using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
///
/// CONV: Convolution Filter
///
///
/// FIR filter applying custom kernel weights via dot product.
/// Foundation for all window-based moving averages.
///
/// Calculation: Result = Σ(kernel[i] × data[i]) where kernel[0] weights oldest sample.
///
/// Detailed documentation
[SkipLocalsInit]
public sealed class Conv : AbstractBase
{
private readonly int _period;
private readonly double[] _kernel;
private readonly RingBuffer _buffer;
private readonly ITValuePublisher? _source;
private readonly TValuePublishedHandler? _subHandler;
private bool _isNew = true;
private bool _disposed;
private record struct State(double LastValidValue);
private State _state;
private State _p_state;
public bool IsNew => _isNew;
public override bool IsHot => _buffer.IsFull;
public Conv(double[] kernel)
{
if (kernel == null || kernel.Length == 0)
{
throw new ArgumentException("Kernel must not be empty", nameof(kernel));
}
_period = kernel.Length;
_kernel = new double[_period];
Array.Copy(kernel, _kernel, _period);
_buffer = new RingBuffer(_period);
Name = $"Conv({_period})";
WarmupPeriod = _period;
_state.LastValidValue = double.NaN;
_p_state.LastValidValue = double.NaN;
}
public Conv(ITValuePublisher source, double[] kernel) : this(kernel)
{
_source = source;
_subHandler = Handle;
_source.Pub += _subHandler;
}
protected override void Dispose(bool disposing)
{
if (!_disposed)
{
if (disposing && _source != null && _subHandler != null)
{
_source.Pub -= _subHandler;
}
_disposed = true;
}
base.Dispose(disposing);
}
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double GetValidValue(double input)
{
if (double.IsFinite(input))
{
_state.LastValidValue = input;
return input;
}
return _state.LastValidValue;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
_isNew = isNew;
if (isNew)
{
_p_state = _state;
}
else
{
_state = _p_state;
}
double val = GetValidValue(input.Value);
if (isNew)
{
_buffer.Add(val);
}
else
{
_buffer.UpdateNewest(val);
}
double result = 0;
if (_buffer.Count > 0)
{
int count = _buffer.Count;
int kernelOffset = _period - count;
ReadOnlySpan kernelSpan = _kernel.AsSpan()[kernelOffset..];
ReadOnlySpan internalBuf = _buffer.InternalBuffer;
if (count < _period)
{
result = internalBuf[..count].DotProduct(kernelSpan);
}
else
{
// Full: data is split at StartIndex (which points to oldest)
int head = _buffer.StartIndex;
int part1Len = _period - head;
result = internalBuf.Slice(head, part1Len).DotProduct(kernelSpan[..part1Len])
+ internalBuf[..head].DotProduct(kernelSpan[part1Len..]);
}
}
Last = new TValue(input.Time, result);
PubEvent(Last);
return Last;
}
public override TSeries Update(TSeries source)
{
if (source.Count == 0)
{
return [];
}
int len = source.Count;
List t = new(len);
List v = new(len);
CollectionsMarshal.SetCount(t, len);
CollectionsMarshal.SetCount(v, len);
var tSpan = CollectionsMarshal.AsSpan(t);
var vSpan = CollectionsMarshal.AsSpan(v);
source.Times.CopyTo(tSpan);
var sourceValues = source.Values;
Batch(sourceValues, vSpan, _kernel);
// Restore state
// We need to replay the last few updates to restore _buffer and _lastValidValue
int windowSize = Math.Min(len, _period);
int startIndex = len - windowSize;
// Find last valid value before the window if possible
if (startIndex > 0)
{
_state.LastValidValue = double.NaN;
for (int i = startIndex - 1; i >= 0; i--)
{
if (double.IsFinite(sourceValues[i]))
{
_state.LastValidValue = sourceValues[i];
break;
}
}
}
else
{
_state.LastValidValue = double.NaN;
}
_buffer.Clear();
// Replay
for (int i = startIndex; i < len; i++)
{
double val = GetValidValue(sourceValues[i]);
_buffer.Add(val);
}
// Set Last
Last = new TValue(source.Times[len - 1], vSpan[len - 1]);
// Save state for isNew=false
_p_state = _state;
return new TSeries(t, v);
}
public override void Prime(ReadOnlySpan source, TimeSpan? step = null)
{
foreach (var value in source)
{
Update(new TValue(DateTime.MinValue, value));
}
}
public static TSeries Batch(TSeries source, double[] kernel)
{
var conv = new Conv(kernel);
return conv.Update(source);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Batch(ReadOnlySpan source, Span output, double[] kernel)
{
if (source.Length != output.Length)
{
throw new ArgumentException("Source and output must have the same length", nameof(output));
}
if (kernel == null || kernel.Length == 0)
{
throw new ArgumentException("Kernel must not be empty", nameof(kernel));
}
int len = source.Length;
int period = kernel.Length;
if (len == 0)
{
return;
}
// Use stackalloc for small kernels to avoid heap allocation
Span window = period <= 256 ? stackalloc double[period] : new double[period];
double lastValid = double.NaN;
int windowIdx = 0; // Points to where the NEXT value goes (circular)
int count = 0;
ReadOnlySpan kernelSpan = kernel.AsSpan();
for (int i = 0; i < len; i++)
{
double val = source[i];
if (double.IsFinite(val))
{
lastValid = val;
}
else
{
val = lastValid;
}
window[windowIdx] = val;
windowIdx = (windowIdx + 1);
if (windowIdx >= period)
{
windowIdx = 0;
}
if (count < period)
{
count++;
}
double sum = 0;
if (count < period)
{
int kernelOffset = period - count;
// Window is [0..count-1]
sum = window[..count].DotProduct(kernelSpan[kernelOffset..]);
}
else
{
// Full buffer - branchless version
int part1Len = period - windowIdx;
sum = window.Slice(windowIdx, part1Len).DotProduct(kernelSpan[..part1Len])
+ window[..windowIdx].DotProduct(kernelSpan[part1Len..]);
}
output[i] = sum;
}
}
public static (TSeries Results, Conv Indicator) Calculate(TSeries source, double[] kernel)
{
var indicator = new Conv(kernel);
TSeries results = indicator.Update(source);
return (results, indicator);
}
public override void Reset()
{
_buffer.Clear();
_state.LastValidValue = double.NaN;
_p_state.LastValidValue = double.NaN;
Last = default;
}
}