Add Egor optimizer wrapper

[relf]

Purpose

This PR integrates the surrogate-based optimizer Egor from the EGObox library.

Egor uses bayesian optimization techniques well-suited to find the global optimum of an expansive-to-evaluate black-box function.
Basically, it uses a surrogate model to approximate the objective function and an infill criterion (aka acquisition function) to guide the search for the optimum.

Resolves relf/EGObox#439

Expected time until merged

a few weeks

Type of change

• Bugfix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (non-backwards-compatible fix or feature)
• Code style update (formatting, renaming)
• Refactoring (no functional changes, no API changes)
• Documentation update
• Maintenance update
• Other (please describe)

Testing

Egor tests have been added to the pyOptSparse test suite.

Checklist

• I have run ruff check and ruff format to make sure the Python code adheres to PEP-8 and is consistently formatted
• I have formatted the Fortran code with fprettify or C/C++ code with clang-format as applicable
• I have run unit and regression tests which pass locally with my changes
• I have added new tests that prove my fix is effective or that my feature works
• I have added necessary documentation

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.99%. Comparing base (20cfa02) to head (aea288e).

Additional details and impacted files

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##             main     #485   +/-   ##
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  Coverage   82.99%   82.99%           
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  Files           1        1           
  Lines         147      147           
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  Hits          122      122           
  Misses         25       25           

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[ewu63]

First things first, let's add egobox to the testing deps of pyproject.toml, so that the test you added may run instead of being skipped for optimizer not available.

[ewu63]

This all looks OK with me, but I will wait for further reviews from @marcomangano and maybe @A-CGray

[marcomangano]

Thanks a lot for this implementation @relf ! Exciting to have Egor available from pyOptSparse.

See my comments below, mostly formatting/comment request except for the options checks.
Would you also mind to add more docstrings to the class/functions in pyEgor.py? You can probably copy-paste most of them from other optimizer wrappers.

[relf]

@marcomangano Thank you for the review! I've addressed your comments.

[marcomangano]

Thanks a lot for the quick fixes! LGTM