using MeetingAssistant;
using MeetingAssistant.Speakers;
using Microsoft.Extensions.Logging.Abstractions;

namespace MeetingAssistant.Tests;

public sealed class ResemblyzerVoiceVectorOutlierPrunerTests
{
    [Fact]
    public void DominantDensityClusterRemovesForeignSpeakerVectorsAtThreshold()
    {
        var identity = IdentityWithVectors(
            Enumerable.Range(0, 16)
                .Select(index => UnitVector(0, index + 2, 0.04f))
                .Concat(Enumerable.Range(0, 4)
                    .Select(index => UnitVector(1, index + 30, 0.04f)))
                .ToList());
        var pruner = CreatePruner();

        var result = pruner.Prune(identity);

        Assert.Equal(4, result);
        Assert.Equal(16, identity.VoiceVectors.Count);
        Assert.All(
            identity.VoiceVectors,
            stored => Assert.True(SpeakerVoiceVectors.Decode(stored)[0] > 0.9f));
    }

    [Fact]
    public void AmbiguousDenseClustersPreserveAllVectors()
    {
        var identity = IdentityWithVectors(
            Enumerable.Range(0, 10)
                .Select(index => UnitVector(0, index + 2, 0.04f))
                .Concat(Enumerable.Range(0, 10)
                    .Select(index => UnitVector(1, index + 30, 0.04f)))
                .ToList());
        var pruner = CreatePruner();

        var result = pruner.Prune(identity);

        Assert.Equal(0, result);
        Assert.Equal(20, identity.VoiceVectors.Count);
    }

    [Fact]
    public void BelowMinimumVectorCountPreservesAllVectorsWithoutEvaluation()
    {
        var identity = IdentityWithVectors(
            Enumerable.Range(0, 15)
                .Select(index => UnitVector(0, index + 2, 0.04f))
                .Concat(Enumerable.Range(0, 4)
                    .Select(index => UnitVector(1, index + 30, 0.04f)))
                .ToList());
        var pruner = CreatePruner();

        var result = pruner.Prune(identity);

        Assert.Equal(0, result);
        Assert.Equal(19, identity.VoiceVectors.Count);
    }

    [Fact]
    public void PruningPreservesOtherModelsAndMalformedStoredRows()
    {
        var identity = IdentityWithVectors(
            Enumerable.Range(0, 16)
                .Select(index => UnitVector(0, index + 2, 0.04f))
                .Concat(Enumerable.Range(0, 4)
                    .Select(index => UnitVector(1, index + 30, 0.04f)))
                .ToList());
        SpeakerVoiceVectors.AddDistinct(
            identity,
            [UnitVector(2, 60, 0.04f)],
            "older-model",
            1000,
            DateTimeOffset.UtcNow);
        identity.VoiceVectors.Add(new SpeakerVoiceVector
        {
            ModelId = "resemblyzer-0.1.4-pretrained",
            Dimensions = 256,
            VectorBytes = [1],
            Fingerprint = "malformed",
            CreatedAt = DateTimeOffset.UtcNow
        });
        identity.VoiceVectors.Add(new SpeakerVoiceVector
        {
            ModelId = "resemblyzer-0.1.4-pretrained",
            Dimensions = 256,
            VectorBytes = new byte[256 * sizeof(float)],
            Fingerprint = "zero-magnitude",
            CreatedAt = DateTimeOffset.UtcNow
        });
        var pruner = CreatePruner();

        var result = pruner.Prune(identity);

        Assert.Equal(4, result);
        Assert.Equal(19, identity.VoiceVectors.Count);
        Assert.Contains(identity.VoiceVectors, vector => vector.ModelId == "older-model");
        Assert.Contains(identity.VoiceVectors, vector => vector.Fingerprint == "malformed");
        Assert.Contains(identity.VoiceVectors, vector => vector.Fingerprint == "zero-magnitude");
    }

    private static ResemblyzerVoiceVectorOutlierPruner CreatePruner()
    {
        return new ResemblyzerVoiceVectorOutlierPruner(
            new ResemblyzerSpeakerRecognitionOptions
            {
                ModelId = "resemblyzer-0.1.4-pretrained",
                OutlierPruningMinimumVectors = 20,
                OutlierPruningNeighborSimilarity = 0.90,
                OutlierPruningMinimumNeighbors = 3,
                OutlierPruningMinimumClusterRatio = 0.60
            },
            NullLogger<ResemblyzerVoiceVectorOutlierPruner>.Instance);
    }

    private static SpeakerIdentity IdentityWithVectors(IReadOnlyList<float[]> vectors)
    {
        var identity = new SpeakerIdentity();
        SpeakerVoiceVectors.AddDistinct(
            identity,
            vectors,
            "resemblyzer-0.1.4-pretrained",
            1000,
            DateTimeOffset.UtcNow);
        return identity;
    }

    private static float[] UnitVector(
        int primaryDimension,
        int secondaryDimension,
        float secondaryValue)
    {
        var vector = new float[256];
        vector[primaryDimension] = 1;
        vector[secondaryDimension] = secondaryValue;
        return vector;
    }
}