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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 extend_partial(self, times, obs_times, obs_losses, config=None):
 """ extends a partially observed curve Parameters: times: numpy array times where to predict the loss obs_times: numpy array times where the curve has already been observed obs_losses: numpy array corresponding observed losses config: numpy array numerical reperesentation of the config; None if no config information is available Returns: -------- mean and variance prediction at input times """

        return self.predict_unseen(times, config)