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

lib/trends_IIR/ema/tests/Ema.Quantower.Tests.cs

@@ -0,0 +1,168 @@
+using TradingPlatform.BusinessLayer;
+
+namespace QuanTAlib.Tests;
+
+public class EmaIndicatorTests
+{
+    [Fact]
+    public void EmaIndicator_Constructor_SetsDefaults()
+    {
+        var indicator = new EmaIndicator();
+
+        Assert.Equal(10, indicator.Period);
+        Assert.Equal(SourceType.Close, indicator.Source);
+        Assert.True(indicator.ShowColdValues);
+        Assert.Equal("EMA - Exponential Moving Average", indicator.Name);
+        Assert.False(indicator.SeparateWindow);
+        Assert.True(indicator.OnBackGround);
+    }
+
+    [Fact]
+    public void EmaIndicator_MinHistoryDepths_EqualsZero()
+    {
+        var indicator = new EmaIndicator { Period = 20 };
+
+        Assert.Equal(0, EmaIndicator.MinHistoryDepths);
+        Assert.Equal(0, ((IWatchlistIndicator)indicator).MinHistoryDepths);
+    }
+
+    [Fact]
+    public void EmaIndicator_ShortName_IncludesPeriodAndSource()
+    {
+        var indicator = new EmaIndicator { Period = 15 };
+
+        Assert.Contains("EMA", indicator.ShortName, StringComparison.Ordinal);
+        Assert.Contains("15", indicator.ShortName, StringComparison.Ordinal);
+    }
+
+    [Fact]
+    public void EmaIndicator_Initialize_CreatesInternalEma()
+    {
+        var indicator = new EmaIndicator { Period = 10 };
+
+        // Initialize should not throw
+        indicator.Initialize();
+
+        // After init, line series should exist
+        Assert.Single(indicator.LinesSeries);
+    }
+
+    [Fact]
+    public void EmaIndicator_ProcessUpdate_HistoricalBar_ComputesValue()
+    {
+        var indicator = new EmaIndicator { Period = 3 };
+        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
+        Assert.Equal(1, indicator.LinesSeries[0].Count);
+        Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)));
+    }
+
+    [Fact]
+    public void EmaIndicator_ProcessUpdate_NewBar_ComputesValue()
+    {
+        var indicator = new EmaIndicator { Period = 3 };
+        indicator.Initialize();
+
+        // Add historical data
+        var now = DateTime.UtcNow;
+        indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
+        indicator.HistoricalData.AddBar(now.AddMinutes(1), 102, 108, 100, 106);
+
+        // Process first update
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewBar));
+
+        // Line series should have values
+        Assert.Equal(2, indicator.LinesSeries[0].Count);
+    }
+
+    [Fact]
+    public void EmaIndicator_ProcessUpdate_NewTick_ProcessesWithoutError()
+    {
+        var indicator = new EmaIndicator { Period = 3 };
+        indicator.Initialize();
+
+        // Add historical data
+        var now = DateTime.UtcNow;
+        indicator.HistoricalData.AddBar(now, 100, 105, 95, 102);
+
+        // Process historical bar first
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+        double firstValue = indicator.LinesSeries[0].GetValue(0);
+
+        // Update with new tick (same bar data - simulates intrabar update)
+        indicator.ProcessUpdate(new UpdateArgs(UpdateReason.NewTick));
+        double secondValue = indicator.LinesSeries[0].GetValue(0);
+
+        // Both values should be finite
+        Assert.True(double.IsFinite(firstValue));
+        Assert.True(double.IsFinite(secondValue));
+    }
+
+    [Fact]
+    public void EmaIndicator_MultipleUpdates_ProducesCorrectEmaSequence()
+    {
+        var indicator = new EmaIndicator { Period = 3 };
+        indicator.Initialize();
+
+        var now = DateTime.UtcNow;
+        double[] closes = { 100, 102, 104, 103, 105, 107, 106 };
+
+        foreach (var close in closes)
+        {
+            indicator.HistoricalData.AddBar(now, close, close + 2, close - 2, close);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+            now = now.AddMinutes(1);
+        }
+
+        // All values should be finite
+        for (int i = 0; i < closes.Length; i++)
+        {
+            Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(closes.Length - 1 - i)));
+        }
+
+        // EMA should be smoothing the values
+        // Last EMA value should be between first and last close
+        double lastEma = indicator.LinesSeries[0].GetValue(0);
+        Assert.True(lastEma >= 100 && lastEma <= 110);
+    }
+
+    [Fact]
