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[WIP] Add surface support #106

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[WIP] Add surface support #106

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pbarbarant
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Fixes #73.

@emdupre
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emdupre commented Nov 28, 2024

Thanks for opening, @pbarbarant ! Let us know when ready for review ; I think this will hugely improve things 🚀

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pbarbarant commented Nov 29, 2024

The main difficulty lies in nilearn/nilearn#4756. After that, the new backend should be able to work seamlessly with surface data.

@pbarbarant pbarbarant added enhancement New feature or request and removed Blocked labels Dec 19, 2024
@pbarbarant pbarbarant marked this pull request as ready for review December 19, 2024 22:03
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pbarbarant commented Dec 19, 2024

Will be operational as soon as nilearn/nilearn#4974 closes.

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CI will pass as soon as nilearn's new release rolls out.

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LGTM overall.

n_pieces = 2
n_vertices_total = img.shape[0]
parcel_masker = ParcellationMasker(n_pieces=n_pieces)
fitted_parcel_masker = parcel_masker.fit(img)
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Suggested change
fitted_parcel_masker = parcel_masker.fit(img)
parcel_masker = parcel_masker.fit(img)

@Remi-Gau
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@pbarbarant

You can do an early with my branch:
pip install git+https://github.com/Remi-Gau/nilearn@fix/4974

I'd rather make sure that the release does not have another bug that this one was hiding.

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Using surface data
4 participants