Add TBar, TBarSeries, TSeries, TValue, and IFeed implementations with comprehensive documentation and examples

- Introduced TBar struct for efficient OHLCV data representation.
- Implemented TBarSeries class for high-performance collection of TBar instances using Structure of Arrays (SoA) layout.
- Added TSeries class for time-series data management with zero-copy access.
- Created TValue struct for time-value pairs with implicit conversions.
- Defined IFeed interface for consistent data feed implementations.
- Developed CsvFeed class for loading historical OHLCV data from CSV files.
- Implemented GBM class for generating synthetic financial data using Geometric Brownian Motion.
- Added Quantower project files for Averages indicator with necessary dependencies and configurations.
- Included extensive usage examples and notebooks for TBar, TBarSeries, TSeries, TValue, and feed implementations.

lib/averages/ema/EmaVector.Tests.cs

@@ -0,0 +1,138 @@
+using System;
+using System.Linq;
+using Xunit;
+using QuanTAlib;
+
+namespace QuanTAlib.Tests;
+
+public class EmaVectorTests
+{
+    [Fact]
+    public void Initialization_WithPeriods_SetsCorrectAlphas()
+    {
+        int[] periods = { 10, 20 };
+        var emaVector = new EmaVector(periods);
+        
+        // We can't check private fields directly, but we can check results after 1 step
+        // Alpha = 2 / (P + 1)
+        // P=10 -> A=2/11
+        // P=20 -> A=2/21
+        
+        var res = emaVector.Update(new TValue(DateTime.Now, 100.0));
+        
+        // First value should be 100.0 due to compensation
+        Assert.Equal(100.0, res[0].Value, 1e-9);
+        Assert.Equal(100.0, res[1].Value, 1e-9);
+    }
+
+    [Fact]
+    public void Calc_Streaming_MatchesSingleEma()
+    {
+        int[] periods = { 5, 10, 20 };
+        var emaVector = new EmaVector(periods);
+        var emaSingles = periods.Select(p => new Ema(p)).ToArray();
+        
+        var values = new double[] { 10, 20, 30, 40, 50, 40, 30, 20, 10 };
+        var time = DateTime.Now;
+
+        foreach (var val in values)
+        {
+            var tVal = new TValue(time, val);
+            var multiRes = emaVector.Update(tVal);
+            
+            for (int i = 0; i < periods.Length; i++)
+            {
+                var singleRes = emaSingles[i].Update(tVal);
+                Assert.Equal(singleRes.Value, multiRes[i].Value, 1e-9);
+                Assert.Equal(singleRes.Time, multiRes[i].Time);
+            }
+            
+            time = time.AddMinutes(1);
+        }
+    }
+
+    [Fact]
+    public void Calc_Series_MatchesSingleEma()
+    {
+        int[] periods = { 5, 10, 20 };
+        var emaVector = new EmaVector(periods);
+        var emaSingles = periods.Select(p => new Ema(p)).ToArray();
+        
+        int len = 100;
+        var t = new System.Collections.Generic.List<long>(len);
+        var v = new System.Collections.Generic.List<double>(len);
+        var now = DateTime.Now;
+        
+        for (int i = 0; i < len; i++)
+        {
+            t.Add(now.AddMinutes(i).Ticks);
+            v.Add(Math.Sin(i * 0.1) * 100);
+        }
+        
+        var series = new TSeries(t, v);
+        
+        var multiRes = emaVector.Calculate(series);
+        
+        for (int i = 0; i < periods.Length; i++)
+        {
+            var singleRes = emaSingles[i].Update(series);
+            
+            Assert.Equal(singleRes.Count, multiRes[i].Count);
+            for (int j = 0; j < len; j++)
+            {
+                Assert.Equal(singleRes.Values[j], multiRes[i].Values[j], 1e-8);
+            }
+        }
+    }
+
+    [Fact]
+    public void Calc_Series_MatchesStreaming()
+    {
+        int[] periods = { 5, 10, 20 };
+        var emaVectorBatch = new EmaVector(periods);
+        var emaVectorStream = new EmaVector(periods);
+        
+        int len = 100;
+        var t = new System.Collections.Generic.List<long>(len);
+        var v = new System.Collections.Generic.List<double>(len);
+        var now = DateTime.Now;
+        
+        for (int i = 0; i < len; i++)
+        {
+            t.Add(now.AddMinutes(i).Ticks);
+            v.Add(Math.Sin(i * 0.1) * 100);
+        }
+        
+        var series = new TSeries(t, v);
+        
+        // Batch calculation
+        var batchRes = emaVectorBatch.Calculate(series);
+        
+        // Streaming calculation
+        for (int i = 0; i < len; i++)
+        {
+            var tVal = new TValue(new DateTime(t[i]), v[i]);
+            var streamRes = emaVectorStream.Update(tVal);
+            
+            for (int j = 0; j < periods.Length; j++)
+            {
+                Assert.Equal(batchRes[j].Values[i], streamRes[j].Value, 1e-9);
+            }
+        }
+    }
+    
+    [Fact]
+    public void Reset_ClearsState()
+    {
+        int[] periods = { 10 };
+        var emaVector = new EmaVector(periods);
+        
+        emaVector.Update(new TValue(DateTime.Now, 100.0));
+        emaVector.Reset();
+        
+        // After reset, next calculation should treat it as first value (warmup)
+        var res = emaVector.Update(new TValue(DateTime.Now, 200.0));
+        
+        Assert.Equal(200.0, res[0].Value, 1e-9);
+    }
+}