using KLHZ.Trader.Core.Contracts.Declisions.Dtos.Enums;
using MathNet.Numerics;

namespace KLHZ.Trader.Core.Math.Declisions.Utils
{
    /// <summary>
    /// Обработка последних интервалов истории изменения цен.
    /// </summary>
    public static class LocalTrends
    {
        public static bool TryGetLocalTrends(DateTime[] times, decimal[] prices, TimeSpan firstPeriod, TimeSpan lastPeriod,
            double meanfullDiff, out TradingEvent res)
        {
            res = TradingEvent.None;
            var success = false;

            if (times.Length == 0)
            {
                return success;
            }
            var x1 = new List<double>();
            var y1 = new List<double>();
            var x1d = new List<DateTime>();
            var x2 = new List<double>();
            var y2 = new List<double>();
            var x2d = new List<DateTime>();
            var y1_approximated = new List<double>();
            var y2_approximated = new List<double>();

            var lastTime = times[times.Length - 1];
            var firstTime = times[0];
            var fullPeriod = firstPeriod + lastPeriod;

            if (lastTime - firstTime > fullPeriod)
            {
                for (int i = 1; i < times.Length - 1; i++)
                {
                    var dt1 = lastTime - times[times.Length - i];
                    if (dt1 <= lastPeriod)
                    {
                        x2.Add((times[times.Length - i] - firstTime).TotalSeconds);
                        x2d.Add(times[times.Length - i]);
                        y2.Add((double)prices[times.Length - i]);
                    }
                    else if (dt1 <= fullPeriod)
                    {
                        x1.Add((times[times.Length - i] - firstTime).TotalSeconds);
                        x1d.Add(times[times.Length - i]);
                        y1.Add((double)prices[times.Length - i]);
                    }
                    else
                    {
                        success = true;
                        break;
                    }
                }

                if (x1.Count > 1 && x2.Count > 1)
                {
                    var line1 = Fit.Line(x1.ToArray(), y1.ToArray());
                    var line2 = Fit.Line(x2.ToArray(), y2.ToArray());
                    foreach (var x in x1)
                    {
                        y1_approximated.Add(line1.A + x * line1.B);
                    }
                    foreach (var x in x2)
                    {
                        y2_approximated.Add(line2.A + x * line2.B);
                    }
                    var diff1 = y1_approximated[0] - y1_approximated[y1_approximated.Count - 1];
                    var diff2 = y2_approximated[0] - y2_approximated[y2_approximated.Count - 1];
                    if (diff1 <= -meanfullDiff && diff2 >= meanfullDiff)
                    {
                        res |= TradingEvent.CloseShort;
                    }
                    else if (diff1 >= meanfullDiff && diff2 <= -meanfullDiff)
                    {
                        res |= TradingEvent.CloseLong;
                    }
                    else if (diff1 <= -meanfullDiff && diff2 >= meanfullDiff)
                    {
                        res |= TradingEvent.CloseShort;
                    }
                    else if (diff1 >= 0 && diff2 <= -meanfullDiff)
                    {
                        res |= TradingEvent.OpenShort;
                    }
                    success = true;
                }

            }
            return success;
        }

        public static bool TryCalcTrendDiff(DateTime[] times, decimal[] prices, out decimal diff)
        {
            diff = 0;
            if (times.Length <= 1 || times.Length != prices.Length)
            {
                return false;
            }
            else
            {
                var startTime = times[0];
                var x = new double[times.Length];
                for (int i = 0; i < times.Length - 1; i++)
                {
                    x[i] = (times[i] - startTime).TotalSeconds;
                }
                var line = Fit.Line(x.ToArray(), prices.Select(p => (double)p).ToArray());

                var p1 = line.A + line.B * 0;
                var p2 = line.A + line.B * (times[times.Length - 1] - times[0]).TotalSeconds;

                diff = (decimal)(p2 - p1);
                return true;
            }
        }
    }
}