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[ENH] add minutes december 2024 #45
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| # Agenda | ||
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| ## News/TODO | ||
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| - 0.11 / Surface API out :tada: !! | ||
| - 0.11.1 should be done soon (when?) because of: | ||
| - [#4904](https://github.com/nilearn/nilearn/issues/4904): `SurfaceMasker cannot fit or transform list of 1D SurfaceImage` | ||
| - [#4922](https://github.com/nilearn/nilearn/issues/4922): `errors when loading filepaths with forward slashes` | ||
| - not caught by our tests... to be added | ||
| - release could take place next week | ||
| - [Nilearn on Bluesky](https://bsky.app/profile/nilearn.bsky.social), start posting about drop-in hours | ||
| - [Himanshu] Abstract for OHBM deadline: Tuesday, December 17, 2024 | ||
| - **report for CZI**: [ACTION][Rémi] will do it | ||
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| ## PRs | ||
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| [List of PR needing review](https://github.com/nilearn/nilearn/pulls?q=is%3Apr+is%3Aopen+label%3A%22Review+required%22) | ||
| - mostly good, just an old one remaining: | ||
| - [#4287](https://github.com/nilearn/nilearn/pull/4287) - `[DOC] Add comparison of meaning differences of GLM between different libraries` | ||
| - already good enough? | ||
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| ## Issues | ||
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| ### Other | ||
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| - [#4885](https://github.com/nilearn/nilearn/issues/4885) - `[ENH] Add function to compute framewise displacement` | ||
| - concerns preprocessing and that is out-of-scope for nilearn | ||
| - [ACTION][Bertrand] to close issue | ||
| - [#4760](https://github.com/nilearn/nilearn/issues/4760) - `use pre-commit CI to run checks and update hooks` | ||
| - [Rémi] remove autofix in CI | ||
| - [#4739](https://github.com/nilearn/nilearn/issues/4739) - `Remove line-length = 79` | ||
| - [ACTION][Rémi] to close issue | ||
| - [#4525](https://github.com/nilearn/nilearn/issues/4525) - `[ENH] Include "goodness of fit" image in GLM reports ?` | ||
| - [#4811](https://github.com/nilearn/nilearn/issues/4811) `[ENH] avoid loading whole nifti-like image data when extracting time-series within a mask` | ||
| - 2 issues | ||
| - the issue of having label maskers return non aggregated data has come before: we probably do not want to change this behavior | ||
| - probably we should have an example of doing this | ||
| - have an example on how to optimize when one has "large images" | ||
| - further optimization may require to push people towards other options (use numpy) | ||
| - need better doc / examples | ||
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| ### Surface | ||
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| - [#4879](https://github.com/nilearn/nilearn/issues/4879) - `Make some surface 'utility functions' public` | ||
| - move them under nilearn.surface but as private | ||
| - naming should be closer to nilearn.image | ||
| - and revisit later | ||
| - [#4878](https://github.com/nilearn/nilearn/issues/4878) - `[ENH] add max and min property to PolyData and SurfaceImage` | ||
| - [Himanshu] make it easy to access data | ||
| - more generally [Surface roadmap](https://github.com/nilearn/nilearn/issues/4889) | ||
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| ### 0.11.2 roadmap | ||
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| - See ['meta' issue](https://github.com/nilearn/nilearn/issues/4890) | ||
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| ## Set time next meeting | ||
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| - January Tuesday 14th at 4pm Paris time | ||
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IIRC ?