using OoplesFinance.StockIndicators;
using OoplesFinance.StockIndicators.Models;
using System;
using System.Linq;
using Skender.Stock.Indicators;
using Xunit;
using Xunit.Abstractions;

namespace QuanTAlib.Tests;

public sealed class StcValidationTests : IDisposable
{
    private readonly ValidationTestData _testData;
    private readonly ITestOutputHelper _output;

    public StcValidationTests(ITestOutputHelper output)
    {
        _output = output;
        _testData = new ValidationTestData();
    }

    public void Dispose()
    {
        _testData.Dispose();
    }

    [Fact]
    public void Validate_Skender_Stc_Deviation()
    {
        // Skender's STC implementation uses a "Single Smoothed" approach (Stoch of MACD).
        // QuanTAlib implements the standard "Double Smoothed" approach (Stoch of Stoch of MACD),
        // as originally defined by Schaff.
        //
        // Example mismatch at index 333:
        // QuanTAlib (Double Smoothed) = 50.0
        // Skender (Single Smoothed) = 97.05
        //
        // This test documents this known deviation rather than failing on it.

        const int cycle = 10;
        int fast = 23;
        int slow = 50;

        var sResult = _testData.SkenderQuotes.GetStc(cycle, fast, slow).ToList();
        var qStc = new Stc(kPeriod: cycle, dPeriod: 3, fastLength: fast, slowLength: slow, smoothing: StcSmoothing.Ema);
        var qResult = qStc.Update(_testData.Data);

        // Skender recommends S+C+250 warmup. 50+10+250 = 310.
        int skip = 310;
        double sumSq = 0;
        int count = 0;

        for (int i = skip; i < qResult.Count; i++)
        {
            double sVal = sResult[i].Stc ?? double.NaN;
            double qVal = qResult[i].Value;

            if (!double.IsNaN(sVal) && !double.IsNaN(qVal))
            {
                sumSq += (sVal - qVal) * (sVal - qVal);
                count++;
            }
        }

        double rmse = Math.Sqrt(sumSq / count);
        _output.WriteLine($"Known Methodology Deviation - RMSE: {rmse:F4}");

        // Assert that we are essentially different (RMSE > 5.0 implies significant deviation)
        // If they accidentally matched (e.g. if we broke our logic to match Skender), this should fail.
        Assert.True(rmse > 5.0, "QuanTAlib STC matches Skender STC, which suggests regression to Single Smoothed logic.");

        // Assert values are valid
        for (int i = skip; i < qResult.Count; i++)
        {
            Assert.True(double.IsFinite(qResult[i].Value));
            Assert.InRange(qResult[i].Value, 0, 100);
        }
    }

    // ── Cross-library: OoplesFinance ──────────────────────────────────────────
    [Fact]
    public void Stc_MatchesOoples_Structural()
    {
        var ooplesData = _testData.SkenderQuotes.Select(static q => new TickerData
        {
            Date = q.Date,
            Open = (double)q.Open,
            High = (double)q.High,
            Low = (double)q.Low,
            Close = (double)q.Close,
            Volume = (double)q.Volume
        }).ToList();

        var stockData = new StockData(ooplesData);
        var oResult = stockData.CalculateSchaffTrendCycle();
        var oValues = oResult.OutputValues.Values.First();

        var stc = new Stc(kPeriod: 10, dPeriod: 3, fastLength: 23, slowLength: 50, smoothing: StcSmoothing.Ema);
        var qValues = new List<double>();
        foreach (var item in _testData.Data)
        {
            qValues.Add(stc.Update(item).Value);
        }

        Assert.True(oValues.Count > 0, "Ooples STC must produce output");
        int finiteCount = 0;
        for (int i = 50; i < Math.Min(oValues.Count, qValues.Count); i++)
        {
            if (double.IsFinite(oValues[i]) && double.IsFinite(qValues[i]))
            {
                finiteCount++;
            }
        }
        Assert.True(finiteCount > 100, $"Expected >100 finite STC pairs, got {finiteCount}");
        _output.WriteLine($"STC Ooples structural: {finiteCount} finite pairs verified.");
    }
}