This code extracts the feature we have chosen from the data (window)

features.py

def _compute_mean_features(window):
    """
    Computes the mean x, y and z acceleration over the given window. 
    """
    return np.mean(window, axis=0)


def _compute_std_features(window):
    '''
    Computes the standard deviation of x, y and z acceleration over the given window. 
    Returns an array of numbers corresponding to the x, y and z values

    '''
    return np.std(window, axis = 0)

def _compute_dominant_frequency(window):
    '''
    Computes the dominant frequency of x, y and z acceleration over the given window. 

    '''
    return np.fft.rfft(window,axis=0).astype(float)[0]
  
def _compute_peak_length(window):

    '''
    Computes the peak length of x, y and z acceleration over the given window. 
    
    '''

    magnitude = _compute_magnitude(window)
    peaks, _ = find_peaks(magnitude, prominence=1)
    
    return [len(peaks)]