+    public void EmaIndicator_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 EmaIndicator { Period = 3, Source = source };
+            indicator.Initialize();
+
+            var now = DateTime.UtcNow;
+            indicator.HistoricalData.AddBar(now, 100, 110, 90, 105);
+            indicator.ProcessUpdate(new UpdateArgs(UpdateReason.HistoricalBar));
+
+            Assert.True(double.IsFinite(indicator.LinesSeries[0].GetValue(0)),
+                $"Source {source} should produce finite value");
+        }
+    }
+
+    [Fact]
+    public void EmaIndicator_Period_CanBeChanged()
+    {
+        var indicator = new EmaIndicator { Period = 5 };
+        Assert.Equal(5, indicator.Period);
+
+        indicator.Period = 20;
+        Assert.Equal(20, indicator.Period);
+        Assert.Equal(0, EmaIndicator.MinHistoryDepths);
+    }
+}

lib/trends_IIR/ema/tests/Ema.Tests.cs

@@ -0,0 +1,707 @@
+namespace QuanTAlib.Tests;
+
+public class EmaTests
+{
+    [Fact]
+    public void Ema_Constructor_Period_ValidatesInput()
+    {
+        Assert.Throws<ArgumentOutOfRangeException>(() => new Ema(0));
+        Assert.Throws<ArgumentOutOfRangeException>(() => new Ema(-1));
+
+        var ema = new Ema(10);
+        Assert.NotNull(ema);
+    }
+
+    [Fact]
+    public void Ema_Constructor_Alpha_ValidatesInput()
+    {
+        Assert.Throws<ArgumentException>(() => new Ema(0.0));
+        Assert.Throws<ArgumentException>(() => new Ema(-0.1));
+        Assert.Throws<ArgumentException>(() => new Ema(1.1));
+
+        var ema = new Ema(0.5);
+        Assert.NotNull(ema);
+    }
+
+    [Fact]
+    public void Ema_Calc_ReturnsValue()
+    {
+        var ema = new Ema(10);
+
+        Assert.Equal(0, ema.Last.Value);
+
+        TValue result = ema.Update(new TValue(DateTime.UtcNow, 100));
+
+        Assert.True(result.Value > 0);
+        Assert.Equal(result.Value, ema.Last.Value);
+    }
+
+    [Fact]
+    public void Ema_Calc_IsNew_AcceptsParameter()
+    {
+        var ema = new Ema(10);
+
+        ema.Update(new TValue(DateTime.UtcNow, 100), isNew: true);
+        double value1 = ema.Last.Value;
+
+        ema.Update(new TValue(DateTime.UtcNow, 105), isNew: true);
+        double value2 = ema.Last.Value;
+
+        // Values should change with new bars
+        Assert.NotEqual(value1, value2);
+    }
+
+    [Fact]
+    public void Ema_Calc_IsNew_False_UpdatesValue()
+    {
+        var ema = new Ema(10);
+
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, 110), isNew: true);
+        double beforeUpdate = ema.Last.Value;
+
+        ema.Update(new TValue(DateTime.UtcNow, 120), isNew: false);
+        double afterUpdate = ema.Last.Value;
+
+        // Update should change the value
+        Assert.NotEqual(beforeUpdate, afterUpdate);
+    }
+
+    [Fact]
+    public void Ema_Reset_ClearsState()
+    {
+        var ema = new Ema(10);
+
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, 105));
+        double valueBefore = ema.Last.Value;
+
+        ema.Reset();
+
+        Assert.Equal(0, ema.Last.Value);
+
+        // After reset, should accept new values
+        ema.Update(new TValue(DateTime.UtcNow, 50));
+        Assert.NotEqual(0, ema.Last.Value);
+        Assert.NotEqual(valueBefore, ema.Last.Value);
+    }
+
+    [Fact]
+    public void Ema_Properties_Accessible()
+    {
+        var ema = new Ema(10);
+
+        Assert.Equal(0, ema.Last.Value);
+        Assert.False(ema.IsHot);
+
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+
+        Assert.NotEqual(0, ema.Last.Value);
+    }
+
+    [Fact]
+    public void Ema_IsHot_BecomesTrueAt95PercentCoverage()
+    {
+        var ema = new Ema(10);
+
+        // Initially IsHot should be false
+        Assert.False(ema.IsHot);
+
+        // IsHot triggers at 95% coverage (E <= 0.05)
+        // E = (1 - alpha)^N where alpha = 2 / (period + 1)
+        // For period 10: alpha = 2/11 ≈ 0.1818, (1-alpha) ≈ 0.8182
+        // N = ln(0.05) / ln(0.8182) ≈ 14.93, so ~15 bars
+
+        int steps = 0;
+        while (!ema.IsHot && steps < 1000)
+        {
+            ema.Update(new TValue(DateTime.UtcNow, 100));
+            steps++;
+        }
+
+        Assert.True(ema.IsHot);
+        Assert.True(steps > 0);
+        // For period 10, should become hot around 15 bars
+        Assert.InRange(steps, 14, 16);
+    }
+
+    [Fact]
+    public void Ema_IsHot_IsPeriodDependent()
+    {
+        // Test that different periods result in different warmup times
