[Epic 2]: Data assimilation in Wofost72_WLP_CWB using pytorch
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Domain
- machine-learning
Research direction
Read pcse/models.py at Wofost72_WLP_CWB and pcse/conf/Wofost72_WLP_CWB.conf first, confirming the SOIL and CROP configuration. Then clarify the variational data-assimilation scope for use cases 1 and 2 and define validation criteria, since the issue does not specify a concrete code change or done condition.
Written by the indexing model from the issue text.
Description
For use cases 1 and 2, we use the model Wofost72_WLP_CWB and explore the Variational DA. The config of Wofost72_WLP_CWB consists:
SOIL = WaterbalanceFD
CROP = Wofost72
this is related to use case 1.
- Dominant language
- Python
- Stars
- 25
- Forks
- 7
- Avg merge
- 14d 3h
- Merged PRs (30d)
- 1
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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