Exemple #1
0
def extract_basic_feats_n_heads(series, modality, field, stat_type, trans_type):
    """
    feature extraction with given time series data
    :return: feature name list, feature value list
    """
    heads = [] + stat_type
    sig_heads = []
    for sig_feat in feat.SIGNAL_FEATS:
        if sig_feat in stat_type:
            heads.remove(sig_feat)
            sig_heads += [sig_feat]

    stats = map(lambda x: comp.compute_basic_stat(series, x), heads)
    stats += comp.compute_peak_stats(series) if feat.AVG_PEAK_INTERVAL in sig_heads else []
    stats += comp.compute_fft_stats(series) if feat.FT_REL_FREQ_1ST in sig_heads else []
    heads += sig_heads
    if trans_type in feat.BIN_NEEDED_TR_TYPES:
        eq_freq = True if feat.DISC_FQ in trans_type else False
        bin_heads, bin_stats = extract_bin_feats_and_heads(series, modality, field, eq_freq)
        heads += bin_heads
        stats += bin_stats
    return heads, stats
Exemple #2
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def get_feature_list(df_raw, c_name):
    return [compute_basic_stat(df_raw[c_name], f)
            for f in STATISTICS]