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python wrapper

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Miha Kralj
2026-02-28 14:14:35 -08:00
parent 82e0248eb0
commit 83e9511261
521 changed files with 62395 additions and 15669 deletions
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lib/statistics/correlation/Correlation.Quantower.Tests.cs
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using TradingPlatform.BusinessLayer;
namespace QuanTAlib.Tests;
public class CorrelationIndicatorTests
{
[Fact]
public void CorrelationIndicator_Constructor_SetsDefaults()
{
var indicator = new CorrelationIndicator();
Assert.Equal(20, indicator.Period);
Assert.Equal(SourceType.Close, indicator.Source);
Assert.Equal(SourceType.Open, indicator.Source2);
Assert.True(indicator.ShowColdValues);
Assert.Equal("CORR - Pearson Correlation Coefficient", indicator.Name);
Assert.True(indicator.SeparateWindow);
Assert.True(indicator.OnBackGround);
}
[Fact]
public void CorrelationIndicator_MinHistoryDepths_EqualsTwo()
{
var indicator = new CorrelationIndicator();
Assert.Equal(2, CorrelationIndicator.MinHistoryDepths);
Assert.Equal(2, ((IWatchlistIndicator)indicator).MinHistoryDepths);
}
[Fact]
public void CorrelationIndicator_ShortName_IncludesPeriodAndSources()
{
var indicator = new CorrelationIndicator { Period = 20 };
Assert.Contains("CORR", indicator.ShortName, StringComparison.Ordinal);
Assert.Contains("20", indicator.ShortName, StringComparison.Ordinal);
}
[Fact]
public void CorrelationIndicator_Initialize_CreatesInternalCorrelation()
{
var indicator = new CorrelationIndicator { Period = 10 };
// Initialize should not throw
indicator.Initialize();
// After init, line series should exist
Assert.Single(indicator.LinesSeries);
}
[Fact]
public void CorrelationIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
{
var indicator = new CorrelationIndicator { Period = 5 };
indicator.Initialize();
// Add historical data
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
// Process update
var args = new UpdateArgs(UpdateReason.HistoricalBar);
indicator.ProcessUpdate(args);
// Line series should have a value (may be NaN during warmup)
Assert.Equal(1, indicator.LinesSeries[0].Count);
}
[Fact]
public void CorrelationIndicator_ProcessUpdate_NewBar_ComputesValue()
{
var indicator = new CorrelationIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
indicator.HistoricalData.AddBar(now.AddMinutes(1), 102, 108, 100, 106);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
Assert.Equal(2, indicator.LinesSeries[0].Count);
}
[Fact]
public void CorrelationIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
{
var indicator = new CorrelationIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
double firstValue = indicator.LinesSeries[0].GetValue(0);
// NewTick should not throw
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
double secondValue = indicator.LinesSeries[0].GetValue(0);
// Values should be produced (may be NaN during warmup, but should not throw)
Assert.True(double.IsNaN(firstValue) || double.IsFinite(firstValue));
Assert.True(double.IsNaN(secondValue) || double.IsFinite(secondValue));
}
[Fact]
public void CorrelationIndicator_MultipleUpdates_ProducesSequence()
{
var indicator = new CorrelationIndicator { Period = 3 };
indicator.Initialize();
var now = DateTime.UtcNow;
// Add bars with different O/C patterns to create varying correlation
double[] opens = { 100, 101, 102, 103, 104, 105 };
double[] closes = { 100, 101, 102, 103, 104, 105 };
for (int i = 0; i < opens.Length; i++)
{
indicator.HistoricalData.AddBar(now.AddMinutes(i), opens[i], opens[i] + 5, opens[i] - 5, closes[i]);
indicator.ProcessUpdate(new UpdateArgs(i == 0 ? UpdateReason.HistoricalBar : UpdateReason.NewBar));
}
// All values should exist
Assert.Equal(opens.Length, indicator.LinesSeries[0].Count);
}
[Fact]
public void CorrelationIndicator_DifferentSourceTypes_Work()
{
var sources = new[] { SourceType.Open, SourceType.High, SourceType.Low, SourceType.Close, SourceType.HL2, SourceType.HLC3 };
foreach (var source in sources)
{
