
}
}
}
[Fact]
public void Reset_ClearsLastValidValue()
{
int[] periods = { 10 };
var emaVector = new EmaVector(periods);
emaVector.Update(new TValue(DateTime.Now, 100.0));
emaVector.Update(new TValue(DateTime.Now, double.NaN));
emaVector.Reset();
var result = emaVector.Update(new TValue(DateTime.Now, 50.0));
Assert.Equal(50.0, result[0].Value, 1e-9);
}
[Fact]
public void NaN_Handling_MatchesSingleEma()
{
int[] periods = { 5, 10, 20 };
var emaVector = new EmaVector(periods);
var emaSingles = periods.Select(p => new Ema(p)).ToArray();
var values = new double[] { 10, 20, double.NaN, 40, double.PositiveInfinity, 60, 70 };
var time = DateTime.Now;
foreach (var val in values)
{
var tVal = new TValue(time, val);
var multiRes = emaVector.Update(tVal);
for (int i = 0; i < periods.Length; i++)
{
var singleRes = emaSingles[i].Update(tVal);
Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
}
time = time.AddMinutes(1);
}
}
[Fact]
public void Values_Property_UpdatesAfterUpdate()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
var result = emaVector.Update(new TValue(DateTime.Now, 100.0));
Assert.Equal(result[0].Value, emaVector.Values[0].Value);
Assert.Equal(result[1].Value, emaVector.Values[1].Value);
}
[Fact]
public void Values_Property_UpdatesAfterCalculate()
{
int[] periods = { 5, 10 };
var emaVector = new EmaVector(periods);
var t = new System.Collections.Generic.List<long> { 100, 200, 300 };
var v = new System.Collections.Generic.List<double> { 10.0, 20.0, 30.0 };
var series = new TSeries(t, v);
var results = emaVector.Calculate(series);
Assert.Equal(results[0].Last.Value, emaVector.Values[0].Value, 1e-9);
Assert.Equal(results[1].Last.Value, emaVector.Values[1].Value, 1e-9);
}
}
lib/core/simd/SimdExtensions.Tests.cs
+730 -249
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@@ -1,249 +1,730 @@
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class SimdExtensionsTests
{
[Fact]
public void SumSIMD_EmptySpan_ReturnsZero()
{
var span = ReadOnlySpan<double>.Empty;
Assert.Equal(0.0, span.SumSIMD());
}
[Fact]
public void SumSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.SumSIMD());
}
[Fact]
public void SumSIMD_MultipleElements_ReturnsCorrectSum()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(55.0, span.SumSIMD(), precision: 10);
}
[Fact]
public void SumSIMD_LargeArray_ReturnsCorrectSum()
{
double[] data = new double[1000];
for (int i = 0; i < data.Length; i++)
data[i] = i + 1.0;
var span = new ReadOnlySpan<double>(data);
double expected = 1000.0 * 1001.0 / 2.0; // Sum of 1..1000
Assert.Equal(expected, span.SumSIMD(), precision: 8);
}
[Fact]
public void MinSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MinSIMD()));
}
[Fact]
public void MinSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MinSIMD());
}
[Fact]
public void MinSIMD_MultipleElements_ReturnsMinimum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(1.0, span.MinSIMD());
}
[Fact]
public void MaxSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MaxSIMD()));
}
[Fact]
public void MaxSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_MultipleElements_ReturnsMaximum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(9.0, span.MaxSIMD());
}
[Fact]
public void AverageSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.AverageSIMD()));
}
[Fact]
public void AverageSIMD_MultipleElements_ReturnsCorrectAverage()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(3.0, span.AverageSIMD(), precision: 10);
}
[Fact]
public void VarianceSIMD_LessThanTwoElements_ReturnsNaN()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD()));
}
[Fact]
public void VarianceSIMD_MultipleElements_ReturnsCorrectVariance()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
// Expected variance: 4.571428... (sample variance)
double variance = span.VarianceSIMD();
Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
}
[Fact]
public void StdDevSIMD_MultipleElements_ReturnsCorrectStdDev()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
// Expected std dev: sqrt(4.571428) ≈ 2.138
double stdDev = span.StdDevSIMD();
Assert.True(Math.Abs(stdDev - 2.138) < 0.01);
}
[Fact]
public void MinMaxSIMD_EmptySpan_ReturnsBothNaN()
{
var span = ReadOnlySpan<double>.Empty;
var (min, max) = span.MinMaxSIMD();
Assert.True(double.IsNaN(min));
Assert.True(double.IsNaN(max));
}
[Fact]
public void MinMaxSIMD_SingleElement_ReturnsSameValue()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(42.5, min);
Assert.Equal(42.5, max);
}
[Fact]
public void MinMaxSIMD_MultipleElements_ReturnsCorrectMinMax()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(1.0, min);
Assert.Equal(9.0, max);
}
[Fact]
public void SIMD_WorksWithTSeriesValues()
{
var series = new TSeries(100);
for (int i = 0; i < 100; i++)
{
series.Add(DateTime.UtcNow.Ticks + i, i + 1.0);
}
var values = series.Values;
double sum = values.SumSIMD();
double avg = values.AverageSIMD();
double min = values.MinSIMD();
double max = values.MaxSIMD();
var (minAlt, maxAlt) = values.MinMaxSIMD();
Assert.Equal(5050.0, sum, precision: 8); // Sum of 1..100
Assert.Equal(50.5, avg, precision: 8);
Assert.Equal(1.0, min);
Assert.Equal(100.0, max);
Assert.Equal(min, minAlt);
Assert.Equal(max, maxAlt);
}
[Fact]
public void SIMD_WorksWithTBarSeriesClose()
{
var gbm = new GBM(startPrice: 100.0);
long startTime = DateTime.UtcNow.Ticks;
var interval = TimeSpan.FromMinutes(1);
var bars = gbm.Fetch(1000, startTime, interval);
var closeValues = bars.Close.Values;
double sum = closeValues.SumSIMD();
double avg = closeValues.AverageSIMD();
double min = closeValues.MinSIMD();
double max = closeValues.MaxSIMD();
Assert.True(sum > 0);
Assert.True(avg > 0);
Assert.True(min > 0);
Assert.True(max > min);
}
[Fact]
public void SIMD_PerformanceTest_LargeDataset()
{
// Generate large dataset
var gbm = new GBM(startPrice: 100.0);
long startTime = DateTime.UtcNow.Ticks;
var interval = TimeSpan.FromMinutes(1);
var bars = gbm.Fetch(10000, startTime, interval);
var closeValues = bars.Close.Values;
// Warm up
_ = closeValues.SumSIMD();
// Test SIMD operations
var sw = System.Diagnostics.Stopwatch.StartNew();
double sum = closeValues.SumSIMD();
double avg = closeValues.AverageSIMD();
double min = closeValues.MinSIMD();
double max = closeValues.MaxSIMD();
var (minAlt, maxAlt) = closeValues.MinMaxSIMD();
double variance = closeValues.VarianceSIMD();
double stdDev = closeValues.StdDevSIMD();
sw.Stop();
// Verify results are valid
Assert.True(sum > 0);
Assert.True(avg > 0);
Assert.True(min > 0);
Assert.True(max > min);
Assert.True(variance > 0);
Assert.True(stdDev > 0);
// Performance should be sub-millisecond for 10k elements
Assert.True(sw.ElapsedMilliseconds < 10,
$"SIMD operations took {sw.ElapsedMilliseconds}ms, expected < 10ms");
}
}
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests;
public class SimdExtensionsTests
{
// ContainsNonFinite tests
[Fact]
public void ContainsNonFinite_EmptySpan_ReturnsFalse()
{
var span = ReadOnlySpan<double>.Empty;
Assert.False(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_AllFinite_ReturnsFalse()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0];
var span = new ReadOnlySpan<double>(data);
Assert.False(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_ContainsNaN_ReturnsTrue()
{
double[] data = [1.0, 2.0, double.NaN, 4.0, 5.0, 6.0, 7.0, 8.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_ContainsPositiveInfinity_ReturnsTrue()
{
double[] data = [1.0, 2.0, 3.0, double.PositiveInfinity, 5.0, 6.0, 7.0, 8.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_ContainsNegativeInfinity_ReturnsTrue()
{
double[] data = [1.0, 2.0, 3.0, 4.0, double.NegativeInfinity, 6.0, 7.0, 8.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_NonFiniteInRemainder_ReturnsTrue()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, double.NaN];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_SingleNaN_ReturnsTrue()
