auto.py 文件源码

def _fit_arima(x, xreg, order, seasonal_order, start_params, trend,
               method, transparams, solver, maxiter, disp, callback,
               fit_params, suppress_warnings, trace, error_action,
               out_of_sample_size, scoring, scoring_args):
    start = time.time()
    try:
        fit = ARIMA(order=order, seasonal_order=seasonal_order,
                    start_params=start_params, trend=trend, method=method,
                    transparams=transparams, solver=solver, maxiter=maxiter,
                    disp=disp, callback=callback,
                    suppress_warnings=suppress_warnings,
                    out_of_sample_size=out_of_sample_size, scoring=scoring,
                    scoring_args=scoring_args)\
            .fit(x, exogenous=xreg, **fit_params)

    # for non-stationarity errors or singular matrices, return None
    except (LinAlgError, ValueError) as v:
        if error_action == 'warn':
            warnings.warn(_fmt_warning_str(order, seasonal_order))
        elif error_action == 'raise':
            # todo: can we do something more informative in case
            # the error is not on the pyramid side?
            raise v
        # if it's 'ignore' or 'warn', we just return None
        fit = None

    # do trace
    if trace:
        print('Fit ARIMA: %s; AIC=%.3f, BIC=%.3f, Fit time=%.3f seconds'
              % (_fmt_order_info(order, seasonal_order),
                 fit.aic() if fit is not None else np.nan,
                 fit.bic() if fit is not None else np.nan,
                 time.time() - start if fit is not None else np.nan))

    return fit