mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-07 13:37:44 +00:00
403 lines
12 KiB
C#
403 lines
12 KiB
C#
using System.Runtime.CompilerServices;
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using System.Runtime.InteropServices;
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namespace QuanTAlib;
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/// <summary>
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/// VIDYA: Variable Index Dynamic Average
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/// </summary>
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/// <remarks>
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/// Tushar Chande's adaptive MA using CMO as volatility index to modulate smoothing.
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/// Flat in choppy markets, responsive in trending conditions.
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///
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/// Calculation: <c>VI = |CMO|; α' = α×VI; VIDYA = α'×P + (1-α')×VIDYA_{t-1}</c>.
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/// </remarks>
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/// <seealso href="Vidya.md">Detailed documentation</seealso>
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/// <seealso href="vidya.pine">Reference Pine Script implementation</seealso>
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[SkipLocalsInit]
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public sealed class Vidya : AbstractBase
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{
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private readonly int _period;
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private readonly double _alpha;
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private readonly RingBuffer _ups;
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private readonly RingBuffer _downs;
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private readonly ITValuePublisher? _source;
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private readonly TValuePublishedHandler? _pubHandler;
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private bool _isNew = true;
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private bool _disposed;
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[StructLayout(LayoutKind.Auto)]
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private record struct State(
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double PrevClose, double LastVidya,
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double CurrentClose, double CurrentVidya,
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bool IsInitialized, int BarCount
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);
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private State _state;
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private State _p_state;
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public Vidya(int period)
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{
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if (period <= 0)
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{
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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}
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_period = period;
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_alpha = 2.0 / (period + 1);
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_ups = new RingBuffer(period);
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_downs = new RingBuffer(period);
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Name = $"Vidya({period})";
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WarmupPeriod = period;
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InitState();
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}
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public Vidya(ITValuePublisher source, int period) : this(period)
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{
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_source = source;
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_pubHandler = Handle;
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source.Pub += _pubHandler;
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}
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protected override void Dispose(bool disposing)
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{
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if (!_disposed)
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{
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if (disposing && _source != null && _pubHandler != null)
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{
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_source.Pub -= _pubHandler;
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}
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_disposed = true;
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}
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base.Dispose(disposing);
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}
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private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
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public bool IsNew => _isNew;
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public override bool IsHot => _state.BarCount >= _period;
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override TValue Update(TValue input, bool isNew = true)
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{
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_isNew = isNew;
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if (isNew)
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{
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_state.BarCount++;
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if (_state.IsInitialized)
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{
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_state.PrevClose = _state.CurrentClose;
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_state.LastVidya = _state.CurrentVidya;
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}
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_p_state = _state;
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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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if (!_state.IsInitialized)
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{
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return input;
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}
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price = _state.CurrentClose;
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}
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if (_state.BarCount <= 1)
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{
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_state.PrevClose = price;
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_state.LastVidya = price;
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_state.CurrentClose = price;
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_state.CurrentVidya = price;
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_state.IsInitialized = true;
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_ups.Add(0, isNew);
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_downs.Add(0, isNew);
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Last = new TValue(input.Time, _state.CurrentVidya);
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PubEvent(Last);
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return Last;
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}
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double change = price - _state.PrevClose;
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double up = change > 0 ? change : 0;
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double down = change < 0 ? -change : 0;
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_ups.Add(up, isNew);
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_downs.Add(down, isNew);
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double sumUp = _ups.Sum;
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double sumDown = _downs.Sum;
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double sum = sumUp + sumDown;
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double vi = 0;
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if (sum > double.Epsilon)
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{
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vi = Math.Abs(sumUp - sumDown) / sum;
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}
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double dynamicAlpha = _alpha * vi;
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double dynamicDecay = 1.0 - dynamicAlpha;
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_state.CurrentVidya = Math.FusedMultiplyAdd(_state.LastVidya, dynamicDecay, dynamicAlpha * price);
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_state.CurrentClose = price;
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Last = new TValue(input.Time, _state.CurrentVidya);
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PubEvent(Last);
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return Last;
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}
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public override TSeries Update(TSeries source)
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{
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if (source.Count == 0)
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{
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return [];
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}
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int len = source.Count;
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var t = new List<long>(len);
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var v = new List<double>(len);
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CollectionsMarshal.SetCount(t, len);
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CollectionsMarshal.SetCount(v, len);
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var tSpan = CollectionsMarshal.AsSpan(t);
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var vSpan = CollectionsMarshal.AsSpan(v);
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Batch(source.Values, vSpan, _period);
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source.Times.CopyTo(tSpan);
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// Replay only the last _period bars to restore internal state
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Reset();
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int start = 0;
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if (len > 2 * _period)
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{
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start = len - _period;
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_state.BarCount = start;
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_state.IsInitialized = true;
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_state.PrevClose = source.Values[start - 1];
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_state.LastVidya = vSpan[start - 1];
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_state.CurrentClose = _state.PrevClose;
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_state.CurrentVidya = _state.LastVidya;
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// Pre-fill buffers with the previous period's data to ensure correct VI calculation
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for (int i = start - _period; i < start; i++)
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{
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double price = source.Values[i];
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double prev = source.Values[i - 1];
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double change = price - prev;
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double up = change > 0 ? change : 0;
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double down = change < 0 ? -change : 0;
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_ups.Add(up);
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_downs.Add(down);
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}
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}
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for (int i = start; i < len; i++)
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{
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Update(new TValue(source.Times[i], source.Values[i]));
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}
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return new TSeries(t, v);
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}
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public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
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{
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if (source.Length == 0)
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{
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return;
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}
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// Reset state
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Reset();
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// Process all data to build up state
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// For recursive indicators like VIDYA, we generally need to process from the start
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// or at least a significant warmup period.
