Match complex version convergence tolerances to real version

Purpose

In some cases, the primal (real) version of XFOIL converges fine, but then the gradient evaluation with the complex version does not converge. Optimizers very much dislike when the primal succeeds and the gradient fails. Most just crash.

One of the reasons I found for this happening is that the tolerances of the real and complex XFOIL versions do not match. This PR fixes this problem. This does not solve all of the situations where the primal succeeds and gradient fails, but it helps many of them. Furthermore, converging the complex evaluations more tightly (by four orders more than before) dramatically improves optimizer convergence near the optimum design, presumably because of more accurate gradients.

Expected time until merged

ASAP as possible

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
[x] Maintenance update
[ ] Other (please describe)

Testing

Checklist

[ ] I have run flake8 and black 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

mdolab / CMPLXFOIL