Adding markers to the pytest test configuration and marking tests that are precision sensitive or slow.
This is an incremental step to improve unit test speeds by separating unit tests (which users can run all of the time) from integration tests which can take very long. Ideally we can refactor the tests to have integration tests run nightly on github actions.
Also marking tests that depend on numerical precision as precision sensitive. By identifying these now, we can be sure the code isn't broken if scipy or numpy decides to make small modifications to their numerical precision.
Adding markers to the pytest test configuration and marking tests that are precision sensitive or slow.
This is an incremental step to improve unit test speeds by separating unit tests (which users can run all of the time) from integration tests which can take very long. Ideally we can refactor the tests to have integration tests run nightly on github actions.
Also marking tests that depend on numerical precision as precision sensitive. By identifying these now, we can be sure the code isn't broken if scipy or numpy decides to make small modifications to their numerical precision.