Document typical results for different datasets/acquisition parameters
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- Dominant language
- Python
- Stars
- 7
- Forks
- 8
- PR merge metrics
- No merged PRs in 30d
Description
This stems from https://github.com/ME-ICA/tedana/pull/849 and is related to #42. Basically, I think it would be awesome if we had some idea of how many components are "typical" for the different criteria, depending on a few factors, such as (1) number of volumes, (2) temporal resolution, and (3) spatial resolution. We could then plot and share those results in the MAPCA documentation, much like how the tedana documentation includes distributions of typical ME-EPI parameters in the literature.
Contributor guide
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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 reading PR #849 and issue #42, then inspect the MAPCA documentation and available datasets or acquisition parameters. Define how component counts should be compared across volume count, temporal resolution, and spatial resolution, and document the resulting typical distributions with plots in the MAPCA documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization, documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100