{
double[] data = [double.NaN];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_TwoElements_AllFinite_ReturnsFalse()
{
double[] data = [1.0, 2.0];
var span = new ReadOnlySpan<double>(data);
Assert.False(span.ContainsNonFinite());
}
[Fact]
public void ContainsNonFinite_TwoElements_OneNaN_ReturnsTrue()
{
double[] data = [1.0, double.NaN];
var span = new ReadOnlySpan<double>(data);
Assert.True(span.ContainsNonFinite());
}
// SumSIMD tests
[Fact]
public void SumSIMD_EmptySpan_ReturnsZero()
{
var span = ReadOnlySpan<double>.Empty;
Assert.Equal(0.0, span.SumSIMD());
}
[Fact]
public void SumSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.SumSIMD());
}
[Fact]
public void SumSIMD_TwoElements_ReturnsSum()
{
double[] data = [1.5, 2.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(4.0, span.SumSIMD());
}
[Fact]
public void SumSIMD_MultipleElements_ReturnsCorrectSum()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(55.0, span.SumSIMD(), precision: 10);
}
[Fact]
public void SumSIMD_LargeArray_ReturnsCorrectSum()
{
double[] data = new double[1000];
for (int i = 0; i < data.Length; i++)
data[i] = i + 1.0;
var span = new ReadOnlySpan<double>(data);
double expected = 1000.0 * 1001.0 / 2.0;
Assert.Equal(expected, span.SumSIMD(), precision: 8);
}
[Fact]
public void SumSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [1.0, 2.0, double.NaN, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.SumSIMD()));
}
[Fact]
public void SumSIMD_ContainsInfinity_ReturnsNaN()
{
double[] data = [1.0, 2.0, double.PositiveInfinity, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.SumSIMD()));
}
[Fact]
public void SumSIMD_NegativeValues_ReturnsCorrectSum()
{
double[] data = [-1.0, -2.0, -3.0, -4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(-10.0, span.SumSIMD());
}
// MinSIMD tests
[Fact]
public void MinSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MinSIMD()));
}
[Fact]
public void MinSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MinSIMD());
}
[Fact]
public void MinSIMD_TwoElements_ReturnsMinimum()
{
double[] data = [5.0, 2.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(2.0, span.MinSIMD());
}
[Fact]
public void MinSIMD_MultipleElements_ReturnsMinimum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(1.0, span.MinSIMD());
}
[Fact]
public void MinSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.MinSIMD()));
}
[Fact]
public void MinSIMD_MinInRemainder_ReturnsCorrectMin()
{
double[] data = [5.0, 2.0, 8.0, 6.0, 9.0, 3.0, 7.0, 4.0, 0.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(0.5, span.MinSIMD());
}
[Fact]
public void MinSIMD_NegativeValues_ReturnsMinimum()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(-8.0, span.MinSIMD());
}
// MaxSIMD tests
[Fact]
public void MaxSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.MaxSIMD()));
}
[Fact]
public void MaxSIMD_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_TwoElements_ReturnsMaximum()
{
double[] data = [5.0, 9.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(9.0, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_MultipleElements_ReturnsMaximum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(9.0, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.MaxSIMD()));
}
[Fact]
public void MaxSIMD_MaxInRemainder_ReturnsCorrectMax()
{
double[] data = [5.0, 2.0, 8.0, 6.0, 4.0, 3.0, 7.0, 1.0, 99.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(99.0, span.MaxSIMD());
}
[Fact]
public void MaxSIMD_NegativeValues_ReturnsMaximum()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(-1.0, span.MaxSIMD());
}
// AverageSIMD tests
[Fact]
public void AverageSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.AverageSIMD()));
}
[Fact]
public void AverageSIMD_TwoElements_ReturnsAverage()
{
double[] data = [2.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(3.0, span.AverageSIMD());
}
[Fact]
public void AverageSIMD_MultipleElements_ReturnsCorrectAverage()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(3.0, span.AverageSIMD(), precision: 10);
}
[Fact]
public void AverageSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [1.0, double.NaN, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.AverageSIMD()));
}
// VarianceSIMD tests
[Fact]
public void VarianceSIMD_LessThanTwoElements_ReturnsNaN()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD()));
}
[Fact]
public void VarianceSIMD_EmptySpan_ReturnsNaN()
{
var span = ReadOnlySpan<double>.Empty;
Assert.True(double.IsNaN(span.VarianceSIMD()));
}
[Fact]
public void VarianceSIMD_TwoElements_ReturnsCorrect()
{
double[] data = [1.0, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(2.0, span.VarianceSIMD(), precision: 10);
}
[Fact]
public void VarianceSIMD_ThreeElements_ReturnsCorrect()
{
double[] data = [1.0, 2.0, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(1.0, span.VarianceSIMD(), precision: 10);
}
[Fact]
public void VarianceSIMD_MultipleElements_ReturnsCorrectVariance()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
double variance = span.VarianceSIMD();
Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
}
[Fact]
public void VarianceSIMD_WithProvidedMean_UsesProvidedMean()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
double mean = 5.0;
double variance = span.VarianceSIMD(mean);
Assert.True(variance > 0);
}
[Fact]
public void VarianceSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [2.0, double.NaN, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD()));
}
[Fact]
public void VarianceSIMD_WithNaNMean_ReturnsNaN()
{
double[] data = [2.0, 4.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD(double.NaN)));
}
[Fact]
public void VarianceSIMD_WithInfinityMean_ReturnsNaN()
{
double[] data = [2.0, 4.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.VarianceSIMD(double.PositiveInfinity)));
}
// StdDevSIMD tests
[Fact]
public void StdDevSIMD_TwoElements_ReturnsCorrect()
{
double[] data = [1.0, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(Math.Abs(span.StdDevSIMD() - 1.414) < 0.01);
}
[Fact]
public void StdDevSIMD_MultipleElements_ReturnsCorrectStdDev()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
double stdDev = span.StdDevSIMD();
Assert.True(Math.Abs(stdDev - 2.138) < 0.01);
}
[Fact]
public void StdDevSIMD_WithProvidedMean_Works()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
double stdDev = span.StdDevSIMD(5.0);
Assert.True(stdDev > 0);
}
[Fact]
public void StdDevSIMD_ContainsNaN_ReturnsNaN()
{
double[] data = [2.0, double.NaN, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(double.IsNaN(span.StdDevSIMD()));
}
// MinMaxSIMD tests
[Fact]
public void MinMaxSIMD_EmptySpan_ReturnsBothNaN()
{
var span = ReadOnlySpan<double>.Empty;
var (min, max) = span.MinMaxSIMD();
Assert.True(double.IsNaN(min));
Assert.True(double.IsNaN(max));
}
[Fact]
public void MinMaxSIMD_SingleElement_ReturnsSameValue()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(42.5, min);
Assert.Equal(42.5, max);
}
[Fact]
public void MinMaxSIMD_TwoElements_ReturnsCorrect()
{
double[] data = [5.0, 2.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(2.0, min);
Assert.Equal(5.0, max);
}
[Fact]
public void MinMaxSIMD_MultipleElements_ReturnsCorrectMinMax()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(1.0, min);
Assert.Equal(9.0, max);
}
[Fact]
public void MinMaxSIMD_ContainsNaN_ReturnsBothNaN()
{
double[] data = [5.0, 2.0, double.NaN, 1.0, 9.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.True(double.IsNaN(min));
Assert.True(double.IsNaN(max));
}
[Fact]
public void MinMaxSIMD_MinMaxInRemainder_ReturnsCorrect()
{
double[] data = [5.0, 2.0, 8.0, 6.0, 4.0, 3.0, 7.0, 5.0, 0.1, 99.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(0.1, min);
Assert.Equal(99.0, max);
}
[Fact]
public void MinMaxSIMD_NegativeValues_ReturnsCorrect()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = span.MinMaxSIMD();
