[refactor] Lighten forecaster.py

[LeonieFreisinger]

Linked to #1133

🔬 Background

Currently, the forecaster.py is very large and contains many functions. We would like to lighten the forecaster.py and move selected functions to other files

🔮 Key changes

• Introduce 3 new files processing.py, splitting.py, transforming.py
• Move functions from forecaster to one of the new files
• adapt test_unit.py and test_integration.py, because they call the moved functions

🔮 Future Recommendations

In a next step, the input varaibles of the moved functions should be adapted. Currently, the full model is passed as an input argument. However, for most functions the actual needed input argument can be further narrowed down.

📋 Review Checklist

• I have performed a self-review of my own code.
• (not applicable) I have commented my code, added docstrings and data types to function definitions.
• (not applicable) I have added pytests to check whether my feature / fix works.

Please make sure to follow our best practices in the Contributing guidelines.

[codecov-commenter]

Codecov Report

Merging #1255 (a8c2ea9) into main (03726d3) will increase coverage by 0.10%.
The diff coverage is 92.71%.

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@@            Coverage Diff             @@
##             main    #1255      +/-   ##
==========================================
+ Coverage   89.56%   89.66%   +0.10%     
==========================================
  Files          35       38       +3     
  Lines        4830     4955     +125     
==========================================
+ Hits         4326     4443     +117     
- Misses        504      512       +8     

Impacted Files	Coverage Δ
neuralprophet/data/splitting.py	90.42% <90.42%> (ø)
neuralprophet/data/processing.py	91.98% <91.98%> (ø)
neuralprophet/data/transforming.py	100.00% <100.00%> (ø)
neuralprophet/forecaster.py	87.06% <100.00%> (-1.43%)	⬇️

... and 9 files with indirect coverage changes

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[noxan]

LGTM :)

Have you considered using the regular verb form e.g. split over the progressive splitting for the filenames? Would make it shorter, no hard feelings, just a personal preference to have it more compact.

[LeonieFreisinger]

Nice suggestion, will adapt that.
Thanks for your review!

[github-actions]

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	MAE	9.82902	9.82902	0.0%	✅
AirPassengers	RMSE	11.7005	11.7005	0.0%	✅
AirPassengers	Loss	0.00056	0.00056	0.0%	✅
AirPassengers	time	7.48551	7.42	-0.88%	✅
YosemiteTemps	MAE_val	1.71298	1.71298	0.0%	✅
YosemiteTemps	RMSE_val	2.26069	2.26069	0.0%	✅
YosemiteTemps	Loss_val	0.00095	0.00095	0.0%	✅
YosemiteTemps	MAE	1.45187	1.45187	0.0%	✅
YosemiteTemps	RMSE	2.16721	2.16721	0.0%	✅
YosemiteTemps	Loss	0.00066	0.00066	0.0%	✅
YosemiteTemps	time	170.072	166.76	-1.95%	✅
PeytonManning	MAE_val	0.58159	0.58159	0.0%	✅
PeytonManning	RMSE_val	0.72216	0.72216	0.0%	✅
PeytonManning	Loss_val	0.01239	0.01239	0.0%	✅
PeytonManning	MAE	0.41671	0.41671	0.0%	✅
PeytonManning	RMSE	0.55961	0.55961	0.0%	✅
PeytonManning	Loss	0.00612	0.00612	0.0%	✅
PeytonManning	time	21.8895	20.58	-5.98%	🎉

Model training plots

Model Training

PeytonManning

YosemiteTemps

AirPassengers