// NORMALIZE: Min-Max Normalization // Scales values to [0, 1] range using min-max scaling over a lookback period // Formula: (x - min) / (max - min) using System.Runtime.CompilerServices; using System.Runtime.InteropServices; namespace QuanTAlib; /// /// NORMALIZE: Min-Max Normalization /// Scales values to the range [0, 1] using min-max normalization over a lookback period. /// /// /// Key properties: /// - Output always between 0 and 1 (inclusive when value equals min or max) /// - Uses rolling window to track min and max /// - Division by zero (flat range) returns 0.5 as neutral value /// - Commonly used for feature scaling and bounded indicators /// [SkipLocalsInit] public sealed class Normalize : AbstractBase { private readonly int _period; private readonly RingBuffer _buffer; [StructLayout(LayoutKind.Auto)] private record struct State(double LastValidNorm, double Min, double Max); private State _state, _p_state; public override bool IsHot => _buffer.Count >= _period; /// /// Initializes a new Normalize indicator with specified lookback period. /// /// Lookback period for min/max calculation (default 14) public Normalize(int period = 14) { if (period < 1) { throw new ArgumentException("Period must be >= 1", nameof(period)); } _period = period; _buffer = new RingBuffer(period); Name = $"Normalize({period})"; WarmupPeriod = period; _state = new State(0.5, double.MaxValue, double.MinValue); _p_state = _state; } /// /// Initializes a new Normalize indicator with source for event-based chaining. /// /// Source indicator for chaining /// Lookback period (default 14) public Normalize(ITValuePublisher source, int period = 14) : this(period) { source.Pub += HandleUpdate; } [MethodImpl(MethodImplOptions.AggressiveInlining)] private void HandleUpdate(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew); [MethodImpl(MethodImplOptions.AggressiveInlining)] private static (double min, double max) FindMinMax(ReadOnlySpan values) { if (values.Length == 0) { return (double.MaxValue, double.MinValue); } double min = values[0]; double max = values[0]; for (int i = 1; i < values.Length; i++) { double v = values[i]; if (v < min) { min = v; } if (v > max) { max = v; } } return (min, max); } [MethodImpl(MethodImplOptions.AggressiveInlining)] public override TValue Update(TValue input, bool isNew = true) { if (isNew) { _p_state = _state; } else { _state = _p_state; } double value = input.Value; double result; if (double.IsFinite(value)) { _buffer.Add(value, isNew); // Find min and max in the buffer var (min, max) = FindMinMax(_buffer.GetSpan()); double range = max - min; // Flat range: return 0.5 as neutral result = range > 0 ? (value - min) / range : 0.5; _state = new State(result, min, max); } else { result = _state.LastValidNorm; } Last = new TValue(input.Time, result); PubEvent(Last, isNew); return Last; } public override TSeries Update(TSeries source) { var result = new TSeries(source.Count); ReadOnlySpan values = source.Values; ReadOnlySpan times = source.Times; for (int i = 0; i < source.Count; i++) { var tv = Update(new TValue(new DateTime(times[i], DateTimeKind.Utc), values[i]), true); result.Add(tv, true); } return result; } public override void Prime(ReadOnlySpan source, TimeSpan? step = null) { TimeSpan interval = step ?? TimeSpan.FromSeconds(1); DateTime time = DateTime.UtcNow - (interval * source.Length); for (int i = 0; i < source.Length; i++) { Update(new TValue(time, source[i]), true); time += interval; } } public static TSeries Batch(TSeries source, int period = 14) { var indicator = new Normalize(period); return indicator.Update(source); } /// /// Calculates Min-Max Normalization over a span of values. /// public static void Batch(ReadOnlySpan source, Span output, int period = 14) { if (source.Length == 0) { throw new ArgumentException("Source cannot be empty", nameof(source)); } if (output.Length < source.Length) { throw new ArgumentException("Output length must be >= source length", nameof(output)); } if (period < 1) { throw new ArgumentException("Period must be >= 1", nameof(period)); } double lastValid = 0.5; for (int i = 0; i < source.Length; i++) { double val = source[i]; if (!double.IsFinite(val)) { output[i] = lastValid; continue; } // Determine window bounds int start = Math.Max(0, i - period + 1); // Find min/max in window - initialize to infinity to handle non-finite starting values double min = double.PositiveInfinity; double max = double.NegativeInfinity; for (int j = start; j <= i; j++) { double v = source[j]; if (double.IsFinite(v)) { if (v < min) { min = v; } if (v > max) { max = v; } } } // If no finite values found in window, use neutral output if (!double.IsFinite(min) || !double.IsFinite(max)) { output[i] = lastValid; continue; } double range = max - min; double result = range > 0 ? (val - min) / range : 0.5; lastValid = result; output[i] = result; } } public static (TSeries Results, Normalize Indicator) Calculate(TSeries source, int period = 14) { var indicator = new Normalize(period); TSeries results = indicator.Update(source); return (results, indicator); } public override void Reset() { _buffer.Clear(); _state = new State(0.5, double.MaxValue, double.MinValue); _p_state = _state; Last = default; } }