Add trend-range gating, vehicle filter, sync cancel, moving time, and UI fixes

- Grey out trend ranges beyond available health history
- Reject implausibly fast (vehicle) activities on upload with feedback
- Add cancel button + cooperative cancellation for Garmin sync
- Show daily steps prominently on the dashboard
- Clear errors for malformed/empty upload ZIPs
- Snap-target dot when drawing a segment on the map
- Time-axis fallback for stationary/HIIT HR timelines; hide map when no GPS
- Parse and display moving time (timer) vs elapsed; backfill task
- Restyle SegmentsPanel like RouteLeaderboard; Laps/Routes/Segments on one row

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

backend/app/services/fit_parser.py

@@ -44,6 +44,33 @@ def _sanitize_speed(val, dist_m=None, dur_s=None) -> Optional[float]:
     return fv
 
 
+# Conservative average-speed ceilings (m/s) above which an activity was almost
+# certainly recorded in a vehicle rather than under human power. Sports not
+# listed fall back to the generous default.
+_VEHICLE_SPEED_CEILINGS = {
+    "running": 8.0,    # ~28.8 km/h — well above elite sprint pace sustained
+    "walking": 8.0,
+    "hiking": 8.0,
+    "cycling": 22.0,   # ~79 km/h — beyond sustained amateur cycling
+}
+_VEHICLE_SPEED_DEFAULT = 25.0   # ~90 km/h
+
+
+def _vehicle_reason(sport_type, avg_speed_ms, dist_m=None, dur_s=None) -> Optional[str]:
+    """Return a human-readable reason if the average speed is implausibly fast for
+    the sport (i.e. the 'activity' looks like car/vehicle travel), else None."""
+    speed = _safe_float(avg_speed_ms)
+    if speed is None and dist_m and dur_s and float(dur_s) > 0:
+        speed = float(dist_m) / float(dur_s)
+    if speed is None or speed <= 0:
+        return None
+    ceiling = _VEHICLE_SPEED_CEILINGS.get(sport_type, _VEHICLE_SPEED_DEFAULT)
+    if speed > ceiling:
+        return (f"Looks like vehicle travel — average speed {speed * 3.6:.0f} km/h "
+                f"exceeds the plausible limit for {sport_type}")
+    return None
+
+
 def _bounding_box(coords):
     if not coords:
         return None
@@ -210,12 +237,22 @@ def parse_fit_file(filepath: str) -> dict:
     if start_time:
         name += " " + start_time.strftime("%Y-%m-%d")
 
+    total_dist = _safe_float(get(session_data, "totalDistance", "total_distance"))
+    elapsed_s = _safe_float(get(session_data, "totalElapsedTime", "total_elapsed_time"))
+    # Timer time = time the device was actively recording (excludes auto/manual pauses).
+    moving_s = _safe_float(get(session_data, "totalTimerTime", "total_timer_time"))
+    avg_speed = _sanitize_speed(
+        get(session_data, "avgSpeed", "avg_speed", "enhancedAvgSpeed", "enhanced_avg_speed"),
+        dist_m=total_dist, dur_s=elapsed_s,
+    )
+
     return {
         "name": name,
         "sport_type": sport_type,
         "start_time": start_time.isoformat() if start_time else None,
-        "distance_m": _safe_float(get(session_data, "totalDistance", "total_distance")),
-        "duration_s": _safe_float(get(session_data, "totalElapsedTime", "total_elapsed_time")),
+        "distance_m": total_dist,
+        "duration_s": elapsed_s,
+        "moving_time_s": moving_s,
         "elevation_gain_m": _safe_float(get(session_data, "totalAscent", "total_ascent")),
         "elevation_loss_m": _safe_float(get(session_data, "totalDescent", "total_descent")),
         "avg_heart_rate": _safe_float(get(session_data, "avgHeartRate", "avg_heart_rate")),
@@ -223,11 +260,7 @@ def parse_fit_file(filepath: str) -> dict:
         "avg_cadence": _safe_float(get(session_data, "avgCadence", "avg_cadence")),
         "avg_power": _safe_float(get(session_data, "avgPower", "avg_power")),
         "normalized_power": _safe_float(get(session_data, "normalizedPower", "normalized_power")),
-        "avg_speed_ms": _sanitize_speed(
-            get(session_data, "avgSpeed", "avg_speed", "enhancedAvgSpeed", "enhanced_avg_speed"),
-            dist_m=_safe_float(get(session_data, "totalDistance", "total_distance")),
-            dur_s=_safe_float(get(session_data, "totalElapsedTime", "total_elapsed_time")),
-        ),
+        "avg_speed_ms": avg_speed,
         "max_speed_ms": _safe_float(get(session_data, "maxSpeed", "max_speed",
                                         "enhancedMaxSpeed", "enhanced_max_speed")),
         "avg_temperature_c": _safe_float(get(session_data, "avgTemperature", "avg_temperature")),
@@ -239,6 +272,7 @@ def parse_fit_file(filepath: str) -> dict:
         "polyline": encoded_polyline,
         "bounding_box": bounding_box,
         "source_type": "fit",
+        "rejected_reason": _vehicle_reason(sport_type, avg_speed, total_dist, moving_s or elapsed_s),
         "data_points": normalized_points,
         "laps": normalized_laps,
     }
@@ -310,20 +344,23 @@ def parse_gpx_file(filepath: str) -> dict:
     end_dt = datetime.fromisoformat(data_points[-1]["timestamp"]) if data_points else None
     duration = (end_dt - start_dt).total_seconds() if (start_dt and end_dt) else None
     sport = track.type.lower() if track.type else "running"
+    gpx_avg_speed = (total_dist / duration) if (total_dist and duration) else None
 
     return {
         "name": track.name or gpx.name or f"Activity {start_dt.date() if start_dt else ''}",
         "sport_type": sport, "start_time": start_time_str,
-        "distance_m": total_dist, "duration_s": duration,
+        "distance_m": total_dist, "duration_s": duration, "moving_time_s": None,
         "elevation_gain_m": uphill, "elevation_loss_m": downhill,
         "avg_heart_rate": (sum(hrs) / len(hrs)) if hrs else None,
         "max_heart_rate": max(hrs) if hrs else None,
         "avg_cadence": None, "avg_power": None, "normalized_power": None,
-        "avg_speed_ms": (total_dist / duration) if (total_dist and duration) else None,
+        "avg_speed_ms": gpx_avg_speed,
         "max_speed_ms": None, "avg_temperature_c": None, "calories": None,
         "training_stress_score": None, "vo2max_estimate": None,
         "polyline": encoded_polyline, "bounding_box": bounding_box,
-        "source_type": "gpx", "data_points": data_points, "laps": [],
+        "source_type": "gpx",
+        "rejected_reason": _vehicle_reason(sport, gpx_avg_speed, total_dist, duration),
+        "data_points": data_points, "laps": [],
     }