How to use the biosppy.tools function in biosppy

- Dominique Makowski (https://github.com/DominiqueMakowski)

    *Dependencies*

    - biosppy

    *See Also*

    - BioSPPY: https://github.com/PIA-Group/BioSPPy

    """
    # Compute gradient (sort of derivative)
    gradient = np.gradient(signal)
    # Find zero-crossings
    zeros, = biosppy.tools.zero_cross(signal=gradient, detrend=True)

    # Find respiratory phases
    phases_indices = []
    for i in zeros:
        if gradient[i+1] > gradient[i-1]:
            phases_indices.append("Inspiration")
        else:
            phases_indices.append("Expiration")

    # Select cycles (inspiration) and expiration onsets
    inspiration_onsets = []
    expiration_onsets = []
    for index, onset in enumerate(zeros):
        if phases_indices[index] == "Inspiration":
            inspiration_onsets.append(onset)
        if phases_indices[index] == "Expiration":

References
    -----------
    - Kim, K. H., Bang, S. W., & Kim, S. R. (2004). Emotion recognition system using short-term monitoring of physiological signals. Medical and biological engineering and computing, 42(3), 419-427.
    - Gamboa, H. (2008). Multi-Modal Behavioral Biometrics Based on HCI and Electrophysiology (Doctoral dissertation, PhD thesis, Universidade Técnica de Lisboa, Instituto Superior Técnico).
    """
    # Processing
    # ===========
    if method == "slow":
        # Compute gradient (sort of derivative)
        gradient = np.gradient(signal)
        # Smoothing
        size = int(0.1 * sampling_rate)
        smooth, _ = biosppy.tools.smoother(signal=gradient, kernel='bartlett', size=size, mirror=True)
        # Find zero-crossings
        zeros, = biosppy.tools.zero_cross(signal=smooth, detrend=True)

        # Separate onsets and peaks
        onsets = []
        peaks = []
        for i in zeros:
            if smooth[i+1] > smooth[i-1]:
                onsets.append(i)
            else:
                peaks.append(i)
    else:
        # find extrema
        peaks, _ = biosppy.tools.find_extrema(signal=signal, mode='max')
        onsets, _ = biosppy.tools.find_extrema(signal=signal, mode='min')


    # Keep only pairs

size = int(0.1 * sampling_rate)
        smooth, _ = biosppy.tools.smoother(signal=gradient, kernel='bartlett', size=size, mirror=True)
        # Find zero-crossings
        zeros, = biosppy.tools.zero_cross(signal=smooth, detrend=True)

        # Separate onsets and peaks
        onsets = []
        peaks = []
        for i in zeros:
            if smooth[i+1] > smooth[i-1]:
                onsets.append(i)
            else:
                peaks.append(i)
    else:
        # find extrema
        peaks, _ = biosppy.tools.find_extrema(signal=signal, mode='max')
        onsets, _ = biosppy.tools.find_extrema(signal=signal, mode='min')


    # Keep only pairs
    peaks = peaks[peaks > onsets[0]]
    onsets = onsets[onsets < peaks[-1]]

    # Artifact Treatment
    # ====================
    # Compute rising times
    risingtimes = peaks-onsets
    risingtimes = risingtimes/sampling_rate*1000

    peaks = peaks[risingtimes > 100]
    onsets = onsets[risingtimes > 100]