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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 correlation_model(prediction, fm):
 """ wraps numpy.corrcoef functionality for model evaluation input: prediction: 2D Matrix the model salience map fm: fixmat Used to compute a FDM to which the prediction is compared. """

    (_, r_x) = calc_resize_factor(prediction, fm.image_size)
    fdm = compute_fdm(fm, scale_factor = r_x)
    return np.corrcoef(fdm.flatten(), prediction.flatten())[0,1]