mirror of
https://github.com/mihakralj/QuanTAlib.git
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Add validation tests for USF and enhance ATR indicator tests
- Introduced Usf.Validation.Tests.cs to validate the USF (Ehlers Ultimate Smoother Filter) for consistency across batch, streaming, and span modes, as well as mathematical properties and coefficient calculations. - Added comprehensive tests for the ATR indicator in Atr.Quantower.Tests.cs, including constructor validation, historical data processing, and handling of NaN/Infinity inputs. - Enhanced Atr.Tests.cs with additional tests for iterative corrections, warmup behavior, and true range calculations. - Updated Atr.cs to ensure warmup period is derived from RMA. - Added new tests for Adosc in Adosc.Tests.cs to validate handling of NaN and Infinity inputs, and to ensure batch calculations match iterative results. - Created a new Volatility.csproj to organize volatility-related implementations.
This commit is contained in:
Miha Kralj
@@ -1,902 +0,0 @@
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# Momentum Indicators Test Implementation Plan
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> **Objective:** Bring all 13 momentum indicators to full compliance with testprotocol.md
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## Executive Summary
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- **Total Missing Tests:** ~72 tests across 12 indicators
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- **Estimated Effort:** 4-6 hours
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- **Priority:** Start with MACD (most deficient), end with VEL (closest to compliant)
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---
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## Phase 1: Critical Deficiencies (MACD, BOP)
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### 1.1 MACD - Add 10 Tests
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**File:** `lib/momentum/macd/Macd.Tests.cs`
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```csharp
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// ADD THESE TESTS:
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[Fact]
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public void Constructor_InvalidParameters_ThrowsArgumentException()
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{
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Assert.Throws<ArgumentException>(() => new Macd(0, 26, 9));
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Assert.Throws<ArgumentException>(() => new Macd(12, 0, 9));
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Assert.Throws<ArgumentException>(() => new Macd(12, 26, 0));
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Assert.Throws<ArgumentException>(() => new Macd(26, 12, 9)); // fast >= slow
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}
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[Fact]
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public void Calc_IsNew_AcceptsParameter()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 49; i++)
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macd.Update(series.Close[i], isNew: true);
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var val1 = macd.Update(series.Close[49], isNew: true);
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var val2 = macd.Update(new TValue(DateTime.UtcNow, series.Close[49].Value + 1), isNew: true);
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Assert.NotEqual(val1.Value, val2.Value);
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}
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[Fact]
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public void Calc_IsNew_False_UpdatesValue()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 49; i++)
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macd.Update(series.Close[i]);
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var val1 = macd.Update(series.Close[49], isNew: true);
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var val2 = macd.Update(new TValue(series.Close[49].Time, series.Close[49].Value + 5), isNew: false);
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Assert.Equal(val1.Time, val2.Time);
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Assert.NotEqual(val1.Value, val2.Value);
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 50; i++)
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macd.Update(series.Close[i]);
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var originalValue = macd.Last;
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for (int m = 0; m < 5; m++)
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{
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var modified = new TValue(series.Close[49].Time, series.Close[49].Value + m);
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macd.Update(modified, isNew: false);
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}
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var restored = macd.Update(series.Close[49], isNew: false);
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Assert.Equal(originalValue.Value, restored.Value, 1e-9);
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}
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[Fact]
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public void Reset_ClearsState()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < series.Count; i++)
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macd.Update(series.Close[i]);
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macd.Reset();
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Assert.Equal(0, macd.Last.Value);
