Add trip history and route replay
Co-authored-by: Copilot <[email protected]>
This commit is contained in:
Mathieu Moran
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import math
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from datetime import datetime
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INACTIVITY_SECONDS = 5 * 60
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GPS_MOTION_METERS = 8
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MIN_GPS_MOTION_SAMPLES = 3
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MAX_GPS_SAMPLE_GAP_SECONDS = 30
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MAX_PLAUSIBLE_SPEED_KMH = 220
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EARTH_RADIUS_KM = 6371.0088
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def _number(value):
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if value is None:
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return None
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try:
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return float(str(value).replace("\x00", "").strip())
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except (TypeError, ValueError):
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return None
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def _timestamp(value):
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try:
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return datetime.fromisoformat(str(value))
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except (TypeError, ValueError):
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return None
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def haversine_km(left, right):
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lat1, lon1 = map(math.radians, left)
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lat2, lon2 = map(math.radians, right)
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latitude_delta = lat2 - lat1
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longitude_delta = lon2 - lon1
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value = (
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math.sin(latitude_delta / 2) ** 2
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+ math.cos(lat1) * math.cos(lat2)
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* math.sin(longitude_delta / 2) ** 2
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)
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return EARTH_RADIUS_KM * 2 * math.atan2(math.sqrt(value), math.sqrt(1 - value))
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def normalize_tracking_rows(rows):
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normalized = []
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for row in rows:
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timestamp = _timestamp(row[1])
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latitude = _number(row[2])
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longitude = _number(row[3])
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speed = _number(row[4]) or 0
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if timestamp is None or latitude is None or longitude is None:
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continue
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if not (-90 <= latitude <= 90 and -180 <= longitude <= 180):
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continue
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normalized.append({
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"id": int(row[0]),
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"datetime": timestamp,
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"latitude": latitude,
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"longitude": longitude,
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"speed": max(0, speed),
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})
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return normalized
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def _segment(row, previous):
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seconds = (row["datetime"] - previous["datetime"]).total_seconds()
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if seconds <= 0:
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return 0, 0
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distance_km = haversine_km(
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(previous["latitude"], previous["longitude"]),
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(row["latitude"], row["longitude"]),
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)
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speed_kmh = distance_km / seconds * 3600
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if speed_kmh > MAX_PLAUSIBLE_SPEED_KMH:
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return 0, speed_kmh
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return distance_km, speed_kmh
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def build_trip_summaries(raw_rows):
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rows = normalize_tracking_rows(raw_rows)
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if len(rows) < 2:
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return []
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obd_motion = []
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gps_motion = []
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for index in range(1, len(rows)):
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seconds = (
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rows[index]["datetime"] - rows[index - 1]["datetime"]
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).total_seconds()
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distance_km, _ = _segment(rows[index], rows[index - 1])
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has_obd_motion = rows[index]["speed"] > 1
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has_gps_motion = (
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0 < seconds <= MAX_GPS_SAMPLE_GAP_SECONDS
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and distance_km * 1000 >= GPS_MOTION_METERS
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)
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if has_obd_motion:
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obd_motion.append({
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"index": index,
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"obd": True,
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"distance_km": distance_km,
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})
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if has_gps_motion:
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gps_motion.append({
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"index": index,
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"obd": False,
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"distance_km": distance_km,
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})
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qualified_gps_motion = []
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gps_sequences = []
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for event in gps_motion:
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if (
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not gps_sequences
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or (
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rows[event["index"]]["datetime"]
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- rows[gps_sequences[-1][-1]["index"]]["datetime"]
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).total_seconds() > MAX_GPS_SAMPLE_GAP_SECONDS
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):
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gps_sequences.append([event])
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else:
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gps_sequences[-1].append(event)
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for sequence in gps_sequences:
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if len(sequence) >= MIN_GPS_MOTION_SAMPLES:
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qualified_gps_motion.extend(sequence)
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motion_by_index = {}
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for event in obd_motion + qualified_gps_motion:
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existing = motion_by_index.get(event["index"])
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if existing is None:
