BitGet_API/BitgetApi/IndicatorConditionSetup/TradingViewConditionSetup.cs

using DevExpress.XtraEditors.TextEditController.InputHandler;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using static System.Windows.Forms.VisualStyles.VisualStyleElement.ToolTip;

namespace BitgetApi.IndicatorConditionSetup
{
    public class TradingViewConditionSetup
    {

        // 기본 파라미터
        public int LengthMA = 34;
        public int LengthSignal = 12;
        public int AdxLength = 12;
        public double AdxThreshold = 24;
        public double RangeThreshold = 1;
        public double RangeThresholdSell = 1;

        // 데이터 입력: High, Low, Close 배열 (최근 것이 맨 끝)
        public List<double> High;
        public List<double> Low;
        public List<double> Close;

        // SMA4 계산용
        private double[] Sma4;

        public void SetData(List<double> high, List<double> low, List<double> close)
        {
            High = high;
            Low = low;
            Close = close;
            Sma4 = ComputeSma4();
        }

        // 1. SMMA 계산
        private double CalcSmma(List<double> src, int len)
        {
            double smma = src.Take(len).Average();
            for (int i = len; i < src.Count; i++)
            {
                smma = (smma * (len - 1) + src[i]) / len;
            }
            return smma;
        }

        // 2. ZLEMA 계산
        private double CalcZlema(List<double> src, int length)
        {
            double ema1 = Ema(src, length);
            double ema2 = Ema(Enumerable.Repeat(ema1, src.Count).ToList(), length);
            double d = ema1 - ema2;
            return ema1 + d;
        }

        // 3. EMA 계산
        private double Ema(List<double> src, int length)
        {
            double alpha = 2.0 / (length + 1);
            double ema = src[0];
            for (int i = 1; i < src.Count; i++)
            {
                ema = alpha * src[i] + (1 - alpha) * ema;
            }
            return ema;
        }

        // 4. SMA(4) 계산
        private double[] ComputeSma4()
        {
            double[] sma4 = new double[Close.Count];
            for (int i = 3; i < Close.Count; i++)
            {
                sma4[i] = (Close[i] + Close[i - 1] + Close[i - 2] + Close[i - 3]) / 4.0;
            }
            return sma4;
        }

        // 5. ADX (가장 간단한 형태)
        private double ComputeAdx()
        {
            // 간단화: 실제 구현 시 true range, directional movement 등 추가 필요
            return 25.0; // 더미값 또는 타 라이브러리 사용 가능
        }

        // 6. Impulse MACD 계산
        public double ComputeMd(bool flag = true)
        {
            if (flag)
            {
                double hi = CalcSmma(High, LengthMA);
                double lo = CalcSmma(Low, LengthMA);
                var hlc3 = High.Zip(Low, (h, l) => (h + l + Close.Last()) / 3).ToList();
                double mi = CalcZlema(hlc3, LengthMA);
                if (mi > hi) return mi - hi;
                else if (mi < lo) return mi - lo;
                return 0;
            }
            else
            {
                var highTemp = new List<double>();
                foreach(var item in High)
                    highTemp.Add(item);
                var lowTemp = new List<double>();
                foreach (var item in Low)
                    lowTemp.Add(item);
                var closeTemp = new List<double>();
                foreach (var item in Close)
                    closeTemp.Add(item);

                highTemp.RemoveAt(highTemp.Count - 1);
                lowTemp.RemoveAt(lowTemp.Count - 1);
                closeTemp.RemoveAt(closeTemp.Count - 1);

                double hi = CalcSmma(highTemp, LengthMA);
                double lo = CalcSmma(lowTemp, LengthMA);
                var hlc3 = highTemp.Zip(lowTemp, (h, l) => (h + l + closeTemp.Last()) / 3).ToList();
                double mi = CalcZlema(hlc3, LengthMA);
                if (mi > hi) return mi - hi;
                else if (mi < lo) return mi - lo;
                return 0;
            }


        }

        // 7. MACD, SignalLine 계산
        public (double macdLine, double signalLine) ComputeMacd()
        {
            double macdLine = Ema(Close, 34) - Ema(Close, 12);
            double signalLine = Ema(Enumerable.Repeat(macdLine, Close.Count).ToList(), 12);
            return (macdLine, signalLine);
        }

        // 7. MACD, SignalLine 계산(이전꺼)
        public (double macdLine, double signalLine) PrevComputeMacd()
        {
            var temp = new List<double>();
            foreach (var item in Close)
                temp.Add(item);
            temp.RemoveAt(temp.Count - 1);

            double macdLine = Ema(temp, 34) - Ema(temp, 12);
            double signalLine = Ema(Enumerable.Repeat(macdLine, temp.Count).ToList(), 12);
            return (macdLine, signalLine);
        }

