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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 getWeights(self, term_i=None):
 """ Return weights for fixed effect term term_i Args: term_i: fixed effect term index Returns: weights of the spefied fixed effect term. The output will be a KxL matrix of weights will be returned, where K is F.shape[1] and L is A.shape[1] of the correspoding fixed effect term (L will be always 1 for single-trait analysis). """

        assert self.init, 'GP not initialised'
        if term_i==None:
            if self.gp.mean.n_terms==1:
                term_i = 0
            else:
                print('VarianceDecomposition: Specify fixed effect term index')
        return self.gp.mean.B[term_i]