Nilearn 0.10.2 is out

Hello everyone!

We have just released Nilearn 0.10.2!

Update from PyPi:

pip install --upgrade nilearn

This is a minor release with some exciting new features:

  • Volume plotting functions like plot_img now have an optional radiological parameter, defaulting to False. If True, this will invert the x-axis and L and R annotations to confirm to radiological conventional view.
  • The decoder class was updated:
    • to use the more efficient LogisticRegressionCV
    • to support LassoCV as a new estimator option
  • Add vmin and symmetric_cbar arguments to plot_img_on_surf
  • Improved contrasts allowing fixed effects on F contrasts
  • There is a new experimental surface API to facilitate working with surface data in downstream surface-based analyses. We provide this API as a nilearn.experimental.surface module as it is still incomplete and subject to change without a deprecation cycle.
  • We now have a DOI on Zenodo for all Nilearn versions: nilearn | Zenodo

You can see the full changelog of this release here: What’s new - Nilearn

The full list of pull requests included in this version: Release 0.10.2 · nilearn/nilearn · GitHub

The full “diff” since last version: Comparing 0.10.1...0.10.2 · nilearn/nilearn · GitHub

11 new contributors !!!

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