77 lines
4.1 KiB
Python
77 lines
4.1 KiB
Python
import pandas as pd
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from scipy.stats import entropy
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def statsFeatures(heartrate_data, features, heartrate_features):
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col_name = "heartrate"
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if "sumhr" in features:
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heartrate_features["sumhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].sum()
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if "maxhr" in features:
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heartrate_features["maxhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].max()
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if "minhr" in features:
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heartrate_features["minhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].min()
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if "avghr" in features:
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heartrate_features["avghr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].mean()
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if "medianhr" in features:
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heartrate_features["medianhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].median()
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if "modehr" in features:
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heartrate_features["modehr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].agg(lambda x: pd.Series.mode(x)[0])
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if "stdhr" in features:
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heartrate_features["stdhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].std()
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if "diffmaxmodehr" in features:
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heartrate_features["diffmaxmodehr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].max() - \
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heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].agg(lambda x: pd.Series.mode(x)[0])
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if "diffminmodehr" in features:
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heartrate_features["diffminmodehr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].agg(lambda x: pd.Series.mode(x)[0]) - \
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heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].min()
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if "entropyhr" in features:
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heartrate_features["entropyhr"] = heartrate_data[["local_segment", col_name]].groupby(["local_segment"])[
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col_name].agg(entropy)
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return heartrate_features
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def extractHRFeaturesFromIntradayData(heartrate_intraday_data, features, time_segment, filter_data_by_segment):
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heartrate_intraday_features = pd.DataFrame(columns=["local_segment"] + features)
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if not heartrate_intraday_data.empty:
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heartrate_intraday_data = filter_data_by_segment(heartrate_intraday_data, time_segment)
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if not heartrate_intraday_data.empty:
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heartrate_intraday_features = pd.DataFrame()
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# get stats of heartrate
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heartrate_intraday_features = statsFeatures(heartrate_intraday_data, features, heartrate_intraday_features)
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heartrate_intraday_features.reset_index(inplace=True)
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return heartrate_intraday_features
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def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
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heartrate_intraday_data = pd.read_csv(sensor_data_files["sensor_data"])
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requested_intraday_features = provider["FEATURES"]
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# name of the features this function can compute
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base_intraday_features_names = ["maxhr", "minhr", "avghr", "medianhr", "modehr", "stdhr", "diffmaxmodehr",
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"diffminmodehr", "entropyhr"]
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# the subset of requested features this function can compute
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intraday_features_to_compute = list(set(requested_intraday_features) & set(base_intraday_features_names))
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# extract features from intraday data
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heartrate_intraday_features = extractHRFeaturesFromIntradayData(heartrate_intraday_data,
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intraday_features_to_compute, time_segment,
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filter_data_by_segment)
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return heartrate_intraday_features
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