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QuanTAlib/lib/trends/ema/Ema.cs
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Miha Kralj b26d5d7751 Enhance code quality and stability across various modules
- Updated .coderabbit.yaml to exclude additional file types from reviews, improving the focus on relevant code changes.
- Modified scanner.sh to handle test failures more gracefully, ensuring that analysis stops on test failures and improving logging.
- Improved sonarscanner.sh to ensure build and test failures are properly reported, enhancing CI reliability.
- Refined SimdExtensions.cs documentation for clarity on variance calculation methods.
- Cleaned up TSeries.Tests.cs by simplifying the test structure and ensuring proper namespace usage.
- Fixed potential issues in tseries.cs by ensuring correct handling of DateTime values.
- Enhanced CsvFeed.cs to improve error handling during CSV parsing, ensuring robustness against malformed data.
- Updated GBM.cs to correctly calculate volume in the current bar, ensuring accurate simulation.
- Adjusted index.html to use globalThis for better compatibility across environments.
- Refined quantalib.csproj to exclude unnecessary files from compilation, streamlining the build process.
- Added comprehensive tests for the Mama class to ensure correct behavior during updates and state management.
- Improved error handling in various trend classes (Kama, Dema, Ema, T3, Tema, Wma) to ensure NaN values are managed correctly.
- Removed redundant Mama.Repro.Tests.cs file and consolidated tests into Mama.Tests.cs for better organization.
- Enhanced T3 and Tema classes to maintain state integrity during updates, particularly with NaN values.
2025-12-10 14:51:58 -05:00

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using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
/// <summary>
/// EMA: Exponential Moving Average
/// </summary>
/// <remarks>
/// EMA applies exponential weighting to data points, giving more weight to recent values.
/// Uses a single state variable for O(1) complexity per update.
///
/// Calculation:
/// alpha = 2 / (period + 1)
/// EMA_new = EMA_old + alpha * (newest - EMA_old)
///
/// Initialization:
/// Uses a compensator factor to correct early-stage bias (when n < period).
/// Output = EMA_state / (1 - (1-alpha)^n)
///
/// O(1) update:
/// No buffer required, only previous EMA value and compensator state.
///
/// IsHot:
/// Becomes true when n = ln(0.05) / ln(1 - alpha)
/// </remarks>
[SkipLocalsInit]
public sealed class Ema : ITValuePublisher
{
private struct State : IEquatable<State>
{
public double Ema;
public double E;
public bool IsHot;
public bool IsCompensated;
public static State New() => new() { Ema = 0, E = 1.0, IsHot = false, IsCompensated = false };
public override bool Equals(object? obj) => obj is State other && Equals(other);
public bool Equals(State other) =>
Ema == other.Ema &&
E == other.E &&
IsHot == other.IsHot &&
IsCompensated == other.IsCompensated;
public override int GetHashCode() => HashCode.Combine(Ema, E, IsHot, IsCompensated);
public static bool operator ==(State left, State right) => left.Equals(right);
public static bool operator !=(State left, State right) => !left.Equals(right);
}
private readonly double _alpha;
private readonly double _decay;
private State _state = State.New();
private State _p_state = State.New();
private double _lastValidValue;
private double _p_lastValidValue;
/// <summary>
/// Display name for the indicator.
/// </summary>
public string Name { get; }
public event Action<TValue>? Pub;
/// <summary>
/// Creates EMA with specified period.
/// Alpha = 2 / (period + 1)
/// </summary>
/// <param name="period">Period for EMA calculation (must be > 0)</param>
public Ema(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 = $"Ema({period})";
}
/// <summary>
/// Creates EMA with specified source and period.
/// Subscribes to source.Pub event.
/// </summary>
/// <param name="source">Source to subscribe to</param>
/// <param name="period">Period for EMA calculation</param>
public Ema(ITValuePublisher source, int period) : this(period)
{
source.Pub += (item) => Update(item);
}
/// <summary>
/// Creates EMA with specified alpha smoothing factor.
/// </summary>
/// <param name="alpha">Smoothing factor (0 &lt; alpha &lt;= 1)</param>
public Ema(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 = $"Ema(α={alpha:F4})";
}
/// <summary>
/// Current EMA value.
/// </summary>
public TValue Last { get; private set; }
/// <summary>
/// True if the EMA has warmed up and is providing valid results.
