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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 rowsum_stdev(x, beta):
 r"""Compute row sum standard deviation. Compute for approximation x, the std dev of the row sums s(x) = ( 1/n \sum_k (x_k beta_k - betabar)^2 )^(1/2) with betabar = 1/n dot(beta,x) Parameters x : array beta : array Returns ------- s(x)/betabar : float Notes ----- equation (7) in Livne/Golub """

    n = x.size
    betabar = (1.0/n) * np.dot(x, beta)
    stdev = np.sqrt((1.0/n) *
                    np.sum(np.power(np.multiply(x, beta) - betabar, 2)))
    return stdev/betabar