Files
geniusrun/backend/internal/sync/mapping.go
Christophe Vila 8ff3d62b2f Add Race workout kind with Garmin eventType auto-detection, sync-time running filter, and pill-based review queue filter
Race is the 8th fixed workout kind, seeded with a real (not placeholder)
rule since Garmin Connect's eventType.typeKey reports "race" for
manually-tagged race activities. Non-running activity types (padel,
cycling, strength training, ...) are now dropped at sync time instead of
being stored. The Review Queue's type filter is now clickable exclusive
pill buttons instead of a dropdown.
2026-07-19 10:52:09 +02:00

221 lines
7.0 KiB
Go

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") }