+        // Formula: N = ln(0.05) / ln((p-1)/(p+1))
+
+        int[] periods = [10, 20, 50, 100];
+        int[] expectedSteps = new int[periods.Length];
+
+        for (int i = 0; i < periods.Length; i++)
+        {
+            int period = periods[i];
+            var ema = new Ema(period);
+
+            int steps = 0;
+            while (!ema.IsHot && steps < 500)
+            {
+                ema.Update(new TValue(DateTime.UtcNow, 100));
+                steps++;
+            }
+
+            expectedSteps[i] = steps;
+        }
+
+        // Verify warmup times increase with period
+        // Period 10 → ~15 bars, Period 20 → ~30 bars, Period 50 → ~75 bars, Period 100 → ~150 bars
+        Assert.True(expectedSteps[0] < expectedSteps[1], $"Period 10 ({expectedSteps[0]}) should be less than Period 20 ({expectedSteps[1]})");
+        Assert.True(expectedSteps[1] < expectedSteps[2], $"Period 20 ({expectedSteps[1]}) should be less than Period 50 ({expectedSteps[2]})");
+        Assert.True(expectedSteps[2] < expectedSteps[3], $"Period 50 ({expectedSteps[2]}) should be less than Period 100 ({expectedSteps[3]})");
+
+        // Verify approximate expected values (N ≈ 1.5 * period for 95% coverage)
+        Assert.InRange(expectedSteps[0], 14, 17);  // Period 10 → ~15
+        Assert.InRange(expectedSteps[1], 28, 32);  // Period 20 → ~30
+        Assert.InRange(expectedSteps[2], 73, 78);  // Period 50 → ~75
+        Assert.InRange(expectedSteps[3], 147, 153); // Period 100 → ~150
+    }
+
+    [Fact]
+    public void Ema_PeriodEquivalence_BothConstructorsWork()
+    {
+        const int period = 20;
+        double alpha = 2.0 / (period + 1);
+
+        var emaPeriod = new Ema(period);
+        var emaAlpha = new Ema(alpha);
+
+        // Both should accept Calc calls and produce same result
+        TValue result1 = emaPeriod.Update(new TValue(DateTime.UtcNow, 100));
+        TValue result2 = emaAlpha.Update(new TValue(DateTime.UtcNow, 100));
+
+        Assert.Equal(result1.Value, result2.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Ema_IterativeCorrections_RestoreToOriginalState()
+    {
+        var ema = new Ema(10);
+        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
+
+        // Feed 10 new values
+        TValue tenthInput = default;
+        for (int i = 0; i < 10; i++)
+        {
+            var bar = gbm.Next(isNew: true);
+            tenthInput = new TValue(bar.Time, bar.Close);
+            ema.Update(tenthInput, isNew: true);
+        }
+
+        // Remember EMA state after 10 values
+        double emaAfterTen = ema.Last.Value;
+
+        // Generate 9 corrections with isNew=false (different values)
+        for (int i = 0; i < 9; i++)
+        {
+            var bar = gbm.Next(isNew: false);
+            ema.Update(new TValue(bar.Time, bar.Close), isNew: false);
+        }
+
+        // Feed the remembered 10th input again with isNew=false
+        TValue finalEma = ema.Update(tenthInput, isNew: false);
+
+        // EMA should match the original state after 10 values
+        Assert.Equal(emaAfterTen, finalEma.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Ema_BatchCalc_MatchesIterativeCalc()
+    {
+        var emaIterative = new Ema(10);
+        var emaBatch = new Ema(10);
+        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1);
+
+        // Generate data
+        var series = new TSeries();
+        for (int i = 0; i < 100; i++)
+        {
+            var bar = gbm.Next(isNew: true);
+            series.Add(bar.Time, bar.Close);
+        }
+
+        Assert.True(series.Count > 0);
+
+        // Calculate iteratively
+        var iterativeResults = new TSeries();
+        foreach (var item in series)
+        {
+            iterativeResults.Add(emaIterative.Update(item));
+        }
+
+        // Calculate batch
+        var batchResults = emaBatch.Update(series);
+
+        // Compare
+        Assert.Equal(iterativeResults.Count, batchResults.Count);
+        for (int i = 0; i < iterativeResults.Count; i++)
+        {
+            Assert.Equal(iterativeResults[i].Value, batchResults[i].Value, 1e-10);
+            Assert.Equal(iterativeResults[i].Time, batchResults[i].Time);
+        }
+    }
+
+    [Fact]
+    public void Ema_Result_ImplicitConversionToDouble()
+    {
+        var ema = new Ema(10);
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+
+        // This should compile and work because TValue has implicit conversion to double
