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我在 Jupyter Notebook 上使用 fbprophet 版本 0.7.1 和 pystan 2.19.1.1 处理季度时间序列数据。

使用额外的回归器，这是我的代码。

    model = Prophet(daily_seasonality = False, weekly_seasonality = False)
    for regressor in extra_regressors:
        model.add_regressor(regressor)
    model.fit(df_train)

这会导致非常长的日志/输出，例如：

Initial log joint probability = -50.7823
Iteration  1. Log joint probability =    36.5594. Improved by 87.3417.
Iteration  2. Log joint probability =    47.9345. Improved by 11.3751.
Iteration  3. Log joint probability =    61.4267. Improved by 13.4922.
Iteration  4. Log joint probability =    70.6681. Improved by 9.24134.
Iteration  5. Log joint probability =    73.2246. Improved by 2.55655.
Iteration  6. Log joint probability =     73.247. Improved by 0.0223382.
Iteration  7. Log joint probability =    73.2556. Improved by 0.00860014.
Iteration  8. Log joint probability =    73.2729. Improved by 0.0173013.
Iteration  9. Log joint probability =    73.3195. Improved by 0.0466379.
Iteration 10. Log joint probability =     73.506. Improved by 0.186518.
Iteration 11. Log joint probability =    73.5193. Improved by 0.0132468.
Iteration 12. Log joint probability =    73.7225. Improved by 0.203195.
Iteration 13. Log joint probability =    73.7487. Improved by 0.0262419.
Iteration 14. Log joint probability =    73.7833. Improved by 0.0345711.
Iteration 15. Log joint probability =    73.7998. Improved by 0.0165609.
Iteration 16. Log joint probability =    73.8655. Improved by 0.0656696.
Iteration 17. Log joint probability =    73.9223. Improved by 0.0567906.
Iteration 18. Log joint probability =    74.0284. Improved by 0.10612.
Iteration 19. Log joint probability =    74.0554. Improved by 0.0269437.
Iteration 20. Log joint probability =    74.0728. Improved by 0.0174187.

如何禁用这些日志？

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