Add optimization test with FD derivatives

[ewu63]

Purpose

Addresses part of #256.

Expected time until merged

A few days.

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

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

❌ Patch coverage is 0% with 78 lines in your changes missing coverage. Please review.
✅ Project coverage is 54.22%. Comparing base (20cfa02) to head (55b30c0).

Files with missing lines	Patch %	Lines
tests/test_optProb.py	0.00%	78 Missing ⚠️

❌ Your patch check has failed because the patch coverage (0.00%) is below the target coverage (50.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files

@@             Coverage Diff             @@
##             main     #487       +/-   ##
===========================================
- Coverage   82.99%   54.22%   -28.78%     
===========================================
  Files           1        1               
  Lines         147      225       +78     
===========================================
  Hits          122      122               
- Misses         25      103       +78     

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[marcomangano]

Which one should be merged first between this PR and #486 ? Both add the same two new files, does it make sense attach them to one PR over the other?

[ewu63]

This is on top of #486, let's wait for that one first.

[A-CGray]

Same overall comment as #486, can you add docstrings for new tests explaining what they are testing?

Also, is there a preferred order in which we should merge this and #486 ?

[A-CGray]

The docstring says that sensStep is the step size, and should be a float. So we need to either

1. Update the docstring
2. Change the implementation so that we take in a float and do self.sensStep = 1j * sensStep when using complex-step

Option 2 would be my slight preference.

[A-CGray]

Also, if we keep the implementation as is and update the docstring, shouldn't we also check that sensStep is purely imaginary (i.e np.real(self.sensStep) == 0?)