Issue/adjuster

[peterdudfield]

Pull Request

Description

• add adjuster model to run after man ml model
• main sql query is in adjuster.py - this could be moved to the datamodel, but for now perhaps its ok
• added tests

Wind results currently do look slightly weird though

#116

How Has This Been Tested?

• CI tests

• ran app locally, and results looks reasonable

• add units tests

• Yes

Checklist:

• My code follows OCF's coding style guidelines
• I have performed a self-review of my own code
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• I have checked my code and corrected any misspellings

[Sukh-P]

Would it be easier to test/ have stronger tests if these weren't random values? Thinking then some of the != asserts in tests below could be stronger = asserts?

[peterdudfield]

your right, they would be better. Trying to work out if to do it in this PR, or put it as a good first issue. The generation values are currently random too, so would need to change them too

[peterdudfield]

#119

[Sukh-P]

This is currently applied to all forecast horizons, is that okay or do we want to add some logic to restrict this to be applied to just day ahead horizons?

[peterdudfield]

Yea, currently not. I was thinking, perhaps to deploy it and see the behaviour on this.
You would hope our ME on the smaller forecast horizons is smaller due to live data, satellite e.t.c, (which i saw breifly when looking at me), so this extra bit of logic might not be necessary.