def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for a subset of users in the experiment."""
loads = pd.concat(ul.mean_experiment_load_for_user_subset(self._subset_size,
self._subset_seed))
return [ul.add_temperatures(loads, period)
for period in ul.experiment_periods()]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing loads and
temperatures for the given user, or for all users in the experiment if
total_load is True."""
temps = read_temperatures()
loads = ul.tempfeeder_exp()[self.user_id]
return [self._join_temp_and_load(temps, loads, period)
for period in ul.experiment_periods()]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
print "Using total load rather than per-user load."
temps = read_temperatures()
loads = pd.concat(ul.total_experiment_load())
return [self._join_temp_and_load(temps, loads, period)
for period in ul.experiment_periods()]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
loads = pd.concat(ul.total_experiment_load())
return [
ul.add_temperatures(loads, period)
for period in ul.experiment_periods()
]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing loads and
temperatures for the given dataset."""
loads = ul.tempfeeder_exp()[self.user_id]
return [
ul.add_temperatures(loads, period)
for period in ul.experiment_periods()
]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing loads and
temperatures for the given user, or for all users in the experiment if
total_load is True."""
temps = read_temperatures()
loads = ul.tempfeeder_exp()[self.user_id]
return [
self._join_temp_and_load(temps, loads, period)
for period in ul.experiment_periods()
]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
print "Using total load rather than per-user load."
temps = read_temperatures()
loads = pd.concat(ul.total_experiment_load())
return [
self._join_temp_and_load(temps, loads, period)
for period in ul.experiment_periods()
]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for a subset of users in the experiment."""
loads = pd.concat(
ul.mean_experiment_load_for_user_subset(self._subset_size,
self._subset_seed))
return [
ul.add_temperatures(loads, period)
for period in ul.experiment_periods()
]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
loads = pd.concat(ul.total_experiment_load())
return [ul.add_temperatures(loads, period)
for period in ul.experiment_periods()]
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing loads and
temperatures for the given dataset."""
loads = ul.tempfeeder_exp()[self.user_id]
return [ul.add_temperatures(loads, period)
for period in ul.experiment_periods()]
def setUpClass(cls):
cls.data = ul.add_temperatures(ul.total_experiment_load()[0],
ul.experiment_periods()[0])