package sync

import (
	"encoding/json"
	"strings"
	"time"

	"smartrun/backend/internal/classify"
	"smartrun/backend/internal/garmin"
	"smartrun/backend/internal/store"
)

// isRunningActivityType reports whether a Garmin activityType.typeKey
// represents a running activity (running, trail_running, treadmill_running,
// track_running, indoor_running, virtual_run, ...) as opposed to other
// sports (padel, cycling, strength training, ...) that also show up in
// get_activities().
func isRunningActivityType(typeKey string) bool {
	return strings.Contains(strings.ToLower(typeKey), "run")
}

func toActivityRow(a garmin.Activity) store.Activity {
	return store.Activity{
		GarminActivityID:        a.ActivityID,
		ActivityName:            a.ActivityName,
		ActivityType:            a.ActivityType.TypeKey,
		EventTypeKey:            a.EventType.TypeKey,
		StartTimeUTC:            a.StartTimeGMT,
		BeginTimestampMs:        a.BeginTimestamp,
		DurationSeconds:         a.Duration,
		DistanceMeters:          a.Distance,
		AvgHR:                   nonZero(a.AverageHR),
		MaxHR:                   nonZero(a.MaxHR),
		AvgSpeedMps:             nonZero(a.AverageSpeed),
		MaxSpeedMps:             nonZero(a.MaxSpeed),
		ElevationGainM:          a.ElevationGain,
		ElevationLossM:          a.ElevationLoss,
		Calories:                nonZero(a.Calories),
		LapCount:                a.LapCount,
		AerobicTrainingEffect:   nonZero(a.AerobicTrainingEffect),
		AnaerobicTrainingEffect: nonZero(a.AnaerobicTrainingEffect),
		TrainingEffectLabel:     a.TrainingEffectLabel,
		VO2MaxValue:             a.VO2MaxValue,
		HrTimeInZone1:           nonZero(a.HrTimeInZone1),
		HrTimeInZone2:           nonZero(a.HrTimeInZone2),
		HrTimeInZone3:           nonZero(a.HrTimeInZone3),
		HrTimeInZone4:           nonZero(a.HrTimeInZone4),
		HrTimeInZone5:           nonZero(a.HrTimeInZone5),
		RawJSON:                 string(a.Raw),
	}
}

// nonZero returns nil for a zero value so store columns stay NULL instead of
// a misleading 0 when Garmin simply didn't report that field.
func nonZero(v float64) *float64 {
	if v == 0 {
		return nil
	}
	return &v
}

// toLapRows converts garmin lap DTOs into store rows, computing each lap's
// HR drift (active laps) or recovery rate (rest laps) from the samples that
// fall within that lap's time window. Lap boundaries are derived from
// cumulative elapsed duration rather than parsing StartTimeGMT, since laps
// are contiguous and this sidesteps timezone parsing entirely.
func toLapRows(laps []garmin.Lap, samples []garmin.Sample) []store.Lap {
	rows := make([]store.Lap, 0, len(laps))
	var elapsedStart float64
	for _, l := range laps {
		elapsedEnd := elapsedStart + l.ElapsedDuration

		var driftPtr, recoveryPtr *float64
		lapSamples := samplesInWindow(samples, elapsedStart, elapsedEnd)
		switch l.IntensityType {
		case "ACTIVE":
			if v, ok := classify.HRDrift(lapSamples); ok {
				driftPtr = &v
			}
		case "REST", "RECOVERY", "COOLDOWN", "WARMUP":
			if v, ok := classify.HRRecovery(lapSamples); ok {
				recoveryPtr = &v
			}
		}

		raw, _ := json.Marshal(l)
		rows = append(rows, store.Lap{
			LapIndex:            l.LapIndex,
			StartTimeUTC:        l.StartTimeGMT,
			DurationSeconds:     l.Duration,
			DistanceMeters:      l.Distance,
			AvgHR:               nonZero(l.AverageHR),
			MaxHR:               nonZero(l.MaxHR),
			AvgSpeedMps:         nonZero(l.AverageSpeed),
			MaxSpeedMps:         nonZero(l.MaxSpeed),
			ElevationGainM:      nonZero(l.ElevationGain),
			ElevationLossM:      nonZero(l.ElevationLoss),
			IntensityType:       l.IntensityType,
			HRDriftBpmPerMin:    driftPtr,
			HRRecoveryBpmPerMin: recoveryPtr,
			RawJSON:             string(raw),
		})
		elapsedStart = elapsedEnd
	}
	return rows
}

