mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-30 18:47:42 +00:00
312 lines
9.3 KiB
C#
312 lines
9.3 KiB
C#
// FDIST: F-Distribution CDF
|
||
// Applies the Fisher-Snedecor CDF F(x; d1, d2) = I(d1*x/(d1*x+d2), d1/2, d2/2)
|
||
// to a min-max normalized price series over a rolling lookback window.
|
||
// Pipeline: MinMax normalization → scaling → regularized incomplete beta function.
|
||
// Reuses Betadist.IncompleteBeta internally — no gamma/CF reimplementation.
|
||
|
||
using System.Runtime.CompilerServices;
|
||
using System.Runtime.InteropServices;
|
||
|
||
namespace QuanTAlib;
|
||
|
||
/// <summary>
|
||
/// FDIST: F-Distribution (Fisher-Snedecor) CDF
|
||
/// Computes F(x; d1, d2) = I(d1·x/(d1·x+d2), d1/2, d2/2) applied to a
|
||
/// min-max normalized price series scaled to a positive real via a 10× factor.
|
||
/// </summary>
|
||
/// <remarks>
|
||
/// Key properties:
|
||
/// - Output always in [0, 1]
|
||
/// - Rolling window tracks min/max for normalization; flat range returns F(0.5·10; d1, d2)
|
||
/// - d1/d2 degrees of freedom control the shape: equal df → symmetric response,
|
||
/// d1 > d2 → right-skewed, d1 < d2 → left-skewed
|
||
/// - Reuses <see cref="Betadist.IncompleteBeta"/> — no special-function duplication
|
||
/// - NaN/Infinity inputs use last-valid-value substitution
|
||
/// </remarks>
|
||
[SkipLocalsInit]
|
||
public sealed class Fdist : AbstractBase
|
||
{
|
||
private readonly int _period;
|
||
private readonly int _d1;
|
||
private readonly int _d2;
|
||
private readonly RingBuffer _buffer;
|
||
|
||
[StructLayout(LayoutKind.Auto)]
|
||
private record struct State(double LastValid);
|
||
private State _state, _p_state;
|
||
|
||
public override bool IsHot => _buffer.Count >= _period;
|
||
|
||
/// <summary>
|
||
/// Initializes a new Fdist indicator.
|
||
/// </summary>
|
||
/// <param name="d1">Numerator degrees of freedom (integer ≥ 1, default 1)</param>
|
||
/// <param name="d2">Denominator degrees of freedom (integer ≥ 1, default 1)</param>
|
||
/// <param name="period">Lookback window for min-max normalization (default 14)</param>
|
||
public Fdist(int d1 = 1, int d2 = 1, int period = 14)
|
||
{
|
||
if (d1 < 1)
|
||
{
|
||
throw new ArgumentException("d1 must be >= 1", nameof(d1));
|
||
}
|
||
|
||
if (d2 < 1)
|
||
{
|
||
throw new ArgumentException("d2 must be >= 1", nameof(d2));
|
||
}
|
||
|
||
if (period < 2)
|
||
{
|
||
throw new ArgumentException("Period must be >= 2", nameof(period));
|
||
}
|
||
|
||
_d1 = d1;
|
||
_d2 = d2;
|
||
_period = period;
|
||
_buffer = new RingBuffer(period);
|
||
Name = $"Fdist({d1},{d2},{period})";
|
||
WarmupPeriod = period;
|
||
_state = new State(0.5);
|
||
_p_state = _state;
|
||
}
|
||
|
||
/// <summary>
|
||
/// Initializes a new Fdist indicator with source for event-based chaining.
|
||
/// </summary>
|
||
/// <param name="source">Source indicator for chaining</param>
|
||
/// <param name="d1">Numerator degrees of freedom (default 1)</param>
|
||
/// <param name="d2">Denominator degrees of freedom (default 1)</param>
|
||
/// <param name="period">Lookback window (default 14)</param>
|
||
public Fdist(ITValuePublisher source, int d1 = 1, int d2 = 1, int period = 14)
|
||
: this(d1, d2, period)
|
||
{
|
||
source.Pub += HandleUpdate;
|
||
}
|
||
|
||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||
private void HandleUpdate(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
|
||
|
||
/// <summary>
|
||
/// F-Distribution CDF: F(x; d1, d2) = I(d1·x/(d1·x+d2), d1/2, d2/2).
|
||
/// Returns 0 for x ≤ 0, uses regularized incomplete beta for x > 0.