Assert.Equal(-8.0, min);
Assert.Equal(-1.0, max);
}
// Integration tests
[Fact]
public void SIMD_WorksWithTSeriesValues()
{
var series = new TSeries(100);
for (int i = 0; i < 100; i++)
{
series.Add(DateTime.UtcNow.Ticks + i, i + 1.0);
}
var values = series.Values;
double sum = values.SumSIMD();
double avg = values.AverageSIMD();
double min = values.MinSIMD();
double max = values.MaxSIMD();
var (minAlt, maxAlt) = values.MinMaxSIMD();
Assert.Equal(5050.0, sum, precision: 8);
Assert.Equal(50.5, avg, precision: 8);
Assert.Equal(1.0, min);
Assert.Equal(100.0, max);
Assert.Equal(min, minAlt);
Assert.Equal(max, maxAlt);
}
[Fact]
public void SIMD_WorksWithTBarSeriesClose()
{
var gbm = new GBM(startPrice: 100.0);
long startTime = DateTime.UtcNow.Ticks;
var interval = TimeSpan.FromMinutes(1);
var bars = gbm.Fetch(1000, startTime, interval);
var closeValues = bars.Close.Values;
double sum = closeValues.SumSIMD();
double avg = closeValues.AverageSIMD();
double min = closeValues.MinSIMD();
double max = closeValues.MaxSIMD();
Assert.True(sum > 0);
Assert.True(avg > 0);
Assert.True(min > 0);
Assert.True(max > min);
}
[Fact]
public void SIMD_PerformanceTest_LargeDataset()
{
var gbm = new GBM(startPrice: 100.0);
long startTime = DateTime.UtcNow.Ticks;
var interval = TimeSpan.FromMinutes(1);
var bars = gbm.Fetch(10000, startTime, interval);
var closeValues = bars.Close.Values;
_ = closeValues.SumSIMD();
var sw = System.Diagnostics.Stopwatch.StartNew();
double sum = closeValues.SumSIMD();
double avg = closeValues.AverageSIMD();
double min = closeValues.MinSIMD();
double max = closeValues.MaxSIMD();
var (minAlt, maxAlt) = closeValues.MinMaxSIMD();
double variance = closeValues.VarianceSIMD();
double stdDev = closeValues.StdDevSIMD();
sw.Stop();
Assert.True(sum > 0);
Assert.True(avg > 0);
Assert.True(min > 0);
Assert.True(max > min);
Assert.True(variance > 0);
Assert.True(stdDev > 0);
Assert.True(sw.ElapsedMilliseconds < 10,
$"SIMD operations took {sw.ElapsedMilliseconds}ms, expected < 10ms");
}
[Fact]
public void SIMD_ScalarFallback_SmallArray()
{
double[] data = [1.0, 2.0, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(6.0, span.SumSIMD());
Assert.Equal(1.0, span.MinSIMD());
Assert.Equal(3.0, span.MaxSIMD());
Assert.Equal(2.0, span.AverageSIMD());
var (min, max) = span.MinMaxSIMD();
Assert.Equal(1.0, min);
Assert.Equal(3.0, max);
}
}
// Tests for internal scalar implementations
public class SimdScalarFallbackTests
{
[Fact]
public void ContainsNonFiniteScalar_AllFinite_ReturnsFalse()
{
double[] data = [1.0, 2.0, 3.0, 4.0];
var span = new ReadOnlySpan<double>(data);
Assert.False(SimdExtensions.ContainsNonFiniteScalar(span));
}
[Fact]
public void ContainsNonFiniteScalar_ContainsNaN_ReturnsTrue()
{
double[] data = [1.0, double.NaN, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(SimdExtensions.ContainsNonFiniteScalar(span));
}
[Fact]
public void ContainsNonFiniteScalar_ContainsInfinity_ReturnsTrue()
{
double[] data = [1.0, double.PositiveInfinity, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.True(SimdExtensions.ContainsNonFiniteScalar(span));
}
[Fact]
public void ContainsNonFiniteScalar_Empty_ReturnsFalse()
{
var span = ReadOnlySpan<double>.Empty;
Assert.False(SimdExtensions.ContainsNonFiniteScalar(span));
}
[Fact]
public void SumScalar_MultipleElements_ReturnsCorrectSum()
{
double[] data = [1.0, 2.0, 3.0, 4.0, 5.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(15.0, SimdExtensions.SumScalar(span));
}
[Fact]
public void SumScalar_NegativeValues_ReturnsCorrectSum()
{
double[] data = [-1.0, -2.0, 3.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(0.0, SimdExtensions.SumScalar(span));
}
[Fact]
public void SumScalar_Empty_ReturnsZero()
{
var span = ReadOnlySpan<double>.Empty;
Assert.Equal(0.0, SimdExtensions.SumScalar(span));
}
[Fact]
public void MinScalar_MultipleElements_ReturnsMinimum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(1.0, SimdExtensions.MinScalar(span));
}
[Fact]
public void MinScalar_NegativeValues_ReturnsMinimum()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(-8.0, SimdExtensions.MinScalar(span));
}
[Fact]
public void MinScalar_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, SimdExtensions.MinScalar(span));
}
[Fact]
public void MaxScalar_MultipleElements_ReturnsMaximum()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(9.0, SimdExtensions.MaxScalar(span));
}
[Fact]
public void MaxScalar_NegativeValues_ReturnsMaximum()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(-1.0, SimdExtensions.MaxScalar(span));
}
[Fact]
public void MaxScalar_SingleElement_ReturnsElement()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
Assert.Equal(42.5, SimdExtensions.MaxScalar(span));
}
[Fact]
public void VarianceScalar_MultipleElements_ReturnsCorrectVariance()
{
double[] data = [2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0];
var span = new ReadOnlySpan<double>(data);
double mean = 5.0;
double variance = SimdExtensions.VarianceScalar(span, mean);
Assert.True(Math.Abs(variance - 4.571428) < 0.0001);
}
[Fact]
public void VarianceScalar_TwoElements_ReturnsCorrectVariance()
{
double[] data = [1.0, 3.0];
var span = new ReadOnlySpan<double>(data);
double mean = 2.0;
Assert.Equal(2.0, SimdExtensions.VarianceScalar(span, mean), precision: 10);
}
[Fact]
public void MinMaxScalar_MultipleElements_ReturnsCorrectMinMax()
{
double[] data = [5.0, 2.0, 8.0, 1.0, 9.0, 3.0, 7.0, 4.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = SimdExtensions.MinMaxScalar(span);
Assert.Equal(1.0, min);
Assert.Equal(9.0, max);
}
[Fact]
public void MinMaxScalar_NegativeValues_ReturnsCorrectMinMax()
{
double[] data = [-5.0, -2.0, -8.0, -1.0];
var span = new ReadOnlySpan<double>(data);
var (min, max) = SimdExtensions.MinMaxScalar(span);
Assert.Equal(-8.0, min);
Assert.Equal(-1.0, max);
}
[Fact]
public void MinMaxScalar_SingleElement_ReturnsSameValue()
{
double[] data = [42.5];
var span = new ReadOnlySpan<double>(data);
var (min, max) = SimdExtensions.MinMaxScalar(span);
Assert.Equal(42.5, min);
Assert.Equal(42.5, max);
}
}
lib/core/simd/SimdExtensions.cs
+76 -47
View File
@@ -9,6 +9,76 @@ namespace QuanTAlib;
/// </summary>
public static class SimdExtensions
{
// Internal scalar implementations for testability
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static bool ContainsNonFiniteScalar(ReadOnlySpan<double> span)
{
for (int i = 0; i < span.Length; i++)
{
if (!double.IsFinite(span[i]))
return true;
}
return false;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static double SumScalar(ReadOnlySpan<double> span)
{
double scalar = 0.0;
for (int i = 0; i < span.Length; i++)
scalar += span[i];
return scalar;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static double MinScalar(ReadOnlySpan<double> span)
{
double min = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] < min)
min = span[i];
}
return min;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static double MaxScalar(ReadOnlySpan<double> span)
{
double max = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] > max)
max = span[i];
}
return max;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static double VarianceScalar(ReadOnlySpan<double> span, double mean)
{
double sumSquares = 0.0;
for (int i = 0; i < span.Length; i++)
{
double diff = span[i] - mean;
sumSquares += diff * diff;
}
return sumSquares / (span.Length - 1);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal static (double Min, double Max) MinMaxScalar(ReadOnlySpan<double> span)
{
double scalarMin = span[0];
double scalarMax = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] < scalarMin) scalarMin = span[i];
if (span[i] > scalarMax) scalarMax = span[i];
}
return (scalarMin, scalarMax);
}
/// <summary>
/// Checks if span contains any non-finite values (NaN or Infinity).
