def fit()

in python/prophet/models.py [0:0]

• 27 lines of code
• 8 McCabe index (conditional complexity)

    def fit(self, stan_init, stan_data, **kwargs):
        (stan_init, stan_data) = self.prepare_data(stan_init, stan_data)

        if 'inits' not in kwargs and 'init' in kwargs:
            kwargs['inits'] = self.prepare_data(kwargs['init'], stan_data)[0]

        args = dict(
            data=stan_data,
            inits=stan_init,
            algorithm='Newton' if stan_data['T'] < 100 else 'LBFGS',
            iter=int(1e4),
        )
        args.update(kwargs)

        try:
            self.stan_fit = self.model.optimize(**args)
        except RuntimeError as e:
            # Fall back on Newton
            if self.newton_fallback and args['algorithm'] != 'Newton':
                logger.warning(
                    'Optimization terminated abnormally. Falling back to Newton.'
                )
                args['algorithm'] = 'Newton'
                self.stan_fit = self.model.optimize(**args)
            else:
                raise e

        params = self.stan_to_dict_numpy(
            self.stan_fit.column_names, self.stan_fit.optimized_params_np)
        for par in params:
            params[par] = params[par].reshape((1, -1))
        return params