my.emfit: move data access layer bits to emfitexport
This commit is contained in:
Dima Gerasimov
karlicoss
parent
975f9dd110
commit
07dd61ca6a
1 changed files with 15 additions and 284 deletions
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@ -2,288 +2,22 @@
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"""
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"""
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[[https://shop-eu.emfit.com/products/emfit-qs][Emfit QS]] sleep tracker
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[[https://shop-eu.emfit.com/products/emfit-qs][Emfit QS]] sleep tracker
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Consumes data exported by https://github.com/karlicoss/backup-emfit
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Consumes data exported by https://github.com/karlicoss/emfitexport
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"""
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"""
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import json
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from datetime import date
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from dataclasses import dataclass
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from datetime import date, datetime, time, timedelta
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from itertools import groupby
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from pathlib import Path
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from pathlib import Path
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from typing import Dict, Iterator, List, NamedTuple, Any, cast
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from typing import Dict, List, Iterator
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import pytz
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from ..core import get_files
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from more_itertools import bucket
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from ..core.common import mcachew
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from ..common import get_files, LazyLogger, cproperty, mcachew
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from ..core.cachew import cache_dir
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from ..core.cachew import cache_dir
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from ..core.error import Res
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from my.config import emfit as config
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from my.config import emfit as config
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logger = LazyLogger(__name__, level='info')
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import emfitexport.dal as dal
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Emfit = dal.Emfit
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def hhmm(minutes):
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return '{:02d}:{:02d}'.format(*divmod(minutes, 60))
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AWAKE = 4
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Sid = str
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# TODO use common tz thing?
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def fromts(ts) -> datetime:
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dt = datetime.fromtimestamp(ts, tz=pytz.utc)
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return dt
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class Mixin:
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# TODO ugh. tricking mypy...
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sleep_minutes_emfit: int
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@property
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# ok, I guess that's reasonable way of defining sleep date
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def date(self):
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return self.end.date() # type: ignore[attr-defined]
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@cproperty
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def time_in_bed(self):
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return int((self.sleep_end - self.sleep_start).total_seconds()) // 60 # type: ignore[attr-defined]
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@property
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def recovery(self):
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return self.hrv_morning - self.hrv_evening # type: ignore[attr-defined]
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@property
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def summary(self):
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return f"""in bed for {hhmm(self.time_in_bed)}
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emfit time: {hhmm(self.sleep_minutes_emfit)}; covered: {self.sleep_hr_coverage:.0f}
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hrv morning: {self.hrv_morning:.0f}
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hrv evening: {self.hrv_evening:.0f}
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avg hr: {self.measured_hr_avg:.0f}
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recovery: {self.recovery:3.0f}
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{self.hrv_lf}/{self.hrv_hf}""" # type: ignore[attr-defined]
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# TODO def use multiple threads for that..
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class EmfitOld(Mixin):
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def __init__(self, sid: str, jj):
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self.sid = sid
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self.jj = jj
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def __hash__(self):
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return hash(self.sid)
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@property
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def hrv_morning(self):
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return self.jj['hrv_rmssd_morning']
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@property
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def hrv_evening(self):
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return self.jj['hrv_rmssd_evening']
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"""
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Bed time, not necessarily sleep
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"""
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@property
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def start(self):
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return fromts(self.jj['time_start'])
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"""
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Bed time, not necessarily sleep
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"""
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@property
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def end(self):
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return fromts(self.jj['time_end'])
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@property
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def epochs(self):
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return self.jj['sleep_epoch_datapoints']
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@property
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def epoch_series(self):
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tss = []
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eps = []
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for [ts, e] in self.epochs:
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tss.append(ts)
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eps.append(e)
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return tss, eps
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@cproperty
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def sleep_start(self) -> datetime:
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for [ts, e] in self.epochs:
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if e == AWAKE:
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continue
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return fromts(ts)
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raise RuntimeError
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@cproperty
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def sleep_end(self) -> datetime:
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for [ts, e] in reversed(self.epochs):
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if e == AWAKE:
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continue
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return fromts(ts)
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raise RuntimeError
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# 'sleep_epoch_datapoints'
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# [[timestamp, number]]
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# so it's actual sleep, without awake
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# ok, so I need time_asleep
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@property
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def sleep_minutes_emfit(self):
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return self.jj['sleep_duration'] // 60
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@property
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def hrv_lf(self):
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return self.jj['hrv_lf']
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@property
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def hrv_hf(self):
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return self.jj['hrv_hf']
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@property
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def strip_awakes(self):
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ff = None
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ll = None
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for i, [ts, e] in enumerate(self.epochs):
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if e != AWAKE:
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ff = i
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break
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for i in range(len(self.epochs) - 1, -1, -1):
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[ts, e] = self.epochs[i]
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if e != AWAKE:
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ll = i
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break
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return self.epochs[ff: ll]
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# # TODO epochs with implicit sleeps? not sure... e.g. night wakeups.
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# # I guess I could input intervals/correct data/exclude days manually?
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# @property
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# def pulse_percentage(self):
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# # TODO pulse intervals are 4 seconds?
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# # TODO ok, how to compute that?...
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# # TODO cut ff start and end?
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# # TODO remove awakes from both sides
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# sp = self.strip_awakes
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# present = {ep[0] for ep in sp}
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# start = min(present)
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# end = max(present)
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# # TODO get start and end in one go?
