def load_text_data(dataset, directory, centre=True):
    """Load in a data set of marker points from the Ohio State University C3D motion capture files (http://accad.osu.edu/research/mocap/mocap_data.htm)."""

    points, point_names = parse_text(os.path.join(directory, dataset + '.txt'))[0:2]
    # Remove markers where there is a NaN
    present_index = [i for i in range(points[0].shape[1]) if not (np.any(np.isnan(points[0][:, i])) or np.any(np.isnan(points[0][:, i])) or np.any(np.isnan(points[0][:, i])))]

    point_names = point_names[present_index]
    for i in range(3):
        points[i] = points[i][:, present_index]
        if centre:
            points[i] = (points[i].T - points[i].mean(axis=1)).T 

    # Concatanate the X, Y and Z markers together
    Y = np.concatenate((points[0], points[1], points[2]), axis=1)
    Y = Y/400.
    connect = read_connections(os.path.join(directory, 'connections.txt'), point_names)
    return Y, connect
def load_text_data ( dataset , directory , centre = True ) : points , point_names = parse_text ( os . path . join ( directory , dataset + '.txt' ) ) [ 0 : 2 ] present_index = [ i for i in range ( points [ 0 ] . shape [ 1 ] ) if not ( np . any ( np . isnan ( points [ 0 ] [ : , i ] ) ) or np . any ( np . isnan ( points [ 0 ] [ : , i ] ) ) or np . any ( np . isnan ( points [ 0 ] [ : , i ] ) ) ) ] point_names = point_names [ present_index ] for i in range ( 3 ) : points [ i ] = points [ i ] [ : , present_index ] if centre : points [ i ] = ( points [ i ] . T - points [ i ] . mean ( axis = 1 ) ) . T Y = np . concatenate ( ( points [ 0 ] , points [ 1 ] , points [ 2 ] ) , axis = 1 ) Y = Y / 400. connect = read_connections ( os . path . join ( directory , 'connections.txt' ) , point_names ) return Y , connect
Load in a data set of marker points from the Ohio State University C3D motion capture files (http://accad.osu.edu/research/mocap/mocap_data.htm).