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Assert.False(macd.IsHot);
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}
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[Fact]
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public void IsHot_BecomesTrueWhenBufferFull()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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Assert.False(macd.IsHot);
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for (int i = 0; i < series.Count; i++)
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{
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macd.Update(series.Close[i]);
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if (i >= 40) break; // Should be hot by warmup
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}
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Assert.True(macd.IsHot);
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}
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[Fact]
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public void NaN_Input_UsesLastValidValue()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 40; i++)
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macd.Update(series.Close[i]);
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var result = macd.Update(new TValue(DateTime.UtcNow, double.NaN));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void Infinity_Input_UsesLastValidValue()
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{
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var macd = new Macd(12, 26, 9);
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var gbm = new GBM();
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var series = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 40; i++)
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macd.Update(series.Close[i]);
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var result = macd.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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var gbm = new GBM(seed: 123);
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var series = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// 1. Batch Mode
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var batchMacd = new Macd(12, 26, 9);
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var batchResult = batchMacd.Update(series.Close);
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double expected = batchResult.Last.Value;
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// 2. Span Mode
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var spanOutput = new double[series.Count];
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Macd.Calculate(series.Close.Values, spanOutput, 12, 26);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamMacd = new Macd(12, 26, 9);
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for (int i = 0; i < series.Count; i++)
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streamMacd.Update(series.Close[i]);
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double streamResult = streamMacd.Last.Value;
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// 4. Eventing Mode
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var pubSource = new TSeries();
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var eventMacd = new Macd(pubSource, 12, 26, 9);
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for (int i = 0; i < series.Count; i++)
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pubSource.Add(series.Close[i]);
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double eventResult = eventMacd.Last.Value;
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Assert.Equal(expected, spanResult, 9);
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Assert.Equal(expected, streamResult, 9);
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Assert.Equal(expected, eventResult, 9);
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}
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[Fact]
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public void SpanBatch_ValidatesInput()
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{
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double[] source = [1, 2, 3, 4, 5];
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double[] output = new double[5];
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double[] wrongSize = new double[3];
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Assert.Throws<ArgumentException>(() => Macd.Calculate(source, wrongSize, 12, 26));
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Assert.Throws<ArgumentException>(() => Macd.Calculate(source, output, 0, 26));
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Assert.Throws<ArgumentException>(() => Macd.Calculate(source, output, 12, 0));
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}
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```
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### 1.2 BOP - Add 9 Tests
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**File:** `lib/momentum/bop/Bop.Tests.cs`
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```csharp
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// ADD THESE TESTS:
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[Fact]
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public void Calc_IsNew_AcceptsParameter()
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{
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var bop = new Bop();
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var bar1 = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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var bar2 = new TBar(DateTime.UtcNow, 15, 25, 10, 20, 100);
