[Epic 3]: Calibration of Wofost81_NWLP_CWB_CNB using big data
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Epic 3
- Dominant language
- Python
- Stars
- 25
- Forks
- 6
- Avg merge
- 2d 23h
- Merged PRs (30d)
- 1
Description
This is related to new use case, calibrating wofost81 using big data. The goal is to show diffwofost can be used in this use case, both form differentiabilty and efficiency perspectives.
After #89, we start making wofost81 differentiable and after #90 together with other implementations, we show a prototype.
This is related to use case 3.
I will add backlogs .... [🎶 🎶 ]
Contributor 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.
Research direction
Start by reviewing the work described in issues #89 and #90, then read the use case 3 context. Clarify the missing backlog items and define what demonstrating WOFOST81 calibration with big data means for both differentiability and efficiency before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100