Files
QuanTAlib/lib/numerics/logtrans/Logtrans.cs
T
86fe32a682 SIMD Refactor: Merge simd-dev into dev (#55)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>
2026-01-18 19:02:03 -08:00

163 lines
4.8 KiB
C#

// LOGTRANS: Natural Logarithm Transformer
// Transforms values using natural logarithm (base e)
using System.Runtime.CompilerServices;
using System.Numerics;
using System.Runtime.Intrinsics;
using System.Runtime.Intrinsics.X86;
namespace QuanTAlib;
/// <summary>
/// LOGTRANS: Natural Logarithm Transformer
/// Applies ln(x) transformation to input values.
/// </summary>
/// <remarks>
/// Key properties:
/// - Compresses large values, expands small values
/// - Useful for transforming multiplicative relationships to additive
/// - Domain: x > 0 (non-positive inputs use last valid value)
/// - Common in financial returns: ln(P_t / P_{t-1})
/// </remarks>
[SkipLocalsInit]
public sealed class Logtrans : AbstractBase
{
private record struct State(double LastValid);
private State _state, _p_state;
public override bool IsHot => true; // No warmup needed
public Logtrans()
{
Name = "Logtrans";
WarmupPeriod = 0;
}
/// <param name="source">Source indicator for chaining</param>
public Logtrans(ITValuePublisher source) : this()
{
source.Pub += HandleUpdate;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private void HandleUpdate(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
if (isNew)
_p_state = _state;
else
_state = _p_state;
// Handle non-positive and non-finite values
double value = input.Value;
double result;
if (double.IsFinite(value) && value > 0)
{
result = Math.Log(value);
_state = new State(result);
}
else
{
result = _state.LastValid;
}
Last = new TValue(input.Time, result);
PubEvent(Last, isNew);
return Last;
}
public override TSeries Update(TSeries source)
{
var result = new TSeries(source.Count);
ReadOnlySpan<double> values = source.Values;
ReadOnlySpan<long> times = source.Times;
for (int i = 0; i < source.Count; i++)
{
var tv = Update(new TValue(new DateTime(times[i], DateTimeKind.Utc), values[i]), true);
result.Add(tv, true);
}
return result;
}
public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
{
TimeSpan interval = step ?? TimeSpan.FromSeconds(1);
DateTime time = DateTime.UtcNow - (interval * source.Length);
for (int i = 0; i < source.Length; i++)
{
Update(new TValue(time, source[i]), true);
time += interval;
}
}
public static TSeries Calculate(TSeries source)
{
var indicator = new Logtrans();
return indicator.Update(source);
}
/// <summary>
/// Calculates natural logarithm over a span of values using SIMD when available.
/// </summary>
public static void Calculate(ReadOnlySpan<double> source, Span<double> output)
{
if (source.Length == 0)
throw new ArgumentException("Source cannot be empty", nameof(source));
if (output.Length < source.Length)
throw new ArgumentException("Output length must be >= source length", nameof(output));
double lastValid = 0.0;
int i = 0;
// SIMD path for AVX2 (process 4 doubles at a time)
if (Avx2.IsSupported && source.Length >= Vector256<double>.Count)
{
int vectorLength = source.Length - (source.Length % Vector256<double>.Count);
for (; i < vectorLength; i += Vector256<double>.Count)
{
// Process scalar for proper last-valid handling (Logtrans has no SIMD intrinsic)
for (int j = 0; j < Vector256<double>.Count; j++)
{
double val = source[i + j];
if (double.IsFinite(val) && val > 0)
{
lastValid = Math.Log(val);
output[i + j] = lastValid;
}
else
{
output[i + j] = lastValid;
}
}
}
}
// Scalar fallback for remaining elements
for (; i < source.Length; i++)
{
double val = source[i];
if (double.IsFinite(val) && val > 0)
{
lastValid = Math.Log(val);
output[i] = lastValid;
}
else
{
output[i] = lastValid;
}
}
}
public override void Reset()
{
_state = default;
_p_state = default;
Last = default;
}
}