func samplesInWindow(samples []garmin.Sample, start, end float64) []classify.SampleInfo {
	var out []classify.SampleInfo
	for _, s := range samples {
		if s.ElapsedSeconds < start || s.ElapsedSeconds >= end {
			continue
		}
		out = append(out, classify.SampleInfo{ElapsedSeconds: s.ElapsedSeconds, HeartRate: s.HeartRate})
	}
	return out
}

func toSampleRows(samples []garmin.Sample) []store.Sample {
	rows := make([]store.Sample, len(samples))
	for i, s := range samples {
		rows[i] = store.Sample{
			ElapsedSeconds: s.ElapsedSeconds,
			TimestampMs:    s.TimestampMS,
			HeartRate:      s.HeartRate,
			SpeedMps:       s.SpeedMps,
			DistanceM:      s.DistanceM,
			ElevationM:     s.ElevationM,
		}
	}
	return rows
}

// buildMetricContext computes the classify.MetricContext for one activity
// from its stored summary and laps, ready to evaluate against workout kind
// rules. maxHR is the user's configured max heart rate, used only to derive
// avg_hr_pct_max (Garmin's activity/lap summaries don't include it directly).
func buildMetricContext(a store.Activity, laps []store.Lap, maxHR float64) classify.MetricContext {
	isRace := 0.0
	if a.EventTypeKey == "race" {
		isRace = 1.0
	}
	ctx := classify.MetricContext{
		"duration_seconds": a.DurationSeconds,
		"distance_meters":  a.DistanceMeters,
		"is_race":          isRace,
	}
	if a.AvgSpeedMps != nil && *a.AvgSpeedMps > 0 {
		ctx["avg_pace_sec_per_km"] = 1000 / *a.AvgSpeedMps
	}
	if a.AvgHR != nil {
		ctx["avg_hr"] = *a.AvgHR
		if maxHR > 0 {
			ctx["avg_hr_pct_max"] = *a.AvgHR / maxHR
		}
	}
	if a.MaxHR != nil {
		ctx["max_hr"] = *a.MaxHR
	}
	if a.ElevationGainM != nil {
		ctx["elevation_gain_m"] = *a.ElevationGainM
	}
	if a.AerobicTrainingEffect != nil {
		ctx["aerobic_training_effect"] = *a.AerobicTrainingEffect
	}
	if a.AnaerobicTrainingEffect != nil {
		ctx["anaerobic_training_effect"] = *a.AnaerobicTrainingEffect
	}
	if a.VO2MaxValue != nil {
		ctx["vo2max_value"] = *a.VO2MaxValue
	}

	lapInfos := make([]classify.LapInfo, len(laps))
	var paces []float64
	var maxDrift, maxRecovery float64
	haveDrift, haveRecovery := false, false
	for i, l := range laps {
		lapInfos[i] = classify.LapInfo{IntensityType: l.IntensityType}
		if l.AvgSpeedMps != nil && *l.AvgSpeedMps > 0 {
			paces = append(paces, 1000 / *l.AvgSpeedMps)
		}
		if l.HRDriftBpmPerMin != nil && (!haveDrift || *l.HRDriftBpmPerMin > maxDrift) {
			maxDrift, haveDrift = *l.HRDriftBpmPerMin, true
		}
		if l.HRRecoveryBpmPerMin != nil && (!haveRecovery || *l.HRRecoveryBpmPerMin > maxRecovery) {
			maxRecovery, haveRecovery = *l.HRRecoveryBpmPerMin, true
		}
	}
	if len(laps) > 0 {
		if classify.DetectIntervalPattern(lapInfos) {
			ctx["lap_interval_pattern"] = 1
		} else {
			ctx["lap_interval_pattern"] = 0
		}
	}
	if len(paces) > 0 {
		ctx["lap_pace_stddev"] = classify.LapPaceStdDev(paces)
	}
	if haveDrift {
		ctx["lap_hr_drift_bpm_per_min"] = maxDrift
	}
	if haveRecovery {
		ctx["lap_hr_recovery_bpm_per_min"] = maxRecovery
	}
	return ctx
}

func loadRuleKinds(kinds []store.WorkoutKind) ([]classify.RuleKind, error) {
	rules := make([]classify.RuleKind, 0, len(kinds))
	for _, k := range kinds {
		var node classify.Node
		if err := json.Unmarshal([]byte(k.RuleJSON), &node); err != nil {
			return nil, err
		}
		rules = append(rules, classify.RuleKind{WorkoutKindID: k.ID, Name: k.Name, Rule: node})
	}
	return rules, nil
}

func dateStr(t time.Time) string { return t.Format("2006-01-02") }