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# for p in self.iter_points():
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# p.ts
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# INT = 30
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# missing = 0
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# total = 0
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# for tt in range(start, end + INT, INT):
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# total += 1
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# if tt not in present:
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# missing += 1
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# # TODO get hr instead!
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# import ipdb; ipdb.set_trace()
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# return missing
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# st = st[0][0]
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# INT = 30
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# for [ts, e] in sp:
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# if e == AWAKE:
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# continue
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# return fromts(ts)
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# raise RuntimeError
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# pass
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def __str__(self) -> str:
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return f"from {self.sleep_start} to {self.sleep_end}"
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# measured_datapoints
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# [[timestamp, pulse, breath?, ??? hrv?]] # every 4 seconds?
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def iter_points(self):
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for ll in self.jj['measured_datapoints']:
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[ts, pulse, br, activity] = ll
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# TODO what the fuck is whaat?? It can't be HRV, it's about 500 ms on average
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# act in csv.. so it must be activity? wonder how is it measured.
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# but I guess makes sense. yeah, "measured_activity_avg": 595, about that
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# makes even more sense given tossturn datapoints only have timestamp
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yield ts, pulse
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@property
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def sleep_hr(self):
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tss = []
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res = []
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for ts, pulse in self.iter_points():
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if self.sleep_start < fromts(ts) < self.sleep_end:
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tss.append(ts)
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res.append(pulse)
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return tss, res
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@property
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def sleep_hr_series(self):
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return self.sleep_hr
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@property
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def hrv(self):
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tss = []
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res = []
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for ll in self.jj['hrv_rmssd_datapoints']:
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[ts, rmssd, _, _, almost_always_zero, _] = ll
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# timestamp,rmssd,tp,lfn,hfn,r_hrv
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# TP is total_power??
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# erm. looks like there is a discrepancy between csv and json data.
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# right, so web is using api v 1. what if i use v1??
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# definitely a discrepancy between v1 and v4. have no idea how to resolve it :(
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# also if one of them is indeed tp value, it must have been rounded.
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# TODO what is the meaning of the rest???
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# they don't look like HR data.
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tss.append(ts)
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res.append(rmssd)
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return tss, res
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@property
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def measured_hr_avg(self):
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return self.jj["measured_hr_avg"]
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@cproperty
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def sleep_hr_coverage(self):
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tss, hrs = self.sleep_hr
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covered = len([h for h in hrs if h is not None])
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expected = len(hrs)
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return covered / expected * 100
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# right, so dataclass is better because you can use mixins
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@dataclass(eq=True, frozen=True)
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class Emfit(Mixin):
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sid: Sid
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hrv_morning: float
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hrv_evening: float
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start: datetime
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end : datetime
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sleep_start: datetime
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sleep_end : datetime
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sleep_hr_coverage: float
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measured_hr_avg: float
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sleep_minutes_emfit: int
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hrv_lf: float
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hrv_hf: float
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@classmethod
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def make(cls, em) -> Iterator['Emfit']:
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# TODO FIXME Result type?
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if em.epochs is None:
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logger.error('%s (on %s) got None in epochs! ignoring', em.sid, em.date)
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return
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yield cls(**{
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# pylint: disable=no-member
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k: getattr(em, k) for k in Emfit.__annotations__
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})
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# TODO move to common?
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# TODO move to common?
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# TODO take __file__ into account somehow?
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# TODO take __file__ into account somehow?
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@mcachew(cache_path=cache_dir() / 'emfit.cache', hashf=dir_hash, logger=logger)
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@mcachew(cache_path=cache_dir() / 'emfit.cache', hashf=dir_hash, logger=dal.log)
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def iter_datas(path: Path=config.export_path) -> Iterator[Emfit]:
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def iter_datas(path: Path=config.export_path) -> Iterator[Res[Emfit]]:
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for f in get_files(path, glob='*.json'):
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# TODO FIMXE excluded_sids
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sid = f.stem
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yield from dal.sleeps(config.export_path)
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if sid in config.excluded_sids:
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continue
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em = EmfitOld(sid=sid, jj=json.loads(f.read_text()))
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yield from Emfit.make(em)
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def get_datas() -> List[Emfit]:
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def get_datas() -> List[Emfit]:
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@ -309,14 +38,16 @@ def get_datas() -> List[Emfit]:
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# TODO move away old entries if there is a diff??
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# TODO move away old entries if there is a diff??
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# TODO merge with jawbone data first
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def by_night() -> Dict[date, Emfit]:
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def by_night() -> Dict[date, Emfit]:
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res: Dict[date, Emfit] = {}
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res: Dict[date, Emfit] = {}
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# TODO shit. I need some sort of interrupted sleep detection?
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# TODO shit. I need some sort of interrupted sleep detection?
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from more_itertools import bucket
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grouped = bucket(get_datas(), key=lambda s: s.date)
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grouped = bucket(get_datas(), key=lambda s: s.date)
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for dd in grouped:
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for dd in grouped:
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sleeps = list(grouped[dd])
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sleeps = list(grouped[dd])
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if len(sleeps) > 1:
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if len(sleeps) > 1:
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logger.warning("multiple sleeps per night, not handled yet: %s", sleeps)
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dal.log.warning("multiple sleeps per night, not handled yet: %s", sleeps)
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continue
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continue
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[s] = sleeps
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[s] = sleeps
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res[s.date] = s
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res[s.date] = s
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