        // 8. RangeBound 필터
        public bool IsRangeBound()
        {
            double highestHigh = High.Skip(High.Count - 12).Max();
            double lowestLow = Low.Skip(Low.Count - 12).Min();
            double range = highestHigh - lowestLow;
            return range < (highestHigh * RangeThreshold / 100.0);
        }

        public bool IsRangeBoundSell()
        {
            double highestHigh = High.Skip(High.Count - 12).Max();
            double lowestLow = Low.Skip(Low.Count - 12).Min();
            double range = highestHigh - lowestLow;
            return range < (highestHigh * RangeThresholdSell / 100.0);
        }

        // 9. 트렌드 여부
        public bool IsTrending()
        {
            return ComputeAdx() > AdxThreshold;
        }
        public double GetAvgData(int range)
        {
            var sma = 0.0;

            for (var i = 0; i < range; i++)
            {
                sma += Close[Close.Count - (i + 1)];
            }
            return sma / range;
        }

        public double GetAvgData(int range, int prev)
        {
            var sma = 0.0;

            for (var i = 0; i < range; i++)
            {
                sma += Close[Close.Count - (i + 1 + prev)];
            }
            return sma / range;
        }

        // 10. 매수 조건
        public bool IsLongSignal()
        {
            double md = ComputeMd();
            double prevMd = ComputeMd(false);
            var (macd, signal) = ComputeMacd();
            var (prevMacd, prevSignal) = PrevComputeMacd();           

            bool isUptrend = Close.Last() > Sma4.Last();            

            return ((prevMd == 0 && md > 0) || (prevMacd < prevSignal && macd > prevMacd && macd > signal && md > 0)) &&
                   IsTrending() && IsSmaMiddle(4, 12, true, GetAvgData(72)) && GetAvgData(4) > GetAvgData(4, 1);

            //return isUptrend &&
            //       ((prevMd == 0 && md > 0) || (macd > prevMacd && signal > prevSignal && md > 0 && macd > signal)) &&
            //       IsTrending() && !IsRangeBound();
        }

        // 11. 매도 조건
        public bool IsShortSignal()
        {
            double md = ComputeMd();
            double prevMd = ComputeMd(false);
            var (macd, signal) = ComputeMacd();
            var (prevMacd, prevSignal) = PrevComputeMacd();

            bool isDowntrend = Close.Last() < Sma4.Last();

            return ((prevMd == 0 && md < 0) || (prevMacd > prevSignal && macd < prevMacd && macd < signal && md < 0)) &&
                   IsTrending() && IsSmaMiddle(4, 12, false, GetAvgData(72)) && GetAvgData(4) < GetAvgData(4, 1);

            //return isDowntrend &&
            //      ((prevMd == 0 && md < 0) || (macd < prevMacd && signal < prevSignal && md < 0 && macd < signal)) &&
            //      IsTrending() && !IsRangeBoundSell();


        }

        public bool IsSmaHigh(int range, int count)
        {
            var list = new List<double>();
            for (int i = Close.Count - count - 1; i < count; i++)
            {
                var sum = 0.0;
                for(int j = 0;j < range; j++)
                {
                    sum += Close[i-j];
                }
                var data = sum / range;
                list.Add(data);
            }

            if (list.Max() == list[list.Count - 1])
                return true;
            else
                return false;
        }

        public bool IsSmaLow(int range, int count)
        {
            var list = new List<double>();
            for (int i = Close.Count - count - 1; i < count; i++)
            {
                var sum = 0.0;
                for (int j = 0; j < range; j++)
                {
                    sum += Close[i - j];
                }
                var data = sum / range;
                list.Add(data);
            }

            if (list.Min() == list[list.Count - 1])
                return true;
            else
                return false;
        }
        
        public bool IsSmaMiddle(int range, int count, bool longFlag, double value) {
            var list = new List<double>();
            for (int i = Close.Count - count - 1; i < count; i++)
            {
                var sum = 0.0;
                for (int j = 0; j < range; j++)
                {
                    sum += Close[i - j];
                }
                var data = sum / range;
                list.Add(data);
            }

            if (longFlag)
            {
                if(value < list.Average())
                {
                    return true;
                }                
            }
            else
            {
                if (value > list.Average())
                {
                    return true;
                }
            }
            return false;
        }
    }
}