integration of the data peeling algorithm

[leslieDLcy]

To integrate the data peeling algorithm for the calibration feature.

[leslieDLcy]

References

1. Please find below the instructions_on_fork.pdf for doing pull request of this addition.

2. an existing repo for data peeling

3. Docstrings are recommended such that users can follow the usage better. Generally, the Google style docstring is used throughout the package. But I have utilised "myst" to enrich the docstring, see for a template of how docstring will be rendered. Please find the source code of that function on Github repo to get the template.

awaiting action:

• integration of the data peeling algorithm;

[leslieDLcy]

@marcodeangelis just a gentle reminder that we are hoping to finish the calibration branch before the end of October. FYI, Dawid has integrated the epistemic filter and Roberto has integrated the KNN approach already.

After the data peeling algorithm is finished, I am hoping to have an example demonstration of it on the documentation webpage just like other example demos already in place. In fact, the readme example in the data peeling repo totally suffices.

[leslieDLcy]

@marcodeangelis FYI, a few updates:

1. new example notebooks added ==>
   https://pyuncertainnumber.readthedocs.io/en/latest/examples/calibration/Data_peeling_demo.html

2. Associate API reference ==>
   https://pyuncertainnumber.readthedocs.io/en/latest/autoapi/pyuncertainnumber/calibration/data_peeling/index.html

Let me know what you make of it. Any suggestions/comments/criticism is appreciated!