namespace QuanTAlib;
using System;

/* <summary>
SMA: Simple Moving Average
    The weights are equally distributed across the period, resulting in a mean() of
    the data within the period/

Sources:
    https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/simple-moving-average-sma/
    https://stats.stackexchange.com/a/24739

Remark:
    This calc doesn't use LINQ or SUM() or any of (slow) iterative methods. It is not as fast as TA-LIB
    implementation, but it does allow incremental additions of inputs and real-time calculations of SMA()

</summary> */

public class SMA_Series : Single_TSeries_Indicator
{
    public SMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
    {
        if (base._data.Count > 0) { base.Add(base._data); }
    }
    private readonly System.Collections.Generic.List<double> _buffer = new();

    public override void Add((System.DateTime t, double v) TValue, bool update)
    {
        if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
        else { _buffer.Add(TValue.v); }
        if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }

        double _sma = 0;
        for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; }
        _sma /= this._buffer.Count;

        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _sma);

        base.Add(result, update);
    }
}