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bop.Update(bar1, isNew: true);
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var val1 = bop.Last.Value;
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bop.Update(bar2, isNew: true);
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var val2 = bop.Last.Value;
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Assert.NotEqual(val1, val2);
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}
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[Fact]
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public void Calc_IsNew_False_UpdatesValue()
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{
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var bop = new Bop();
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var bar1 = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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var bar2 = new TBar(DateTime.UtcNow, 10, 25, 5, 20, 100);
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var val1 = bop.Update(bar1, isNew: true);
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var val2 = bop.Update(bar2, isNew: false);
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Assert.Equal(val1.Time, val2.Time);
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Assert.NotEqual(val1.Value, val2.Value);
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var bop = new Bop();
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var bar = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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var originalValue = bop.Update(bar, isNew: true);
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for (int i = 0; i < 5; i++)
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{
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var modified = new TBar(bar.Time, bar.Open, bar.High + i, bar.Low, bar.Close, bar.Volume);
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bop.Update(modified, isNew: false);
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}
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var restored = bop.Update(bar, isNew: false);
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Assert.Equal(originalValue.Value, restored.Value, 1e-9);
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}
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[Fact]
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public void Reset_ClearsState()
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{
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var bop = new Bop();
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var bar = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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bop.Update(bar);
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bop.Reset();
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Assert.Equal(0, bop.Last.Value);
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}
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[Fact]
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public void IsHot_BecomesTrueWhenBufferFull()
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{
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var bop = new Bop();
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Assert.False(bop.IsHot);
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var bar = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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bop.Update(bar);
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Assert.True(bop.IsHot); // BOP is hot immediately (no warmup needed)
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}
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[Fact]
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public void NaN_Input_UsesLastValidValue()
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{
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var bop = new Bop();
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var bar1 = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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var barNaN = new TBar(DateTime.UtcNow, double.NaN, 20, 5, 15, 100);
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bop.Update(bar1);
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var result = bop.Update(barNaN);
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void Infinity_Input_UsesLastValidValue()
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{
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var bop = new Bop();
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var bar1 = new TBar(DateTime.UtcNow, 10, 20, 5, 15, 100);
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var barInf = new TBar(DateTime.UtcNow, double.PositiveInfinity, 20, 5, 15, 100);
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bop.Update(bar1);
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var result = bop.Update(barInf);
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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var gbm = new GBM(seed: 123);
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var bars = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// 1. Batch Mode
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var batchResult = Bop.Batch(bars);
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double expected = batchResult.Last.Value;
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// 2. Span Mode
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var spanOutput = new double[bars.Count];
