64 lines
1.9 KiB
Go
64 lines
1.9 KiB
Go
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package classify
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import "sort"
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const (
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StatusAssigned = "assigned"
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StatusNeedsReview = "needs_review"
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// DefaultMinConfidence is the score below which even a single matching
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// kind is sent to manual review rather than auto-assigned.
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DefaultMinConfidence = 0.6
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)
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// RuleKind is one active workout kind's rule, as loaded from the store.
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type RuleKind struct {
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WorkoutKindID int64
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Name string
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Rule Node
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}
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// ScoredKind is one kind that matched an activity's metrics, with its
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// confidence score.
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type ScoredKind struct {
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WorkoutKindID int64 `json:"workout_kind_id"`
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Name string `json:"name"`
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Score float64 `json:"score"`
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}
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// Result is the outcome of classifying one activity.
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type Result struct {
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Status string
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WorkoutKindID *int64
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Confidence *float64
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Candidates []ScoredKind // every kind that matched, sorted by score descending
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}
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// Classify evaluates every active kind's rule against ctx and decides
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// whether the activity is cleanly assignable, or needs manual review
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// because zero kinds matched, multiple kinds matched, or the single match's
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// confidence fell below minConfidence.
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func Classify(ctx MetricContext, kinds []RuleKind, minConfidence float64) Result {
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candidates := []ScoredKind{}
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for _, k := range kinds {
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matched, score := k.Rule.Evaluate(ctx)
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if matched {
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candidates = append(candidates, ScoredKind{WorkoutKindID: k.WorkoutKindID, Name: k.Name, Score: score})
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}
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}
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sort.Slice(candidates, func(i, j int) bool { return candidates[i].Score > candidates[j].Score })
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if len(candidates) != 1 {
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return Result{Status: StatusNeedsReview, Candidates: candidates}
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}
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only := candidates[0]
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if only.Score < minConfidence {
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return Result{Status: StatusNeedsReview, Candidates: candidates}
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}
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id := only.WorkoutKindID
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score := only.Score
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return Result{Status: StatusAssigned, WorkoutKindID: &id, Confidence: &score, Candidates: candidates}
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}
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