neurostuff / neurostuff/PyMARE
Use masked arrays in computations
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 58
- Forks
- 16
- Avg merge
- 5h 7m
- Merged PRs (30d)
- 4
Description
Related to #9, we should add support for masked arrays wherever possible—this will allow vectorized estimation even when the studies in parallel datasets differ (i.e., users pass in NaN values in different studies for different datasets).
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 reading related issue #9 and tracing the computation paths involved in parallel datasets and NaN values. The issue does not name files or tests; completion would require masked-array support wherever applicable and vectorized estimation when studies differ across datasets.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100