docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files

- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
2026-08-23 21:18:04 +00:00 · 2026-03-12 12:34:16 -07:00
parent 8937b0c0fa
commit 060649192f
1149 changed files with 1780 additions and 3316 deletions
@@ -0,0 +1,210 @@
+using QuanTAlib.Tests;
+using Skender.Stock.Indicators;
+using OoplesFinance.StockIndicators;
+using OoplesFinance.StockIndicators.Models;
+
+namespace QuanTAlib;
+
+public sealed class ConvValidationTests : IDisposable
+{
+    private readonly ValidationTestData _testData;
+    private bool _disposed;
+
+    public ConvValidationTests()
+    {
+        _testData = new ValidationTestData(count: 10000, seed: 123);
+    }
+
+    public void Dispose()
+    {
+        Dispose(true);
+    }
+
+    private void Dispose(bool disposing)
+    {
+        if (_disposed)
+        {
+            return;
+        }
+
+        _disposed = true;
+
+        if (disposing)
+        {
+            _testData?.Dispose();
+        }
+    }
+
+    private static double[] GenerateWmaKernel(int period)
+    {
+        double divisor = period * (period + 1) / 2.0;
+        double[] kernel = new double[period];
+        for (int i = 0; i < period; i++)
+        {
+            kernel[i] = (i + 1) / divisor;
+        }
+        return kernel;
+    }
+
+    [Fact]
+    public void Validate_Against_Sma()
+    {
+        // SMA(10) is equivalent to Conv with 10 weights of 1/10
+        const int period = 10;
+        double weight = 1.0 / period;
+        double[] kernel = new double[period];
+        Array.Fill(kernel, weight);
+
+        var sma = new Sma(period);
+        var conv = new Conv(kernel);
+
+        for (int i = 0; i < _testData.Data.Count; i++)
+        {
+            var item = _testData.Data[i];
+            var smaVal = sma.Update(item);
+            var convVal = conv.Update(item);
+
+            if (i >= period) // Skip warmup
+            {
+                Assert.Equal(smaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
+            }
+        }
+    }
+
+    [Fact]
+    public void Validate_Against_Wma()
+    {
+        int period = 10;
+        double[] kernel = GenerateWmaKernel(period);
+
+        var wma = new Wma(period);
+        var conv = new Conv(kernel);
+
+        for (int i = 0; i < _testData.Data.Count; i++)
+        {
+            var item = _testData.Data[i];
+            var wmaVal = wma.Update(item);
+            var convVal = conv.Update(item);
+
+            if (i >= period) // Skip warmup
+            {
+                Assert.Equal(wmaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
+            }
+        }
+    }
+
+    [Fact]
+    public void Validate_Against_Trima()
+    {
+        // TRIMA(10) - Even period
+        // Weights: 1, 2, 3, 4, 5, 5, 4, 3, 2, 1
+        // Sum: 30
+        int period = 10;
+        double[] kernel = new double[period];
+        double sum = 0;
+
+        // Generate triangular weights
+        int mid = period / 2;
+        for (int i = 0; i < period; i++)
+        {
+            double val = (i < mid) ? (i + 1) : (period - i);
+            kernel[i] = val;
+            sum += val;
+        }
+
+        // Normalize
+        for (int i = 0; i < period; i++)
+        {
+            kernel[i] /= sum;
+        }
+
+        var trima = new Trima(period);
+        var conv = new Conv(kernel);
+
+        for (int i = 0; i < _testData.Data.Count; i++)
+        {
+            var item = _testData.Data[i];
+            var trimaVal = trima.Update(item);
+            var convVal = conv.Update(item);
+
+            if (i >= period) // Skip warmup
+            {
+                Assert.Equal(trimaVal.Value, convVal.Value, ValidationHelper.DefaultTolerance);
+            }
+        }
+    }
+
+    [Fact]
+    public void Validate_Against_Skender_Wma()
+    {
+        int period = 14;
+        var skenderWma = _testData.SkenderQuotes.GetWma(period).ToList();
+        double[] kernel = GenerateWmaKernel(period);
+        var conv = new Conv(kernel);
+        var result = conv.Update(_testData.Data);
+
+        ValidationHelper.VerifyData(result, skenderWma, (s) => s.Wma, skip: period);
+    }
+
+    [Fact]
+    public void Validate_Against_TALib_Wma()
+    {
+        int period = 14;
+        double[] input = _testData.Data.Values.ToArray();
+        double[] output = new double[input.Length];
+
+        var retCode = TALib.Functions.Wma<double>(input, 0..^0, output, out var outRange, period);
+        Assert.Equal(TALib.Core.RetCode.Success, retCode);
+
+        double[] kernel = GenerateWmaKernel(period);
+        var conv = new Conv(kernel);
+        var result = conv.Update(_testData.Data);
+
+        ValidationHelper.VerifyData(result, output, outRange, lookback: period - 1);
+    }
+
+    [Fact]
+    public void Validate_Against_Tulip_Wma()
+    {
+        int period = 14;
+        double[] input = _testData.Data.Values.ToArray();
+
+        var wmaIndicator = Tulip.Indicators.wma;
+        double[][] inputs = { input };
+        double[] options = { period };
+        double[][] outputs = { new double[input.Length - period + 1] };
+
+        wmaIndicator.Run(inputs, options, outputs);
+        double[] output = outputs[0];
+
+        double[] kernel = GenerateWmaKernel(period);
+        var conv = new Conv(kernel);
+        var result = conv.Update(_testData.Data);
+
+        ValidationHelper.VerifyData(result, output, lookback: period - 1);
+    }
+
+    [Fact]
+    public void Validate_Against_Ooples_Wma()
+    {
+        int period = 14;
+        var ooplesData = _testData.SkenderQuotes.Select(q => new TickerData
+        {
+            Date = q.Date,
+            Open = (double)q.Open,
+            High = (double)q.High,
+            Low = (double)q.Low,
+            Close = (double)q.Close,
+            Volume = (double)q.Volume
+        }).ToList();
+
+        var stockData = new StockData(ooplesData);
+        var ooplesWma = stockData.CalculateWeightedMovingAverage(length: period).OutputValues["Wma"];
+
+        double[] kernel = GenerateWmaKernel(period);
+        var conv = new Conv(kernel);
+        var result = conv.Update(_testData.Data);
+
+        ValidationHelper.VerifyData(result, ooplesWma, (s) => s, skip: period, tolerance: ValidationHelper.OoplesTolerance);
+    }
+}