146 lines
4.1 KiB
Python
Executable file
146 lines
4.1 KiB
Python
Executable file
#!/usr/bin/env python3
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# TODO this should be in dashboard
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from pathlib import Path
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# from kython.plotting import *
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from csv import DictReader
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from itertools import islice
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from typing import Dict, Any, NamedTuple, Dict
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# sleep = []
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# with open('2017.csv', 'r') as fo:
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# reader = DictReader(fo)
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# for line in islice(reader, 0, 10):
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# sleep
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# print(line)
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import numpy as np # type: ignore
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import matplotlib.pyplot as plt # type: ignore
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from numpy import genfromtxt # type: ignore
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import matplotlib.pylab as pylab # type: ignore
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pylab.rcParams['figure.figsize'] = (32.0, 24.0)
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pylab.rcParams['font.size'] = 10
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jawboneDataFeatures = Path(__file__).parent / 'features.csv' # Data File Path
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featureDesc: Dict[str, str] = {}
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for x in genfromtxt(jawboneDataFeatures, dtype='unicode', delimiter=','):
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featureDesc[x[0]] = x[1]
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def _safe_float(s: str):
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if len(s) == 0:
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return None
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return float(s)
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def _safe_int(s: str):
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if len(s) == 0:
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return None
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return int(float(s)) # TODO meh
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def _safe_mins(s: float):
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if s is None:
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return None
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return s / 60
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class SleepData(NamedTuple):
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date: str
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asleep_time: float
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awake_time: float
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total: float
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awake: float # 'awake for' from app, time awake duing sleep (seconds)
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awakenings: int
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light: float # 'light sleep' from app (seconds)
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deep: float # 'deep sleep' from app (sec)
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quality: float # ???
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@classmethod
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def from_jawbone_dict(cls, d: Dict[str, Any]):
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return cls(
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date=d['DATE'],
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asleep_time=_safe_mins(_safe_float(d['s_asleep_time'])),
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awake_time=_safe_mins(_safe_float(d['s_awake_time'])),
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total=_safe_mins(_safe_float(d['s_duration'])),
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light=_safe_mins(_safe_float(d['s_light'])),
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deep =_safe_mins(_safe_float(d['s_deep'])),
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awake=_safe_mins(_safe_float(d['s_awake'])),
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awakenings=_safe_int(d['s_awakenings']),
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quality=_safe_float(d['s_quality']),
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)
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def is_bad(self):
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return self.deep is None and self.light is None
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# @property
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# def total(self) -> float:
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# return self.light + self.deep
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def iter_useful(data_file: str):
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from csv import DictReader
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with open(data_file) as fo:
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reader = DictReader(fo)
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for d in reader:
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dt = SleepData.from_jawbone_dict(d)
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if not dt.is_bad():
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yield dt
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# TODO <<< hmm. these files do contain deep and light sleep??
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# also steps stats??
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from my.config import jawbone as config
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p = config.export_dir / 'old_csv'
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# TODO with_my?
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files = [
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p / "2015.csv",
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p / "2016.csv",
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p / "2017.csv",
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]
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from kython import concat, parse_date
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useful = concat(*(list(iter_useful(str(f))) for f in files))
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# for u in useful:
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# print(f"{u.total} {u.asleep_time} {u.awake_time}")
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# # pprint(u.total)
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# pprint(u)
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# pprint("---")
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dates = [parse_date(u.date, yearfirst=True, dayfirst=False) for u in useful]
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# TODO filter outliers?
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# TODO don't need this anymore? it's gonna be in dashboards package
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from kython.plotting import plot_timestamped
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for attr, lims, mavg, fig in [ # type: ignore
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('light', (0, 400), 5, None),
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('deep', (0, 600), 5, None),
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('total', (200, 600), 5, None),
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('awake_time', (0, 1200), None, 1),
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('asleep_time', (-100, 1000), None, 1),
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# ('awakenings', (0, 5)),
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]:
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dates_wkd = [d for d in dates if d.weekday() < 5]
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dates_wke = [d for d in dates if d.weekday() >= 5]
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for dts, dn in [
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(dates, 'total'),
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(dates_wkd, 'weekday'),
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(dates_wke, 'weekend')
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]:
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mavgs = []
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if mavg is not None:
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mavgs.append((mavg, 'green'))
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fig = plot_timestamped(
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dts, # type: ignore
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[getattr(u, attr) for u in useful],
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marker='.',
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ratio=(16, 4),
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mavgs=mavgs,
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ylimits=lims,
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ytick_size=60,
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# figure=1,
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)
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plt.savefig(f'{attr}_{dn}.png')
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# TODO use proper names?
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# plt.savefig('res.png')
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# fig.show()
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