mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-18 02:28:05 +00:00
- Introduced Usf.Validation.Tests.cs to validate the USF (Ehlers Ultimate Smoother Filter) for consistency across batch, streaming, and span modes, as well as mathematical properties and coefficient calculations. - Added comprehensive tests for the ATR indicator in Atr.Quantower.Tests.cs, including constructor validation, historical data processing, and handling of NaN/Infinity inputs. - Enhanced Atr.Tests.cs with additional tests for iterative corrections, warmup behavior, and true range calculations. - Updated Atr.cs to ensure warmup period is derived from RMA. - Added new tests for Adosc in Adosc.Tests.cs to validate handling of NaN and Infinity inputs, and to ensure batch calculations match iterative results. - Created a new Volatility.csproj to organize volatility-related implementations.
152 lines
4.9 KiB
C#
152 lines
4.9 KiB
C#
using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// RMA: Running Moving Average (also known as Wilder's Moving Average or SMMA)
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/// </summary>
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/// <remarks>
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/// RMA is an Exponential Moving Average (EMA) with a different smoothing factor.
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/// While EMA uses alpha = 2 / (period + 1), RMA uses alpha = 1 / period.
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///
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/// Calculation:
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/// alpha = 1 / period
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/// RMA_new = RMA_old + alpha * (newest - RMA_old)
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///
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/// This implementation wraps the EMA implementation to ensure identical behavior and performance,
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/// utilizing the same O(1) update complexity and zero-allocation architecture.
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Rma : AbstractBase
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{
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private readonly Ema _ema;
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/// <summary>
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/// Creates RMA with specified period.
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/// Alpha = 1 / period
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/// </summary>
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/// <param name="period">Period for RMA calculation (must be > 0)</param>
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public Rma(int period)
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{
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if (period <= 0)
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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_ema = new Ema(1.0 / period);
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Name = $"Rma({period})";
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WarmupPeriod = _ema.WarmupPeriod;
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}
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/// <summary>
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/// Creates RMA with specified source and period.
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/// Subscribes to source.Pub event.
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/// </summary>
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/// <param name="source">Source to subscribe to</param>
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/// <param name="period">Period for RMA calculation</param>
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public Rma(ITValuePublisher source, int period) : this(period)
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{
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ArgumentNullException.ThrowIfNull(source);
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source.Pub += Handle;
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}
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/// <summary>
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/// Creates RMA with specified source and period.
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/// </summary>
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/// <param name="source">Source series</param>
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/// <param name="period">Period for RMA calculation (must be > 0)</param>
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public Rma(TSeries source, int period) : this(period)
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{
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ArgumentNullException.ThrowIfNull(source);
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Prime(source.Values);
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if (source.Count > 0)
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{
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Last = new TValue(source.LastTime, Last.Value);
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}
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source.Pub += Handle;
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}
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/// <summary>
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/// True if the RMA has warmed up and is providing valid results.
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/// </summary>
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public override bool IsHot => _ema.IsHot;
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/// <summary>
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/// Initializes the indicator state using the provided history.
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/// </summary>
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/// <param name="source">Historical data</param>
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public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
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{
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_ema.Prime(source);
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Last = _ema.Last;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
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public override TValue Update(TValue input, bool isNew = true)
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{
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TValue result = _ema.Update(input, isNew);
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Last = result;
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PubEvent(Last, isNew);
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return result;
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}
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public override TSeries Update(TSeries source)
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{
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TSeries result = _ema.Update(source);
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Last = _ema.Last;
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return result;
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}
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/// <summary>
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/// Calculates RMA for the entire series using a new instance.
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/// </summary>
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/// <param name="source">Input series</param>
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public static TSeries Batch(TSeries source, int period)
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{
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ArgumentNullException.ThrowIfNull(source);
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var rma = new Rma(period);
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return rma.Update(source);
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}
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/// <summary>
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/// Calculates RMA in-place using period, writing results to pre-allocated output span.
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/// Zero-allocation method for maximum performance.
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/// Alpha = 1 / period
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/// </summary>
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/// <param name="source">Input values</param>
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public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period)
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{
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if (period <= 0)
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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if (output.Length < source.Length)
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throw new ArgumentException("Output span must be at least as long as source span", nameof(output));
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double alpha = 1.0 / period;
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Ema.Batch(source, output, alpha);
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}
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/// <summary>
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/// Runs a high-performance batch calculation on history and returns
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/// a "Hot" Rma instance ready to process the next tick immediately.
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/// </summary>
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/// <param name="source">Historical time series</param>
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/// <param name="period">RMA Period</param>
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/// <returns>A tuple containing the full calculation results and the hot indicator instance</returns>
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public static (TSeries Results, Rma Indicator) Calculate(TSeries source, int period)
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{
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ArgumentNullException.ThrowIfNull(source);
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var rma = new Rma(period);
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TSeries results = rma.Update(source);
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return (results, rma);
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}
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/// <summary>
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/// Resets the RMA state.
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/// </summary>
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public override void Reset()
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{
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_ema.Reset();
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Last = default;
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}
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} |