ecg_quality_averageQRS.py

def ecg_quality_averageQRS(ecg_cleaned, rpeaks=None, sampling_rate=1000):

    # Sanitize inputs
    if rpeaks is None:
        _, rpeaks = ecg_peaks(ecg_cleaned, sampling_rate=sampling_rate)
        rpeaks = rpeaks["ECG_R_Peaks"]

    # Get heartbeats
    heartbeats = ecg_segment(ecg_cleaned, rpeaks, sampling_rate)
    data = epochs_to_df(heartbeats).pivot(index="Label", columns="Time", values="Signal")
    data.index = data.index.astype(int)
    data = data.sort_index()

    # Filter Nans
    missing = data.T.isnull().sum().values
    nonmissing = np.where(missing == 0)[0]

    data = data.iloc[nonmissing, :]

    # Compute distance
    dist = distance(data, method="mean")
    dist = rescale(np.abs(dist), to=[0, 1])
    dist = np.abs(dist - 1)  # So that 1 is top quality

    # Replace missing by 0
    quality = np.zeros(len(heartbeats))
    quality[nonmissing] = dist

    # Interpolate
    quality = signal_interpolate(
        rpeaks, quality, x_new=np.arange(len(ecg_cleaned)), method="quadratic"
    )

    return quality