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Bop.Calculate(bars.Open.Values, bars.High.Values, bars.Low.Values, bars.Close.Values, spanOutput);
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double spanResult = spanOutput[^1];
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// 3. Streaming Mode
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var streamBop = new Bop();
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for (int i = 0; i < bars.Count; i++)
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streamBop.Update(bars[i]);
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double streamResult = streamBop.Last.Value;
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Assert.Equal(expected, spanResult, 9);
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Assert.Equal(expected, streamResult, 9);
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}
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[Fact]
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public void SpanBatch_ValidatesInput()
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{
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double[] open = [1, 2, 3];
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double[] high = [2, 3, 4];
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double[] low = [0, 1, 2];
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double[] close = [1.5, 2.5, 3.5];
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double[] output = new double[3];
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double[] wrongSize = new double[2];
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Assert.Throws<ArgumentException>(() => Bop.Calculate(open, high, low, close, wrongSize));
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}
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```
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---
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## Phase 2: Medium Deficiencies (DMX, CFB)
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### 2.1 DMX - Add 7 Tests
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**File:** `lib/momentum/dmx/Dmx.Tests.cs`
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```csharp
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// ADD THESE TESTS:
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[Fact]
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public void Constructor_InvalidParameters_ThrowsArgumentException()
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{
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Assert.Throws<ArgumentException>(() => new Dmx(0));
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Assert.Throws<ArgumentException>(() => new Dmx(-1));
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var dmx = new Dmx(14);
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var gbm = new GBM();
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var bars = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 50; i++)
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dmx.Update(bars[i]);
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var originalValue = dmx.Last;
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for (int m = 0; m < 5; m++)
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{
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var modified = new TBar(bars[49].Time, bars[49].Open, bars[49].High + m, bars[49].Low - m, bars[49].Close, bars[49].Volume);
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dmx.Update(modified, isNew: false);
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}
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var restored = dmx.Update(bars[49], isNew: false);
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Assert.Equal(originalValue.Value, restored.Value, 1e-9);
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}
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[Fact]
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public void IsHot_BecomesTrueWhenBufferFull()
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{
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var dmx = new Dmx(14);
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var gbm = new GBM();
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var bars = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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Assert.False(dmx.IsHot);
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for (int i = 0; i < bars.Count; i++)
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{
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dmx.Update(bars[i]);
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if (dmx.IsHot) break;
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}
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Assert.True(dmx.IsHot);
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}
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[Fact]
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public void NaN_Input_UsesLastValidValue()
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{
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var dmx = new Dmx(14);
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var gbm = new GBM();
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var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 30; i++)
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dmx.Update(bars[i]);
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var nanBar = new TBar(DateTime.UtcNow, double.NaN, double.NaN, double.NaN, double.NaN, 100);
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var result = dmx.Update(nanBar);
