def extract_features_from_rawdata(chunk, header, period, features):
with open(
os.path.join(os.path.dirname(__file__),
"resources/channel_info.json")) as channel_info_file:
channel_info = json.loads(channel_info_file.read())
data = [convert_to_dict(X, header, channel_info) for X in chunk]
return extract_features(data, period, features)
def extract_features_from_rawdata(chunk, header, period, features):
with open(
os.path.join(os.path.dirname(__file__),
"resources/channel_info.json")) as channel_info_file:
channel_info = json.loads(channel_info_file.read())
with open(
os.path.join(
os.path.dirname(__file__),
"resources/plausible_values.json")) as plausible_values_file:
plausible_values = json.loads(plausible_values_file.read())
# transform raw 2d array for each instance into separate lists for each attribute that contains timestamped tuples
# with attribute values (also apply value transformation from channel_info.json.
data = [convert_to_dict(X, header, channel_info) for X in chunk]
data = [
remove_implausible_values(X, header, plausible_values) for X in data
]
return extract_features(data, period, features)
def extract_features_from_rawdata(chunk, header, period, features):
with open(os.path.join(os.path.dirname(__file__), "channel_info.json")) as channel_info_file:
channel_info = json.loads(channel_info_file.read())
data = [convert_to_dict(X, header, channel_info) for X in chunk]
return extract_features(data, period, features)
