move jawbone into my. from private provider

my/jawbone/plots.py

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