+        double result = ema.Last.Value;
+
+        Assert.Equal(100.0, result, 1e-10);
+    }
+
+    [Fact]
+    public void Ema_NaN_Input_UsesLastValidValue()
+    {
+        var ema = new Ema(10);
+
+        // Feed some valid values
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, 110));
+
+        // Feed NaN - should use last valid value (110)
+        var resultAfterNaN = ema.Update(new TValue(DateTime.UtcNow, double.NaN));
+
+        // Result should be finite (not NaN)
+        Assert.True(double.IsFinite(resultAfterNaN.Value));
+        // EMA should continue to evolve (may differ slightly due to substitution)
+        Assert.NotEqual(0, resultAfterNaN.Value);
+    }
+
+    [Fact]
+    public void Ema_Infinity_Input_UsesLastValidValue()
+    {
+        var ema = new Ema(10);
+
+        // Feed some valid values
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, 110));
+
+        // Feed positive infinity - should use last valid value
+        var resultAfterPosInf = ema.Update(new TValue(DateTime.UtcNow, double.PositiveInfinity));
+        Assert.True(double.IsFinite(resultAfterPosInf.Value));
+
+        // Feed negative infinity - should use last valid value
+        var resultAfterNegInf = ema.Update(new TValue(DateTime.UtcNow, double.NegativeInfinity));
+        Assert.True(double.IsFinite(resultAfterNegInf.Value));
+    }
+
+    [Fact]
+    public void Ema_MultipleNaN_ContinuesWithLastValid()
+    {
+        var ema = new Ema(10);
+
+        // Feed valid values
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, 110));
+        ema.Update(new TValue(DateTime.UtcNow, 120));
+
+        // Feed multiple NaN values
+        var r1 = ema.Update(new TValue(DateTime.UtcNow, double.NaN));
+        var r2 = ema.Update(new TValue(DateTime.UtcNow, double.NaN));
+        var r3 = ema.Update(new TValue(DateTime.UtcNow, double.NaN));
+
+        // All results should be finite
+        Assert.True(double.IsFinite(r1.Value));
+        Assert.True(double.IsFinite(r2.Value));
+        Assert.True(double.IsFinite(r3.Value));
+
+        // EMA should converge toward last valid value (120) with repeated substitution
+        // Values should be getting closer to 120
+        Assert.True(r3.Value > r1.Value || Math.Abs(r3.Value - 120) < Math.Abs(r1.Value - 120));
+    }
+
+    [Fact]
+    public void Ema_BatchCalc_HandlesNaN()
+    {
+        var ema = new Ema(10);
+
+        // Create series with NaN values interspersed
+        var series = new TSeries();
+        series.Add(DateTime.UtcNow.Ticks, 100);
+        series.Add(DateTime.UtcNow.Ticks + 1, 110);
+        series.Add(DateTime.UtcNow.Ticks + 2, double.NaN);
+        series.Add(DateTime.UtcNow.Ticks + 3, 120);
+        series.Add(DateTime.UtcNow.Ticks + 4, double.PositiveInfinity);
+        series.Add(DateTime.UtcNow.Ticks + 5, 130);
+
+        var results = ema.Update(series);
+
+        // All results should be finite
+        foreach (var result in results)
+        {
+            Assert.True(double.IsFinite(result.Value), $"Expected finite value but got {result.Value}");
+        }
+    }
+
+    [Fact]
+    public void Ema_Reset_ClearsLastValidValue()
+    {
+        var ema = new Ema(10);
+
+        // Feed values including NaN
+        ema.Update(new TValue(DateTime.UtcNow, 100));
+        ema.Update(new TValue(DateTime.UtcNow, double.NaN));
+
+        // Reset
+        ema.Reset();
+
+        // After reset, first valid value should establish new baseline
+        var result = ema.Update(new TValue(DateTime.UtcNow, 50));
+        Assert.Equal(50.0, result.Value, 1e-10);
+    }
+
+    // ============== Span API Tests ==============
+
+    [Fact]
+    public void Ema_SpanBatch_Period_ValidatesInput()
+    {
+        double[] source = [1, 2, 3, 4, 5];
+        double[] output = new double[5];
+        double[] wrongSizeOutput = new double[3];
+
+        // Period must be > 0
+        Assert.Throws<ArgumentException>(() => Ema.Batch(source.AsSpan(), output.AsSpan(), 0));
+        Assert.Throws<ArgumentException>(() => Ema.Batch(source.AsSpan(), output.AsSpan(), -1));
+
+        // Output must be same length as source
+        Assert.Throws<ArgumentException>(() => Ema.Batch(source.AsSpan(), wrongSizeOutput.AsSpan(), 3));
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_Alpha_ValidatesInput()
+    {
+        double[] source = [1, 2, 3, 4, 5];
