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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 F_to_K(self, F, method='doubling'):
 """ Compute agent 2's best cost-minimizing response K, given F. Parameters F : array_like(float, ndim=2) A k x n array method : str, optional(default='doubling') Solution method used in solving the associated Riccati equation, str in {'doubling', 'qz'}. Returns ------- K : array_like(float, ndim=2) Agent's best cost minimizing response for a given F P : array_like(float, ndim=2) The value function for a given F """

        Q2 = self.beta * self.theta
        R2 = - self.R - dot(F.T, dot(self.Q, F))
        A2 = self.A - dot(self.B, F)
        B2 = self.C
        lq = LQ(Q2, R2, A2, B2, beta=self.beta)
        neg_P, neg_K, d = lq.stationary_values(method=method)

        return -neg_K, -neg_P