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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 lins_ccc(y_true, y_pred):
 """ Lin's Concordance Correlation Coefficient. See https://en.wikipedia.org/wiki/Concordance_correlation_coefficient Parameters y_true: ndarray vector of true targets y_pred: ndarray vector of predicted targets Returns ------- float: 1.0 for a perfect match between :code:`y_true` and :code:`y_pred`, less otherwise Example ------- True True """


    t = y_true.mean()
    p = y_pred.mean()
    St = y_true.var()
    Sp = y_pred.var()
    Spt = np.mean((y_true - t) * (y_pred - p))

    return 2 * Spt / (St + Sp + (t - p)**2)