(v3.3.1) - Sinergym observation normalization improved

[AlejandroCN7]

Description

The normalization wrapper in Sinergym, based on the default Gymnasium wrapper, has encountered a functionality issue.

When a model is trained using this normalization, the calibration is lost post-process. Consequently, when the model is loaded for evaluation, the absence of normalization calibration results in poor agent performance.

Motivation and Context

This PR records the averages and deviations updated during this process, and offer the ability to load them either in the constructor or via a method to use it in evaluation tasks. These evaluations are configurable, whose normalization calibrations can be not updated during that process.

• [x] I have raised an issue to propose this change (required for new features and bug fixes)

Why is this change required? What problem does it solve? Please, reference issue or issues opened previously.

Fixes #407

Types of changes

• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to change)
• [x] Documentation (update in the documentation)
• [x] Improvement (of an existing feature)
• [ ] Others

Checklist:

• [x] I've read the CONTRIBUTION guide (required)
• [x] My change requires a change to the documentation.
• [x] I have updated the tests.
• [x] I have updated the documentation accordingly.
• [ ] I have reformatted the code using autopep8 second level aggressive.
• [ ] I have reformatted the code using isort.
• [ ] I have ensured cd docs && make spelling && make html pass (required if documentation has been updated.)
• [ ] I have ensured pytest tests/ -vv pass. (required).
• [ ] I have ensured pytype -d import-error sinergym/ pass. (required)

Changelog:

• Updated NormalizeObservation wrapper with this new functionality.
• Added documentation and API reference explaining the new features.
• New tests for this wrapper have been designed and developed.
• Updated training and loading DRL models scripts to use the new features.
• Added warning in notebook example.

Extra:

• Added warning in 2ZoneDatacenter advising of issue #395.