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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_mr_filters(data_shape, opt='', coarse=False):
 # pragma: no cover """Get mr_transform filters This method obtains wavelet filters by calling mr_transform Parameters data_shape : tuple 2D data shape opt : list, optional List of additonal mr_transform options coarse : bool, optional Option to keep coarse scale (default is 'False') Returns ------- np.ndarray 3D array of wavelet filters """


    # Adjust the shape of the input data.
    data_shape = np.array(data_shape)
    data_shape += data_shape % 2 - 1

    # Create fake data.
    fake_data = np.zeros(data_shape)
    fake_data[tuple(zip(data_shape // 2))] = 1

    # Call mr_transform.
    mr_filters = call_mr_transform(fake_data, opt=opt)

    # Return filters
    if coarse:
        return mr_filters
    else:
        return mr_filters[:-1]