orbit/template/ktr.py [500:518]:
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        if self._seasonality:
            max_seasonality = np.round(np.max(self._seasonality)).astype(int)
            if num_of_observations < max_seasonality:
                raise ModelException(
                    "Number of observations {} is less than max seasonality {}".format(
                        num_of_observations, max_seasonality
                    )
                )
        # get some reasonable offset to regularize response to make default priors scale-insensitive
        if self._seasonality:
            max_seasonality = np.round(np.max(self._seasonality)).astype(int)
            self.response_offset = np.nanmean(response[:max_seasonality])
        else:
            self.response_offset = np.nanmean(response)

        self.is_valid_response = ~np.isnan(response)
        # [0] to convert tuple back to array
        self.which_valid_response = np.where(self.is_valid_response)[0]
        self.num_of_valid_response = len(self.which_valid_response)
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orbit/template/ktrlite.py [275:293]:
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        if self._seasonality:
            max_seasonality = np.round(np.max(self._seasonality)).astype(int)
            if num_of_observations < max_seasonality:
                raise ModelException(
                    "Number of observations {} is less than max seasonality {}".format(
                        num_of_observations, max_seasonality
                    )
                )
        # get some reasonable offset to regularize response to make default priors scale-insensitive
        if self._seasonality:
            max_seasonality = np.round(np.max(self._seasonality)).astype(int)
            self.response_offset = np.nanmean(response[:max_seasonality])
        else:
            self.response_offset = np.nanmean(response)

        self.is_valid_response = ~np.isnan(response)
        # [0] to convert tuple back to array
        self.which_valid_response = np.where(self.is_valid_response)[0]
        self.num_of_valid_response = len(self.which_valid_response)
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