/// Returns true if any non-finite value is found.
@@ -26,8 +96,6 @@ public static class SimdExtensions
for (; i <= span.Length - vectorSize; i += vectorSize)
{
var vector = new Vector<double>(span.Slice(i, vectorSize));
// Check for NaN: NaN != NaN is true
// Check for Infinity: IsInfinity
for (int j = 0; j < vectorSize; j++)
{
if (!double.IsFinite(vector[j]))
@@ -45,13 +113,7 @@ public static class SimdExtensions
return false;
}
// Scalar fallback
for (int i = 0; i < span.Length; i++)
{
if (!double.IsFinite(span[i]))
return true;
}
return false;
return ContainsNonFiniteScalar(span);
}
/// <summary>
@@ -92,11 +154,7 @@ public static class SimdExtensions
return result;
}
// Scalar fallback
double scalar = 0.0;
for (int i = 0; i < span.Length; i++)
scalar += span[i];
return scalar;
return SumScalar(span);
}
/// <summary>
@@ -144,14 +202,7 @@ public static class SimdExtensions
return result;
}
// Scalar fallback
double min = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] < min)
min = span[i];
}
return min;
return MinScalar(span);
}
/// <summary>
@@ -199,14 +250,7 @@ public static class SimdExtensions
return result;
}
// Scalar fallback
double max = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] > max)
max = span[i];
}
return max;
return MaxScalar(span);
}
/// <summary>
@@ -270,14 +314,7 @@ public static class SimdExtensions
return result / (span.Length - 1);
}
// Scalar fallback
double sumSquares = 0.0;
for (int i = 0; i < span.Length; i++)
{
double diff = span[i] - m;
sumSquares += diff * diff;
}
return sumSquares / (span.Length - 1);
return VarianceScalar(span, m);
}
/// <summary>
@@ -339,14 +376,6 @@ public static class SimdExtensions
return (min, max);
}
// Scalar fallback
double scalarMin = span[0];
double scalarMax = span[0];
for (int i = 1; i < span.Length; i++)
{
if (span[i] < scalarMin) scalarMin = span[i];
if (span[i] > scalarMax) scalarMax = span[i];
}
return (scalarMin, scalarMax);
return MinMaxScalar(span);
}
}
lib/core/tbar/TBar.Tests.cs
+353 -76
View File
@@ -1,76 +1,353 @@
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TBarTests
{
[Fact]
public void Constructor_SetsPropertiesCorrectly()
{
long time = DateTime.UtcNow.Ticks;
double open = 100;
double high = 110;
double low = 90;
double close = 105;
double volume = 1000;
var bar = new TBar(time, open, high, low, close, volume);
Assert.Equal(time, bar.Time);
Assert.Equal(open, bar.Open);
Assert.Equal(high, bar.High);
Assert.Equal(low, bar.Low);
Assert.Equal(close, bar.Close);
Assert.Equal(volume, bar.Volume);
}
[Fact]
public void HL2_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 105, 1000);
Assert.Equal(100.0, bar.HL2); // (110 + 90) / 2
}
[Fact]
public void OHL3_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 105, 1000);
Assert.Equal(100.0, bar.OHL3); // (100 + 110 + 90) / 3
}
[Fact]
public void HLC3_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.HLC3); // (110 + 90 + 100) / 3
}
[Fact]
public void OHLC4_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.OHLC4); // (100 + 110 + 90 + 100) / 4
}
[Fact]
public void HLCC4_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.HLCC4); // (110 + 90 + 100 + 100) / 4
}
[Fact]
public void ImplicitConversion_ToTValue_ReturnsClosePriceWithTime()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue tv = bar;
Assert.Equal(time, tv.Time);
Assert.Equal(105.0, tv.Value);
}
}
}
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TBarTests
{
[Fact]
public void Constructor_SetsPropertiesCorrectly()
{
long time = DateTime.UtcNow.Ticks;
double open = 100;
double high = 110;
double low = 90;
double close = 105;
double volume = 1000;
var bar = new TBar(time, open, high, low, close, volume);
Assert.Equal(time, bar.Time);
Assert.Equal(open, bar.Open);
Assert.Equal(high, bar.High);
Assert.Equal(low, bar.Low);
Assert.Equal(close, bar.Close);
Assert.Equal(volume, bar.Volume);
}
[Fact]
public void Constructor_WithDateTime_SetsPropertiesCorrectly()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
double open = 100;
double high = 110;
double low = 90;
double close = 105;
double volume = 1000;
var bar = new TBar(dateTime, open, high, low, close, volume);
Assert.Equal(dateTime.Ticks, bar.Time);
Assert.Equal(open, bar.Open);
Assert.Equal(high, bar.High);
Assert.Equal(low, bar.Low);
Assert.Equal(close, bar.Close);
Assert.Equal(volume, bar.Volume);
}
[Fact]
public void AsDateTime_ReturnsCorrectDateTime()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
var bar = new TBar(dateTime, 100, 110, 90, 105, 1000);
Assert.Equal(dateTime, bar.AsDateTime);
Assert.Equal(DateTimeKind.Utc, bar.AsDateTime.Kind);
}
[Fact]
public void O_Property_ReturnsTValueWithOpenPrice()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue o = bar.O;
Assert.Equal(time, o.Time);
Assert.Equal(100.0, o.Value);
}
[Fact]
public void H_Property_ReturnsTValueWithHighPrice()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue h = bar.H;
Assert.Equal(time, h.Time);
Assert.Equal(110.0, h.Value);
}
[Fact]
public void L_Property_ReturnsTValueWithLowPrice()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue l = bar.L;
Assert.Equal(time, l.Time);
Assert.Equal(90.0, l.Value);
}
[Fact]
public void C_Property_ReturnsTValueWithClosePrice()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue c = bar.C;
Assert.Equal(time, c.Time);
Assert.Equal(105.0, c.Value);
}
[Fact]
public void V_Property_ReturnsTValueWithVolume()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue v = bar.V;
Assert.Equal(time, v.Time);
Assert.Equal(1000.0, v.Value);
}
[Fact]
public void HL2_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 105, 1000);
Assert.Equal(100.0, bar.HL2);
}
[Fact]
public void OC2_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 104, 1000);
Assert.Equal(102.0, bar.OC2);
}
[Fact]
public void OHL3_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 105, 1000);
Assert.Equal(100.0, bar.OHL3);
}
[Fact]
public void HLC3_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.HLC3);
}
[Fact]
public void OHLC4_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.OHLC4);
}
[Fact]
public void HLCC4_CalculatesCorrectly()
{
var bar = new TBar(0, 100, 110, 90, 100, 1000);
Assert.Equal(100.0, bar.HLCC4);
}
[Fact]
public void ImplicitConversion_ToDouble_ReturnsClosePrice()
{
var bar = new TBar(0, 100, 110, 90, 105, 1000);
