package main

import (
	"encoding/json"
	"testing"
)

func ratingTestSegment(label string, start, duration, confidence float64) aiSegmentMeta {
	return aiSegmentMeta{
		Label:           label,
		StartSeconds:    start,
		EndSeconds:      start + duration,
		DurationSeconds: duration,
		Score:           confidence,
	}
}

func TestComputeHighlightRatingSpansAllStars(t *testing.T) {
	tests := []struct {
		name     string
		segments []aiSegmentMeta
		want     int
	}{
		{
			name: "one weak standing detection",
			segments: []aiSegmentMeta{
				ratingTestSegment("position:standing", 10, 6, 0.45),
			},
			want: 1,
		},
		{
			name: "one brief strong position",
			segments: []aiSegmentMeta{
				ratingTestSegment("position:doggy", 10, 8, 0.72),
			},
			want: 2,
		},
		{
			name: "two solid position segments",
			segments: []aiSegmentMeta{
				ratingTestSegment("position:doggy", 20, 18, 0.78),
				ratingTestSegment("position:cowgirl", 120, 18, 0.78),
			},
			want: 3,
		},
		{
			name: "several long high quality positions",
			segments: []aiSegmentMeta{
				ratingTestSegment("position:doggy", 20, 25, 0.82),
				ratingTestSegment("position:cowgirl", 120, 25, 0.82),
				ratingTestSegment("position:missionary", 220, 25, 0.82),
				ratingTestSegment("position:blowjob", 320, 25, 0.82),
			},
			want: 4,
		},
		{
			name: "exceptional sustained and varied positions",
			segments: []aiSegmentMeta{
				ratingTestSegment("position:doggy", 10, 40, 0.90),
				ratingTestSegment("position:cowgirl", 100, 40, 0.90),
				ratingTestSegment("position:missionary", 190, 40, 0.90),
				ratingTestSegment("position:blowjob", 280, 40, 0.90),
				ratingTestSegment("position:cunnilingus", 370, 40, 0.90),
				ratingTestSegment("position:reverse_cowgirl", 460, 40, 0.90),
			},
			want: 5,
		},
	}

	for _, tt := range tests {
		t.Run(tt.name, func(t *testing.T) {
			got := computeHighlightRating(tt.segments, 600)
			if got.Stars != tt.want {
				t.Fatalf("stars = %d, want %d (score %.1f)", got.Stars, tt.want, got.Score)
			}
		})
	}
}

func TestComputeHighlightRatingRewardsPositionDuration(t *testing.T) {
	short := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 8, 0.80),
	}, 600)
	medium := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 35, 0.80),
	}, 600)
	long := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 120, 0.80),
	}, 600)

	if !(short.Score < medium.Score && medium.Score < long.Score) {
		t.Fatalf(
			"position duration should increase score: short=%.1f medium=%.1f long=%.1f",
			short.Score,
			medium.Score,
			long.Score,
		)
	}
}

func TestComputeHighlightRatingActionPrefersSustainedActivity(t *testing.T) {
	briefPeak := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 8, 0.95),
	}, 600)
	sustained := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 45, 0.55),
	}, 600)

	if sustained.ActionScore <= briefPeak.ActionScore {
		t.Fatalf(
			"sustained action should outrank a brief peak: sustained=%.1f brief=%.1f",
			sustained.ActionScore,
			briefPeak.ActionScore,
		)
	}
	if sustained.Score <= briefPeak.Score {
		t.Fatalf(
			"rating should follow sustained action: sustained=%.1f brief=%.1f",
			sustained.Score,
			briefPeak.Score,
		)
	}
}

func TestComputeHighlightRatingRatesContextWithoutPosition(t *testing.T) {
	clothingOnly := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("clothing:lingerie", 10, 60, 0.90),
		ratingTestSegment("clothing:lingerie", 120, 60, 0.90),
		ratingTestSegment("clothing:lingerie", 230, 60, 0.90),
	}, 600)
	richContext := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("combo:body:breasts+clothing:lingerie", 10, 45, 0.90),
		ratingTestSegment("combo:object:vibrator+clothing:lingerie", 120, 60, 0.90),
		ratingTestSegment("combo:body:penis+object:dildo", 240, 45, 0.90),
	}, 600)

	if clothingOnly.Stars != 2 {
		t.Fatalf(
			"clothing-only stars = %d, want 2 (score %.1f)",
			clothingOnly.Stars,
			clothingOnly.Score,
		)
	}
	if richContext.Stars != 3 {
		t.Fatalf(
			"rich context stars = %d, want 3 (score %.1f)",
			richContext.Stars,
			richContext.Score,
		)
	}
	if richContext.Stars > 3 {
		t.Fatalf("context rating must stay below 4 stars: %#v", richContext)
	}
}

func TestComputeHighlightRatingPositionsOutrankContext(t *testing.T) {
	context := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("combo:body:breasts+clothing:lingerie+object:vibrator", 10, 240, 0.95),
	}, 600)
	positions := computeHighlightRating([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 40, 0.90),
		ratingTestSegment("position:cowgirl", 100, 40, 0.90),
		ratingTestSegment("position:missionary", 190, 40, 0.90),
		ratingTestSegment("position:blowjob", 280, 40, 0.90),
	}, 600)

	if positions.Score <= context.Score || positions.Stars <= context.Stars {
		t.Fatalf(
			"positions should outrank context: positions=%.1f/%d context=%.1f/%d",
			positions.Score,
			positions.Stars,
			context.Score,
			context.Stars,
		)
	}
}

