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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 distance_correlation_af_inv_sqr(x, y):
 """ Square of the affinely invariant distance correlation. Computes the estimator for the square of the affinely invariant distance correlation between two random vectors. .. warning:: The return value of this function is undefined when the covariance matrix of :math:`x` or :math:`y` is singular. Parameters x: array_like First random vector. The columns correspond with the individual random variables while the rows are individual instances of the random vector. y: array_like Second random vector. The columns correspond with the individual random variables while the rows are individual instances of the random vector. Returns ------- numpy scalar Value of the estimator of the squared affinely invariant distance correlation. See Also -------- distance_correlation u_distance_correlation Examples -------- 1.0 1.0 """

    x = _af_inv_scaled(x)
    y = _af_inv_scaled(y)

    correlation = distance_correlation_sqr(x, y)
    return 0 if np.isnan(correlation) else correlation