double closePrice = bar;
Assert.Equal(105.0, closePrice);
}
[Fact]
public void ImplicitConversion_ToTValue_ReturnsClosePriceWithTime()
{
long time = DateTime.UtcNow.Ticks;
var bar = new TBar(time, 100, 110, 90, 105, 1000);
TValue tv = bar;
Assert.Equal(time, tv.Time);
Assert.Equal(105.0, tv.Value);
}
[Fact]
public void ImplicitConversion_ToDateTime_ReturnsCorrectDateTime()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
var bar = new TBar(dateTime, 100, 110, 90, 105, 1000);
DateTime result = bar;
Assert.Equal(dateTime, result);
Assert.Equal(DateTimeKind.Utc, result.Kind);
}
[Fact]
public void ToString_ReturnsFormattedString()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
var bar = new TBar(dateTime, 100.5, 110.25, 90.75, 105.0, 1000.0);
string result = bar.ToString();
Assert.Contains("2024-06-15", result);
Assert.Contains("10:30:00", result);
Assert.Contains("O=100.50", result);
Assert.Contains("H=110.25", result);
Assert.Contains("L=90.75", result);
Assert.Contains("C=105.00", result);
Assert.Contains("V=1000.00", result);
}
[Fact]
public void Equals_TBar_SameBars_ReturnsTrue()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.True(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentTime_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12346, 100, 110, 90, 105, 1000);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentOpen_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 101, 110, 90, 105, 1000);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentHigh_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 111, 90, 105, 1000);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentLow_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 91, 105, 1000);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentClose_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 106, 1000);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_TBar_DifferentVolume_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 105, 1001);
Assert.False(bar1.Equals(bar2));
}
[Fact]
public void Equals_Object_SameTBar_ReturnsTrue()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
object bar2 = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.True(bar1.Equals(bar2));
}
[Fact]
public void Equals_Object_DifferentType_ReturnsFalse()
{
var bar = new TBar(12345, 100, 110, 90, 105, 1000);
object other = "not a TBar";
Assert.False(bar.Equals(other));
}
[Fact]
public void Equals_Object_Null_ReturnsFalse()
{
var bar = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.False(bar.Equals(null));
}
[Fact]
public void GetHashCode_SameBars_ReturnsSameHashCode()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.Equal(bar1.GetHashCode(), bar2.GetHashCode());
}
[Fact]
public void GetHashCode_DifferentBars_ReturnsDifferentHashCode()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12346, 100, 110, 90, 105, 1000);
Assert.NotEqual(bar1.GetHashCode(), bar2.GetHashCode());
}
[Fact]
public void EqualityOperator_SameBars_ReturnsTrue()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.True(bar1 == bar2);
}
[Fact]
public void EqualityOperator_DifferentBars_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12346, 100, 110, 90, 105, 1000);
Assert.False(bar1 == bar2);
}
[Fact]
public void InequalityOperator_SameBars_ReturnsFalse()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12345, 100, 110, 90, 105, 1000);
Assert.False(bar1 != bar2);
}
[Fact]
public void InequalityOperator_DifferentBars_ReturnsTrue()
{
var bar1 = new TBar(12345, 100, 110, 90, 105, 1000);
var bar2 = new TBar(12346, 100, 110, 90, 105, 1000);
Assert.True(bar1 != bar2);
}
}
}
lib/core/tbarseries/TBarSeries.Tests.cs
+418 -58
View File
@@ -1,58 +1,418 @@
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TBarSeriesTests
{
[Fact]
public void Add_NewBar_IncreasesCount()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: true);
Assert.Single(series);
Assert.Equal(105.0, series.Last.Close);
}
[Fact]
public void Add_UpdateBar_DoesNotIncreaseCount()
{
var series = new TBarSeries();
long time = DateTime.UtcNow.Ticks;
var bar1 = new TBar(time, 100, 110, 90, 105, 1000);
var bar2 = new TBar(time, 100, 112, 90, 108, 1200);
series.Add(bar1, isNew: true);
series.Add(bar2, isNew: false);
Assert.Single(series);
Assert.Equal(108.0, series.Last.Close);
Assert.Equal(112.0, series.Last.High);
}
[Fact]
public void SubSeries_AreUpdated()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: true);
Assert.Single(series.Open);
Assert.Single(series.High);
Assert.Single(series.Low);
Assert.Single(series.Close);
Assert.Single(series.Volume);
Assert.Equal(100.0, series.Open.Last.Value);
Assert.Equal(110.0, series.High.Last.Value);
Assert.Equal(90.0, series.Low.Last.Value);
Assert.Equal(105.0, series.Close.Last.Value);
Assert.Equal(1000.0, series.Volume.Last.Value);
}
}
}
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TBarSeriesTests
{
[Fact]
public void Constructor_Default_CreatesEmptySeries()
{
var series = new TBarSeries();
Assert.Empty(series);
}
[Fact]
public void Constructor_WithCapacity_CreatesEmptySeries()
{
var series = new TBarSeries(100);
Assert.Empty(series);
}
[Fact]
public void Name_DefaultValue_IsBar()
{
var series = new TBarSeries();
Assert.Equal("Bar", series.Name);
}
[Fact]
public void Name_CanBeSet()
{
var series = new TBarSeries { Name = "TestBars" };
Assert.Equal("TestBars", series.Name);
}
[Fact]
public void Add_NewBar_IncreasesCount()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: true);
Assert.Single(series);
Assert.Equal(105.0, series.Last.Close);
}
[Fact]
public void Add_UpdateBar_DoesNotIncreaseCount()
{
var series = new TBarSeries();
long time = DateTime.UtcNow.Ticks;
var bar1 = new TBar(time, 100, 110, 90, 105, 1000);
var bar2 = new TBar(time, 100, 112, 90, 108, 1200);
series.Add(bar1, isNew: true);
series.Add(bar2, isNew: false);
Assert.Single(series);
Assert.Equal(108.0, series.Last.Close);
Assert.Equal(112.0, series.Last.High);
}
[Fact]
public void Add_UpdateOnEmptySeries_AddsNewBar()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: false);
Assert.Single(series);
}
[Fact]
public void Add_WithLongTime_AddsBar()
{
var series = new TBarSeries();
long time = DateTime.UtcNow.Ticks;
series.Add(time, 100, 110, 90, 105, 1000, isNew: true);
Assert.Single(series);
Assert.Equal(time, series.Last.Time);
