def load_building(self, root_directory, building_name):
''' Loads electrical data for specified building
'''
# Each building has a week worth data
# Files are named as follows:
# Home 01_1min_2012-0903.xlsx to Home 01_1min_2012-0909.xlsx
# Pattern building_name + "_1min_2012-09" + ['03'-'09'].xlsx
building_folder = os.path.join(root_directory, '1_min', building_name)
df = pd.DataFrame()
for day in ["03", "04", "05", "06", "07", "08", "09"]:
spreadsheet = pd.ExcelFile(
os.path.join(building_folder,
"%s_1min_2012-09%s.xlsx" % (building_name, day)))
temp_df = spreadsheet.parse('Sheet1',
index_col=0,
date_parser=True)
df = df.append(temp_df)
df = self.standardize(df)
# Create a new building
building = Building()
# Add mains
building = self.add_mains(building, df)
# Add appliances
building = self.add_appliances(building, df)
# Adding this building to dict of buildings
building_name = building_name.replace(" ", "_")
self.buildings[building_name] = building
def load_building(self, root_directory, building_name):
# Construct new Building and set known attributes
building = Building()
# MIT's coorindates
building.geographic_coordinates = (42.360091, -71.09416)
# Load labels
building_dir = os.path.join(root_directory, building_name)
labels = load_labels(building_dir)
# Load mains
mains_chans = [chan for chan, label in labels.iteritems()
if label == 'mains']
mains_chan_dict = {}
for mains_chan in mains_chans:
col_name = 'mains_{:d}_meter_1_active'.format(mains_chan)
mains_chan_dict[col_name] = load_chan(building_dir, mains_chan)
# Make a DataFrame containing all mains channels
df = pd.DataFrame(mains_chan_dict)
df = df.tz_localize('UTC')
df = df.tz_convert('US/Eastern') # MIT is on the east coast!
building.electric.mains = df
# Load sub metered channels
# TODO
# Convert from REDD channel names to standardised names
# Set up wiring
self.buildings[building_name] = building
def __init__(self):
super(AMPDS, self).__init__()
self.urls = ['http://ampds.org/']
self.citations = [
'Stephen Makonin, Fred Popowich, Lyn Bartram, '
'Bob Gill, and Ivan V. Bajic,'
'AMPds: A Public Dataset for Load Disaggregation and'
'Eco-Feedback Research, in Electrical Power and Energy'
'Conference (EPEC), 2013 IEEE, pp. 1-6, 2013.'
]
self.building = Building()
self.buildings['Home_01'] = self.building
self.nominal_voltage = 230
def load_building(self, root_directory, building_name):
spreadsheet = pd.ExcelFile(
os.path.join(root_directory,
"15_min/Homes 01-10_15min_2012-0819-0825 .xlsx"))
df = spreadsheet.parse(building_name, index_col=0, date_parser=True)
df = self.standardize(df)
# Create a new building
building = Building()
# Add mains
building = self.add_mains(building, df)
# Add appliances
building = self.add_appliances(building, df)
# Adding this building to dict of buildings
building_name = building_name.replace(" ", "_")
self.buildings[building_name] = building
