llnl / llnl/macc

Help Identifying the Physical Meaning of Model Inputs and Outputs

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Dominant language
Python
Stars
30
Forks
10
PR merge metrics
No merged PRs in 30d

Description

I have reviewed the references that are supposed to describe the physical meaning of the model inputs and outputs/scalars, but I have not been able to identify this information clearly.

Could I get assistance identifying what the inputs physically represent and what the outputs/scalars physically represent?

Specifically, I would like to understand:

What physical quantities the input variables correspond to.
What physical quantities the output/scalar variables correspond to.
How to determine which input variable corresponds to which physical quantity.
How to determine which output/scalar variable corresponds to which physical quantity.

Any guidance on where this information is defined in the documentation, dataset, code, or associated references would be very helpful.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the existing references and documentation, then trace the input, output, and scalar variables through the dataset and Python code. Identify where each variable-to-quantity mapping is defined or missing, and document the physical meanings and how to determine each correspondence.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
documentation, machine-learning
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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