using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
///
/// TEMA: Triple Exponential Moving Average
///
///
/// Uses triple smoothing to further reduce lag beyond DEMA.
/// Excellent for fast trend identification with minimal overshoot.
///
/// Calculation: TEMA = 3×EMA1 - 3×EMA2 + EMA3 (cascaded EMAs).
///
/// Detailed documentation
/// Reference Pine Script implementation
[SkipLocalsInit]
public sealed class Tema : 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 _state3 = EmaState.New();
private EmaState _p_state1 = EmaState.New();
private EmaState _p_state2 = EmaState.New();
private EmaState _p_state3 = EmaState.New();
private readonly TValuePublishedHandler _handler;
private double _lastValidValue;
private double _p_lastValidValue;
public override bool IsHot => _state3.E <= 0.09;
public Tema(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 = $"Tema({period})";
WarmupPeriod = period * 3;
_handler = Handle;
}
public Tema(ITValuePublisher source, int period) : this(period)
{
source.Pub += _handler;
}
public Tema(TSeries source, int period) : this(period)
{
Prime(source.Values);
if (source.Count > 0)
{
Last = new TValue(source.LastTime, Last.Value);
}
source.Pub += _handler;
}
public Tema(double alpha)
{
if (alpha <= 0 || alpha >= 1)
{
throw new ArgumentException("Alpha must be strictly between 0 and 1", nameof(alpha));
}
_alpha = alpha;
_decay = 1.0 - alpha;
Name = $"Tema(α={alpha:F4})";
WarmupPeriod = (int)(3 * (2.0 / alpha - 1.0));
_handler = Handle;
}
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
///
/// Initializes the indicator state using the provided history.
///
/// Historical data
public override void Prime(ReadOnlySpan source, TimeSpan? step = null)
{
if (source.Length == 0)
{
return;
}
// Reset state
_state1 = EmaState.New();
_state2 = EmaState.New();
_state3 = EmaState.New();
_p_state1 = EmaState.New();
_p_state2 = EmaState.New();
_p_state3 = EmaState.New();
_lastValidValue = 0;
_p_lastValidValue = 0;
// Run the calculation on the history to update state
// We don't need the output, just the final state
int len = source.Length;
double lastValid = 0;
// Search for the first finite value to initialize lastValid
// If no finite value is found, lastValid remains 0
for (int i = 0; i < len; i++)
{
if (double.IsFinite(source[i]))
{
lastValid = source[i];
break;
}
}
EmaState s1 = _state1;
EmaState s2 = _state2;
EmaState s3 = _state3;
double alpha = _alpha;
double decay = _decay;
for (int i = 0; i < len; i++)
{
double val = source[i];
if (double.IsFinite(val))
{
lastValid = val;
}
else
{
val = lastValid;
}
double e1 = Compute(val, alpha, decay, ref s1);
double e2 = Compute(e1, alpha, decay, ref s2);
Compute(e2, alpha, decay, ref s3);
}
_state1 = s1;
_state2 = s2;
_state3 = s3;
_lastValidValue = lastValid;
// Calculate the initial "Last" value
// We need to re-compute the last step to get the result
// But Compute updates state, so we can't just call it again without side effects if we pass ref state.
// However, we can calculate the result from the current state.
// TEMA = 3 * EMA1 - 3 * EMA2 + EMA3
// The state contains the updated EMA values (Ema field).
// But wait, Compute returns the *compensated* value.
// The state.Ema is the raw EMA value.
// We need to apply compensation logic to get the correct E1, E2, E3.