+        double[] output = new double[5];
+
+        // Alpha must be > 0 and <= 1
+        Assert.Throws<ArgumentOutOfRangeException>(() => Ema.Batch(source.AsSpan(), output.AsSpan(), 0.0));
+        Assert.Throws<ArgumentOutOfRangeException>(() => Ema.Batch(source.AsSpan(), output.AsSpan(), -0.1));
+        Assert.Throws<ArgumentOutOfRangeException>(() => Ema.Batch(source.AsSpan(), output.AsSpan(), 1.1));
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_MatchesTSeriesBatch()
+    {
+        var series = new TSeries();
+        double[] source = new double[100];
+        double[] output = new double[100];
+
+        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.1, seed: 42);
+        for (int i = 0; i < 100; i++)
+        {
+            var bar = gbm.Next(isNew: true);
+            source[i] = bar.Close;
+            series.Add(bar.Time, bar.Close);
+        }
+
+        // Calculate with TSeries API
+        var tseriesResult = Ema.Batch(series, 10);
+
+        // Calculate with Span API
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 10);
+
+        // Compare results - allow small tolerance due to bias correction differences
+        for (int i = 0; i < 100; i++)
+        {
+            Assert.Equal(tseriesResult[i].Value, output[i], 1e-9);
+        }
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_PeriodAndAlphaEquivalent()
+    {
+        double[] source = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100];
+        double[] outputPeriod = new double[10];
+        double[] outputAlpha = new double[10];
+
+        int period = 5;
+        double alpha = 2.0 / (period + 1);
+
+        Ema.Batch(source.AsSpan(), outputPeriod.AsSpan(), period);
+        Ema.Batch(source.AsSpan(), outputAlpha.AsSpan(), alpha);
+
+        // Results should be identical
+        for (int i = 0; i < 10; i++)
+        {
+            Assert.Equal(outputPeriod[i], outputAlpha[i], 1e-10);
+        }
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_ZeroAllocation()
+    {
+        double[] source = new double[10000];
+        double[] output = new double[10000];
+
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 42);
+        for (int i = 0; i < source.Length; i++)
+        {
+            source[i] = gbm.Next().Close;
+        }
+
+        // Warm up
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 100);
+
+        // This test verifies the method runs without throwing
+        Assert.True(double.IsFinite(output[^1]));
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_HandlesNaN()
+    {
+        double[] source = [100, 110, double.NaN, 120, 130];
+        double[] output = new double[5];
+
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 3);
+
+        // All outputs should be finite
+        foreach (var val in output)
+        {
+            Assert.True(double.IsFinite(val), $"Expected finite value but got {val}");
+        }
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_BiasCorrection_Works()
+    {
+        double[] source = [100, 100, 100, 100, 100];
+        double[] output = new double[5];
+
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 3);
+
+        // With bias correction, first value should equal input
+        Assert.Equal(100.0, output[0], 1e-10);
+
+        // All values should converge to 100 since input is constant
+        foreach (var val in output)
+        {
+            Assert.Equal(100.0, val, 1e-9);
+        }
+    }
+
+    [Fact]
+    public void Ema_SpanBatch_Alpha_DirectUsage()
+    {
+        double[] source = [10, 20, 30, 40, 50];
+        double[] output = new double[5];
+
+        // Use alpha = 0.5 directly
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 0.5);
+
+        // Results should be finite and reasonable
+        Assert.True(double.IsFinite(output[^1]));
+        Assert.True(output[^1] > 10 && output[^1] <= 50);
+    }
+
+    [Fact]
+    public void Chainability_Works()
+    {
+        var source = new TSeries();
+        var ema = new Ema(source, 10);
+
+        source.Add(new TValue(DateTime.UtcNow, 100));
+        Assert.Equal(100, ema.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Prime_SetsStateCorrectly()
+    {
+        var ema = new Ema(5);
+        double[] history = [10, 20, 30, 40, 50];
+
+        ema.Prime(history);
+
+        // EMA(5) of 10,20,30,40,50
+        // Alpha = 2/6 = 1/3
+        // 10 -> 10
+        // 20 -> 10 + 1/3(10) = 13.33...
+        // ...
