using System;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
///
/// DEMA: Double Exponential Moving Average
///
///
/// Reduces lag by applying double smoothing and subtracting the extra smoothing.
/// More responsive than EMA while maintaining smoothness.
///
/// Calculation: DEMA = 2×EMA(p) - EMA(EMA(p)).
///
/// Detailed documentation
/// Reference Pine Script implementation
[SkipLocalsInit]
public sealed class Dema : AbstractBase
{
[StructLayout(LayoutKind.Auto)]
private record struct EmaState(double Ema, double E, bool IsHot, bool IsCompensated)
{
public static EmaState New() => new() { Ema = 0, E = 1.0, IsHot = false, IsCompensated = false };
}
private readonly double _alpha;
private readonly double _decay;
private EmaState _state1 = EmaState.New();
private EmaState _state2 = EmaState.New();
private EmaState _p_state1 = EmaState.New();
private EmaState _p_state2 = EmaState.New();
private double _lastValidValue = double.NaN;
private double _p_lastValidValue = double.NaN;
private bool _isNew = true;
private readonly ITValuePublisher? _publisher;
private readonly TValuePublishedHandler? _listener;
public bool IsNew => _isNew;
public override bool IsHot => _state2.IsHot;
public Dema(int period)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
_alpha = 2.0 / (period + 1);
_decay = 1.0 - _alpha;
Name = $"Dema({period})";
WarmupPeriod = period;
}
public Dema(ITValuePublisher source, int period) : this(period)
{
_publisher = source;
_listener = Handle;
source.Pub += _listener;
}
public Dema(double alpha)
{
if (alpha <= 0 || alpha > 1)
{
throw new ArgumentException("Alpha must be between 0 and 1", nameof(alpha));
}
_alpha = alpha;
_decay = 1.0 - alpha;
Name = $"Dema(α={alpha:F4})";
WarmupPeriod = (int)((2.0 / alpha) - 1.0);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
_isNew = isNew;
if (isNew)
{
_p_state1 = _state1;
_p_state2 = _state2;
_p_lastValidValue = _lastValidValue;
}
else
{
_state1 = _p_state1;
_state2 = _p_state2;
_lastValidValue = _p_lastValidValue;
}
// EMA1
double val = input.Value;
if (double.IsFinite(val))
{
_lastValidValue = val;
}
else
{
val = _lastValidValue;
}
if (double.IsNaN(val))
{
Last = new TValue(input.Time, double.NaN);
PubEvent(Last, isNew);
return Last;
}
double e1 = Compute(val, _alpha, _decay, ref _state1);
// EMA2 (input is e1, which is always valid)
double e2 = Compute(e1, _alpha, _decay, ref _state2);
double result = Math.FusedMultiplyAdd(2.0, e1, -e2);
Last = new TValue(input.Time, result);
PubEvent(Last, isNew);
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;
// Capture pre-batch state for rollback
EmaState preBatch_s1 = _state1;
EmaState preBatch_s2 = _state2;
double preBatch_lastValid = _lastValidValue;
// Use current state for calculation
EmaState s1 = _state1;
EmaState s2 = _state2;
double lastValid = _lastValidValue;
double alpha = _alpha;
double decay = _decay;
for (int i = 0; i < len; i++)
{
double val = sourceValues[i];
if (double.IsFinite(val))
{
lastValid = val;
}
else
{
val = lastValid;
}
if (double.IsNaN(val))
{
vSpan[i] = double.NaN;
continue;
}
double e1 = Compute(val, alpha, decay, ref s1);
double e2 = Compute(e1, alpha, decay, ref s2);
vSpan[i] = Math.FusedMultiplyAdd(2.0, e1, -e2);
}
// Update instance state with post-batch values
_state1 = s1;
_state2 = s2;
_lastValidValue = lastValid;
// Preserve pre-batch state for rollback (isNew=false)
_p_state1 = preBatch_s1;
_p_state2 = preBatch_s2;
_p_lastValidValue = preBatch_lastValid;
Last = new TValue(tSpan[len - 1], vSpan[len - 1]);
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));
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private static double Compute(double input, double alpha, double decay, ref EmaState state)
{
state.Ema = Math.FusedMultiplyAdd(state.Ema, decay, alpha * input);
double result;
if (!state.IsCompensated)
{
state.E *= decay;
if (!state.IsHot && state.E <= 0.05) // COVERAGE_THRESHOLD
{
state.IsHot = true;
}
if (state.E <= 1e-10) // COMPENSATOR_THRESHOLD
{
state.IsCompensated = true;
result = state.Ema;
}
else
{
result = state.Ema / (1.0 - state.E);
}
}
else
{
result = state.Ema;
}
return result;
}
public static TSeries Batch(TSeries source, int period)
{
var dema = new Dema(period);
return dema.Update(source);
}
public static TSeries Batch(TSeries source, double alpha)
{
var dema = new Dema(alpha);
return dema.Update(source);
}
public static void Batch(ReadOnlySpan source, Span output, int period)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
double alpha = 2.0 / (period + 1);
Batch(source, output, alpha);
}
public static void Batch(ReadOnlySpan source, Span output, double alpha)
{
if (source.Length != output.Length)
{
throw new ArgumentException("Source and output must have the same length", nameof(output));
}
if (alpha <= 0 || alpha > 1)
{
throw new ArgumentException("Alpha must be between 0 and 1", nameof(alpha));
}
if (source.Length == 0)
{
return;
}
double decay = 1.0 - alpha;
double lastValid = double.NaN;
// State for EMA1
double ema1_val = 0;
double ema1_e = 1.0;
bool ema1_isCompensated = false;
// State for EMA2
double ema2_val = 0;
double ema2_e = 1.0;
bool ema2_isCompensated = false;
for (int i = 0; i < source.Length; i++)
{
double val = source[i];
if (double.IsFinite(val))
{
lastValid = val;
}
else
{
val = lastValid;
}
if (double.IsNaN(val))
{
output[i] = double.NaN;
continue;
}
// Update EMA1
ema1_val = Math.FusedMultiplyAdd(ema1_val, decay, alpha * val);
double e1;
if (!ema1_isCompensated)
{
ema1_e *= decay;
if (ema1_e <= 1e-10)
{
ema1_isCompensated = true;
e1 = ema1_val;
}
else
{
e1 = ema1_val / (1.0 - ema1_e);
}
}
else
{
e1 = ema1_val;
}
// Update EMA2 (input is e1)
ema2_val = Math.FusedMultiplyAdd(ema2_val, decay, alpha * e1);
double e2;
if (!ema2_isCompensated)
{
ema2_e *= decay;
if (ema2_e <= 1e-10)
{
ema2_isCompensated = true;
e2 = ema2_val;
}
else
{
e2 = ema2_val / (1.0 - ema2_e);
}
}
else
{
e2 = ema2_val;
}
// DEMA = 2 * EMA1 - EMA2
output[i] = Math.FusedMultiplyAdd(2.0, e1, -e2);
}
}
public static (TSeries Results, Dema Indicator) Calculate(TSeries source, int period)
{
var indicator = new Dema(period);
TSeries results = indicator.Update(source);
return (results, indicator);
}
public override void Reset()
{
_state1 = EmaState.New();
_state2 = EmaState.New();
_p_state1 = EmaState.New();
_p_state2 = EmaState.New();
_lastValidValue = double.NaN;
_p_lastValidValue = double.NaN;
Last = default;
}
protected override void Dispose(bool disposing)
{
if (disposing && _publisher != null && _listener != null)
{
_publisher.Pub -= _listener;
}
base.Dispose(disposing);
}
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
}