[refactor] Extract plot utils into dedicated file

[LeonieFreisinger]

Problem referring #965
Helper functions in plotting related files are defined in actual plotting files. This enlarges the file content.

Solution
Relocate plotting-related helper functions to a separate file utils_plot.py

Key Changes:

• Check the plotting-related .py files for helper functions and move them to utils_plot.py
• Check utils.py for plotting-related helper functions and move them to utils_plot.py

Functions that were not relocated:
plot_trend_change(), plot_trend(), plot_daily(), plot_weekly(), plot_yearly(), plot_custom_season(), plot_lagged_weights(), plot_scalar_weights(), plot_forecast_component(), plot_multiforecast_component()

[codecov-commenter]

Codecov Report

Merging #1000 (c6e1bed) into main (e592381) will increase coverage by 0.00%.
The diff coverage is 90.00%.

@@           Coverage Diff           @@
##             main    #1000   +/-   ##
=======================================
  Coverage   89.88%   89.89%           
=======================================
  Files          18       19    +1     
  Lines        4655     4659    +4     
=======================================
+ Hits         4184     4188    +4     
  Misses        471      471           

Impacted Files	Coverage Δ
neuralprophet/utils.py	81.08% <ø> (-0.34%)	⬇️
neuralprophet/plot_utils.py	89.77% <89.77%> (ø)
neuralprophet/forecaster.py	88.01% <100.00%> (ø)
neuralprophet/plot_forecast_matplotlib.py	81.66% <100.00%> (ø)
neuralprophet/plot_forecast_plotly.py	86.82% <100.00%> (-0.77%)	⬇️
neuralprophet/plot_model_parameters_matplotlib.py	90.50% <100.00%> (-0.24%)	⬇️
neuralprophet/plot_model_parameters_plotly.py	94.86% <100.00%> (ø)

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

[LeonieFreisinger]

@noxan would be amazing if you can review this PR. Should be a fast one.
P.S: I did not relocate the functions that call a plot command, since they in my eyes are not a helper function.

Thanks a lot!

[noxan]

LGTM - one note on this massive function to build the component plotting configuration (it is too massive) for a follow up and just wondering: would plot_utils.py be a better name? Otherwise good to go from my side.

[noxan]

At some point we should definitely refactor this method... also in parts related to #1004

[noxan]

@LeonieFreisinger let me know what you think and otherwise I'd merge it directly (possibly create follow up issues).

[noxan]

PS: Congrats on securing pull request #1000 - 🎉 💯0

[LeonieFreisinger]

LGTM - one note on this massive function to build the component plotting configuration (it is too massive) for a follow up and just wondering: would plot_utils.py be a better name? Otherwise good to go from my side.

@noxan thanks for the fast review. Initially planned to name the module plot_utils.py. However, I aligned it with utils.py and utils_torch.py. I agree with changing it. Should we rename the utils_torch.py as well to torch_utils.py?
Then I open a new issue for it to keep it separate. As well as for the get_valid_configuration() and link it to #1004.

[noxan]

Thanks @LeonieFreisinger - good point about having consistent naming for our util* files, let's take the discussion to the issue you created :)

[github-actions]

af344bf

Model Benchmark

Benchmark	Metric	main	current	diff
YosemiteTemps	MAE_val	1.72949	1.72948	-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	93.4	153.57	64.42%	⚠️
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	11.7	18.97	62.14%	⚠️
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	7.18	59.2%	⚠️

Model training plots

Model Training

PeytonManning

YosemiteTemps

AirPassengers

[ourownstory]

Congratulations @LeonieFreisinger you merged our #1000 th Pull Request! You won a free tour around Stanford campus! Please let me know your availability.

[LeonieFreisinger]

Congratulations @LeonieFreisinger you merged our #1000 th Pull Request! You won a free tour around Stanford campus! Please let me know your availability.

definitely feel honored of saving PR1000. hahhaha @ourownstory almost as good as winning the lottery.