var indicator = new CorrelationIndicator { Period = 5, Source = source, Source2 = SourceType.Close };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 110, 90, 105);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
// Should have computed a value (may be NaN during warmup, but should not throw)
Assert.Equal(1, indicator.LinesSeries[0].Count);
}
}
[Fact]
public void CorrelationIndicator_CorrelationBounds()
{
// This test verifies the indicator produces values in valid range [-1, +1]
var indicator = new CorrelationIndicator { Period = 5, Source = SourceType.Close, Source2 = SourceType.Open };
indicator.Initialize();
var now = DateTime.UtcNow;
// Add bars with varying patterns
for (int i = 0; i < 20; i++)
{
double open = 100 + i;
double close = 100 + i + (i % 2 == 0 ? 2 : -1); // Varying relationship
indicator.HistoricalData.AddBar(now.AddMinutes(i), open, open + 5, open - 5, close);
indicator.ProcessUpdate(new UpdateArgs(i == 0 ? UpdateReason.HistoricalBar : UpdateReason.NewBar));
}
// After warmup, should have values in valid range
Assert.Equal(20, indicator.LinesSeries[0].Count);
// Check that values are bounded
for (int i = 0; i < 20; i++)
{
double value = indicator.LinesSeries[0].GetValue(i);
if (double.IsFinite(value))
{
Assert.InRange(value, -1.0, 1.0);
}
}
}
[Fact]
public void CorrelationIndicator_DifferentSource2Types_Work()
{
var source2Types = new[] { SourceType.Open, SourceType.High, SourceType.Low, SourceType.HL2 };
foreach (var source2 in source2Types)
{
var indicator = new CorrelationIndicator { Period = 5, Source = SourceType.Close, Source2 = source2 };
indicator.Initialize();
var now = DateTime.UtcNow;
indicator.HistoricalData.AddBar(now, 100, 110, 90, 105);
indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
Assert.Equal(1, indicator.LinesSeries[0].Count);
}
}
[Fact]
public void CorrelationIndicator_Period_CanBeChanged()
{
var indicator = new CorrelationIndicator { Period = 50 };
Assert.Equal(50, indicator.Period);
indicator.Period = 100;
Assert.Equal(100, indicator.Period);
}
[Fact]
public void CorrelationIndicator_Source2_CanBeChanged()
{
var indicator = new CorrelationIndicator { Source2 = SourceType.High };
Assert.Equal(SourceType.High, indicator.Source2);
indicator.Source2 = SourceType.Low;
Assert.Equal(SourceType.Low, indicator.Source2);
}
[Fact]
public void CorrelationIndicator_ReInitialize_ResetsState()
{
var indicator = new CorrelationIndicator { Period = 5 };
indicator.Initialize();
var now = DateTime.UtcNow;
for (int i = 0; i < 10; i++)
{
indicator.HistoricalData.AddBar(now.AddMinutes(i), 100 + i, 105 + i, 95 + i, 102 + i);
indicator.ProcessUpdate(new UpdateArgs(i == 0 ? UpdateReason.HistoricalBar : UpdateReason.NewBar));
}
Assert.Equal(10, indicator.LinesSeries[0].Count);
// Re-initialize should work without errors
var indicator2 = new CorrelationIndicator { Period = 5 };
indicator2.Initialize();
indicator2.HistoricalData.AddBar(now.AddMinutes(100), 200, 210, 190, 205);
indicator2.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
Assert.Equal(1, indicator2.LinesSeries[0].Count);
}
[Fact]
public void CorrelationIndicator_HighLow_ProducesPositiveCorrelation()
{
// Test with High vs Low - they should be positively correlated
var indicator = new CorrelationIndicator { Period = 10, Source = SourceType.High, Source2 = SourceType.Low };
indicator.Initialize();
var now = DateTime.UtcNow;
// Add bars with typical High > Low relationship
for (int i = 0; i < 15; i++)
{
double mid = 100 + (i * 0.5);
double spread = 5;
indicator.HistoricalData.AddBar(now.AddMinutes(i), mid, mid + spread, mid - spread, mid);
indicator.ProcessUpdate(new UpdateArgs(i == 0 ? UpdateReason.HistoricalBar : UpdateReason.NewBar));
}
Assert.Equal(15, indicator.LinesSeries[0].Count);
// After warmup period, High and Low should show positive correlation
// (they both trend together as price moves)
double lastValue = indicator.LinesSeries[0].GetValue(0);
if (double.IsFinite(lastValue))
{
Assert.True(lastValue > 0, $"Expected positive correlation for High vs Low, got {lastValue}");
}
}
[Fact]
public void CorrelationIndicator_Description_IsSet()