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motion_by_index[event["index"]] = event.copy()
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else:
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existing["obd"] = existing["obd"] or event["obd"]
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existing["distance_km"] = max(
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existing["distance_km"], event["distance_km"]
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)
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motion = [
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motion_by_index[index] for index in sorted(motion_by_index)
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]
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groups = []
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for event in motion:
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event_gap = (
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(
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rows[event["index"]]["datetime"]
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- rows[groups[-1][-1]["index"]]["datetime"]
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).total_seconds()
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if groups
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else None
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)
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if (
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not groups
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or event_gap <= 0
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or event_gap > INACTIVITY_SECONDS
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):
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groups.append([event])
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else:
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groups[-1].append(event)
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trips = []
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for events in groups:
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if not any(event["obd"] for event in events) and len(events) < MIN_GPS_MOTION_SAMPLES:
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continue
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start_index = max(0, events[0]["index"] - 1)
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end_index = events[-1]["index"]
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trip_rows = rows[start_index:end_index + 1]
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distance_km = 0
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segment_speeds = []
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obd_speeds = []
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has_obd_motion = any(event["obd"] for event in events)
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for previous, row in zip(trip_rows, trip_rows[1:]):
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segment_km, segment_speed = _segment(row, previous)
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minimum_distance_meters = 1 if has_obd_motion else GPS_MOTION_METERS
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if segment_km * 1000 >= minimum_distance_meters:
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distance_km += segment_km
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segment_speeds.append(segment_speed)
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if row["speed"] > 0:
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obd_speeds.append(row["speed"])
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start = trip_rows[0]
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end = trip_rows[-1]
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duration_seconds = max(
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0, int((end["datetime"] - start["datetime"]).total_seconds())
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)
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if not any(event["obd"] for event in events) and duration_seconds < 10:
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continue
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trips.append({
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"id": start["id"],
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"start_tracking_id": start["id"],
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"end_tracking_id": end["id"],
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"start_datetime": start["datetime"].isoformat(sep=" "),
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"end_datetime": end["datetime"].isoformat(sep=" "),
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"start_gpsx": start["latitude"],
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"start_gpsy": start["longitude"],
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"end_gpsx": end["latitude"],
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"end_gpsy": end["longitude"],
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"distance_km": round(distance_km, 3),
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"duration_seconds": duration_seconds,
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"point_count": len(trip_rows),
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"average_speed_kmh": round(
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distance_km / duration_seconds * 3600, 1
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) if duration_seconds else 0,
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"max_speed_kmh": round(
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max(obd_speeds or segment_speeds or [0]), 1
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),
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})
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return trips
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def route_points(raw_rows, max_points=2000):
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rows = normalize_tracking_rows(raw_rows)
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filtered_rows = []
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for row in rows:
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if filtered_rows:
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_, segment_speed = _segment(row, filtered_rows[-1])
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if segment_speed > MAX_PLAUSIBLE_SPEED_KMH:
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continue
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filtered_rows.append(row)
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rows = filtered_rows
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for index, row in enumerate(rows):
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row["speed_source"] = "obd" if row["speed"] > 0 else "gps"
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if row["speed"] <= 0 and index:
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distance_km, segment_speed = _segment(row, rows[index - 1])
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row["speed"] = (
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segment_speed
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if distance_km * 1000 >= GPS_MOTION_METERS
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else 0
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)
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if len(rows) <= max_points:
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selected = rows
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else:
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indexes = {
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round(index * (len(rows) - 1) / (max_points - 1))
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for index in range(max_points)
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}
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selected = [row for index, row in enumerate(rows) if index in indexes]
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return [{
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"id": row["id"],
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"datetime": row["datetime"].isoformat(sep=" "),
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"latitude": row["latitude"],
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"longitude": row["longitude"],
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"speed": round(row["speed"], 1),
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"speed_source": row["speed_source"],
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} for row in selected]
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