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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 lnlike(self, X):
 """ Use a softened version of the interpolant as a likelihood. """

        return -3.5*np.log(self._interpolant(X[0], X[1], grid=False))