+        // We can verify against a fresh EMA fed with same data
+        var verifyEma = new Ema(5);
+        foreach (var val in history)
+        {
+            verifyEma.Update(new TValue(DateTime.UtcNow, val));
+        }
+
+        Assert.Equal(verifyEma.Last.Value, ema.Last.Value, 1e-10);
+        Assert.Equal(verifyEma.IsHot, ema.IsHot);
+
+        // Verify it continues correctly
+        ema.Update(new TValue(DateTime.UtcNow, 60));
+        verifyEma.Update(new TValue(DateTime.UtcNow, 60));
+        Assert.Equal(verifyEma.Last.Value, ema.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Prime_HandlesNaN_InHistory()
+    {
+        var ema = new Ema(5);
+        double[] history = [10, 20, double.NaN, 40, 50];
+
+        ema.Prime(history);
+
+        var verifyEma = new Ema(5);
+        foreach (var val in history)
+        {
+            verifyEma.Update(new TValue(DateTime.UtcNow, val));
+        }
+
+        Assert.Equal(verifyEma.Last.Value, ema.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Prime_AllNaNs_ReturnsNaN()
+    {
+        var ema = new Ema(5);
+        double[] history = [double.NaN, double.NaN, double.NaN];
+
+        ema.Prime(history);
+
+        Assert.True(double.IsNaN(ema.Last.Value));
+    }
+
+    [Fact]
+    public void Calculate_ReturnsCorrectResultsAndHotIndicator()
+    {
+        var series = new TSeries();
+        for (int i = 1; i <= 20; i++)
+        {
+            series.Add(DateTime.UtcNow, i * 10);
+        }
+
+        // EMA(5)
+        var (results, indicator) = Ema.Calculate(series, 5);
+
+        // Check results
+        Assert.Equal(20, results.Count);
+
+        // Verify against standard calculation
+        var verifyEma = new Ema(5);
+        var verifyResults = verifyEma.Update(series);
+
+        Assert.Equal(verifyResults.Last.Value, results.Last.Value, 1e-10);
+        Assert.Equal(verifyEma.Last.Value, indicator.Last.Value, 1e-10);
+
+        // Check indicator state
+        Assert.True(indicator.IsHot);
+
+        // Verify indicator continues correctly
+        indicator.Update(new TValue(DateTime.UtcNow, 210));
+        verifyEma.Update(new TValue(DateTime.UtcNow, 210));
+        Assert.Equal(verifyEma.Last.Value, indicator.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Ema_Batch_AllNaNs_ReturnsNaN()
+    {
+        double[] source = [double.NaN, double.NaN, double.NaN];
+        double[] output = new double[3];
+
+        Ema.Batch(source.AsSpan(), output.AsSpan(), 5);
+
+        // Should be all NaNs, not 0s
+        foreach (var val in output)
+        {
+            Assert.True(double.IsNaN(val), $"Expected NaN but got {val}");
+        }
+    }
+
+    [Fact]
+    public void Ema_AllModes_ProduceSameResult()
+    {
+        // Arrange
+        int period = 10;
+        var gbm = new GBM(startPrice: 100, mu: 0.05, sigma: 0.2, seed: 123);
+        var bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        var series = bars.Close;
+
+        // 1. Batch Mode
+        var batchSeries = Ema.Batch(series, period);
+        double expected = batchSeries.Last.Value;
+
+        // 2. Span Mode
+        var tValues = series.Values.ToArray(); // Need array for Span modification safety if any
+        var spanInput = new ReadOnlySpan<double>(tValues);
+        var spanOutput = new double[tValues.Length];
+        Ema.Batch(spanInput, spanOutput, period);
+        double spanResult = spanOutput[^1];
+
+        // 3. Streaming Mode
+        var streamingInd = new Ema(period);
+        for (int i = 0; i < series.Count; i++)
+        {
+            streamingInd.Update(series[i]);
+        }
+        double streamingResult = streamingInd.Last.Value;
+
+        // 4. Eventing Mode
+        var pubSource = new TSeries();
+        var eventingInd = new Ema(pubSource, period);
+        for (int i = 0; i < series.Count; i++)
+        {
+            pubSource.Add(series[i]);
+        }
+        double eventingResult = eventingInd.Last.Value;
+
+        // Assert
+        // Precision 9 due to potential accumulation differences in loop vs batch optimizations
+        Assert.Equal(expected, spanResult, precision: 9);
+        Assert.Equal(expected, streamingResult, precision: 9);
+        Assert.Equal(expected, eventingResult, precision: 9);
+    }
+
+    [Fact]
+    public void Prime_SingleValue_SetsState()
+    {
+        var ema = new Ema(5);
+        double[] history = [100];
+
+        ema.Prime(history);
+
+        // Single value should be returned as-is (bias-corrected to itself)
+        Assert.Equal(100.0, ema.Last.Value, 1e-10);
+        Assert.False(ema.IsHot); // Not hot with only 1 value
+
+        // Verify against streaming
+        var verifyEma = new Ema(5);
+        verifyEma.Update(new TValue(DateTime.UtcNow, 100));
+        Assert.Equal(verifyEma.Last.Value, ema.Last.Value, 1e-10);
+    }
+
+    [Fact]
+    public void Prime_ThenUpdate_StateWorksCorrectly()
+    {
+        var ema = new Ema(5);
+        double[] history = [10, 20, 30, 40, 50];
+
+        ema.Prime(history);
+        double afterPrime = ema.Last.Value;
+
+        // After Prime, an isNew=true should advance the state
