36 lines
2.0 KiB
Python
36 lines
2.0 KiB
Python
import pandas as pd
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import numpy as np
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def dbdp_features(sensor_data_files, time_segment, provider, filter_data_by_segment, *args, **kwargs):
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acc_data = pd.read_csv(sensor_data_files["sensor_data"])
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requested_features = provider["FEATURES"]
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# name of the features this function can compute
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base_features_names = ["maxmagnitude", "minmagnitude", "avgmagnitude", "medianmagnitude", "stdmagnitude"]
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# the subset of requested features this function can compute
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features_to_compute = list(set(requested_features) & set(base_features_names))
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acc_features = pd.DataFrame(columns=["local_segment"] + features_to_compute)
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if not acc_data.empty:
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acc_data = filter_data_by_segment(acc_data, time_segment)
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if not acc_data.empty:
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acc_features = pd.DataFrame()
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# get magnitude related features: magnitude = sqrt(x^2+y^2+z^2)
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magnitude = acc_data.apply(lambda row: np.sqrt(row["double_values_0"] ** 2 + row["double_values_1"] ** 2 + row["double_values_2"] ** 2), axis=1)
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acc_data = acc_data.assign(magnitude = magnitude.values)
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if "maxmagnitude" in features_to_compute:
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acc_features["maxmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].max()
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if "minmagnitude" in features_to_compute:
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acc_features["minmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].min()
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if "avgmagnitude" in features_to_compute:
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acc_features["avgmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].mean()
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if "medianmagnitude" in features_to_compute:
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acc_features["medianmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].median()
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if "stdmagnitude" in features_to_compute:
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acc_features["stdmagnitude"] = acc_data.groupby(["local_segment"])["magnitude"].std()
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acc_features = acc_features.reset_index()
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return acc_features |