More detailed explanation on how to set up ``pyenv`` on ``Linux`` and…

[HarmonicReflux]

… Windows.

What remains a TODO is a more detailed refinement of the documentation in terms of separating the way that exist to install MUSE. It should be made explicitly clear to settle on either of the following options.They are:

i) standalone-muse ii) pipx-based installation iii) virtual-env-based either via

• conda or -pyenv in combination withvenv iv) developers (ideally via a virtual-env based setup as explained in iii)

Description

Clearer documentation to for setting up pyenv on Linux and Windows.

Fixes #357

Type of change

Please add a line in the relevant section of CHANGELOG.md to document the change (include PR #) - note reverse order of PR #s.

• [ ] New feature (non-breaking change which adds functionality)
• [ X] Optimization (non-breaking, back-end change that speeds up the code)
• [ ] Bug fix (non-breaking change which fixes an issue)
• [ ] Breaking change (whatever its nature)

Key checklist

• [ ] All tests pass: $ python -m pytest
• [ ] The documentation builds and looks OK: $ python -m sphinx -b html docs docs/build

Further checks

• [ ] Code is commented, particularly in hard-to-understand areas
• [ ] Tests added that prove fix is effective or that feature works

[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 71.27%. Comparing base (d331f46) to head (31f548d).

Additional details and impacted files

```diff @@ Coverage Diff @@ ## develop #367 +/- ## =========================================== + Coverage 71.24% 71.27% +0.03% =========================================== Files 44 44 Lines 5870 5870 Branches 1158 1158 =========================================== + Hits 4182 4184 +2 + Misses 1366 1365 -1 + Partials 322 321 -1 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

[HarmonicReflux]

I got a notable observation regarding this draft pull-request: Earlier today, all tests, except the one on Mac-OS, Python 3.12, run successfully. As Chris recommended in today's sprint, just re-running the failed test, fixed the issue by itself. How come a failed test repairs itself, merely by re-running it?

[dalonsoa]

MUSE uses random numbers in some of the tests to populate the arrays and some of these, occasionally, result in unfeasible data. Not a great situation, but easy to spot as it is often just the run for one OS and Python version failing for no apparent reason.

[dalonsoa]

@HarmonicReflux , I'll review this once you have implemented @alexdewar suggestions, so I work on a more polished version of the docs.