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https://github.com/mihakralj/QuanTAlib.git
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158 lines
4.9 KiB
C#
158 lines
4.9 KiB
C#
using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// Median: Central Tendency Measure
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/// A robust statistical measure that finds the middle value in a sorted dataset.
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/// The median is less sensitive to outliers than the mean, making it particularly
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/// useful for analyzing price data with extreme values.
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/// </summary>
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/// <remarks>
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/// The Median calculation process:
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/// 1. Collects values over specified period
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/// 2. Sorts values in ascending order
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/// 3. Finds middle value(s)
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/// 4. Averages two middle values if even count
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///
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/// Key characteristics:
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/// - Robust to outliers
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/// - Always represents actual data point
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/// - Splits dataset in half
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/// - More stable than mean
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/// - Maintains data scale
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///
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/// Formula:
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/// For odd n: median = value at position (n+1)/2
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/// For even n: median = (value at n/2 + value at (n/2)+1) / 2
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///
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/// Market Applications:
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/// - Price distribution analysis
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/// - Trend identification
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/// - Outlier detection
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/// - Support/resistance levels
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/// - Filter extreme movements
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///
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/// Sources:
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/// https://en.wikipedia.org/wiki/Median
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/// "Statistics for Trading" - Technical Analysis of Financial Markets
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///
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/// Note: More robust than mean for non-normal distributions
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Median : AbstractBase
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{
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private readonly int Period;
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private readonly CircularBuffer _buffer;
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/// <param name="period">The number of points to consider for median calculation.</param>
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/// <exception cref="ArgumentOutOfRangeException">Thrown when period is less than 1.</exception>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Median(int period)
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{
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if (period < 1)
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{
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throw new ArgumentOutOfRangeException(nameof(period),
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"Period must be greater than or equal to 1.");
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}
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Period = period;
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WarmupPeriod = period;
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_buffer = new CircularBuffer(period);
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Name = $"Median(period={period})";
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Init();
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}
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The number of points to consider for median calculation.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Median(object source, int period) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override void Init()
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{
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base.Init();
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_buffer.Clear();
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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}
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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private static void QuickSort(Span<double> arr, int left, int right)
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{
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if (left < right)
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{
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int pivotIndex = Partition(arr, left, right);
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QuickSort(arr, left, pivotIndex - 1);
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QuickSort(arr, pivotIndex + 1, right);
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}
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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private static int Partition(Span<double> arr, int left, int right)
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{
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double pivot = arr[right];
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int i = left - 1;
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for (int j = left; j < right; j++)
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{
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if (arr[j] <= pivot)
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{
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i++;
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(arr[i], arr[j]) = (arr[j], arr[i]);
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}
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}
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(arr[i + 1], arr[right]) = (arr[right], arr[i + 1]);
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return i + 1;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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private static double CalculateMedian(Span<double> sortedValues)
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{
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int middleIndex = sortedValues.Length / 2;
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return (sortedValues.Length % 2 == 0)
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? (sortedValues[middleIndex - 1] + sortedValues[middleIndex]) / 2.0
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: sortedValues[middleIndex];
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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double median;
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if (_index >= Period)
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{
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// Create a temporary buffer on the stack
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Span<double> values = stackalloc double[Period];
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_buffer.GetSpan().CopyTo(values);
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// Sort values in-place
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QuickSort(values, 0, values.Length - 1);
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// Calculate median based on odd/even count
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median = CalculateMedian(values);
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}
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else
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{
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// Not enough data, use average as temporary measure
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median = _buffer.Average();
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}
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IsHot = _index >= WarmupPeriod;
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return median;
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}
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}
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