def _load_dataset(self, dataset_name):
if dataset_name == "bc-data":
self._dataset = bc.load()
elif dataset_name == "total-load":
self._dataset = ul.total_experiment_load()[1]['Load']
else:
raise RuntimeError("Invalid dataset name: %s" % dataset_name)
def _load_dataset(self, dataset_name):
if dataset_name == "bc-data":
self._dataset = bc.load()
elif dataset_name == "total-load":
self._dataset = ul.total_experiment_load()[1]['Load']
else:
raise RuntimeError("Invalid dataset name: %s" % dataset_name)
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
load = bc.load()
data = pd.DataFrame({'Load': load, 'Temperature': 0})
test_period_starts = "2010-03-15 00:00:00"
(train, test) = (data[:test_period_starts], data[test_period_starts:])
return (train, test)
def _prepare_dataset(self):
"""Return datasets for the experiment periods containing the total load
for all users in the experiment."""
load = bc.load()
data = pd.DataFrame({'Load': load, 'Temperature': 0})
test_period_starts = "2010-03-15 00:00:00"
(train, test) = (data[:test_period_starts], data[test_period_starts:])
return (train, test)
def _show_smoother():
import sg.data.bchydro as bchydro
import matplotlib.pyplot as plt
all_timeseries = bchydro.load()
week = all_timeseries.data[0:24*7]
sm = BSplineSmoother(week, smoothness=0)
t = np.linspace(0, 1, 1000)
y = sm.splev(t)
plt.figure()
plt.plot(t, y)
plt.title("Show smoother")
def setUpModule():
np.seterr(all='raise')
global bchydro_timeseries
bchydro_timeseries = bchydro.load()
def setUpModule():
np.seterr(all='raise')
global bchydro_timeseries
bchydro_timeseries = bchydro.load()
# Short demonstration of the utilities to load BCHydro data
import sys
import os
from datetime import timedelta as dt
import matplotlib.pyplot as plt
import sg.data.bchydro as bc
if __name__ == "__main__":
# Option 1: load the entire dataset as a timeseries
timeseries = bc.load()
filtered = [x if x > 10 else 4000 for x in timeseries]
plt.plot(filtered, '-')
plt.title("The entire BC Hydro dataset")
# Option 2: load the using the Dataset class
dataset = bc.Dataset(period=dt(days=30), step_length=dt(days=7))
plt.figure()
plt.plot(dataset.get_random_period(), '-')
plt.title("A randomly selected 30-day period from the BC Hydro dataset")
plt.show()