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void Infinity_Input_UsesLastValidValue()
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{
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var dmx = new Dmx(14);
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var gbm = new GBM();
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var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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for (int i = 0; i < 30; i++)
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dmx.Update(bars[i]);
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var infBar = new TBar(DateTime.UtcNow, double.PositiveInfinity, double.PositiveInfinity, 0, 100, 100);
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var result = dmx.Update(infBar);
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Assert.True(double.IsFinite(result.Value));
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}
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[Fact]
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public void AllModes_ProduceSameResult()
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{
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var gbm = new GBM(seed: 123);
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var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
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// 1. Batch Mode
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var batchResult = Dmx.Batch(bars, 14);
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double expected = batchResult.Last.Value;
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// 2. Streaming Mode
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var streamDmx = new Dmx(14);
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for (int i = 0; i < bars.Count; i++)
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streamDmx.Update(bars[i]);
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double streamResult = streamDmx.Last.Value;
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Assert.Equal(expected, streamResult, 9);
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}
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[Fact]
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public void SpanBatch_ValidatesInput()
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{
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// Add if DMX has span API
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}
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```
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### 2.2 CFB - Add 5 Tests
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**File:** `lib/momentum/cfb/Cfb.Tests.cs`
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```csharp
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// ADD THESE TESTS:
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||||
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[Fact]
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public void Constructor_InvalidParameters_ThrowsArgumentException()
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{
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Assert.Throws<ArgumentException>(() => new Cfb(Array.Empty<int>()));
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Assert.Throws<ArgumentException>(() => new Cfb(new[] { 0, 10 }));
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Assert.Throws<ArgumentException>(() => new Cfb(new[] { -1, 10 }));
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}
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[Fact]
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public void IterativeCorrections_RestoreToOriginalState()
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{
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var cfb = new Cfb();
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||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 50; i++)
|
||||
cfb.Update(new TValue(bars.Close.Times[i], bars.Close.Values[i]));
|
||||
|
||||
var originalValue = cfb.Last;
|
||||
|
||||
for (int m = 0; m < 5; m++)
|
||||
{
|
||||
var modified = new TValue(bars.Close.Times[49], bars.Close.Values[49] + m);
|
||||
cfb.Update(modified, isNew: false);
|
||||
}
|
||||
|
||||
var restored = cfb.Update(new TValue(bars.Close.Times[49], bars.Close.Values[49]), isNew: false);
|
||||
Assert.Equal(originalValue.Value, restored.Value, 1e-9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void IsHot_BecomesTrueWhenBufferFull()
|
||||
{
|
||||
var cfb = new Cfb(new[] { 5, 10 });
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < bars.Count; i++)
|
||||
{
|
||||
cfb.Update(new TValue(bars.Close.Times[i], bars.Close.Values[i]));
|
||||
if (cfb.IsHot) break;
|
||||
}
|
||||
|
||||
Assert.True(cfb.IsHot);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void NaN_Input_UsesLastValidValue()
|
||||
{
|
||||
var cfb = new Cfb();
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 30; i++)
|
||||
cfb.Update(new TValue(bars.Close.Times[i], bars.Close.Values[i]));
|
||||
|
||||
var result = cfb.Update(new TValue(DateTime.UtcNow, double.NaN));
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Infinity_Input_UsesLastValidValue()
|
||||
{
|
||||
var cfb = new Cfb();
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 30; i++)
|
||||
cfb.Update(new TValue(bars.Close.Times[i], bars.Close.Values[i]));
|
||||
|
||||
var result = cfb.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void AllModes_ProduceSameResult()
|
||||
{
|
||||
var gbm = new GBM(seed: 123);
|
||||
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// 1. Batch Mode
|
||||
var batchResult = Cfb.Batch(bars.Close);