+        ema.Update(new TValue(DateTime.UtcNow, 60), isNew: true);
+        double afterNewBar = ema.Last.Value;
+
+        // Values should be different
+        Assert.NotEqual(afterPrime, afterNewBar);
+
+        // isNew=false with a different value should recalculate from previous state
+        ema.Update(new TValue(DateTime.UtcNow, 70), isNew: false);
+        double afterCorrection = ema.Last.Value;
+
+        // Correction with 70 should give different result than 60
+        Assert.NotEqual(afterNewBar, afterCorrection);
+
+        // isNew=false with original value (60) should restore to afterNewBar
+        ema.Update(new TValue(DateTime.UtcNow, 60), isNew: false);
+        Assert.Equal(afterNewBar, ema.Last.Value, 1e-10);
+    }
+}

lib/trends_IIR/ema/tests/Ema.Validation.Tests.cs

@@ -0,0 +1,316 @@
+using OoplesFinance.StockIndicators;
+using OoplesFinance.StockIndicators.Models;
+using Skender.Stock.Indicators;
+using TALib;
+using Xunit.Abstractions;
+
+namespace QuanTAlib.Tests;
+
+public sealed class EmaValidationTests : IDisposable
+{
+    private readonly ValidationTestData _testData;
+    private readonly ITestOutputHelper _output;
+    private bool _disposed;
+
+    public EmaValidationTests(ITestOutputHelper output)
+    {
+        _output = output;
+        _testData = new ValidationTestData();
+    }
+
+    public void Dispose()
+    {
+        Dispose(true);
+    }
+
+    private void Dispose(bool disposing)
+    {
+        if (_disposed)
+        {
+            return;
+        }
+
+        _disposed = true;
+
+        if (disposing)
+        {
+            _testData?.Dispose();
+        }
+    }
+
+    [Fact]
+    public void Validate_Skender_Batch()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (batch TSeries)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResult = ema.Update(_testData.Data);
+
+            // Calculate Skender EMA
+            var sResult = _testData.SkenderQuotes.GetEma(period).ToList();
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResult, sResult, (s) => s.Ema);
+        }
+        _output.WriteLine("EMA Batch(TSeries) validated successfully against Skender");
+    }
+
+    [Fact]
+    public void Validate_Skender_Streaming()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (streaming)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResults = new List<double>();
+            foreach (var item in _testData.Data)
+            {
+                qResults.Add(ema.Update(item).Value);
+            }
+
+            // Calculate Skender EMA
+            var sResult = _testData.SkenderQuotes.GetEma(period).ToList();
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResults, sResult, (s) => s.Ema);
+        }
+        _output.WriteLine("EMA Streaming validated successfully against Skender");
+    }
+
+    [Fact]
+    public void Validate_Skender_Span()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for Span API
+        double[] sourceData = _testData.RawData.ToArray();
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (Span API)
+            double[] qOutput = new double[sourceData.Length];
+            global::QuanTAlib.Ema.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
+
+            // Calculate Skender EMA
+            var sResult = _testData.SkenderQuotes.GetEma(period).ToList();
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qOutput, sResult, (s) => s.Ema);
+        }
+        _output.WriteLine("EMA Span validated successfully against Skender");
+    }
+
+    [Fact]
+    public void Validate_Talib_Batch()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for TA-Lib (double[])
+        double[] tData = _testData.RawData.ToArray();
+        double[] output = new double[tData.Length];
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (batch TSeries)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResult = ema.Update(_testData.Data);
+
+            // Calculate TA-Lib EMA
+            var retCode = TALib.Functions.Ema<double>(tData, 0..^0, output, out var outRange, period);
+            Assert.Equal(TALib.Core.RetCode.Success, retCode);
+
+            int lookback = TALib.Functions.EmaLookback(period);
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResult, output, outRange, lookback);
+        }
+        _output.WriteLine("EMA Batch(TSeries) validated successfully against TA-Lib");
+    }
+
+    [Fact]
+    public void Validate_Talib_Streaming()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for TA-Lib (double[])
+        double[] tData = _testData.RawData.ToArray();
+        double[] output = new double[tData.Length];
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (streaming)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResults = new List<double>();
+            foreach (var item in _testData.Data)
+            {
+                qResults.Add(ema.Update(item).Value);
+            }
+
+            // Calculate TA-Lib EMA
+            var retCode = TALib.Functions.Ema<double>(tData, 0..^0, output, out var outRange, period);
+            Assert.Equal(TALib.Core.RetCode.Success, retCode);
+
