def preprocess_iawe(building, freq):
building.utility.electric = building.utility.electric.sum_split_supplies()
building = prepb.filter_out_implausible_values(
building, Measurement('voltage', ''), 160, 260)
building = prepb.filter_datetime(building, '7-13-2013', '8-4-2013')
building = prepb.downsample(building, rule=freq)
building = prepb.fill_appliance_gaps(building)
building = prepb.prepend_append_zeros(
building, '7-13-2013', '8-4-2013', freq, 'Asia/Kolkata')
building = prepb.drop_missing_mains(building)
building = prepb.make_common_index(building)
building = prepb.filter_top_k_appliances(building, k=6)
return building
COLUMNS[key] = """\textbf{\specialcell[h]{""" + value + """}}"""
else:
COLUMNS[key] = key
stats_df = pd.DataFrame(index=DATASETS.keys(), columns=COLUMNS.values())
for ds_name, ds_path in DATASETS.iteritems():
if LOAD_DATASETS:
dataset = DataSet()
print("##################################################")
print("Loading", ds_path)
dataset.load_hdf5(ds_path)
if ds_name == "Smart*":
building = dataset.buildings[1]
building = prepb.filter_out_implausible_values(
building, Measurement('power', 'active'), max_threshold=20000)
#electric = building.utility.electric
#electric.crop('2012-06-05', '2012-06-10')
#building = prepb.filter_channels_with_less_than_x_samples(
# building, 100)
dataset.buildings[1] = building
print("Preprocessed!")
if ds_name == 'iAWE':
print("Pre-processing iAWE...")
electric = dataset.buildings[1].utility.electric
electric.crop('2013/6/11', '2013/7/31')
# elif ds_name == 'UKPD':
# electric = dataset.buildings[1].utility.electric
# electric.appliances = electric.remove_channels_from_appliances(
import nilmtk.preprocessing.electricity.single as prep
from nilmtk.stats.electricity.building import plot_missing_samples_using_bitmap
from nilmtk.sensors.electricity import Measurement
from nilmtk.dataset import DataSet
dataset = DataSet()
dataset.load_hdf5("/home/nipun/Dropbox/nilmtk_datasets/iawe")
building = dataset.buildings[1]
# 1. sum together split mains and DualSupply appliances
building.utility.electric = building.utility.electric.sum_split_supplies()
# optional. (required for iAWE) remove samples where voltage outside range
# Fixing implausible voltage values
building = prepb.filter_out_implausible_values(
building, Measurement('voltage', ''), 160, 260)
# optional. (required for iAWE) Note that this will remove motor as it does not have
# any data in this period
building = prepb.filter_datetime(
building, '7-13-2013', '8-4-2013')
# 2. downsample mains, circuits and appliances
building = prepb.downsample(building, rule='1T')
# 3. Fill large gaps in appliances with zeros and forward-fill small gaps
building = prepb.fill_appliance_gaps(building)
# optional. (required for iAWE)
building = prepb.prepend_append_zeros(
building, '7-13-2013', '8-4-2013', '1T', 'Asia/Kolkata')
