[Neuroimaging] Nilearn 0.10.3

Bertrand Thirion bertrand.thirion at inria.fr
Wed Jan 31 16:40:18 EST 2024


Thx Rémi ! 
Bertrand 

> From: "remi gau" <remi.gau at gmail.com>
> To: "Neuroimaging analysis in Python" <neuroimaging at python.org>
> Sent: Wednesday, January 31, 2024 2:25:37 PM
> Subject: [Neuroimaging] Nilearn 0.10.3

> Hello everyone!

> We have just released Nilearn 0.10.3!

> Update from PyPi:

> pip install --upgrade nilearn New Surface API

> We are further developing our surface API [
> https://nilearn.github.io/stable/modules/experimental.html | experimental
> module ] and we are interested in getting your feedback on this. We have an
> example showcasing what can be done here: [
> https://nilearn.github.io/stable/auto_examples/08_experimental/plot_surface_image_and_maskers.html#sphx-glr-auto-examples-08-experimental-plot-surface-image-and-maskers-py
> |
> https://nilearn.github.io/stable/auto_examples/08_experimental/plot_surface_image_and_maskers.html#sphx-glr-auto-examples-08-experimental-plot-surface-image-and-maskers-py
> ] .

> Please add comments in this issue: [
> https://github.com/nilearn/nilearn/issues/4158 |
> https://github.com/nilearn/nilearn/issues/4158 ] Changes

> Support for python 3.7 has been dropped. We recommend moving to python >= 3.11.

> Note we have bumped the minimum supported versions of some of our dependencies:

>     *

> Numpy – v1.19.0
>     *

> SciPy – v1.8.0
>     *

> Scikit-learn – v1.0.0
>     *

> Nibabel – v4.0.0
>     *

> Pandas – v1.1.5
>     *

> Joblib – v1.0.0

> This is a minor release with some exciting new features:

>     *

> Allow passing arguments to [
> https://nilearn.github.io/stable/modules/generated/nilearn.glm.first_level.first_level_from_bids.html#nilearn.glm.first_level.first_level_from_bids
> |  first_level_from_bids ] to build first level models that include specific
> set of confounds by relying on the strategies from [
> https://nilearn.github.io/stable/modules/generated/nilearn.interfaces.fmriprep.load_confounds.html#nilearn.interfaces.fmriprep.load_confounds
> |  load_confounds ]
>     *

> Support passing t and F contrasts to [
> https://nilearn.github.io/stable/modules/generated/nilearn.glm.compute_contrast.html#nilearn.glm.compute_contrast
> |  compute_contrast ] that have fewer columns than the number of estimated
> parameters. Remaining columns are padded with zero
>     *

> [
> https://nilearn.github.io/stable/modules/generated/nilearn.maskers.NiftiSpheresMasker.html#nilearn.maskers.NiftiSpheresMasker
> | NiftiSpheresMasker ] now has generate_report method
>     *

> Update the CompCor strategy in [
> https://nilearn.github.io/stable/modules/generated/nilearn.interfaces.fmriprep.load_confounds.html#nilearn.interfaces.fmriprep.load_confounds
> |  load_confounds ] and [
> https://nilearn.github.io/stable/modules/generated/nilearn.interfaces.fmriprep.load_confounds_strategy.html#nilearn.interfaces.fmriprep.load_confounds_strategy
> |  load_confounds_strategy ] to support fmriprep 21.x series and above
>     *

> Combine GLM examples plot_fixed_effect and plot_fiac_analysis into a single
> example plot_two_runs_model
>     *

> Allow setting vmin in [
> https://nilearn.github.io/stable/modules/generated/nilearn.plotting.plot_glass_brain.html#nilearn.plotting.plot_glass_brain
> |  plot_glass_brain ] and [
> https://nilearn.github.io/stable/modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map
> |  plot_stat_map ]
>     *

> When plotting thresholded statistical maps with a colorbar, the threshold
> value(s) will now be displayed as tick labels on the colorbar

> You can see the full changelog of this release here: [
> https://nilearn.github.io/stable/changes/whats_new.html#id1 |
> https://nilearn.github.io/stable/changes/whats_new.html#id1 ]

> The full list of pull requests included in this version:

> [ https://github.com/nilearn/nilearn/releases/tag/0.10.3 |
> https://github.com/nilearn/nilearn/releases/tag/0.10.3 ]

> The full “diff” since last version:

> [ https://github.com/nilearn/nilearn/compare/0.10.2...0.10.3 |
> https://github.com/nilearn/nilearn/compare/0.10.2...0.10.3 ]

> Contributors

> Thanks to our 7 new contributors !!!!

>     *

> NIkhil Krish ( [ https://github.com/NIkhilgKrish | @NIkhilgKrish ] ) made their
> first contribution in [ https://github.com/nilearn/nilearn/pull/4042 |  #4042 ]
>     *

> Mia Zawally ( [ https://github.com/MIZwally | @MIZwally ] ) made their first
> contribution in [ https://github.com/nilearn/nilearn/pull/4051 |  #4051 ]
>     *

> Jordi Huguet ( [ https://github.com/jhuguetn | @jhuguetn ] ) made their first
> contribution in [ https://github.com/nilearn/nilearn/pull/4028 |  #4028 ]
>     *

> Tamer Gezici ( [ https://github.com/TamerGezici | @TamerGezici ] ) made their
> first contribution in [ https://github.com/nilearn/nilearn/pull/4122 |  #4122 ]
>     *

> Christina Roßmanith ( [ https://github.com/crossmanith | @crossmanith ] ) made
> their first contribution in [ https://github.com/nilearn/nilearn/pull/4136 |
>  #4136 ]
>     *

> Suramya Pokharel ( [ https://github.com/SuramyaP | @SuramyaP ] ) made their
> first contribution in [ https://github.com/nilearn/nilearn/pull/4159 |  #4159 ]
>     *

> Paul Reiners ( [ https://github.com/paul-reiners | @paul-reiners ] ) made their
> first contribution in [ https://github.com/nilearn/nilearn/pull/4208 |  #4208 ]
> Nilearn links

>    * Github: [ https://github.com/nilearn/nilearn |
>     https://github.com/nilearn/nilearn ]
>    * Documentation: [ https://nilearn.github.io/stable/changes/whats_new.html#id1 |
>     https://nilearn.github.io ]
>    * Pypi: [ https://pypi.org/project/nilearn/ | https://pypi.org/project/nilearn/
>     ]
>     * X: [ https://twitter.com/nilearn | https://twitter.com/nilearn ]
>     * Mastodon: [ https://fosstodon.org/@nilearn | https://fosstodon.org/@nilearn ]
>     * Discord: [ https://discord.gg/SsQABEJHkZ | https://discord.gg/SsQABEJHkZ ]
>    * Digital object identifier: [ https://zenodo.org/doi/10.5281/zenodo.8397156 |
>     https://zenodo.org/doi/10.5281/zenodo.8397156 ]
>    * Research resource identifier: [
>    https://scicrunch.org/resources/data/record/nlx_144509-1/SCR_001362/resolver?q=nilearn&l=nilearn&i=rrid:scr_001362
>     | RRID:SCR_001362 ]

> --

> Rémi Gau (on behalf of the Nilearn dev team)

> _______________________________________________
> Neuroimaging mailing list
> Neuroimaging at python.org
> https://mail.python.org/mailman/listinfo/neuroimaging
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