Davide Scaini
59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
"""Downsample a list of DataPoints to at most 1 sample/second and build
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the BAS timeseries object (parallel arrays)."""
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from datetime import datetime
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from typing import Optional
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from bincio.extract.models import DataPoint
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def build_timeseries(
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points: list[DataPoint],
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started_at: datetime,
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privacy: str = "public",
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) -> dict:
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"""Return the BAS `timeseries` object.
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privacy='no_gps' or 'private' → lat/lon set to null.
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Downsamples so at most one point per second is emitted.
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"""
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if not points:
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return {"t": []}
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include_gps = privacy not in ("no_gps", "private")
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# Downsample: keep at most one point per second
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sampled: list[DataPoint] = []
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last_t: Optional[int] = None
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for p in points:
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t = int((p.timestamp - started_at).total_seconds())
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if t < 0:
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continue
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if last_t is not None and t <= last_t:
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continue # skip sub-second duplicates and non-monotonic points
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sampled.append(p)
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last_t = t
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ts_vals = [int((p.timestamp - started_at).total_seconds()) for p in sampled]
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lat_vals = [round(p.lat, 7) if p.lat is not None else None for p in sampled] if include_gps else None
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lon_vals = [round(p.lon, 7) if p.lon is not None else None for p in sampled] if include_gps else None
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ele_vals = [round(p.elevation_m, 1) if p.elevation_m is not None else None for p in sampled]
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spd_vals = [round(p.speed_kmh, 2) if p.speed_kmh is not None else None for p in sampled]
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hr_vals = [p.hr_bpm for p in sampled]
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cad_vals = [p.cadence_rpm for p in sampled]
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pwr_vals = [p.power_w for p in sampled]
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tmp_vals = [round(p.temperature_c, 1) if p.temperature_c is not None else None for p in sampled]
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result: dict = {
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"t": ts_vals,
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"lat": lat_vals,
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"lon": lon_vals,
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"elevation_m": ele_vals,
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"speed_kmh": spd_vals,
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"hr_bpm": hr_vals,
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"cadence_rpm": cad_vals,
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"power_w": pwr_vals,
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"temperature_c": tmp_vals,
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}
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return result
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