using HSchool.Content;

namespace HSchool.Ai.Tests;

public class LessonLearningTests
{
    private static readonly SkillDef Math = new()
    {
        DefName = "Mathematics",
        Range = new IntRange { Min = 0, Max = 100 },
    };

    [Fact]
    public void HungryLearnsLessThanFull()
    {
        var full = LessonLearning.Gain(50, Math, share: 1, lessonSkillPerHour: 0.05f, hours: 0.75f, hunger: 1f, traitOffset: 0, teacherSkill: 100);
        var hungry = LessonLearning.Gain(50, Math, share: 1, lessonSkillPerHour: 0.05f, hours: 0.75f, hunger: 0.1f, traitOffset: 0, teacherSkill: 100);

        Assert.True(full > 50);
        Assert.True(hungry > 50);
        Assert.True(full - 50 > hungry - 50);
    }

    [Fact]
    public void DiligentOffset_RaisesTheGain()
    {
        var plain = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 100);
        var diligent = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 8, 100);

        Assert.True(diligent > plain);
    }

    [Fact]
    public void TeacherSkill20_GainsLessThan80()
    {
        var weak = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 20);
        var strong = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 80);

        Assert.True(weak > 50);
        Assert.True(strong - 50 > weak - 50);
    }

    [Fact]
    public void TeacherFactor_MatchesNeedCurve()
    {
        Assert.Equal(LessonLearning.NeedFactor(0f), LessonLearning.TeacherFactor(0f));
        Assert.Equal(LessonLearning.NeedFactor(1f), LessonLearning.TeacherFactor(100f));
        Assert.Equal(LessonLearning.NeedFactor(0.2f), LessonLearning.TeacherFactor(20f));
    }

    [Fact]
    public void MultiSkillSubject_AveragesListedSkills_NotDictionaryOrder()
    {
        var (catalog, _) = Fixtures.Vanilla();
        var subject = catalog.Subjects["PrimarySchool"];
        var skills = new Dictionary<string, float>(StringComparer.Ordinal)
        {
            ["Biology"] = 100,
            ["Literature"] = 100,
            ["RussianLanguage"] = 100,
            ["Mathematics"] = 0,
        };

        var average = LessonLearning.AverageTeacherSkill(subject, skills, catalog);

        Assert.Equal(75f, average);
        Assert.NotEqual(skills.Values.First(), average);
    }

    [Fact]
    public void ColdLearnsLessThanWarm()
    {
        var warm = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 100, warmth: 1f);
        var cold = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 100, warmth: 0.1f);

        Assert.True(cold > 50);
        Assert.True(warm - 50 > cold - 50);
    }

    [Fact]
    public void HungerStillCutsWhenWarm()
    {
        var full = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, hunger: 1f, traitOffset: 0, teacherSkill: 100, warmth: 1f);
        var hungry = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, hunger: 0.1f, traitOffset: 0, teacherSkill: 100, warmth: 1f);

        Assert.True(full - 50 > hungry - 50);
        Assert.Equal(
            LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 0.1f, 0, 100),
            hungry);
    }

    [Fact]
    public void MissingWarmthArgument_DefaultsToFull()
    {
        var implied = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 0.1f, 0, 100);
        var explicitWarm = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 0.1f, 0, 100, warmth: 1f);

        Assert.Equal(explicitWarm, implied);
    }
    [Fact]
    public void MissingTeacherSkill_UsesRangeMin_AndStillGains()
    {
        var (catalog, _) = Fixtures.Vanilla();
        var subject = catalog.Subjects["Mathematics"];
        var min = catalog.Skills["Mathematics"].Range.Min;
        var average = LessonLearning.AverageTeacherSkill(subject, new Dictionary<string, float>(), catalog);
        var gained = LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, average);

        Assert.Equal(min, average);
        Assert.True(gained > 50);
        Assert.True(gained < LessonLearning.Gain(50, Math, 1, 0.05f, 1f, 1f, 0, 100));
    }
}