128 lines
3.5 KiB
Python
128 lines
3.5 KiB
Python
import matplotlib.dates as md # type: ignore
|
|
import numpy as np # type: ignore
|
|
import seaborn as sns # type: ignore
|
|
import matplotlib.pyplot as plt
|
|
|
|
|
|
def plot_file(jj: str):
|
|
pts = jj['sleep_epoch_datapoints']
|
|
|
|
|
|
tss = [datetime.fromtimestamp(p[0]) for p in pts]
|
|
vals = [p[1] for p in pts]
|
|
|
|
plt.figure(figsize=(20,10))
|
|
plt.plot(tss, vals)
|
|
|
|
|
|
xformatter = md.DateFormatter('%H:%M')
|
|
xlocator = md.MinuteLocator(interval = 15)
|
|
|
|
## Set xtick labels to appear every 15 minutes
|
|
plt.gcf().axes[0].xaxis.set_major_locator(xlocator)
|
|
|
|
## Format xtick labels as HH:MM
|
|
plt.gcf().axes[0].xaxis.set_major_formatter(xformatter)
|
|
|
|
|
|
|
|
plt.xlabel('time')
|
|
plt.ylabel('phase')
|
|
plt.title('Sleep phases')
|
|
plt.grid(True)
|
|
plt.savefig(f"{f}.png")
|
|
plt.close() # TODO
|
|
# plt.show()
|
|
|
|
pass
|
|
|
|
|
|
def plot_all():
|
|
for jj in iter_datas():
|
|
plot_file(jj)
|
|
|
|
|
|
# def stats():
|
|
# for jj in iter_datas():
|
|
# # TODO fimezone??
|
|
# # TODOgetinterval on 16 aug -- err it's pretty stupid. I shouldn't count bed exit interval...
|
|
# st = fromts(jj['time_start'])
|
|
# en = fromts(jj['time_end'])
|
|
# tfmt = "%Y-%m-%d %a"
|
|
# tot_mins = 0
|
|
# res = []
|
|
# res.append(f"{st.strftime(tfmt)} -- {en.strftime(tfmt)}")
|
|
# for cls in ['rem', 'light', 'deep']:
|
|
# mins = jj[f'sleep_class_{cls}_duration'] // 60
|
|
# res += [cls, hhmm(mins)]
|
|
# tot_mins += mins
|
|
# res += ["total", hhmm(tot_mins)]
|
|
# print(*res)
|
|
|
|
|
|
def stats():
|
|
datas = get_datas()
|
|
cur = datas[0].date
|
|
for jj in datas:
|
|
# import ipdb; ipdb.set_trace()
|
|
while cur < jj.date:
|
|
cur += timedelta(days=1)
|
|
if cur.weekday() == 0:
|
|
print("---")
|
|
if cur != jj.date:
|
|
print(" ")
|
|
# cur = jj.date
|
|
print(f"{jj.date.strftime('%m.%d %a')} {jj.hrv_morning:.0f} {jj.hrv_evening:.0f} {jj.hrv_morning - jj.hrv_evening:3.0f} {hhmm(jj.sleep_minutes)} {jj.hrv_lf}/{jj.hrv_hf} {jj.sleep_hr_coverage:3.0f}")
|
|
|
|
|
|
def plot_recovery_vs_hr_percentage():
|
|
sns.set(color_codes=True)
|
|
xs = []
|
|
ys = []
|
|
for jj in get_datas():
|
|
xs.append(jj.hrv_morning - jj.hrv_evening)
|
|
ys.append(jj.sleep_hr_coverage)
|
|
ax = sns.regplot(x=xs, y=ys) # "recovery", y="percentage", data=pdata)
|
|
ax.set(xlabel='recovery', ylabel='percentage')
|
|
plt.show()
|
|
|
|
|
|
def plot_hr():
|
|
jj = get_datas()[-1]
|
|
tss, uu = jj.sleep_hr
|
|
tss = tss[::10]
|
|
uu = uu[::10]
|
|
plt.figure(figsize=(15,4))
|
|
ax = sns.pointplot(tss, uu, markers=" ")
|
|
ax.set(ylim=(None, 1000))
|
|
|
|
plt.show()
|
|
|
|
# TODO ok, would be nice to have that every morning in timeline
|
|
# also timeline should have dynamic filters? maybe by tags
|
|
# then I could enable emfit feed and slog feed (pulled from all org notes) and see the correlation? also could pull workouts provider (and wlog) -- actually wlog processing could be moved to timeline too
|
|
|
|
# TODO could plot 'recovery' thing and see if it is impacted by workouts
|
|
|
|
|
|
# TODO time_start, time_end
|
|
|
|
# plot_hrv()
|
|
# stats()
|
|
# plot_recovery_vs_hr_percentage()
|
|
# stats()
|
|
# import matplotlib
|
|
# matplotlib.use('Agg')
|
|
|
|
|
|
# TODO maybe rmssd should only be computed if we have a reasonable chunk of datas
|
|
# also, trust it only if it's stable
|
|
|
|
# plot_timestamped([p[0] for p in pts], [p[1] for p in pts], mavgs=[]).savefig('res.png')
|
|
# TODO X axes: show hours and only two dates
|
|
# TODO 4 is awake, 3 REM, 2 light, 1 deep
|
|
|
|
|
|
|
|
|
|
# deviartion beyond 25-75 or 75-25 is bad??
|