Add TTM Scalper indicator implementation in C# and Pine Script; update Blma class for average calculation; remove missing indicators report and oscillator docs rewrite plans.

lib/reversals/psar/Psar.Validation.Tests.cs

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+// PSAR Validation Tests - Parabolic Stop And Reverse
+// Cross-validated against Skender.Stock.Indicators GetParabolicSar()
+
+using Skender.Stock.Indicators;
+
+namespace QuanTAlib.Tests;
+
+public sealed class PsarValidationTests
+{
+    private static TBarSeries CreateGbmBars(int count = 500, int seed = 42)
+    {
+        var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.20, seed: seed);
+        return gbm.Fetch(count, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+    }
+
+    // ── Cross-library: Skender ───────────────────────────────────────────
+
+    [Fact]
+    public void StreamingMatchesSkender()
+    {
+        var _data = new ValidationTestData();
+
+        // Skender: GetParabolicSar(accelerationStep, maxAccelerationFactor, initialFactor)
+        var skenderResults = _data.SkenderQuotes
+            .GetParabolicSar(0.02, 0.2, 0.02)
+            .ToList();
+
+        // QuanTAlib streaming
+        var psar = new Psar(afStart: 0.02, afIncrement: 0.02, afMax: 0.20);
+        var ourValues = new double[_data.Bars.Count];
+        for (int i = 0; i < _data.Bars.Count; i++)
+        {
+            _ = psar.Update(_data.Bars[i], isNew: true);
+            ourValues[i] = psar.Sar;
+        }
+
+        // Compare warm values (skip first bar where SAR is initialization)
+        int matched = 0;
+        for (int i = 2; i < skenderResults.Count && i < _data.Bars.Count; i++)
+        {
+            if (skenderResults[i].Sar.HasValue && double.IsFinite(ourValues[i]))
+            {
+                Assert.Equal(
+                    skenderResults[i].Sar!.Value,
+                    ourValues[i],
+                    precision: 6);
+                matched++;
+            }
+        }
+
+        Assert.True(matched > 0, "Should have matched at least one warm value");
+        _data.Dispose();
+    }
+
+    // ── Self-Consistency: Streaming == Batch ──────────────────────────────
+
+    [Fact]
+    public void StreamingMatchesBatch()
+    {
+        var bars = CreateGbmBars();
+
+        // Streaming
+        var streaming = new Psar();
+        var streamValues = new double[bars.Count];
+        for (int i = 0; i < bars.Count; i++)
+        {
+            _ = streaming.Update(bars[i], isNew: true);
+            streamValues[i] = streaming.Sar;
+        }
+
+        // Batch
+        var batchResults = Psar.Batch(bars);
+
+        for (int i = 0; i < bars.Count; i++)
+        {
+            Assert.Equal(streamValues[i], batchResults[i].Value, precision: 10);
+        }
+    }
+
+    // ── Self-Consistency: Streaming == Span ───────────────────────────────
+
+    [Fact]
+    public void StreamingMatchesSpan()
+    {
+        var bars = CreateGbmBars();
+
+        // Streaming
+        var streaming = new Psar();
+        var streamValues = new double[bars.Count];
+        for (int i = 0; i < bars.Count; i++)
+        {
+            _ = streaming.Update(bars[i], isNew: true);
+            streamValues[i] = streaming.Sar;
+        }
+
+        // Span
+        var spanOutput = new double[bars.Count];
+        Psar.Batch(bars.OpenValues, bars.HighValues, bars.LowValues, bars.CloseValues, spanOutput);
+
+        for (int i = 0; i < bars.Count; i++)
+        {
+            Assert.Equal(streamValues[i], spanOutput[i], precision: 10);
+        }
+    }
+
+    // ── AF Sensitivity ───────────────────────────────────────────────────
+
+    [Fact]
+    public void HigherAfStart_TighterTrailingStop()
+    {
+        var bars = CreateGbmBars(count: 100);
+
+        var slow = new Psar(afStart: 0.01, afIncrement: 0.01, afMax: 0.20);
+        var fast = new Psar(afStart: 0.10, afIncrement: 0.05, afMax: 0.50);
+
+        for (int i = 0; i < bars.Count; i++)
+        {
+            _ = slow.Update(bars[i], isNew: true);
+            _ = fast.Update(bars[i], isNew: true);
+        }
+
+        // Higher AF = more responsive = SAR closer to price
+        // Just verify both produce finite output (direction depends on data)
+        Assert.True(double.IsFinite(slow.Sar));
+        Assert.True(double.IsFinite(fast.Sar));
+    }
+
+    // ── Determinism ──────────────────────────────────────────────────────
+
+    [Fact]
+    public void SameInput_ProducesSameOutput()
+    {
+        var bars = CreateGbmBars(count: 200, seed: 123);
+
+        var psar1 = new Psar();
+        var psar2 = new Psar();
+
+        for (int i = 0; i < bars.Count; i++)
+        {
+            _ = psar1.Update(bars[i], isNew: true);
+            _ = psar2.Update(bars[i], isNew: true);
+        }
+
+        Assert.Equal(psar1.Sar, psar2.Sar);
+    }
+
+    // ── Calculate Returns Valid Indicator ─────────────────────────────────
+
+    [Fact]
+    public void Calculate_ReturnsValidIndicatorAndResults()
+    {
+        var bars = CreateGbmBars(count: 100);
+
+        var (results, indicator) = Psar.Calculate(bars);
+
+        Assert.NotNull(results);
+        Assert.Equal(bars.Count, results.Count);
+        Assert.True(indicator.IsHot);
+        Assert.True(double.IsFinite(indicator.Sar));
+    }
+
+    // ── Reversal Count Is Reasonable ─────────────────────────────────────
+
+    [Fact]
+    public void ReversalCount_IsReasonable()
+    {
+        var bars = CreateGbmBars(count: 500);
+        var psar = new Psar();
+
+        int reversals = 0;
+        bool prevIsLong = true;
+
+        for (int i = 0; i < bars.Count; i++)
+        {
+            _ = psar.Update(bars[i], isNew: true);
+
+            if (i > 0 && psar.IsLong != prevIsLong)
+            {
+                reversals++;
+            }
+            prevIsLong = psar.IsLong;
+        }
+
+        // In 500 bars of GBM data, expect several reversals but not every bar
+        Assert.True(reversals > 5, $"Expected > 5 reversals, got {reversals}");
+        Assert.True(reversals < 250, $"Expected < 250 reversals, got {reversals}");
+    }
+}