|
||||
double expected = batchResult.Last.Value;
|
||||
|
||||
// 2. Span Mode
|
||||
var spanOutput = new double[bars.Count];
|
||||
Cfb.Batch(bars.Close.Values.ToArray(), spanOutput);
|
||||
double spanResult = spanOutput[^1];
|
||||
|
||||
// 3. Streaming Mode
|
||||
var streamCfb = new Cfb();
|
||||
for (int i = 0; i < bars.Count; i++)
|
||||
streamCfb.Update(new TValue(bars.Close.Times[i], bars.Close.Values[i]));
|
||||
double streamResult = streamCfb.Last.Value;
|
||||
|
||||
Assert.Equal(expected, spanResult, 9);
|
||||
Assert.Equal(expected, streamResult, 9);
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Phase 3: Standard Deficiencies (ADX, ADXR, AO, APO, Aroon, AroonOsc)
|
||||
|
||||
These 6 indicators all have the same pattern of missing tests. Create a template:
|
||||
|
||||
### Template for TBar-based Indicators (ADX, ADXR, AO, Aroon, AroonOsc)
|
||||
|
||||
```csharp
|
||||
// ADD THESE 6 TESTS TO EACH:
|
||||
|
||||
[Fact]
|
||||
public void IterativeCorrections_RestoreToOriginalState()
|
||||
{
|
||||
var indicator = new [IndicatorName](period);
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 50; i++)
|
||||
indicator.Update(bars[i]);
|
||||
|
||||
var originalValue = indicator.Last;
|
||||
|
||||
for (int m = 0; m < 5; m++)
|
||||
{
|
||||
var modified = new TBar(bars[49].Time, bars[49].Open, bars[49].High + m, bars[49].Low - m, bars[49].Close, bars[49].Volume);
|
||||
indicator.Update(modified, isNew: false);
|
||||
}
|
||||
|
||||
var restored = indicator.Update(bars[49], isNew: false);
|
||||
Assert.Equal(originalValue.Value, restored.Value, 1e-9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void IsHot_BecomesTrueWhenBufferFull()
|
||||
{
|
||||
var indicator = new [IndicatorName](period);
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
Assert.False(indicator.IsHot);
|
||||
|
||||
for (int i = 0; i < bars.Count; i++)
|
||||
{
|
||||
indicator.Update(bars[i]);
|
||||
if (indicator.IsHot) break;
|
||||
}
|
||||
|
||||
Assert.True(indicator.IsHot);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void NaN_Input_UsesLastValidValue()
|
||||
{
|
||||
var indicator = new [IndicatorName](period);
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 40; i++)
|
||||
indicator.Update(bars[i]);
|
||||
|
||||
var nanBar = new TBar(DateTime.UtcNow, double.NaN, double.NaN, double.NaN, double.NaN, 100);
|
||||
var result = indicator.Update(nanBar);
|
||||
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Infinity_Input_UsesLastValidValue()
|
||||
{
|
||||
var indicator = new [IndicatorName](period);
|
||||
var gbm = new GBM();
|
||||
var bars = gbm.Fetch(50, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 40; i++)
|
||||
indicator.Update(bars[i]);
|
||||
|
||||
var infBar = new TBar(DateTime.UtcNow, double.PositiveInfinity, double.PositiveInfinity, 0, 100, 100);
|
||||
var result = indicator.Update(infBar);
|
||||
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void AllModes_ProduceSameResult()
|
||||
{
|
||||
var gbm = new GBM(seed: 123);
|
||||
var bars = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// 1. Batch Mode
|
||||
var batchResult = [IndicatorName].Batch(bars, period);
|
||||
double expected = batchResult.Last.Value;
|
||||
|
||||
// 2. Streaming Mode
|
||||
var streamIndicator = new [IndicatorName](period);
|
||||
for (int i = 0; i < bars.Count; i++)
|
||||
streamIndicator.Update(bars[i]);
|
||||
double streamResult = streamIndicator.Last.Value;
|
||||
|
||||
Assert.Equal(expected, streamResult, 9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SpanBatch_ValidatesInput()
|
||||
{
|
||||
// Implement if indicator has Span API
|
||||
}
|
||||
```
|
||||
|
||||
### Template for TValue-based Indicator (APO)
|
||||
|
||||
Similar pattern but uses `series.Close[i]` instead of `bars[i]`.
|
||||
|
||||
---
|
||||
|
||||
## Phase 4: Minor Deficiencies (RSX, VEL)
|
||||
|
||||
### 4.1 RSX - Add 4 Tests
|
||||
|
||||
```csharp
|
||||
[Fact]
|
||||
public void IterativeCorrections_RestoreToOriginalState()
|
||||
{
|
||||
var rsx = new Rsx(14);
|
||||
var gbm = new GBM();
|
||||
var series = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 50; i++)
|
||||
rsx.Update(new TValue(series.Close.Times[i], series.Close.Values[i]));
|
||||
|
||||
var originalValue = rsx.Last;
|
||||
|
||||
for (int m = 0; m < 5; m++)
|
||||
{
|
||||
var modified = new TValue(series.Close.Times[49], series.Close.Values[49] + m);
|
||||
rsx.Update(modified, isNew: false);
|
||||
}
|
||||
|
||||
var restored = rsx.Update(new TValue(series.Close.Times[49], series.Close.Values[49]), isNew: false);
|
||||
Assert.Equal(originalValue.Value, restored.Value, 1e-9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void IsHot_BecomesTrueWhenBufferFull()
|
||||
{
|
||||
var rsx = new Rsx(14);
|
||||
var gbm = new GBM();
|
||||
var series = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
Assert.False(rsx.IsHot);
|
||||
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
{
|
||||
rsx.Update(new TValue(series.Close.Times[i], series.Close.Values[i]));
|
||||
if (rsx.IsHot) break;
|
||||
}
|
||||
|
||||
Assert.True(rsx.IsHot);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Infinity_Input_UsesLastValidValue()
|
||||
{
|
||||
var rsx = new Rsx(14);
|
||||
rsx.Update(new TValue(DateTime.UtcNow, 100));
|
||||
var result = rsx.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
|
||||
|
||||
Assert.False(double.IsInfinity(result.Value));
|
||||
Assert.InRange(result.Value, 0, 100);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void AllModes_ProduceSameResult()
|
||||
{
|
||||
int period = 14;
|
||||
var gbm = new GBM(seed: 123);
|
||||
var series = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// 1. Batch Mode