+            int lookback = TALib.Functions.EmaLookback(period);
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResults, output, outRange, lookback);
+        }
+        _output.WriteLine("EMA Streaming validated successfully against TA-Lib");
+    }
+
+    [Fact]
+    public void Validate_Talib_Span()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data
+        double[] sourceData = _testData.RawData.ToArray();
+        double[] talibOutput = new double[sourceData.Length];
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (Span API)
+            double[] qOutput = new double[sourceData.Length];
+            global::QuanTAlib.Ema.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
+
+            // Calculate TA-Lib EMA
+            var retCode = TALib.Functions.Ema<double>(sourceData, 0..^0, talibOutput, out var outRange, period);
+            Assert.Equal(TALib.Core.RetCode.Success, retCode);
+
+            int lookback = TALib.Functions.EmaLookback(period);
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qOutput, talibOutput, outRange, lookback);
+        }
+        _output.WriteLine("EMA Span validated successfully against TA-Lib");
+    }
+
+    [Fact]
+    public void Validate_Tulip_Batch()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for Tulip (double[])
+        double[] tData = _testData.RawData.ToArray();
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (batch TSeries)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResult = ema.Update(_testData.Data);
+
+            // Calculate Tulip EMA
+            var emaIndicator = Tulip.Indicators.ema;
+            double[][] inputs = { tData };
+            double[] options = { period };
+            double[][] outputs = { new double[tData.Length] };
+
+            emaIndicator.Run(inputs, options, outputs);
+            var tResult = outputs[0];
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResult, tResult, 0);
+        }
+        _output.WriteLine("EMA Batch(TSeries) validated successfully against Tulip");
+    }
+
+    [Fact]
+    public void Validate_Tulip_Streaming()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for Tulip (double[])
+        double[] tData = _testData.RawData.ToArray();
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (streaming)
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResults = new List<double>();
+            foreach (var item in _testData.Data)
+            {
+                qResults.Add(ema.Update(item).Value);
+            }
+
+            // Calculate Tulip EMA
+            var emaIndicator = Tulip.Indicators.ema;
+            double[][] inputs = { tData };
+            double[] options = { period };
+            double[][] outputs = { new double[tData.Length] };
+
+            emaIndicator.Run(inputs, options, outputs);
+            var tResult = outputs[0];
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qResults, tResult, 0);
+        }
+        _output.WriteLine("EMA Streaming validated successfully against Tulip");
+    }
+
+    [Fact]
+    public void Validate_Tulip_Span()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data
+        double[] sourceData = _testData.RawData.ToArray();
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA (Span API)
+            double[] qOutput = new double[sourceData.Length];
+            global::QuanTAlib.Ema.Batch(sourceData.AsSpan(), qOutput.AsSpan(), period);
+
+            // Calculate Tulip EMA
+            var emaIndicator = Tulip.Indicators.ema;
+            double[][] inputs = { sourceData };
+            double[] options = { period };
+            double[][] outputs = { new double[sourceData.Length] };
+
+            emaIndicator.Run(inputs, options, outputs);
+            var tResult = outputs[0];
+
+            // Compare last 100 records
+            ValidationHelper.VerifyData(qOutput, tResult, 0);
+        }
+        _output.WriteLine("EMA Span validated successfully against Tulip");
+    }
+
+    [Fact]
+    public void Validate_Against_Ooples()
+    {
+        int[] periods = { 5, 10, 20, 50, 100 };
+
+        // Prepare data for Ooples (List<TickerData>)
+        var ooplesData = _testData.SkenderQuotes.Select(q => new TickerData
+        {
+            Date = q.Date,
+            Close = (double)q.Close,
+            High = (double)q.High,
+            Low = (double)q.Low,
+            Open = (double)q.Open,
+            Volume = (double)q.Volume
+        }).ToList();
+
+        foreach (var period in periods)
+        {
+            // Calculate QuanTAlib EMA
+            var ema = new global::QuanTAlib.Ema(period);
+            var qResult = ema.Update(_testData.Data);
+
+            // Calculate Ooples EMA
+            var stockData = new StockData(ooplesData);
+            var oResult = stockData.CalculateExponentialMovingAverage(period);
+            var oValues = oResult.OutputValues.Values.First();
+
+            // Compare
+            ValidationHelper.VerifyData(qResult, oValues, (s) => s, tolerance: ValidationHelper.OoplesTolerance);
+        }
+        _output.WriteLine("EMA validated successfully against Ooples");
+    }
+}