mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-13 08:08:05 +00:00
228 lines
7.2 KiB
C#
228 lines
7.2 KiB
C#
using System;
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using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// MESA Adaptive Moving Average (MAMA)
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/// A trend-following indicator that adapts to the market's phase rate of change.
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/// </summary>
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[SkipLocalsInit]
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public sealed class Mama : ITValuePublisher
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{
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public TValue Last { get; private set; }
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public TValue Fama { get; private set; }
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public bool IsHot => _state.Index > 6;
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public event Action<TValue>? Pub;
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private readonly double _fastLimit;
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private readonly double _slowLimit;
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private record struct State(
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double Period, double Phase, double Mama, double Fama, double SumPr,
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double I2, double Q2, double Re, double Im, double LastValidPrice, int Index
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);
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private State _state;
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private State _p_state;
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private readonly RingBuffer _priceBuffer;
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private readonly RingBuffer _smoothBuffer;
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private readonly RingBuffer _detrender;
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private readonly RingBuffer _I1_buffer;
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private readonly RingBuffer _Q1_buffer;
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private const double c1 = 0.0962;
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private const double c2 = 0.5769;
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private const double TWOPI = 2.0 * Math.PI;
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private const double RadToDeg = 180.0 / Math.PI;
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public Mama(double fastLimit = 0.5, double slowLimit = 0.05)
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{
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if (fastLimit <= slowLimit || fastLimit <= 0 || slowLimit <= 0)
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{
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throw new ArgumentException("FastLimit must be > SlowLimit and > 0");
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}
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_fastLimit = fastLimit;
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_slowLimit = slowLimit;
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_priceBuffer = new RingBuffer(7);
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_smoothBuffer = new RingBuffer(7);
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_detrender = new RingBuffer(7);
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_I1_buffer = new RingBuffer(7);
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_Q1_buffer = new RingBuffer(7);
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Name = $"Mama({fastLimit:F2},{slowLimit:F2})";
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Init();
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}
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public Mama(ITValuePublisher source, double fastLimit = 0.5, double slowLimit = 0.05) : this(fastLimit, slowLimit)
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{
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source.Pub += (item) => Update(item);
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}
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public void Init()
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{
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_state = default;
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_state.Mama = double.NaN;
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_state.Fama = double.NaN;
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_p_state = _state;
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_priceBuffer.Clear();
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_smoothBuffer.Clear();
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_detrender.Clear();
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_I1_buffer.Clear();
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_Q1_buffer.Clear();
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Last = new TValue(DateTime.MinValue, double.NaN);
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Fama = new TValue(DateTime.MinValue, double.NaN);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public TValue Update(TValue input, bool isNew = true)
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{
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if (isNew)
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{
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_p_state = _state;
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_state.Index++;
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}
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else
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{
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_state = _p_state;
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}
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double price = input.Value;
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if (!double.IsFinite(price))
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{
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price = _state.LastValidPrice;
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}
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else
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{
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_state.LastValidPrice = price;
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}
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_priceBuffer.Add(price, isNew);
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if (_state.Index > 6)
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{
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double adj = (0.075 * _state.Period) + 0.54;
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// Smooth
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double smooth = (4.0 * _priceBuffer[^1] + 3.0 * _priceBuffer[^2] + 2.0 * _priceBuffer[^3] + _priceBuffer[^4]) * 0.1;
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_smoothBuffer.Add(smooth, isNew);
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// Detrender
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double dt = (c1 * _smoothBuffer[^1] + c2 * _smoothBuffer[^3] - c2 * _smoothBuffer[^5] - c1 * _smoothBuffer[^7]) * adj;
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_detrender.Add(dt, isNew);
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// Q1