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// Given we don't know the "correct" previous VIDYA without processing,
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// we process the whole provided history.
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double prevClose = source[0];
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double lastVidya = source[0];
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// Initialize state
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_state.PrevClose = prevClose;
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_state.LastVidya = lastVidya;
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_state.CurrentClose = prevClose;
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_state.CurrentVidya = lastVidya;
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_state.IsInitialized = true;
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_state.BarCount = 1;
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_ups.Add(0);
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_downs.Add(0);
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for (int i = 1; i < source.Length; i++)
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{
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double price = source[i];
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if (!double.IsFinite(price))
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{
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price = prevClose;
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}
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double change = price - prevClose;
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double up = change > 0 ? change : 0;
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double down = change < 0 ? -change : 0;
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_ups.Add(up);
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_downs.Add(down);
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_state.BarCount++;
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double sumUp = _ups.Sum;
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double sumDown = _downs.Sum;
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double sum = sumUp + sumDown;
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double vi = 0;
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if (sum > double.Epsilon)
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{
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vi = Math.Abs(sumUp - sumDown) / sum;
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}
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double dynamicAlpha = _alpha * vi;
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double dynamicDecay = 1.0 - dynamicAlpha;
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double currentVidya = Math.FusedMultiplyAdd(lastVidya, dynamicDecay, dynamicAlpha * price);
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_state.CurrentVidya = currentVidya;
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_state.CurrentClose = price;
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prevClose = price;
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lastVidya = currentVidya;
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}
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_state.PrevClose = prevClose;
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_state.LastVidya = lastVidya;
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// Set Last
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// Note: Time is not available in Span, so we use MinValue.
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// It will be updated on next Update.
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Last = new TValue(DateTime.MinValue, _state.CurrentVidya);
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_p_state = _state;
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}
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public override void Reset()
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{
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_ups.Clear();
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_downs.Clear();
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InitState();
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_p_state = _state;
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Last = default;
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}
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private void InitState()
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{
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_state = new State(
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PrevClose: double.NaN,
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LastVidya: double.NaN,
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CurrentClose: double.NaN,
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CurrentVidya: double.NaN,
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IsInitialized: false,
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BarCount: 0
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);
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}
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public static TSeries Batch(TSeries source, int period)
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{
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var vidya = new Vidya(period);
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return vidya.Update(source);
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}
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public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period)
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{
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if (period <= 0)
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{
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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}
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if (source.Length != output.Length)
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{
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throw new ArgumentException("Source and output must have the same length", nameof(output));
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}
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if (source.Length == 0)
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{
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return;
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}
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double alpha = 2.0 / (period + 1);
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// Use arrays for buffers to avoid heap allocations if possible,
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// but period is dynamic.
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// We can use ArrayPool or just new double[period] if period is small.
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// For simplicity and safety with large periods, let's use ArrayPool.
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double[] ups = System.Buffers.ArrayPool<double>.Shared.Rent(period);
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double[] downs = System.Buffers.ArrayPool<double>.Shared.Rent(period);
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Array.Clear(ups, 0, period);
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Array.Clear(downs, 0, period);
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try
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{
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int head = 0;
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double sumUp = 0;
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double sumDown = 0;
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double prevClose = source[0];
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double lastVidya = source[0];
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output[0] = source[0];
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for (int i = 1; i < source.Length; i++)
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{
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double price = source[i];
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if (!double.IsFinite(price))
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{
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price = prevClose;
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}
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double change = price - prevClose;
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double up = change > 0 ? change : 0;
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double down = change < 0 ? -change : 0;
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sumUp -= ups[head];
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sumDown -= downs[head];
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ups[head] = up;
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downs[head] = down;
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sumUp += up;
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sumDown += down;
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head++;
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if (head >= period)
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{
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head = 0;
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}
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double sum = sumUp + sumDown;
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double vi = 0;
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if (sum > double.Epsilon)
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{
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vi = Math.Abs(sumUp - sumDown) / sum;
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}
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double dynamicAlpha = alpha * vi;
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double dynamicDecay = 1.0 - dynamicAlpha;
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double currentVidya = Math.FusedMultiplyAdd(lastVidya, dynamicDecay, dynamicAlpha * price);
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output[i] = currentVidya;
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prevClose = price;
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lastVidya = currentVidya;
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}
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}
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finally
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{
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System.Buffers.ArrayPool<double>.Shared.Return(ups);
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System.Buffers.ArrayPool<double>.Shared.Return(downs);
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}
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}
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public static (TSeries Results, Vidya Indicator) Calculate(TSeries source, int period)
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{
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var indicator = new Vidya(period);
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TSeries results = indicator.Update(source);
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return (results, indicator);
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}
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} |