|
||||
var batchResult = Rsx.Batch(series.Close, period);
|
||||
double expected = batchResult.Last.Value;
|
||||
|
||||
// 2. Span Mode
|
||||
var spanOutput = new double[series.Count];
|
||||
Rsx.Batch(series.Close.Values.ToArray(), spanOutput, period);
|
||||
double spanResult = spanOutput[^1];
|
||||
|
||||
// 3. Streaming Mode
|
||||
var streamRsx = new Rsx(period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
streamRsx.Update(new TValue(series.Close.Times[i], series.Close.Values[i]));
|
||||
double streamResult = streamRsx.Last.Value;
|
||||
|
||||
// 4. Eventing Mode
|
||||
var pubSource = new TSeries();
|
||||
var eventRsx = new Rsx(pubSource, period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
pubSource.Add(new TValue(series.Close.Times[i], series.Close.Values[i]));
|
||||
double eventResult = eventRsx.Last.Value;
|
||||
|
||||
Assert.Equal(expected, spanResult, 9);
|
||||
Assert.Equal(expected, streamResult, 9);
|
||||
Assert.Equal(expected, eventResult, 9);
|
||||
}
|
||||
```
|
||||
|
||||
### 4.2 VEL - Add 4 Tests
|
||||
|
||||
```csharp
|
||||
[Fact]
|
||||
public void IterativeCorrections_RestoreToOriginalState()
|
||||
{
|
||||
var vel = new Vel(10);
|
||||
var gbm = new GBM();
|
||||
var series = gbm.Fetch(100, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 50; i++)
|
||||
vel.Update(series.Close[i]);
|
||||
|
||||
var originalValue = vel.Last;
|
||||
|
||||
for (int m = 0; m < 5; m++)
|
||||
{
|
||||
var modified = new TValue(series.Close[49].Time, series.Close[49].Value + m);
|
||||
vel.Update(modified, isNew: false);
|
||||
}
|
||||
|
||||
var restored = vel.Update(series.Close[49], isNew: false);
|
||||
Assert.Equal(originalValue.Value, restored.Value, 1e-9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void NaN_Input_UsesLastValidValue()
|
||||
{
|
||||
var vel = new Vel(10);
|
||||
var gbm = new GBM();
|
||||
var series = gbm.Fetch(20, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 15; i++)
|
||||
vel.Update(series.Close[i]);
|
||||
|
||||
var result = vel.Update(new TValue(DateTime.UtcNow, double.NaN));
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void Infinity_Input_UsesLastValidValue()
|
||||
{
|
||||
var vel = new Vel(10);
|
||||
var gbm = new GBM();
|
||||
var series = gbm.Fetch(20, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
for (int i = 0; i < 15; i++)
|
||||
vel.Update(series.Close[i]);
|
||||
|
||||
var result = vel.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
|
||||
Assert.True(double.IsFinite(result.Value));
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void AllModes_ProduceSameResult()
|
||||
{
|
||||
int period = 10;
|
||||
var gbm = new GBM(seed: 123);
|
||||
var series = gbm.Fetch(200, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
|
||||
|
||||
// 1. Batch Mode
|
||||
var batchResult = Vel.Batch(series.Close, period);
|
||||
double expected = batchResult.Last.Value;
|
||||
|
||||
// 2. Span Mode
|
||||
var spanOutput = new double[series.Count];
|
||||
Vel.Batch(series.Close.Values.ToArray().AsSpan(), spanOutput.AsSpan(), period);
|
||||
double spanResult = spanOutput[^1];
|
||||
|
||||
// 3. Streaming Mode
|
||||
var streamVel = new Vel(period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
streamVel.Update(series.Close[i]);
|
||||
double streamResult = streamVel.Last.Value;
|
||||
|
||||
// 4. Eventing Mode
|
||||
var pubSource = new TSeries();
|
||||
var eventVel = new Vel(pubSource, period);
|
||||
for (int i = 0; i < series.Count; i++)
|
||||
pubSource.Add(series.Close[i]);
|
||||
double eventResult = eventVel.Last.Value;
|
||||
|
||||
Assert.Equal(expected, spanResult, 9);
|
||||
Assert.Equal(expected, streamResult, 9);
|
||||
Assert.Equal(expected, eventResult, 9);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void SpanBatch_ValidatesInput()
|
||||
{
|
||||
double[] source = [1, 2, 3, 4, 5];
|
||||
double[] output = new double[5];
|
||||
double[] wrongSize = new double[3];
|
||||
|
||||
Assert.Throws<ArgumentException>(() => Vel.Batch(source.AsSpan(), wrongSize.AsSpan(), 3));
|
||||
Assert.Throws<ArgumentException>(() => Vel.Batch(source.AsSpan(), output.AsSpan(), 0));
|
||||
Assert.Throws<ArgumentException>(() => Vel.Batch(source.AsSpan(), output.AsSpan(), -1));
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Implementation Checklist
|
||||
|
||||
### Phase 1 (Priority: Critical)
|
||||
- [ ] MACD.Tests.cs - Add 10 tests
|
||||
- [ ] BOP.Tests.cs - Add 9 tests
|
||||
|
||||
### Phase 2 (Priority: High)
|
||||
- [ ] DMX.Tests.cs - Add 7 tests
|
||||
- [ ] CFB.Tests.cs - Add 5 tests
|
||||
|
||||
### Phase 3 (Priority: Medium)
|
||||
- [ ] ADX.Tests.cs - Add 6 tests
|
||||
- [ ] ADXR.Tests.cs - Add 6 tests
|
||||
- [ ] AO.Tests.cs - Add 6 tests
|
||||
- [ ] APO.Tests.cs - Add 6 tests
|
||||
- [ ] Aroon.Tests.cs - Add 6 tests
|
||||
- [ ] AroonOsc.Tests.cs - Add 6 tests
|
||||
|
||||
### Phase 4 (Priority: Low)
|
||||
- [ ] RSX.Tests.cs - Add 4 tests
|
||||
- [ ] VEL.Tests.cs - Add 4 tests
|
||||
|
||||
---
|
||||
|
||||
## Verification Steps
|
||||
|
||||
After implementing all tests:
|
||||
|
||||
1. Run all tests: `dotnet test lib/QuanTAlib.Tests.csproj`
|
||||
2. Verify no regressions in existing tests
|
||||
3. Check test coverage meets targets
|
||||
4. Update docs/validation.md with compliance status
|
||||
@@ -1,171 +0,0 @@
|
||||
# Roslyn SARIF Generation and Codacy Integration
|
||||
|
||||
## Overview
|
||||
|
||||
QuanTAlib now automatically generates Roslyn SARIF (Static Analysis Results Interchange Format) files during every build and uploads them to Codacy for continuous code quality monitoring.
|
||||
|
||||
## Configuration
|
||||
|
||||
### Build Configuration
|