|
||
/// </summary>
|
||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||
public static double FCdf(double x, int d1, int d2)
|
||
{
|
||
if (x <= 0.0)
|
||
{
|
||
return 0.0;
|
||
}
|
||
|
||
double d1d = d1;
|
||
double d2d = d2;
|
||
double xBeta = d1d * x / Math.FusedMultiplyAdd(d1d, x, d2d);
|
||
return Betadist.IncompleteBeta(xBeta, d1d * 0.5, d2d * 0.5);
|
||
}
|
||
|
||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||
private static (double min, double max) FindMinMax(ReadOnlySpan<double> values)
|
||
{
|
||
if (values.Length == 0)
|
||
{
|
||
return (double.MaxValue, double.MinValue);
|
||
}
|
||
|
||
double min = values[0];
|
||
double max = values[0];
|
||
for (int i = 1; i < values.Length; i++)
|
||
{
|
||
double v = values[i];
|
||
if (v < min)
|
||
{
|
||
min = v;
|
||
}
|
||
|
||
if (v > max)
|
||
{
|
||
max = v;
|
||
}
|
||
}
|
||
|
||
return (min, max);
|
||
}
|
||
|
||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||
public override TValue Update(TValue input, bool isNew = true)
|
||
{
|
||
if (isNew)
|
||
{
|
||
_p_state = _state;
|
||
}
|
||
else
|
||
{
|
||
_state = _p_state;
|
||
}
|
||
|
||
double value = input.Value;
|
||
double result;
|
||
|
||
if (double.IsFinite(value))
|
||
{
|
||
_buffer.Add(value, isNew);
|
||
|
||
var (min, max) = FindMinMax(_buffer.GetSpan());
|
||
double range = max - min;
|
||
|
||
// Flat range → use midpoint 0.5; scale by 10 to spread F-CDF response across (0,∞)
|
||
double xNorm = range > 0.0 ? (value - min) / range : 0.5;
|
||
|
||
// Map [0,1] → [0,10] to place output in a useful part of the F-CDF response curve
|
||
double xF = xNorm * 10.0;
|
||
|
||
result = FCdf(xF, _d1, _d2);
|
||
_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 Batch(TSeries source, int d1 = 1, int d2 = 1, int period = 14)
|
||
{
|
||
var indicator = new Fdist(d1, d2, period);
|
||
return indicator.Update(source);
|
||
}
|
||
|
||
/// <summary>
|
||
/// Calculates F-Distribution CDF over a span of values.
|
||
/// Uses a sliding window min-max normalization identical to the streaming path.
|
||
/// </summary>
|
||
public static void Batch(
|
||
ReadOnlySpan<double> source, Span<double> output,
|
||
int d1 = 1, int d2 = 1, int period = 14)
|
||
{
|
||
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));
|
||
}
|
||
|
||
if (d1 < 1)
|
||
{
|
||
throw new ArgumentException("d1 must be >= 1", nameof(d1));
|
||
}
|
||
|
||
if (d2 < 1)
|
||
{
|
||
throw new ArgumentException("d2 must be >= 1", nameof(d2));
|
||
}
|
||
|
||
if (period < 2)
|
||
{
|
||
throw new ArgumentException("Period must be >= 2", nameof(period));
|
||
}
|
||
|
||
double lastValid = 0.5;
|
||
|
||
for (int i = 0; i < source.Length; i++)
|
||
{
|
||
double val = source[i];
|
||
if (!double.IsFinite(val))
|
||
{
|
||
output[i] = lastValid;
|
||
continue;
|
||
}
|
||
|
||
int start = Math.Max(0, i - period + 1);
|
||
|
||
double min = double.PositiveInfinity;
|
||
double max = double.NegativeInfinity;
|
||
|
||
for (int j = start; j <= i; j++)
|
||
{
|
||
double v = source[j];
|
||
if (double.IsFinite(v))
|
||
{
|
||
if (v < min)
|
||
{
|
||
min = v;
|
||
}
|
||
|
||
if (v > max)
|
||
{
|
||
max = v;
|
||
}
|
||
}
|
||
}
|
||
|
||
if (!double.IsFinite(min) || !double.IsFinite(max))
|
||
{
|
||
output[i] = lastValid;
|
||
continue;
|
||
}
|
||
|
||
double range = max - min;
|
||
double xNorm = range > 0.0 ? (val - min) / range : 0.5;
|
||
double xF = xNorm * 10.0;
|
||
|
||
double result = FCdf(xF, d1, d2);
|
||
lastValid = result;
|
||
output[i] = result;
|
||
}
|
||
}
|
||
|
||
/// <summary>
|
||
/// Pure static F-CDF helper. Identical to <see cref="FCdf"/> but exposed
|
||
/// with a more explicit name for downstream consumers and validation tests.
|
||
/// </summary>
|
||
public static double StaticCdf(double x, int d1, int d2) => FCdf(x, d1, d2);
|
||
|
||
public static (TSeries Results, Fdist Indicator) Calculate(
|
||
TSeries source, int d1 = 1, int d2 = 1, int period = 14)
|
||
{
|
||
var indicator = new Fdist(d1, d2, period);
|
||
TSeries results = indicator.Update(source);
|
||
return (results, indicator);
|
||
}
|
||
|
||
public override void Reset()
|
||
{
|
||
_buffer.Clear();
|
||
_state = new State(0.5);
|
||
_p_state = _state;
|
||
Last = default;
|
||
}
|
||
}
|