def set_sleep_params(self, start_mean, start_std, end_mean, end_std):
"""
This function sets the biological sleep parameters themselves and the sleep parameter distribution functions.
:param int start_mean: the mean sleep start time [minutes]
:param int start_std: the standard deviation of start time [minutes]
:param int end_mean: the mean sleep end time [minutes]
:param int end_std: the standard deviation of end time [minutes]
:return: None
"""
DAY_2_MIN = temporal.DAY_2_MIN
# set the standard deviation of the sleep duration
self.sleep_start_mean, self.sleep_start_std = start_mean, start_std
self.sleep_end_mean, self.sleep_end_std = end_mean, end_std
self.sleep_start = self.sleep_start_mean
self.sleep_end = self.sleep_end_mean
self.sleep_dt = (self.sleep_end - self.sleep_start) % DAY_2_MIN
self.f_sleep_start = mg.set_distribution(-self.start_trunc, self.start_trunc, self.sleep_start_mean, \
self.sleep_start_std)
self.f_sleep_end = mg.set_distribution(-self.end_trunc, self.end_trunc, self.sleep_end_mean, \
self.sleep_end_std)
return
def __init__(self):
DAY_2_MIN = temporal.DAY_2_MIN
# the gender
self.gender = FEMALE
# the age [years]
self.age = AGE
# biology related to sleeping
self.sleep_start_mean = SLEEP_START_MEAN
self.sleep_start_std = SLEEP_START_STD
self.sleep_start = self.sleep_start_mean
self.sleep_start_univ = 0
self.sleep_end_mean = SLEEP_END_MEAN
self.sleep_end_std = SLEEP_END_STD
self.sleep_end = self.sleep_end_mean
self.sleep_end_univ = 0
self.sleep_dt = (self.sleep_end - self.sleep_start + 1) % DAY_2_MIN
self.start_trunc = SLEEP_START_TRUNC
self.end_trunc = SLEEP_END_TRUNC
# these are the probability distributions for sampling start and end times
self.f_sleep_start = mg.set_distribution(-self.start_trunc, self.start_trunc, self.sleep_start_mean, \
self.sleep_start_std)
self.f_sleep_end = mg.set_distribution(-self.end_trunc, self.end_trunc, self.sleep_end_mean, \
self.sleep_end_std)
return
def __init__(self, id=BREAKFAST, start_mean=BREAKFAST_START_MEAN, start_std=BREAKFAST_START_STD, \
start_trunc=BREAKFAST_START_TRUNC, dt_mean=BREAKFAST_DT_MEAN, dt_std=BREAKFAST_DT_STD, \
dt_trunc=BREAKFAST_DT_TRUNC):
self.id = id
self.start_mean = start_mean
self.start_std = start_std
self.start_trunc = start_trunc
self.dt_mean = dt_mean
self.dt_std = dt_std
self.dt_trunc = dt_trunc
self.t_start = self.start_mean
self.dt = self.dt_mean
self.f_start = mg.set_distribution(-self.start_trunc, self.start_trunc,
self.start_mean, self.start_std)
self.f_dt = mg.set_distribution(-self.dt_trunc, self.dt_trunc,
self.dt_mean, self.dt_std)
self.t_start_univ = 0
self.day = 0
return
def set_work_distribution(self):
"""
This function sets the following distributions for work:
* work start time distribution
* work end time distribution
:return: None
"""
self.f_work_start = mg.set_distribution(-self.work_start_trunc, self.work_start_trunc, \
self.t_start_mean, self.t_start_std)
self.f_work_end = mg.set_distribution(-self.work_end_trunc, self.work_end_trunc, \
self.t_end_mean, self.t_end_std)
return
def set_meal(self, id, start_mean, start_std, start_trunc, dt_mean, dt_std,
dt_trunc):
"""
This function sets the values associated with the Meal object.
:param int id: the meal type (breakfast, lunch, or dinner)
:param int start_mean: the mean start time of the meal [minutes, time of day]
:param int start_std: the standard deviation of start time [minutes]
:param int start_turnc: the number of standard deviations in the start time distribution
:param int dt_mean: the mean duration of a meal [minutes]
:param int dt_std: the standard deviation of meal duration [minutes]
:param int dt_trunc: the number of standard deviations in the duration distribution
:return: None
"""
self.id = id
self.start_mean = start_mean
self.start_std = start_std
self.start_trunc = start_trunc
self.dt_mean = dt_mean
self.dt_std = dt_std
self.dt_trunc = dt_trunc
self.t_start = self.start_mean
self.dt = self.dt_mean
self.f_start = mg.set_distribution(-self.start_trunc, self.start_trunc, self.start_mean, \
self.start_std)
self.f_dt, self.dt_std = mg.set_distribution_dt(-self.dt_trunc, self.dt_trunc, self.dt_mean, self.dt_std, \
x_min=DT_MIN)
return