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double q1 = (c1 * dt + c2 * _detrender[^3] - c2 * _detrender[^5] - c1 * _detrender[^7]) * adj;
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_Q1_buffer.Add(q1, isNew);
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// I1 = dt[3]
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double i1 = _detrender[^4];
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_I1_buffer.Add(i1, isNew);
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// Advance phases
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// jI = CalculateHilbertTransform(_i1, adj)
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double jI = (c1 * i1 + c2 * _I1_buffer[^3] - c2 * _I1_buffer[^5] - c1 * _I1_buffer[^7]) * adj;
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// jQ = CalculateHilbertTransform(_q1, adj)
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double jQ = (c1 * q1 + c2 * _Q1_buffer[^3] - c2 * _Q1_buffer[^5] - c1 * _Q1_buffer[^7]) * adj;
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// Phasor addition
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double i2_val = i1 - jQ;
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double q2_val = q1 + jI;
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// Smooth i2, q2
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_state.I2 = 0.2 * i2_val + 0.8 * _p_state.I2;
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_state.Q2 = 0.2 * q2_val + 0.8 * _p_state.Q2;
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// Homodyne discriminator
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double re_val = (_state.I2 * _p_state.I2) + (_state.Q2 * _p_state.Q2);
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double im_val = (_state.I2 * _p_state.Q2) - (_state.Q2 * _p_state.I2);
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// Smooth re, im
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_state.Re = 0.2 * re_val + 0.8 * _p_state.Re;
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_state.Im = 0.2 * im_val + 0.8 * _p_state.Im;
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// Calculate Period
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double period = (Math.Abs(_state.Im) > double.Epsilon && Math.Abs(_state.Re) > double.Epsilon)
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? TWOPI / Math.Atan(_state.Im / _state.Re)
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: 0.0;
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// Adjust Period
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double periodCap = _p_state.Period * 1.5;
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double periodFloor = _p_state.Period * 0.67;
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if (period > periodCap) period = periodCap;
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if (period < periodFloor) period = periodFloor;
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if (period < 6.0) period = 6.0;
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if (period > 50.0) period = 50.0;
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// Smooth Period
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_state.Period = 0.2 * period + 0.8 * _p_state.Period;
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// Phase calculation
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_state.Phase = Math.Abs(i1) >= double.Epsilon ? Math.Atan(q1 / i1) * RadToDeg : 0.0;
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// Adaptive alpha
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double delta = Math.Max(_p_state.Phase - _state.Phase, 1.0);
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double alpha = _fastLimit / delta;
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alpha = Math.Clamp(alpha, _slowLimit, _fastLimit);
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// Final indicators
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_state.Mama = alpha * _priceBuffer[^1] + (1.0 - alpha) * _p_state.Mama;
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_state.Fama = 0.5 * alpha * _state.Mama + (1.0 - 0.5 * alpha) * _p_state.Fama;
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}
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else
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{
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// Initialization phase
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_state.SumPr += price;
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double avg = _state.Index > 0 ? _state.SumPr / _state.Index : price;
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_state.Mama = avg;
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_state.Fama = avg;
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// Initialize buffers with 0
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_smoothBuffer.Add(0, isNew);
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_detrender.Add(0, isNew);
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_I1_buffer.Add(0, isNew);
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_Q1_buffer.Add(0, isNew);
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}
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Last = new TValue(input.Time, _state.Mama);
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Fama = new TValue(input.Time, _state.Fama);
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Pub?.Invoke(Last);
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return Last;
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}
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public TSeries Update(TSeries source)
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{
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if (source.Count == 0) return [];
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int len = source.Count;
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var v = new List<double>(len);
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var t = new List<long>(len);
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for (int i = 0; i < len; i++)
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{
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var item = source[i];
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var result = Update(item);
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v.Add(result.Value);
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t.Add(item.Time);
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}
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return new TSeries(t, v);
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}
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public static void Calculate(ReadOnlySpan<double> source, Span<double> output, double fastLimit = 0.5, double slowLimit = 0.05)
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{
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var mama = new Mama(fastLimit, slowLimit);
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for (int i = 0; i < source.Length; i++)
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{
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output[i] = mama.Update(new TValue(DateTime.MinValue, source[i])).Value;
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}
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}
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public string Name { get; set; }
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}
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