using Xunit.Abstractions;

namespace QuanTAlib.Tests;

public class VidyaValidationTests
{
    // Note: OoplesFinance VIDYA implementation diverges significantly from our reference implementation
    // (Chande Momentum Oscillator based), likely due to different volatility calculation or smoothing logic.
    // Therefore, we do not validate against Ooples for VIDYA.

    private readonly ValidationTestData _testData;
    private readonly ITestOutputHelper _output;

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

    [Fact]
    public void ValidateAgainstReference()
    {
        // Note: Tulip's VIDYA implementation uses Standard Deviation ratio (1992 version),
        // while QuanTAlib uses Chande Momentum Oscillator (1994 version).
        // Therefore, we cannot validate against Tulip.
        // We validate against a simple, readable reference implementation of the CMO-based VIDYA.

        const int period = 14;

        // QuanTAlib
        var vidya = new Vidya(period);
        var qResults = new List<double>();
        foreach (var item in _testData.Data)
        {
            qResults.Add(vidya.Update(item).Value);
        }

        // Reference Implementation
        var refResults = CalculateVidyaReference(_testData.Data, period);

        // Compare
        ValidationHelper.VerifyData(qResults, refResults, x => x, tolerance: 1e-9);

        _output.WriteLine("VIDYA validated successfully against reference implementation");
    }

    [Fact]
    public void ValidateBatchAgainstReference()
    {
        const int period = 14;

        // QuanTAlib Batch
        var qResults = Vidya.Batch(_testData.Data, period);

        // Reference Implementation
        var refResults = CalculateVidyaReference(_testData.Data, period);

        // Compare
        ValidationHelper.VerifyData(qResults, refResults, x => x, tolerance: 1e-9);

        _output.WriteLine("VIDYA Batch validated successfully against reference implementation");
    }

    private static List<double> CalculateVidyaReference(TSeries data, int period)
    {
        var results = new List<double>();
        var prices = data.Select(x => x.Value).ToList();
        double alpha = 2.0 / (period + 1);

        double prevVidya = 0;

        for (int i = 0; i < prices.Count; i++)
        {
            if (i == 0)
            {
                results.Add(prices[i]);
                prevVidya = prices[i];
                continue;
            }

            double sumUp = 0;
            double sumDown = 0;

            var changes = new List<double>();
            for (int j = 1; j <= i; j++)
            {
                changes.Add(prices[j] - prices[j - 1]);
            }

            var recentChanges = changes.TakeLast(period).ToList();

            sumUp = recentChanges.Where(x => x > 0).Sum();
            sumDown = recentChanges.Sum(x => x < 0 ? -x : 0);

            double sum = sumUp + sumDown;
            double vi = 0;
            if (sum > 0)
            {
                vi = Math.Abs(sumUp - sumDown) / sum;
            }

            double dynamicAlpha = alpha * vi;
            double currentVidya = dynamicAlpha * prices[i] + (1 - dynamicAlpha) * prevVidya;

            results.Add(currentVidya);
            prevVidya = currentVidya;
        }

        return results;
    }
}