Updating minimum dependency requirements

[marcomangano]

Purpose

Issues like #387 show that the current minimum dependency versions are out of date - even considering our own stencil of supported dependencies. I updated the minimum numpy and scipy versions to our stable set of dependencies.

However, I think we should also update the mdolab-baseclasses version and, more importantly, the minimum python version. The code itself is not changing but this would create issues for the users who are still relying on older python environments.

@nwu63 suggests to adopt the NEP29 (or the more recent SPEC 0 policy) to avoid this issue, but I think at that point we should extend this to the whole organization packages. I want to hear @eirikurj take as well as he has been working on a way to map these dependencies over time.

Expected time until merged

1 day if we are ok with only updating numpy and scipy

Type of change

• [ ] Bugfix (non-breaking change which fixes an issue)
• [ ] New feature (non-breaking change which adds functionality)
• [x] 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