Fix: Improve TimeSeries.__getitem__ frequency inference

[DavidKleindienst]

Fixes #2089 .

Summary

Currently when indexing a TimeSeries, the frequency of the new TimeSeries is inferred from dates of the new TimeSeries.
However, we often have information to do a more correct inference, in particular in the following cases:

• The __getitem__ argument is a pd.DatetimeIndex with a set .freq attribute
• We index with a slice

This PR contains the following improvements to frequency inference in the TimeSeries.__getitem__ method:

• When a pd.DatetimeIndex with a set .freq attribute is used as __getitem__ argument, we use this attribute as the new TimeSeries frequency
• When a slice without step parameter is used as __getitem__ argument, the original TimeSeries frequency is used
• When a slice with step parameter is used as __getitem__ argument, the new frequency is derived by multiplying step with the original TimeSeries frequency
• A unittest for frequency inference is added

This means that inferring the frequency from the dates of the new TimeSeries will only be used either when a pd.DatetimeIndex without .freq attribute is used as __getitem__ argument or when indexing by a single int or pd.Timestamp value.

RangeIndexed TimeSeries are not affected by this PR.

Other Information

[codecov-commenter]

Codecov Report

Attention: 5 lines in your changes are missing coverage. Please review.

Comparison is base (de4afd1) 93.91% compared to head (d8b5eae) 93.88%.

Files	Patch %	Lines
darts/timeseries.py	77.27%	5 Missing ⚠️

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Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2152      +/-   ##
==========================================
- Coverage   93.91%   93.88%   -0.04%     
==========================================
  Files         135      135              
  Lines       13321    13335      +14     
==========================================
+ Hits        12511    12520       +9     
- Misses        810      815       +5     

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[dennisbader]

Thanks for this @DavidKleindienst , looks great 🚀

I made some minor adaptions so the frequency inference applies identically to integer indexed TimeSeries.

[dennisbader]

@DavidKleindienst, you can ignore the failing unit tests for now, it is a problem with one of the dataset sources that they're fixing now.