def get_data(pre_win, post_win):
settings = setup(dataset='test', data_loc='./data/controlIntervention/', subject_n=3)
data = Dataset(
settings,
trim=True,
check=False,
used_data_types=[DATA_TYPES.event, DATA_TYPES.fitbit]
)
minutes = post_win+pre_win
PNUM = 0
bars = []
for evt in data.subject_data[0].event_data.time:
time = evt-timedelta(minutes=pre_win)
bars.append(data.get_steps_after_time(time, minutes, PNUM))
pids = [1]*len(bars) # all events are same participant
return minutes, pids, bars
def get_fake_data(pre_win, post_win, minutes, pids, bars):
# returns data from randomly chosen fake data points
settings = setup(dataset='test', data_loc='./data/controlIntervention/', subject_n=3)
data = Dataset(
settings,
trim=True,
check=False,
used_data_types=[DATA_TYPES.event, DATA_TYPES.fitbit]
)
PNUM = 0
fake_bars = []
for evt in data.subject_data[0].event_data.time:
time = evt-timedelta(days=1, minutes=pre_win) # get random(ish) time
fake_bars.append(data.get_steps_after_time(time, minutes, PNUM))
diff_bars = []
for i in range(len(bars)):
diff_bars.append(list_subtract(bars[i], fake_bars[i]))
return minutes, pids, diff_bars