}
[Fact]
public void Add_WithDateTime_AddsBar()
{
var series = new TBarSeries();
var dt = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
series.Add(dt, 100, 110, 90, 105, 1000, isNew: true);
Assert.Single(series);
Assert.Equal(dt.Ticks, series.Last.Time);
}
[Fact]
public void Add_WithEnumerables_AddsMultipleBars()
{
var series = new TBarSeries();
var times = new long[] { 100, 200, 300 };
var opens = new double[] { 10, 20, 30 };
var highs = new double[] { 15, 25, 35 };
var lows = new double[] { 5, 15, 25 };
var closes = new double[] { 12, 22, 32 };
var volumes = new double[] { 100, 200, 300 };
series.Add(times, opens, highs, lows, closes, volumes);
Assert.Equal(3, series.Count);
Assert.Equal(10, series[0].Open);
Assert.Equal(32, series[2].Close);
}
[Fact]
public void SubSeries_AreUpdated()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: true);
Assert.Single(series.Open);
Assert.Single(series.High);
Assert.Single(series.Low);
Assert.Single(series.Close);
Assert.Single(series.Volume);
Assert.Equal(100.0, series.Open.Last.Value);
Assert.Equal(110.0, series.High.Last.Value);
Assert.Equal(90.0, series.Low.Last.Value);
Assert.Equal(105.0, series.Close.Last.Value);
Assert.Equal(1000.0, series.Volume.Last.Value);
}
[Fact]
public void SubSeries_Aliases_Work()
{
var series = new TBarSeries();
var bar = new TBar(DateTime.UtcNow.Ticks, 100, 110, 90, 105, 1000);
series.Add(bar, isNew: true);
Assert.Same(series.Open, series.O);
Assert.Same(series.High, series.H);
Assert.Same(series.Low, series.L);
Assert.Same(series.Close, series.C);
Assert.Same(series.Volume, series.V);
}
[Fact]
public void SubSeries_HaveCorrectNames()
{
var series = new TBarSeries();
Assert.Equal("Open", series.Open.Name);
Assert.Equal("High", series.High.Name);
Assert.Equal("Low", series.Low.Name);
Assert.Equal("Close", series.Close.Name);
Assert.Equal("Volume", series.Volume.Name);
}
[Fact]
public void Last_EmptySeries_ReturnsDefault()
{
var series = new TBarSeries();
var last = series.Last;
Assert.Equal(0, last.Time);
Assert.Equal(0.0, last.Open);
Assert.Equal(0.0, last.Close);
}
[Fact]
public void Last_NonEmptySeries_ReturnsLastBar()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
var last = series.Last;
Assert.Equal(200, last.Time);
Assert.Equal(22.0, last.Close);
}
[Fact]
public void LastTime_EmptySeries_ReturnsZero()
{
var series = new TBarSeries();
Assert.Equal(0, series.LastTime);
}
[Fact]
public void LastTime_NonEmptySeries_ReturnsLastTime()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(200, series.LastTime);
}
[Fact]
public void LastOpen_EmptySeries_ReturnsNaN()
{
var series = new TBarSeries();
Assert.True(double.IsNaN(series.LastOpen));
}
[Fact]
public void LastOpen_NonEmptySeries_ReturnsLastOpen()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(20.0, series.LastOpen);
}
[Fact]
public void LastHigh_EmptySeries_ReturnsNaN()
{
var series = new TBarSeries();
Assert.True(double.IsNaN(series.LastHigh));
}
[Fact]
public void LastHigh_NonEmptySeries_ReturnsLastHigh()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(25.0, series.LastHigh);
}
[Fact]
public void LastLow_EmptySeries_ReturnsNaN()
{
var series = new TBarSeries();
Assert.True(double.IsNaN(series.LastLow));
}
[Fact]
public void LastLow_NonEmptySeries_ReturnsLastLow()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(15.0, series.LastLow);
}
[Fact]
public void LastClose_EmptySeries_ReturnsNaN()
{
var series = new TBarSeries();
Assert.True(double.IsNaN(series.LastClose));
}
[Fact]
public void LastClose_NonEmptySeries_ReturnsLastClose()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(22.0, series.LastClose);
}
[Fact]
public void LastVolume_EmptySeries_ReturnsNaN()
{
var series = new TBarSeries();
Assert.True(double.IsNaN(series.LastVolume));
}
[Fact]
public void LastVolume_NonEmptySeries_ReturnsLastVolume()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(200.0, series.LastVolume);
}
[Fact]
public void Indexer_ReturnsCorrectBar()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
series.Add(300, 30, 35, 25, 32, 300);
Assert.Equal(100, series[0].Time);
Assert.Equal(10.0, series[0].Open);
Assert.Equal(200, series[1].Time);
Assert.Equal(22.0, series[1].Close);
Assert.Equal(300, series[2].Time);
Assert.Equal(32.0, series[2].Close);
}
[Fact]
public void Count_ReturnsCorrectValue()
{
var series = new TBarSeries();
Assert.Empty(series);
series.Add(100, 10, 15, 5, 12, 100);
Assert.Single(series);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(2, series.Count);
}
[Fact]
public void GetEnumerator_IteratesAllBars()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
series.Add(300, 30, 35, 25, 32, 300);
var list = series.ToList();
Assert.Equal(3, list.Count);
Assert.Equal(10.0, list[0].Open);
Assert.Equal(22.0, list[1].Close);
Assert.Equal(32.0, list[2].Close);
}
[Fact]
public void GetEnumerator_NonGeneric_Works()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
IEnumerable enumerable = series;
var list = new List<object>();
foreach (var item in enumerable)
{
list.Add(item);
}
Assert.Equal(2, list.Count);
}
[Fact]
public void Pub_Event_IsRaisedOnAdd()
{
var series = new TBarSeries();
TBar? received = null;
series.Pub += bar => received = bar;
var barToAdd = new TBar(100, 10, 15, 5, 12, 100);
series.Add(barToAdd, isNew: true);
Assert.NotNull(received);
Assert.Equal(100, received.Value.Time);
Assert.Equal(12.0, received.Value.Close);
}
[Fact]
public void Pub_Event_IsRaisedOnUpdate()
{
var series = new TBarSeries();
TBar? received = null;
series.Add(100, 10, 15, 5, 12, 100);
series.Pub += bar => received = bar;
series.Add(100, 10, 18, 5, 15, 150, isNew: false);
Assert.NotNull(received);
Assert.Equal(15.0, received.Value.Close);
Assert.Equal(18.0, received.Value.High);
}
[Fact]
public void SubSeries_ShareSameTimeArray()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
Assert.Equal(series.Open.Times[0], series.Close.Times[0]);
Assert.Equal(series.High.Times[1], series.Volume.Times[1]);
}
[Fact]
public void Add_MultipleBars_MaintainsOrder()
{
var series = new TBarSeries();
series.Add(100, 10, 15, 5, 12, 100);
series.Add(200, 20, 25, 15, 22, 200);
series.Add(300, 30, 35, 25, 32, 300);
Assert.Equal(3, series.Count);
Assert.Equal(100, series[0].Time);
Assert.Equal(200, series[1].Time);
Assert.Equal(300, series[2].Time);
}
}
}
