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python wrapper
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Miha Kralj
@@ -1,195 +0,0 @@
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using Xunit;
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using TradingPlatform.BusinessLayer;
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namespace QuanTAlib.Tests;
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public class NormdistIndicatorTests
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{
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[Fact]
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public void NormdistIndicator_Constructor_SetsDefaults()
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{
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var indicator = new NormdistIndicator();
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Assert.Equal(SourceType.Close, indicator.Source);
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Assert.Equal(0.0, indicator.Mu);
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Assert.Equal(1.0, indicator.Sigma);
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Assert.Equal(14, indicator.Period);
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Assert.True(indicator.ShowColdValues);
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Assert.Equal("NORMDIST - Normal Distribution CDF", indicator.Name);
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Assert.True(indicator.SeparateWindow);
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Assert.True(indicator.OnBackGround);
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}
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[Fact]
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public void NormdistIndicator_MinHistoryDepths_EqualsPeriod()
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{
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var indicator = new NormdistIndicator { Period = 30 };
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Assert.Equal(30, indicator.MinHistoryDepths);
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}
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[Fact]
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public void NormdistIndicator_ShortName_IsCorrect()
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{
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var indicator = new NormdistIndicator { Mu = 0.5, Sigma = 2.0, Period = 20 };
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Assert.Equal("NORMDIST(0.50,2.00,20)", indicator.ShortName);
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}
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[Fact]
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public void NormdistIndicator_Initialize_CreatesTwoLineSeries()
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{
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var indicator = new NormdistIndicator();
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indicator.Initialize();
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Assert.Equal(2, indicator.LinesSeries.Count);
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Assert.Equal("NormDist", indicator.LinesSeries[0].Name);
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Assert.Equal("Mid", indicator.LinesSeries[1].Name);
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}
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[Fact]
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public void NormdistIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
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{
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var indicator = new NormdistIndicator { Period = 5 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 5; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105 + i, 95 - i, 100 + i);
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var args = new UpdateArgs(UpdateReason.HistoricalBar);
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indicator.ProcessUpdate(args);
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}
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// After 5 bars (= period), should have valid output
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double val = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(val), "Output must be finite after warmup");
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Assert.True(val >= 0.0 && val <= 1.0, $"Output {val} must be in [0,1]");
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}
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[Fact]
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public void NormdistIndicator_ProcessUpdate_NewBar_AddsNewValue()
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{
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var indicator = new NormdistIndicator { Period = 3 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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// Feed 3 historical bars
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for (int i = 0; i < 3; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105, 95, 100 + i);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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// Feed a new bar
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indicator.HistoricalData.AddBar(now.AddMinutes(3), 0, 106, 96, 103);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
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Assert.Equal(4, indicator.LinesSeries[0].Count);
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}
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[Fact]
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public void NormdistIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
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{
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var indicator = new NormdistIndicator { Period = 3 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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indicator.HistoricalData.AddBar(now, 0, 105, 95, 100);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
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// 2 values: one historical, one intra-bar update
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Assert.Equal(2, indicator.LinesSeries[0].Count);
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}
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[Fact]
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public void NormdistIndicator_MidLine_IsAlwaysHalf()
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{
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var indicator = new NormdistIndicator { Period = 3 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 5; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 105, 95, 100 + i);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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// Mid line should always be 0.5
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for (int i = 0; i < indicator.LinesSeries[1].Count; i++)
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{
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double mid = indicator.LinesSeries[1].GetValue(i);
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Assert.Equal(0.5, mid, 1e-10);
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}
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}
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[Fact]
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public void NormdistIndicator_DifferentSourceType_Works()
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{
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var indicator = new NormdistIndicator { Period = 3, Source = SourceType.High };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 3; i++)
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{
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// High = 110+i, Low = 90, Close = 100
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 110 + i, 90, 100);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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double val = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(val));
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}
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[Fact]
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public void NormdistIndicator_OutputInRange_AfterManyBars()
