mirror of
https://github.com/mihakralj/QuanTAlib.git
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154 lines
4.2 KiB
C#
154 lines
4.2 KiB
C#
// LOGTRANS: Natural Logarithm Transformer
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// Transforms values using natural logarithm (base e)
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using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// LOGTRANS: Natural Logarithm Transformer
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/// Applies ln(x) transformation to input values.
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/// </summary>
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/// <remarks>
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/// Key properties:
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/// - Compresses large values, expands small values
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/// - Useful for transforming multiplicative relationships to additive
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/// - Domain: x > 0 (non-positive inputs use last valid value)
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/// - Common in financial returns: ln(P_t / P_{t-1})
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Logtrans : AbstractBase
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{
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private record struct State(double LastValid);
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private State _state, _p_state;
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public override bool IsHot => true; // No warmup needed
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public Logtrans()
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{
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Name = "Logtrans";
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WarmupPeriod = 0;
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}
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/// <summary>
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/// Creates Logtrans with source for event-based chaining.
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/// </summary>
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/// <param name="source">Source indicator for chaining</param>
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public Logtrans(ITValuePublisher source) : this()
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{
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source.Pub += HandleUpdate;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private void HandleUpdate(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
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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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if (isNew)
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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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// Handle non-positive and non-finite values
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double value = input.Value;
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double result;
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if (double.IsFinite(value) && value > 0)
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{
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result = Math.Log(value);
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_state = new State(result);
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}
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else
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{
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result = _state.LastValid;
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}
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Last = new TValue(input.Time, result);
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PubEvent(Last, isNew);
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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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var result = new TSeries(source.Count);
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ReadOnlySpan<double> values = source.Values;
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ReadOnlySpan<long> times = source.Times;
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for (int i = 0; i < source.Count; i++)
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{
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var tv = Update(new TValue(new DateTime(times[i], DateTimeKind.Utc), values[i]), true);
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result.Add(tv, true);
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}
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return result;
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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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TimeSpan interval = step ?? TimeSpan.FromSeconds(1);
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DateTime time = DateTime.UtcNow - (interval * source.Length);
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for (int i = 0; i < source.Length; i++)
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{
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Update(new TValue(time, source[i]), true);
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time += interval;
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}
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}
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public static TSeries Batch(TSeries source)
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{
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var indicator = new Logtrans();
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return indicator.Update(source);
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}
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/// <summary>
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/// Calculates natural logarithm over a span of values.
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/// Note: Math.Log has no SIMD intrinsic; uses scalar path with last-valid substitution.
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/// </summary>
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public static void Batch(ReadOnlySpan<double> source, Span<double> output)
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{
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if (source.Length == 0)
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{
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throw new ArgumentException("Source cannot be empty", nameof(source));
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}
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if (output.Length < source.Length)
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{
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throw new ArgumentException("Output length must be >= source length", nameof(output));
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}
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double lastValid = 0.0;
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for (int i = 0; i < source.Length; i++)
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{
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double val = source[i];
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if (double.IsFinite(val) && val > 0)
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{
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lastValid = Math.Log(val);
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output[i] = lastValid;
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}
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else
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{
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output[i] = lastValid;
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}
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}
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}
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public static (TSeries Results, Logtrans Indicator) Calculate(TSeries source)
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{
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var indicator = new Logtrans();
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TSeries results = indicator.Update(source);
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return (results, indicator);
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}
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public override void Reset()
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{
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_state = default;
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_p_state = default;
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Last = default;
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}
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} |