Feature/pattern change detection

[A-Aherbil]

Implementation of the three adaptive change point detection algorithms with a real-time visualization dashboard.

Algorithms: ADWIN, AV-CUSUM, STPH

[A-Tarraf]

There are several points that need to be fixed before merging.
Several things mentioned under https://github.com/tuda-parallel/FTIO/blob/feature/pattern_change_detection/docs/students_contribute.md are missing. This includes:

• Documentation and license for new files: https://github.com/tuda-parallel/FTIO/blob/feature/pattern_change_detection/docs/students_contribute.md#-module-documentation-and-licensing
• Adding test cases: https://github.com/tuda-parallel/FTIO/blob/feature/pattern_change_detection/docs/students_contribute.md#-module-documentation-and-licensing
• Adding a documentation: https://github.com/tuda-parallel/FTIO/blob/feature/pattern_change_detection/docs/students_contribute.md#-module-documentation-and-licensing

[A-Tarraf]

some open ToDos

[A-Tarraf]

It looks much better! Thank you for your changes. Could you just maybe:

1. Extend and test the documentation? I tried the call predictor X.jsonl -e no -f 100 -w frequency hits --online_adaptation adwin but it did not work. I think the problem was frequency_hits.
2. Include also a documentation on how the GUI works and how it automatically connects. I was also wondering how I can display multiple predictions at once and what the bandwidth over time of the original signal looks like. The old plots from FTIO always include both the predictions and the original signal.
3. Maybe only enable to forward data to the gui if an explicit argument (--gui) is passed

[A-Tarraf]

only small function documentation are missing now

[A-Tarraf]

great work, well done!

[A-Tarraf]

Perfect, thank you!