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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 noncentral_t_like(x, mu, lam, nu):
 R""" Non-central Student's T log-likelihood. Describes a normal variable whose precision is gamma distributed. .. math:: f(x|\mu,\lambda,\nu) = \frac{\Gamma(\frac{\nu + 1}{2})}{\Gamma(\frac{\nu}{2})} \left(\frac{\lambda}{\pi\nu}\right)^{\frac{1}{2}} \left[1+\frac{\lambda(x-\mu)^2}{\nu}\right]^{-\frac{\nu+1}{2}} :Parameters: - `x` : Input data. - `mu` : Location parameter. - `lambda` : Scale parameter. - `nu` : Degrees of freedom. """

    mu = np.asarray(mu)
    lam = np.asarray(lam)
    nu = np.asarray(nu)
    return flib.nct(x, mu, lam, nu)