package classify

import "sort"

const (
	StatusAssigned    = "assigned"
	StatusNeedsReview = "needs_review"

	// DefaultMinConfidence is the score below which even a single matching
	// kind is sent to manual review rather than auto-assigned.
	DefaultMinConfidence = 0.6
)

// RuleKind is one active workout kind's rule, as loaded from the store.
type RuleKind struct {
	WorkoutKindID int64
	Name          string
	Rule          Node
}

// ScoredKind is one kind that matched an activity's metrics, with its
// confidence score.
type ScoredKind struct {
	WorkoutKindID int64   `json:"workout_kind_id"`
	Name          string  `json:"name"`
	Score         float64 `json:"score"`
}

// Result is the outcome of classifying one activity.
type Result struct {
	Status        string
	WorkoutKindID *int64
	Confidence    *float64
	Candidates    []ScoredKind // every kind that matched, sorted by score descending
}

// Classify evaluates every active kind's rule against ctx and decides
// whether the activity is cleanly assignable, or needs manual review
// because zero kinds matched, multiple kinds matched, or the single match's
// confidence fell below minConfidence.
func Classify(ctx MetricContext, kinds []RuleKind, minConfidence float64) Result {
	candidates := []ScoredKind{}
	for _, k := range kinds {
		matched, score := k.Rule.Evaluate(ctx)
		if matched {
			candidates = append(candidates, ScoredKind{WorkoutKindID: k.WorkoutKindID, Name: k.Name, Score: score})
		}
	}
	sort.Slice(candidates, func(i, j int) bool { return candidates[i].Score > candidates[j].Score })

	if len(candidates) != 1 {
		return Result{Status: StatusNeedsReview, Candidates: candidates}
	}

	only := candidates[0]
	if only.Score < minConfidence {
		return Result{Status: StatusNeedsReview, Candidates: candidates}
	}

	id := only.WorkoutKindID
	score := only.Score
	return Result{Status: StatusAssigned, WorkoutKindID: &id, Confidence: &score, Candidates: candidates}
}