/// </summary>
public bool IsHot => _state.IsHot;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double GetValidValue(double input)
{
if (double.IsFinite(input))
{
_lastValidValue = input;
return input;
}
return _lastValidValue;
}
private const double COVERAGE_THRESHOLD = 0.05;
private const double COMPENSATOR_THRESHOLD = 1e-10;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public TValue Update(TValue input, bool isNew = true)
{
if (isNew)
{
_p_state = _state;
_p_lastValidValue = _lastValidValue;
}
else
{
_state = _p_state;
_lastValidValue = _p_lastValidValue;
}
double val = GetValidValue(input.Value);
val = Compute(val, _alpha, _decay, ref _state);
Last = new TValue(input.Time, val);
Pub?.Invoke(Last);
return Last;
}
public TSeries Update(TSeries source)
{
if (source.Count == 0) return [];
int len = source.Count;
var t = new List<long>(len);
var v = new List<double>(len);
CollectionsMarshal.SetCount(t, len);
CollectionsMarshal.SetCount(v, len);
var tSpan = CollectionsMarshal.AsSpan(t);
var vSpan = CollectionsMarshal.AsSpan(v);
var sourceValues = source.Values;
var sourceTimes = source.Times;
State state = _state;
double lastValidValue = _lastValidValue;
CalculateCore(sourceValues, vSpan, _alpha, ref state, ref lastValidValue);
_state = state;
_lastValidValue = lastValidValue;
sourceTimes.CopyTo(tSpan);
_p_state = _state;
_p_lastValidValue = _lastValidValue;
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 State state)
{
state.Ema += alpha * (input - state.Ema);
double result;
if (!state.IsCompensated)
{
state.E *= decay;
if (!state.IsHot && state.E <= COVERAGE_THRESHOLD)
state.IsHot = true;
if (state.E <= COMPENSATOR_THRESHOLD)
{
state.IsCompensated = true;
result = state.Ema;
}
else
{
result = state.Ema / (1.0 - state.E);
}
}
else
{
result = state.Ema;
}
return result;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static void CalculateCore(ReadOnlySpan<double> source, Span<double> output, double alpha, ref State state, ref double lastValidValue)
{
int len = source.Length;
double decay = 1.0 - alpha;
int i = 0;
if (!state.IsCompensated)
{
for (; i < len && state.E > COMPENSATOR_THRESHOLD; i++)
{
double val = source[i];
if (double.IsFinite(val))
lastValidValue = val;
else
val = lastValidValue;
state.Ema += alpha * (val - state.Ema);
state.E *= decay;
if (!state.IsHot && state.E <= COVERAGE_THRESHOLD)
state.IsHot = true;
output[i] = state.Ema / (1.0 - state.E);
}
if (state.E <= COMPENSATOR_THRESHOLD)
state.IsCompensated = true;
}
for (; i < len; i++)
{
double val = source[i];
if (double.IsFinite(val))
lastValidValue = val;
else
val = lastValidValue;
state.Ema += alpha * (val - state.Ema);
output[i] = state.Ema;
}
}
/// <summary>
/// Calculates EMA for the entire series using a new instance.
/// </summary>
/// <param name="source">Input series</param>
/// <param name="period">EMA period</param>
/// <returns>EMA series</returns>
public static TSeries Calculate(TSeries source, int period)
{
var ema = new Ema(period);
return ema.Update(source);
}
/// <summary>
/// Calculates EMA in-place using period, writing results to pre-allocated output span.
/// Zero-allocation method for maximum performance.
/// Alpha = 2 / (period + 1)
/// </summary>
/// <param name="source">Input values</param>
/// <param name="output">Output span (must be same length as source)</param>
/// <param name="period">EMA period (must be > 0)</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Calculate(ReadOnlySpan<double> source, Span<double> output, int period)
{
if (period <= 0)
throw new ArgumentException("Period must be greater than 0", nameof(period));
double alpha = 2.0 / (period + 1);
Calculate(source, output, alpha);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Calculate(ReadOnlySpan<double> source, Span<double> output, double alpha)
{
if (source.Length != output.Length)
throw new ArgumentException("Source and output must have the same length");
if (alpha <= 0 || alpha > 1)
throw new ArgumentException("Alpha must be between 0 and 1", nameof(alpha));
if (source.Length == 0) return;
var state = State.New();
double lastValid = 0;
CalculateCore(source, output, alpha, ref state, ref lastValid);
}
/// <summary>
/// Resets the EMA state.
/// </summary>
public void Reset()
{
_state = State.New();
_p_state = _state;
_lastValidValue = 0;
_p_lastValidValue = 0;
Last = default;
}
}