lib/core/tseries/TSeries.Tests.cs
+345 -49
View File
@@ -1,49 +1,345 @@
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TSeriesTests
{
[Fact]
public void Add_NewValue_IncreasesCount()
{
var series = new TSeries();
long time = DateTime.UtcNow.Ticks;
series.Add(time, 10.0, isNew: true);
Assert.Single(series);
Assert.Equal(10.0, series.Last.Value);
}
[Fact]
public void Add_UpdateValue_DoesNotIncreaseCount()
{
var series = new TSeries();
long time = DateTime.UtcNow.Ticks;
series.Add(time, 10.0, isNew: true);
series.Add(time, 11.0, isNew: false);
Assert.Single(series);
Assert.Equal(11.0, series.Last.Value);
}
[Fact]
public void Add_MultipleValues_MaintainsOrder()
{
var series = new TSeries();
long t0 = DateTime.UtcNow.Ticks;
long t1 = t0 + TimeSpan.TicksPerMinute;
series.Add(t0, 10.0, isNew: true);
series.Add(t1, 20.0, isNew: true);
Assert.Equal(2, series.Count);
Assert.Equal(10.0, series[0].Value);
Assert.Equal(20.0, series[1].Value);
}
}
}
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TSeriesTests
{
[Fact]
public void Constructor_Default_CreatesEmptySeries()
{
var series = new TSeries();
Assert.Empty(series);
}
[Fact]
public void Constructor_WithCapacity_CreatesEmptySeries()
{
var series = new TSeries(100);
Assert.Empty(series);
}
[Fact]
public void Constructor_WithLists_WrapsExistingData()
{
var times = new List<long> { 100, 200, 300 };
var values = new List<double> { 1.0, 2.0, 3.0 };
var series = new TSeries(times, values);
Assert.Equal(3, series.Count);
Assert.Equal(1.0, series[0].Value);
Assert.Equal(2.0, series[1].Value);
Assert.Equal(3.0, series[2].Value);
}
[Fact]
public void Name_DefaultValue_IsData()
{
var series = new TSeries();
Assert.Equal("Data", series.Name);
}
[Fact]
public void Name_CanBeSet()
{
var series = new TSeries { Name = "TestSeries" };
Assert.Equal("TestSeries", series.Name);
}
[Fact]
public void Add_NewValue_IncreasesCount()
{
var series = new TSeries();
long time = DateTime.UtcNow.Ticks;
series.Add(time, 10.0, isNew: true);
Assert.Single(series);
Assert.Equal(10.0, series.Last.Value);
}
[Fact]
public void Add_UpdateValue_DoesNotIncreaseCount()
{
var series = new TSeries();
long time = DateTime.UtcNow.Ticks;
series.Add(time, 10.0, isNew: true);
series.Add(time, 11.0, isNew: false);
Assert.Single(series);
Assert.Equal(11.0, series.Last.Value);
}
[Fact]
public void Add_MultipleValues_MaintainsOrder()
{
var series = new TSeries();
long t0 = DateTime.UtcNow.Ticks;
long t1 = t0 + TimeSpan.TicksPerMinute;
series.Add(t0, 10.0, isNew: true);
series.Add(t1, 20.0, isNew: true);
Assert.Equal(2, series.Count);
Assert.Equal(10.0, series[0].Value);
Assert.Equal(20.0, series[1].Value);
}
[Fact]
public void Add_TValue_AddsNewItem()
{
var series = new TSeries();
var tv = new TValue(DateTime.UtcNow.Ticks, 42.0);
series.Add(tv);
Assert.Single(series);
Assert.Equal(42.0, series.Last.Value);
}
[Fact]
public void Add_TValueWithIsNew_AddsOrUpdates()
{
var series = new TSeries();
var tv1 = new TValue(DateTime.UtcNow.Ticks, 42.0);
var tv2 = new TValue(DateTime.UtcNow.Ticks, 43.0);
series.Add(tv1, isNew: true);
series.Add(tv2, isNew: false);
Assert.Single(series);
Assert.Equal(43.0, series.Last.Value);
}
[Fact]
public void Add_WithDateTime_AddsValue()
{
var series = new TSeries();
var dt = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
series.Add(dt, 100.0, isNew: true);
Assert.Single(series);
Assert.Equal(dt.Ticks, series.Last.Time);
Assert.Equal(100.0, series.Last.Value);
}
[Fact]
public void Add_EnumerableDoubles_AddsAllValues()
{
var series = new TSeries();
var values = new[] { 1.0, 2.0, 3.0, 4.0, 5.0 };
series.Add(values);
Assert.Equal(5, series.Count);
Assert.Equal(1.0, series[0].Value);
Assert.Equal(5.0, series[4].Value);
}
[Fact]
public void Add_UpdateOnEmptySeries_AddsNewItem()
{
var series = new TSeries();
var tv = new TValue(DateTime.UtcNow.Ticks, 42.0);
series.Add(tv, isNew: false);
Assert.Single(series);
Assert.Equal(42.0, series.Last.Value);
}
[Fact]
public void Last_EmptySeries_ReturnsDefault()
{
var series = new TSeries();
var last = series.Last;
Assert.Equal(0, last.Time);
Assert.Equal(0.0, last.Value);
}
[Fact]
public void Last_NonEmptySeries_ReturnsLastValue()
{
var series = new TSeries();
series.Add(100, 10.0);
series.Add(200, 20.0);
var last = series.Last;
Assert.Equal(200, last.Time);
Assert.Equal(20.0, last.Value);
}
[Fact]
public void LastValue_EmptySeries_ReturnsNaN()
{
var series = new TSeries();
Assert.True(double.IsNaN(series.LastValue));
}
[Fact]
public void LastValue_NonEmptySeries_ReturnsLastValue()
{
var series = new TSeries();
series.Add(100, 10.0);
series.Add(200, 20.0);
Assert.Equal(20.0, series.LastValue);
}
[Fact]
public void LastTime_EmptySeries_ReturnsZero()
{
var series = new TSeries();
Assert.Equal(0, series.LastTime);
}
[Fact]
public void LastTime_NonEmptySeries_ReturnsLastTime()
{
var series = new TSeries();
series.Add(100, 10.0);
series.Add(200, 20.0);
Assert.Equal(200, series.LastTime);
}
[Fact]
public void Values_ReturnsReadOnlySpanOfValues()
{
var series = new TSeries();
series.Add(100, 1.0);
series.Add(200, 2.0);
series.Add(300, 3.0);
ReadOnlySpan<double> values = series.Values;
Assert.Equal(3, values.Length);
Assert.Equal(1.0, values[0]);
Assert.Equal(2.0, values[1]);
Assert.Equal(3.0, values[2]);
}
[Fact]
public void Times_ReturnsReadOnlySpanOfTimes()
{
var series = new TSeries();
series.Add(100, 1.0);
series.Add(200, 2.0);
series.Add(300, 3.0);
ReadOnlySpan<long> times = series.Times;
Assert.Equal(3, times.Length);
Assert.Equal(100, times[0]);
Assert.Equal(200, times[1]);
Assert.Equal(300, times[2]);
}
[Fact]
public void Indexer_ReturnsCorrectTValue()
{
var series = new TSeries();
series.Add(100, 10.0);
series.Add(200, 20.0);
series.Add(300, 30.0);
Assert.Equal(100, series[0].Time);
Assert.Equal(10.0, series[0].Value);
Assert.Equal(200, series[1].Time);
Assert.Equal(20.0, series[1].Value);
Assert.Equal(300, series[2].Time);
Assert.Equal(30.0, series[2].Value);
}
[Fact]
public void GetEnumerator_IteratesAllValues()
{
var series = new TSeries();
series.Add(100, 1.0);
series.Add(200, 2.0);
series.Add(300, 3.0);
var list = series.ToList();
Assert.Equal(3, list.Count);
Assert.Equal(1.0, list[0].Value);
Assert.Equal(2.0, list[1].Value);
Assert.Equal(3.0, list[2].Value);
}
[Fact]
public void GetEnumerator_NonGeneric_Works()
{
var series = new TSeries();