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{
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var indicator = new NormdistIndicator { Period = 20 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 76001);
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var bars = gbm.Fetch(50, now.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < bars.Close.Count; i++)
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{
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double price = bars.Close[i].Value;
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indicator.HistoricalData.AddBar(
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new DateTime(bars.Close[i].Time, DateTimeKind.Utc),
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0, price * 1.01, price * 0.99, price);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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// Check all computed values are in [0, 1]
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for (int i = 0; i < indicator.LinesSeries[0].Count; i++)
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{
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double val = indicator.LinesSeries[0].GetValue(i);
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Assert.True(val >= 0.0 && val <= 1.0, $"Value {val} at index {i} out of range");
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}
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}
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[Fact]
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public void NormdistIndicator_FlatPrices_OutputNearHalf()
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{
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// When all prices identical, z=0 → CDF = 0.5
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var indicator = new NormdistIndicator { Period = 5, Mu = 0.0, Sigma = 1.0 };
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indicator.Initialize();
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var now = DateTime.UtcNow;
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for (int i = 0; i < 10; i++)
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{
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indicator.HistoricalData.AddBar(now.AddMinutes(i), 0, 101, 99, 100);
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indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
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}
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double val = indicator.LinesSeries[0].GetValue(0);
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Assert.True(double.IsFinite(val));
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Assert.True(val >= 0.0 && val <= 1.0);
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}
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[Fact]
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public void NormdistIndicator_CustomMuSigma_ShortNameReflects()
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{
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var indicator = new NormdistIndicator { Mu = -0.5, Sigma = 1.5, Period = 14 };
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Assert.Equal("NORMDIST(-0.50,1.50,14)", indicator.ShortName);
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}
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}
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@@ -1,72 +0,0 @@
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using System.Drawing;
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using TradingPlatform.BusinessLayer;
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using static QuanTAlib.IndicatorExtensions;
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namespace QuanTAlib;
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/// <summary>
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/// NORMDIST (Normal Distribution CDF) Quantower indicator.
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/// Computes Φ(z; μ, σ) applied to a z-score normalized price series
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/// over a rolling lookback window.
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/// </summary>
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public class NormdistIndicator : Indicator, IWatchlistIndicator
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{
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[DataSourceInput]
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public SourceType Source { get; set; } = SourceType.Close;
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[InputParameter("Mean (μ)", sortIndex: 0, minimum: -100.0, maximum: 100.0, increment: 0.1, decimalPlaces: 3)]
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public double Mu { get; set; } = 0.0;
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[InputParameter("Std Dev (σ)", sortIndex: 1, minimum: 0.001, maximum: 100.0, increment: 0.1, decimalPlaces: 3)]
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public double Sigma { get; set; } = 1.0;
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[InputParameter("Period", sortIndex: 2, minimum: 2, maximum: 2000, increment: 1)]
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public int Period { get; set; } = 14;
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[InputParameter("Show Cold Values", sortIndex: 100)]
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public bool ShowColdValues { get; set; } = true;
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private Normdist? _normdist;
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private Func<IHistoryItem, double>? _selector;
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public int MinHistoryDepths => Period;
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public override string ShortName => $"NORMDIST({Mu:F2},{Sigma:F2},{Period})";
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public NormdistIndicator()
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{
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Name = "NORMDIST - Normal Distribution CDF";
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Description = "Applies the Gaussian CDF to a z-score normalized price series";
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SeparateWindow = true;
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OnBackGround = true;
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}
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protected override void OnInit()
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{
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_normdist = new Normdist(Mu, Sigma, Period);
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_selector = Source.GetPriceSelector();
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AddLineSeries(new LineSeries("NormDist", Color.Cyan, 2, LineStyle.Solid));
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// Reference level at 0.5 (midpoint / rolling mean)
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AddLineSeries(new LineSeries("Mid", Color.Gray, 1, LineStyle.Dash));
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}
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protected override void OnUpdate(UpdateArgs args)
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{
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if (_normdist == null || _selector == null)
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{
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return;
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}
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var item = HistoricalData[0, SeekOriginHistory.End];
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double value = _selector(item);
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bool isNew = args.IsNewBar();
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TValue input = new(item.TimeLeft, value);
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_normdist.Update(input, isNew);
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bool isHot = _normdist.IsHot;
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LinesSeries[0].SetValue(_normdist.Last.Value, isHot, ShowColdValues);
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LinesSeries[1].SetValue(0.5, isHot, ShowColdValues);
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}
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}
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