rapids/src/features/empatica_temperature/cf/main.py

52 lines
2.3 KiB
Python

import pandas as pd
from scipy.stats import entropy
from CalculatingFeatures.helper_functions import convert1DEmpaticaToArray, convertInputInto2d, genericFeatureNames
from CalculatingFeatures.calculate_features import calculateFeatures
def getSampleRate(data):
try:
timestamps_diff = data['timestamp'].iloc[1] - data['timestamp'].iloc[0]
except:
raise Exception("Error occured while trying to get the sample rate from the first two sequential timestamps.")
return 1000/timestamps_diff
def extractTempFeaturesFromIntradayData(temperature_intraday_data, features, time_segment, filter_data_by_segment):
temperature_intraday_features = pd.DataFrame(columns=["local_segment"] + features)
if not temperature_intraday_data.empty:
sample_rate = getSampleRate(temperature_intraday_data)
temperature_intraday_data = filter_data_by_segment(temperature_intraday_data, time_segment)
if not temperature_intraday_data.empty:
temperature_intraday_features = pd.DataFrame()
# apply methods from calculate features module
temperature_intraday_features = \
temperature_intraday_data.groupby('local_segment').apply(\
lambda x: calculateFeatures(convertInputInto2d(x['temperature'], x.shape[0]), fs=int(sample_rate), featureNames=features))
temperature_intraday_features.reset_index(inplace=True)
return temperature_intraday_features
def cf_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
temperature_intraday_data = pd.read_csv(sensor_data_files["sensor_data"])
requested_intraday_features = provider["FEATURES"]
# name of the features this function can compute
base_intraday_features_names = genericFeatureNames
# the subset of requested features this function can compute
intraday_features_to_compute = list(set(requested_intraday_features) & set(base_intraday_features_names))
# extract features from intraday data
temperature_intraday_features = extractTempFeaturesFromIntradayData(temperature_intraday_data,
intraday_features_to_compute, time_segment,
filter_data_by_segment)
return temperature_intraday_features