||||
|
||||
The `Directory.Build.props` file has been configured to generate SARIF files for all projects:
|
||||
|
||||
```xml
|
||||
<PropertyGroup>
|
||||
<EnableNETAnalyzers>true</EnableNETAnalyzers>
|
||||
<EnforceCodeStyleInBuild>true</EnforceCodeStyleInBuild>
|
||||
<TreatWarningsAsErrors Condition="'$(Configuration)' == 'Release'">true</TreatWarningsAsErrors>
|
||||
<ErrorLog>$(MSBuildProjectDirectory)/roslyn.sarif</ErrorLog>
|
||||
<ErrorLogFormat>SARIF2.1</ErrorLogFormat>
|
||||
</PropertyGroup>
|
||||
```
|
||||
|
||||
### Git Configuration
|
||||
|
||||
SARIF files are excluded from version control via `.gitignore`:
|
||||
|
||||
```
|
||||
# Roslyn SARIF files (generated during build and uploaded to Codacy)
|
||||
**/roslyn.sarif
|
||||
roslyn.sarif
|
||||
```
|
||||
|
||||
## CI/CD Pipeline
|
||||
|
||||
### Build Phase
|
||||
|
||||
The GitHub Actions workflow (`Publish.yml`) includes SARIF generation in the build step:
|
||||
|
||||
1. **Build Projects**: All projects are built in Debug configuration
|
||||
2. **Collect SARIF Files**: All `roslyn.sarif` files are collected from project directories
|
||||
3. **Upload Artifacts**: SARIF files are uploaded as artifacts for downstream jobs
|
||||
|
||||
### Codacy Upload Phase
|
||||
|
||||
A dedicated job (`Codacy_SARIF_Upload`) handles SARIF file uploads:
|
||||
|
||||
1. **Download SARIF Reports**: Retrieves SARIF artifacts from the build job
|
||||
2. **Install Codacy CLI**: Downloads the latest Codacy Analysis CLI
|
||||
3. **Upload to Codacy**: Uploads each SARIF file using the Codacy CLI with project metadata
|
||||
|
||||
## Local Development
|
||||
|
||||
### Generate SARIF Files
|
||||
|
||||
SARIF files are automatically generated during any build:
|
||||
|
||||
```bash
|
||||
dotnet build --configuration Debug
|
||||
```
|
||||
|
||||
After building, SARIF files will be located in each project directory:
|
||||
- `lib/roslyn.sarif` - Main library analysis
|
||||
- `quantower/roslyn.sarif` - Quantower adapter analysis
|
||||
|
||||
### View SARIF Files
|
||||
|
||||
SARIF files are JSON-formatted and can be viewed with:
|
||||
- Visual Studio Code with SARIF Viewer extension
|
||||
- Any text editor (JSON format)
|
||||
- Codacy web interface (after upload)
|
||||
|
||||
## Analyzers Included
|
||||
|
||||
The following Roslyn analyzers contribute to the SARIF reports:
|
||||
|
||||
1. **Roslynator.Analyzers** (v4.12.9)
|
||||
- Code style and quality rules
|
||||
- Performance optimizations
|
||||
- Modern C# patterns
|
||||
|
||||
2. **Meziantou.Analyzer** (v2.0.183)
|
||||
- Security and correctness rules
|
||||
- API usage guidelines
|
||||
- Best practices enforcement
|
||||
|
||||
3. **SonarAnalyzer.CSharp** (v10.x)
|
||||
- Code smells and bugs
|
||||
- Security vulnerabilities
|
||||
- Maintainability issues
|
||||
|
||||
4. **.NET SDK Analyzers**
|
||||
- Framework-specific rules
|
||||
- API compatibility
|
||||
- Performance guidelines
|
||||
|
||||
## Suppressed Rules
|
||||
|
||||
Certain rules are suppressed globally in `Directory.Build.props`:
|
||||
|
||||
```xml
|
||||
<NoWarn>$(NoWarn);S1144;S1944;S2053;S2245;S2259;S2583;S2589;S3329;S3655;S3776;S3949;S3966;S4158;S4347;S5773;S6781;MA0048;MA0051</NoWarn>
|
||||
```
|
||||
|
||||
These suppressions are intentional design decisions aligned with QuanTAlib's high-performance requirements.
|
||||
|
||||
## Codacy Integration
|
||||
|
||||
### Required Secrets
|
||||
|
||||
The GitHub Actions workflow requires the following secret:
|
||||
|
||||
- `CODACY_PROJECT_TOKEN`: API token for uploading results to Codacy
|
||||
|
||||
### Upload Process
|
||||
|
||||
1. SARIF files are collected after build
|
||||
2. Each SARIF file is uploaded individually
|
||||
3. Results are associated with the specific commit SHA
|
||||
4. Tool identifier: `roslyn`
|
||||
5. Upload continues even if individual files fail
|
||||
|
||||
### View Results
|
||||
|
||||
Analysis results are available at:
|
||||
https://app.codacy.com/gh/mihakralj/QuanTAlib
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### SARIF Not Generated
|
||||
|
||||
If SARIF files are not being generated:
|
||||
|
||||
1. Verify `ErrorLog` property is set in `Directory.Build.props`
|
||||
2. Ensure analyzers are installed (check NuGet packages)
|
||||
3. Build in Debug or Release configuration (not Clean)
|
||||
4. Check MSBuild output for analyzer warnings
|
||||
|
||||
### Upload Failures
|
||||
|
||||
If Codacy uploads fail:
|
||||
|
||||
1. Verify `CODACY_PROJECT_TOKEN` secret is set
|
||||
2. Check GitHub Actions logs for specific errors
|
||||
3. Ensure SARIF files contain valid JSON
|
||||
4. Verify network connectivity to Codacy API
|
||||
|
||||
### Large SARIF Files
|
||||
|
||||
If SARIF files become too large:
|
||||
|
||||
1. Increase `upload-batch-size` in the workflow
|
||||
2. Consider splitting uploads by project
|
||||
3. Review suppressed warnings (might need adjustment)
|
||||
4. Use `--upload-batch-size 100000` for very large files
|
||||
|
||||
## Performance Impact
|
||||
|
||||
- **Build Time**: +5-10% due to analyzer execution
|
||||
- **SARIF Generation**: <1s per project
|
||||
- **File Size**: 100KB-500KB per project
|
||||
- **Upload Time**: 2-5s per SARIF file
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
Potential improvements for consideration:
|
||||
|
||||
1. **Differential Analysis**: Upload only changed files
|
||||
2. **Parallel Uploads**: Upload multiple SARIF files concurrently
|
||||
3. **Local Validation**: Pre-commit hooks to validate SARIF
|
||||
4. **Custom Rules**: Project-specific analyzer configurations
|
||||
5. **Trend Analysis**: Track metrics over time
|
||||
Reference in New Issue
Block a user