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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 vclose(L, V):
 """ gets the closest vector """

    lam, X = 0, []
    for k in range(3):
        lam = lam + V[k] * L[k]
    beta = np.sqrt(1. - lam**2)
    for k in range(3):
        X.append((old_div((V[k] - lam * L[k]), beta)))
    return X