Fixed random_design function to pull from the dataset in the thermoelastic2d problem.

[gapaza]

Description

I modified the random_design method of the thermoelastic2d problem such that it returns a randomly sampled design in the dataset. Previously, it was just returning a randomly generated design with uniform density.

Type of change

Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)

Screenshots

Checklist:

• I have run the pre-commit checks with pre-commit run --all-files
• I have run ruff check . and ruff format
• I have run mypy .
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

Reviewer Checklist:

• The content of this PR brings value to the community. It is not too specific to a particular use case.
• The tests and checks pass (linting, formatting, type checking). For a new problem, double check the github actions workflow to ensure the problem is being tested.
• The documentation is updated.
• The code is understandable and commented. No large code blocks are left unexplained, no huge file. Can I read and understand the code easily?
• There is no merge conflict.
• The changes are not breaking the existing results (datasets, training curves, etc.). If they do, is there a good reason for it? And is the associated problem version bumped?
• For a new problem, has the dataset been generated with our slurm script so we can re-generate it if needed? (This also ensures that the problem is running on the HPC.)
• For bugfixes, it is a robust fix and not a hacky workaround.