{
var indicator = new CorrelationIndicator();
Assert.Contains("linear", indicator.Description, StringComparison.OrdinalIgnoreCase);
Assert.Contains("-1", indicator.Description, StringComparison.Ordinal);
Assert.Contains("+1", indicator.Description, StringComparison.Ordinal);
}
[Fact]
public void CorrelationIndicator_PerfectCorrelation_ReturnsOne()
{
// When Close == Open for all bars, correlation should be 1.0 (or NaN if zero variance)
var indicator = new CorrelationIndicator { Period = 5, Source = SourceType.Close, Source2 = SourceType.Open };
indicator.Initialize();
var now = DateTime.UtcNow;
// Add bars where Close always equals Open (perfect linear relationship)
for (int i = 0; i < 10; i++)
{
double price = 100 + i * 2; // Trending up
indicator.HistoricalData.AddBar(now.AddMinutes(i), price, price + 5, price - 5, price);
indicator.ProcessUpdate(new UpdateArgs(i == 0 ? UpdateReason.HistoricalBar : UpdateReason.NewBar));
}
Assert.Equal(10, indicator.LinesSeries[0].Count);
// When Open == Close exactly, we get perfect correlation = 1.0
double lastValue = indicator.LinesSeries[0].GetValue(0);
if (double.IsFinite(lastValue))
{
Assert.Equal(1.0, lastValue, precision: 6);
}
}
}
lib/statistics/correlation/Correlation.Quantower.cs
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using System.Drawing;
using System.Runtime.CompilerServices;
using TradingPlatform.BusinessLayer;
namespace QuanTAlib;
/// <summary>
/// Quantower adapter for Correlation indicator.
/// Measures the Pearson correlation coefficient between two price series.
/// </summary>
/// <remarks>
/// This adapter compares two different price sources from the same symbol (e.g., Close vs Open,
/// Close vs Volume, High vs Low). For cross-symbol correlation analysis, use the core
/// Correlation class directly with data from multiple symbols.
///
/// The output is the Pearson correlation coefficient, ranging from -1 to +1.
/// Values near +1 indicate strong positive correlation, near -1 indicate strong negative correlation.
/// </remarks>
[SkipLocalsInit]
public sealed class CorrelationIndicator : Indicator, IWatchlistIndicator
{
[InputParameter("Period", sortIndex: 0, minimum: 2, maximum: 10000)]
public int Period { get; set; } = 20;
[IndicatorExtensions.DataSourceInput]
public SourceType Source { get; set; } = SourceType.Close;
[InputParameter("Source 2 Type", sortIndex: 2)]
public SourceType Source2 { get; set; } = SourceType.Open;
[InputParameter("Show cold values", sortIndex: 21)]
public bool ShowColdValues { get; set; } = true;
private Correlation _correlation = null!;
private readonly LineSeries _series;
private string _sourceName = null!;
private Func<IHistoryItem, double> _priceSelector = null!;
private Func<IHistoryItem, double> _priceSelector2 = null!;
public static int MinHistoryDepths => 2;
int IWatchlistIndicator.MinHistoryDepths => MinHistoryDepths;
public override string ShortName => $"CORR({Period}):{_sourceName}/{Source2}";
public CorrelationIndicator()
{
OnBackGround = true;
SeparateWindow = true;
Name = "CORR - Pearson Correlation Coefficient";
Description = "Measures linear relationship between two price sources. Range: -1 (inverse) to +1 (perfect positive).";
_series = new LineSeries(name: "Correlation", color: IndicatorExtensions.Statistics, width: 2, style: LineStyle.Solid);
AddLineSeries(_series);
}
protected override void OnInit()
{
_priceSelector = Source.GetPriceSelector();
_priceSelector2 = Source2.GetPriceSelector();
_sourceName = Source.ToString();
_correlation = new Correlation(Period);
base.OnInit();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override void OnUpdate(UpdateArgs args)
{
bool isNew = args.IsNewBar();
// Get both price sources from the same bar
var item = HistoricalData[Count - 1, SeekOriginHistory.Begin];
double valueA = _priceSelector(item);
double valueB = _priceSelector2(item);
var tvalA = new TValue(item.TimeLeft.Ticks, valueA);
var tvalB = new TValue(item.TimeLeft.Ticks, valueB);
double value = _correlation.Update(tvalA, tvalB, isNew).Value;
_series.SetValue(value, _correlation.IsHot, ShowColdValues);
}
}