series.Add(100, 1.0);
series.Add(200, 2.0);
IEnumerable enumerable = series;
var list = new List<object>();
foreach (var item in enumerable)
{
list.Add(item);
}
Assert.Equal(2, list.Count);
}
[Fact]
public void Pub_Event_IsRaisedOnAdd()
{
var series = new TSeries();
TValue? received = null;
series.Pub += tv => received = tv;
series.Add(100, 42.0);
Assert.NotNull(received);
Assert.Equal(100, received.Value.Time);
Assert.Equal(42.0, received.Value.Value);
}
[Fact]
public void Pub_Event_IsRaisedOnUpdate()
{
var series = new TSeries();
TValue? received = null;
series.Add(100, 42.0);
series.Pub += tv => received = tv;
series.Add(100, 43.0, isNew: false);
Assert.NotNull(received);
Assert.Equal(43.0, received.Value.Value);
}
[Fact]
public void Count_ReturnsCorrectValue()
{
var series = new TSeries();
Assert.Empty(series);
series.Add(100, 1.0);
Assert.Single(series);
series.Add(200, 2.0);
Assert.Equal(2, series.Count);
}
}
}
lib/core/tvalue/TValue.Tests.cs
+185 -51
View File
@@ -1,51 +1,185 @@
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TValueTests
{
[Fact]
public void Constructor_SetsPropertiesCorrectly()
{
long time = DateTime.UtcNow.Ticks;
double value = 123.45;
var tValue = new TValue(time, value);
Assert.Equal(time, tValue.Time);
Assert.Equal(value, tValue.Value);
}
[Fact]
public void AsDateTime_ReturnsCorrectDateTime()
{
DateTime dt = new DateTime(2023, 1, 1, 12, 0, 0, DateTimeKind.Utc);
long ticks = dt.Ticks;
var tValue = new TValue(ticks, 100.0);
Assert.Equal(dt, tValue.AsDateTime);
}
[Fact]
public void ToString_FormatsCorrectly()
{
DateTime dt = new DateTime(2023, 1, 1, 12, 0, 0, DateTimeKind.Utc);
var tValue = new TValue(dt.Ticks, 123.456);
string result = tValue.ToString();
Assert.Contains(dt.ToString("yyyy-MM-dd HH:mm:ss"), result);
Assert.Contains("123.46", result); // Default formatting usually 2 decimals or similar
}
[Fact]
public void ImplicitConversion_ToDouble()
{
var tValue = new TValue(DateTime.UtcNow.Ticks, 42.0);
double val = tValue;
Assert.Equal(42.0, val);
}
}
}
using System;
using Xunit;
using QuanTAlib;
namespace QuanTAlib.Tests
{
public class TValueTests
{
[Fact]
public void Constructor_WithLongTime_SetsPropertiesCorrectly()
{
long time = DateTime.UtcNow.Ticks;
double value = 123.45;
var tValue = new TValue(time, value);
Assert.Equal(time, tValue.Time);
Assert.Equal(value, tValue.Value);
}
[Fact]
public void Constructor_WithDateTime_SetsPropertiesCorrectly()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
double value = 123.45;
var tValue = new TValue(dateTime, value);
Assert.Equal(dateTime.Ticks, tValue.Time);
Assert.Equal(value, tValue.Value);
}
[Fact]
public void AsDateTime_ReturnsCorrectDateTime()
{
var dt = new DateTime(2023, 1, 1, 12, 0, 0, DateTimeKind.Utc);
var tValue = new TValue(dt.Ticks, 100.0);
Assert.Equal(dt, tValue.AsDateTime);
Assert.Equal(DateTimeKind.Utc, tValue.AsDateTime.Kind);
}
[Fact]
public void ToString_FormatsCorrectly()
{
var dt = new DateTime(2023, 1, 1, 12, 0, 0, DateTimeKind.Utc);
var tValue = new TValue(dt.Ticks, 123.456);
string result = tValue.ToString();
Assert.Contains("2023-01-01", result);
Assert.Contains("12:00:00", result);
Assert.Contains("123.46", result);
}
[Fact]
public void ImplicitConversion_ToDouble_ReturnsValue()
{
var tValue = new TValue(DateTime.UtcNow.Ticks, 42.0);
double val = tValue;
Assert.Equal(42.0, val);
}
[Fact]
public void ImplicitConversion_ToDateTime_ReturnsCorrectDateTime()
{
var dateTime = new DateTime(2024, 6, 15, 10, 30, 0, DateTimeKind.Utc);
var tValue = new TValue(dateTime.Ticks, 100.0);
DateTime result = tValue;
Assert.Equal(dateTime, result);
Assert.Equal(DateTimeKind.Utc, result.Kind);
}
[Fact]
public void Equals_TValue_SameValues_ReturnsTrue()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12345, 100.0);
Assert.True(tv1.Equals(tv2));
}
[Fact]
public void Equals_TValue_DifferentTime_ReturnsFalse()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12346, 100.0);
Assert.False(tv1.Equals(tv2));
}
[Fact]
public void Equals_TValue_DifferentValue_ReturnsFalse()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12345, 101.0);
Assert.False(tv1.Equals(tv2));
}
[Fact]
public void Equals_Object_SameTValue_ReturnsTrue()
{
var tv1 = new TValue(12345, 100.0);
object tv2 = new TValue(12345, 100.0);
Assert.True(tv1.Equals(tv2));
}
[Fact]
public void Equals_Object_DifferentType_ReturnsFalse()
{
var tv = new TValue(12345, 100.0);
object other = "not a TValue";
Assert.False(tv.Equals(other));
}
[Fact]
public void Equals_Object_Null_ReturnsFalse()
{
var tv = new TValue(12345, 100.0);
Assert.False(tv.Equals(null));
}
[Fact]
public void GetHashCode_SameValues_ReturnsSameHashCode()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12345, 100.0);
Assert.Equal(tv1.GetHashCode(), tv2.GetHashCode());
}
[Fact]
public void GetHashCode_DifferentValues_ReturnsDifferentHashCode()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12346, 100.0);
Assert.NotEqual(tv1.GetHashCode(), tv2.GetHashCode());
}
[Fact]
public void EqualityOperator_SameValues_ReturnsTrue()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12345, 100.0);
Assert.True(tv1 == tv2);
}
[Fact]
public void EqualityOperator_DifferentValues_ReturnsFalse()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12346, 100.0);
Assert.False(tv1 == tv2);
}
[Fact]
public void InequalityOperator_SameValues_ReturnsFalse()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12345, 100.0);
Assert.False(tv1 != tv2);
}
[Fact]
public void InequalityOperator_DifferentValues_ReturnsTrue()
{
var tv1 = new TValue(12345, 100.0);
var tv2 = new TValue(12346, 100.0);
Assert.True(tv1 != tv2);
}
}
}
lib/quantalib.csproj
+5 -1
View File
@@ -1,6 +1,6 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFrameworks>net8.0;net9.0;net10.0</TargetFrameworks>
<TargetFrameworks>net10.0</TargetFrameworks>
<Title>QuanTAlib</Title>
<Product>Library of TA Calculations, Charts and Strategies for Quantower</Product>
<Description>Quantitative Technical Analysis Library in C# for Quantower</Description>
@@ -32,6 +32,10 @@
<UserSecretsId>6afc11a7-4355-4f5e-9fdf-22431e5b03cb</UserSecretsId>
</PropertyGroup>
<ItemGroup>
<InternalsVisibleTo Include="QuanTAlib.Tests" />
</ItemGroup>
<ItemGroup>
<Compile Include="**\*.cs" Exclude="**\*.Tests.cs;**\*.Quantower.cs;obj\**\*.cs" />
</ItemGroup>