Support for holidays of multiple countries

[leoniewgnr]

👨‍🔬 Status quo
Currently it is only possible to consider holidays of one country. If another country is added, the previous one is overwritten. Addresses issue #763

👨‍🎨 Key changes
It is possible now to add a list of countries, whose holidays should be considered. For example m.add_country_holidays(country_name = ["US", "Germany"]) will consider holidays of the US and Germany. For redundant holidays (here: 'Christmas Day' and 'Erster Weihnachtstag') the name of the last mentioned country will be kept (here: 'Erster Weihnachtstag')

🕵️‍♂️ Review Checklist

• I have performed a self-review of my own code.
• I have commented my code, added Docstrings and data types to function definitions.
• My code follows the style guidelines described under CONTRIBUTING.md.
• I have added pytests to check whether my feature / fix works
• All gh actions pass or the failure is not related to my code.

[codecov-commenter]

Codecov Report

Merging #1001 (88764b4) into main (dcad17c) will increase coverage by 0.01%.
The diff coverage is 80.95%.

@@            Coverage Diff             @@
##             main    #1001      +/-   ##
==========================================
+ Coverage   90.26%   90.28%   +0.01%     
==========================================
  Files          21       21              
  Lines        4736     4744       +8     
==========================================
+ Hits         4275     4283       +8     
  Misses        461      461              

Impacted Files	Coverage Δ
neuralprophet/forecaster.py	88.44% <ø> (ø)
neuralprophet/time_dataset.py	94.54% <80.00%> (+0.10%)	⬆️
neuralprophet/utils.py	82.73% <81.81%> (+0.15%)	⬆️

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[noxan]

Great work, looks very good to me overall. I've added a few minor suggestions and there are a few flake8 warnings which you should look at (one of them is actually critical as the variable name is not defined). Nothing big, you're on a good track, keep it up 👍

[noxan]

LGTM - I've added two minor suggestions which I'd add before merging and one note about duplicate code which we could extract to a helper function

[github-actions]

20c1835

Model Benchmark

Benchmark	Metric	main	current	diff
AirPassengers	MAE_val	15.2698	15.2698	0.0%	✅
AirPassengers	RMSE_val	19.4209	19.4209	0.0%	✅
AirPassengers	Loss_val	0.00195	0.00195	0.0%	✅
AirPassengers	RegLoss_val	0	0	0.0%	✅
AirPassengers	epoch	89	89	0.0%	✅
AirPassengers	MAE	9.82902	9.82902	0.0%	✅
AirPassengers	RMSE	11.7005	11.7005	0.0%	✅
AirPassengers	Loss	0.00056	0.00056	0.0%	✅
AirPassengers	RegLoss	0	0	0.0%	✅
AirPassengers	time	4.51	4.49	-0.44%	✅
AirPassengers	system_performance	0.8028	0.7978	-0.62%	✅
AirPassengers	system_std	0.00306	0.00248	-18.95%	✅
PeytonManning	MAE_val	0.64636	0.64636	0.0%	✅
PeytonManning	RMSE_val	0.79276	0.79276	0.0%	✅
PeytonManning	Loss_val	0.01494	0.01494	0.0%	✅
PeytonManning	RegLoss_val	0	0	0.0%	✅
PeytonManning	epoch	37	37	0.0%	✅
PeytonManning	MAE	0.42701	0.42701	0.0%	✅
PeytonManning	RMSE	0.57032	0.57032	0.0%	✅
PeytonManning	Loss	0.00635	0.00635	0.0%	✅
PeytonManning	RegLoss	0	0	0.0%	✅
PeytonManning	time	11.73	11.74	0.09%	✅
PeytonManning	system_performance	0.792	0.7874	-0.58%	✅
PeytonManning	system_std	0.00063	0.00049	-22.22%	✅
YosemiteTemps	MAE_val	1.72949	1.72949	0.0%	✅
YosemiteTemps	RMSE_val	2.27386	2.27386	0.0%	✅
YosemiteTemps	Loss_val	0.00096	0.00096	0.0%	✅
YosemiteTemps	RegLoss_val	0	0	0.0%	✅
YosemiteTemps	epoch	84	84	0.0%	✅
YosemiteTemps	MAE	1.45189	1.45189	0.0%	✅
YosemiteTemps	RMSE	2.16631	2.16631	0.0%	✅
YosemiteTemps	Loss	0.00066	0.00066	0.0%	✅
YosemiteTemps	RegLoss	0	0	0.0%	✅
YosemiteTemps	time	92.45	93.12	0.72%	✅
YosemiteTemps	system_performance	0.8114	0.7964	-1.85%	✅
YosemiteTemps	system_std	0.00224	0.00196	-12.5%	✅

Model training plots

Model Training

PeytonManning

YosemiteTemps

AirPassengers