double GetCompensated(EmaState s)
{
if (s.IsCompensated)
{
return s.Ema;
}
return s.Ema / (1.0 - s.E);
}
double e1_final = GetCompensated(_state1);
double e2_final = GetCompensated(_state2);
double e3_final = GetCompensated(_state3);
// TEMA = 3 * e1 - 3 * e2 + e3 = FMA(3, e1, FMA(-3, e2, e3))
double result = Math.FusedMultiplyAdd(3.0, e1_final, Math.FusedMultiplyAdd(-3.0, e2_final, e3_final));
Last = new TValue(DateTime.MinValue, result);
_p_state1 = _state1;
_p_state2 = _state2;
_p_state3 = _state3;
_p_lastValidValue = _lastValidValue;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
if (isNew)
{
_p_state1 = _state1;
_p_state2 = _state2;
_p_state3 = _state3;
_p_lastValidValue = _lastValidValue;
}
else
{
_state1 = _p_state1;
_state2 = _p_state2;
_state3 = _p_state3;
_lastValidValue = _p_lastValidValue;
}
// EMA1
double val = input.Value;
if (double.IsFinite(val))
{
_lastValidValue = val;
}
else
{
val = _lastValidValue;
}
double e1 = Compute(val, _alpha, _decay, ref _state1);
// EMA2 (input is e1)
double e2 = Compute(e1, _alpha, _decay, ref _state2);
// EMA3 (input is e2)
double e3 = Compute(e2, _alpha, _decay, ref _state3);
// TEMA = 3 * e1 - 3 * e2 + e3 = FMA(3, e1, FMA(-3, e2, e3))
double result = Math.FusedMultiplyAdd(3.0, e1, Math.FusedMultiplyAdd(-3.0, e2, e3));
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;
// Use current state
EmaState s1 = _state1;
EmaState s2 = _state2;
EmaState s3 = _state3;
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;
}
double e1 = Compute(val, alpha, decay, ref s1);
double e2 = Compute(e1, alpha, decay, ref s2);
double e3 = Compute(e2, alpha, decay, ref s3);
// TEMA = 3 * e1 - 3 * e2 + e3 = FMA(3, e1, FMA(-3, e2, e3))
vSpan[i] = Math.FusedMultiplyAdd(3.0, e1, Math.FusedMultiplyAdd(-3.0, e2, e3));
}
// Update instance state
_state1 = s1;
_state2 = s2;
_state3 = s3;
_p_state1 = s1;
_p_state2 = s2;
_p_state3 = s3;
_lastValidValue = lastValid;
_p_lastValidValue = lastValid;
Last = new TValue(tSpan[len - 1], vSpan[len - 1]);
return new TSeries(t, v);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static double Compute(double input, double alpha, double decay, ref EmaState state)
{
// EMA update: ema = decay * ema + alpha * input = FMA(decay, ema, alpha * input)
state.Ema = Math.FusedMultiplyAdd(decay, state.Ema, 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 tema = new Tema(period);
return tema.Update(source);
}
public static TSeries Batch(TSeries source, double alpha)
{
var tema = new Tema(alpha);
return tema.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 strictly between 0 and 1", nameof(alpha));
}
if (source.Length == 0)
{
return;
}
double decay = 1.0 - alpha;
double lastValid = 0;
// Search for the first finite value to initialize lastValid
for (int i = 0; i < source.Length; i++)
{
if (double.IsFinite(source[i]))
{
lastValid = source[i];
break;
}
}
// 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;
// State for EMA3
double ema3_val = 0;
double ema3_e = 1.0;
bool ema3_isCompensated = false;
for (int i = 0; i < source.Length; i++)
{
double val = source[i];
if (double.IsFinite(val))
{
lastValid = val;
}
else
{
val = lastValid;
}
// Update EMA1: ema = decay * ema + alpha * input = FMA(decay, ema, alpha * input)
ema1_val = Math.FusedMultiplyAdd(decay, ema1_val, 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): ema = decay * ema + alpha * input
ema2_val = Math.FusedMultiplyAdd(decay, ema2_val, 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;
}
// Update EMA3 (input is e2): ema = decay * ema + alpha * input
ema3_val = Math.FusedMultiplyAdd(decay, ema3_val, alpha * e2);
double e3;
if (!ema3_isCompensated)
{
ema3_e *= decay;
if (ema3_e <= 1e-10)
{
ema3_isCompensated = true;
e3 = ema3_val;
}
else
{
e3 = ema3_val / (1.0 - ema3_e);
}
}
else
{
e3 = ema3_val;
}
// TEMA = 3 * EMA1 - 3 * EMA2 + EMA3 = FMA(3, e1, FMA(-3, e2, e3))
output[i] = Math.FusedMultiplyAdd(3.0, e1, Math.FusedMultiplyAdd(-3.0, e2, e3));
}
}
public static (TSeries Results, Tema Indicator) Calculate(TSeries source, int period)
{
var indicator = new Tema(period);
TSeries results = indicator.Update(source);
return (results, indicator);
}
public override void Reset()
{
_state1 = EmaState.New();
_state2 = EmaState.New();
_state3 = EmaState.New();
_p_state1 = EmaState.New();
_p_state2 = EmaState.New();
_p_state3 = EmaState.New();
_lastValidValue = 0;
_p_lastValidValue = 0;
Last = default;
}
}