func TestComputeHighlightRatingExplicitSignalsBoostPositions(t *testing.T) {
	positionSegments := []aiSegmentMeta{
		ratingTestSegment("position:doggy", 20, 18, 0.78),
		ratingTestSegment("position:cowgirl", 120, 18, 0.78),
	}

	base := computeHighlightRating(positionSegments, 600)
	withObject := computeHighlightRating(append(
		append([]aiSegmentMeta{}, positionSegments...),
		ratingTestSegment("object:dildo", 220, 60, 0.90),
	), 600)
	withClothing := computeHighlightRating(append(
		append([]aiSegmentMeta{}, positionSegments...),
		ratingTestSegment("clothing:lingerie", 220, 60, 0.90),
	), 600)
	withBody := computeHighlightRating(append(
		append([]aiSegmentMeta{}, positionSegments...),
		ratingTestSegment("body:pussy", 220, 60, 0.90),
	), 600)

	if !(base.Score < withObject.Score &&
		withObject.Score < withClothing.Score &&
		withClothing.Score < withBody.Score) {
		t.Fatalf(
			"explicit signal priority is wrong: base=%.1f object=%.1f clothing=%.1f body=%.1f",
			base.Score,
			withObject.Score,
			withClothing.Score,
			withBody.Score,
		)
	}
}

func TestComputeHighlightRatingExplicitContextCanElevateStrongPositions(t *testing.T) {
	positions := []aiSegmentMeta{
		ratingTestSegment("position:doggy", 20, 25, 0.82),
		ratingTestSegment("position:cowgirl", 120, 25, 0.82),
		ratingTestSegment("position:missionary", 220, 25, 0.82),
		ratingTestSegment("position:blowjob", 320, 25, 0.82),
	}
	positionOnly := computeHighlightRating(positions, 600)
	withExplicitContext := computeHighlightRating(append(
		append([]aiSegmentMeta{}, positions...),
		ratingTestSegment("body:pussy", 400, 90, 0.92),
		ratingTestSegment("clothing:lingerie", 500, 90, 0.92),
	), 600)

	if positionOnly.Stars != 4 {
		t.Fatalf("position-only stars = %d, want 4 (score %.1f)", positionOnly.Stars, positionOnly.Score)
	}
	if withExplicitContext.Stars != 5 {
		t.Fatalf(
			"positions with explicit context stars = %d, want 5 (score %.1f)",
			withExplicitContext.Stars,
			withExplicitContext.Score,
		)
	}
}

func TestComputeHighlightRatingLongMixedContextRegression(t *testing.T) {
	segments := []aiSegmentMeta{
		ratingTestSegment("object:dildo", 24.5, 5, 0.792783260345459),
		ratingTestSegment("object:dildo", 43.5, 8, 0.923585057258606),
		ratingTestSegment("clothing:lingerie", 94.5, 21, 0.9069388088058022),
		ratingTestSegment("clothing:lingerie", 120.5, 33, 0.887133002281189),
		ratingTestSegment("object:vibrator", 215.5, 6, 0.40453797578811646),
		ratingTestSegment("combo:body:breasts+clothing:lingerie", 298.5, 8, 0.6898824721574783),
		ratingTestSegment("object:vibrator", 330.5, 5, 0.6836381554603577),
		ratingTestSegment("clothing:lingerie", 348.5, 59, 0.9197490215301514),
		ratingTestSegment("combo:object:vibrator+object:collar+clothing:lingerie", 416.5, 36, 0.8156423893044976),
		ratingTestSegment("clothing:lingerie", 465.5, 36, 0.8007044196128845),
	}

	got := computeHighlightRating(segments, 504)
	if got.Stars != 3 {
		t.Fatalf("stars = %d, want 3 (score %.1f)", got.Stars, got.Score)
	}

	encoded, err := json.Marshal(got)
	if err != nil {
		t.Fatal(err)
	}
	t.Logf("rating=%s", encoded)
}

func TestPrepareAIRatingSegmentsKeepsDifferentPositionsSeparate(t *testing.T) {
	segments := prepareAIRatingSegments([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 12, 0.85),
		ratingTestSegment("position:cowgirl", 23, 12, 0.85),
	})

	if len(segments) != 2 {
		t.Fatalf("segments = %d, want 2: %#v", len(segments), segments)
	}
	if segments[0].Position == segments[1].Position {
		t.Fatalf("different positions were collapsed: %#v", segments)
	}
}

func TestPrepareAIRatingSegmentsMergesSamePositionAcrossShortGap(t *testing.T) {
	segments := prepareAIRatingSegments([]aiSegmentMeta{
		ratingTestSegment("position:doggy", 10, 12, 0.85),
		ratingTestSegment("position:doggy", 23, 12, 0.85),
	})

	if len(segments) != 1 {
		t.Fatalf("segments = %d, want 1: %#v", len(segments), segments)
	}
	if segments[0].Position != "doggy" {
		t.Fatalf("position = %q, want doggy", segments[0].Position)
	}
	if segments[0].DurationSeconds != 24 {
		t.Fatalf(
			"duration = %.1f, want 24 seconds of actual position evidence",
			segments[0].DurationSeconds,
		)
	}
	if segments[0].RatingIntensity <= 0 {
		t.Fatalf("rating intensity = %.3f, want a positive heatcurve value", segments[0].RatingIntensity)
	}

	wantIntensity := ratingClamp01(
		ratingSegmentSeverity(segments[0].Label) *
			ratingConfidenceWeight(segments[0].Score),
	)
	if diff := segments[0].RatingIntensity - wantIntensity; diff < -0.0001 || diff > 0.0001 {
		t.Fatalf(
			"rating intensity = %.4f, want %.4f",
			segments[0].RatingIntensity,
			wantIntensity,
		)
	}
}