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python3-nilearn-0.7.0-bp153.1.1 RPM for noarch

From OpenSuSE Leap 15.3 for noarch

Name: python3-nilearn Distribution: SUSE Linux Enterprise 15 SP3
Version: 0.7.0 Vendor: openSUSE
Release: bp153.1.1 Build date: Sat Mar 6 21:01:19 2021
Group: Development/Languages/Python Build host: cloud127
Size: 10409690 Source RPM: python-nilearn-0.7.0-bp153.1.1.src.rpm
Packager: https://bugs.opensuse.org
Url: https://github.com/nilearn/nilearn
Summary: Statistical learning tool for neuroimaging
 
Nilearn is a Python module for statistical learning on
NeuroImaging data.

Provides

Requires

License

BSD-3-Clause

Changelog

* Fri Jan 29 2021 Ben Greiner <code@bnavigator.de>
  - Skip python36 build because Tumbleweed updates to SciPy 1.6.0
    which dropped support for Python 3.6 (NEP 29)
* Fri Nov 20 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Add runtime deps: python-requests
* Mon Nov 16 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Update to 0.7.0
  - Add patch to fix aarch64 test:
    * nilearn-fix-aarch64.patch
  - Drop upstreamed patches:
    * fix-test_save_cmap.patch
    * update-numpy-warning.patch
  - Disable 'test_clean_confounds' and 'test_reorder_img_mirror '
    until we have a fix. See:
      https://github.com/nilearn/nilearn/issues/2608
      https://github.com/nilearn/nilearn/issues/2610
* Wed Oct 14 2020 Guillaume GARDET <guillaume.gardet@opensuse.org>
  - Backport patches to fix some tests:
    * update-numpy-warning.patch - https://github.com/nilearn/nilearn/pull/2530
    * fix-test_save_cmap.patch   - https://github.com/nilearn/nilearn/pull/2543
* Wed Apr 29 2020 Tomáš Chvátal <tchvatal@suse.com>
  - Use xdist to speedup the tests to take less than 30 mins
* Thu Jan 30 2020 Todd R <toddrme2178@gmail.com>
  - Update to version 0.6.1
    + ENHANCEMENTS
    * html pages use the user-provided plot title, if any, as their title
    + Fixes
    * Fetchers for developmental_fmri and localizer datasets resolve URLs correctly.
* Mon Jan 06 2020 Todd R <toddrme2178@gmail.com>
  - Update to version 0.6.0
    + HIGHLIGHTS
    * Python2 and 3.4 are no longer supported. We recommend upgrading to Python 3.6 minimum.
    * Support for Python3.5 wil be removed in the 0.7.x release.
      Users with a Python3.5 environment will be warned at their first Nilearn import.
    * joblib is now a dependency
    * Minimum supported versions of packages have been bumped up.
      > Matplotlib -- v2.0
      > Scikit-learn -- v0.19
      > Scipy -- v0.19
    + NEW
    * A new method for :class:`nilearn.input_data.NiftiMasker` instances
      for generating reports viewable in a web browser, Jupyter Notebook, or VSCode.
    * A new function :func:`nilearn.image.get_data` to replace the deprecated
      nibabel method `Nifti1Image.get_data`. Now use `nilearn.image.get_data(img)`
      rather than `img.get_data()`. This is because Nibabel is removing the
      `get_data` method. You may also consider using the Nibabel
      `Nifti1Image.get_fdata`, which returns the data cast to floating-point.
      See https://github.com/nipy/nibabel/wiki/BIAP8 .
      As a benefit, the `get_data` function works on niimg-like objects such as
      filenames (see http://nilearn.github.io/manipulating_images/input_output.html ).
    * Parcellation method ReNA: Fast agglomerative clustering based on recursive
      nearest neighbor grouping.
      Yields very fast & accurate models, without creation of giant
      clusters.
    * Plot connectome strength
      Use :func:`nilearn.plotting.plot_connectome_strength` to plot the strength of a
      connectome on a glass brain.  Strength is absolute sum of the edges at a node.
    * Optimization to image resampling
    * New brain development fMRI dataset fetcher
      :func:`nilearn.datasets.fetch_development_fmri` can be used to download
      movie-watching data in children and adults. A light-weight dataset
      implemented for teaching and usage in the examples. All the connectivity examples
      are changed from ADHD to brain development fmri dataset.
    + ENHANCEMENTS
    * :func:`nilearn.plotting.view_img_on_surf`, :func:`nilearn.plotting.view_surf`
      and :func:`nilearn.plotting.view_connectome` can display a title, and allow
      disabling the colorbar, and setting its height and the fontsize of its ticklabels.
    * Rework of the standardize-options of :func:`nilearn.signal.clean` and the various Maskers
      in `nilearn.input_data`. You can now set `standardize` to `zscore` or `psc`. `psc` stands
      for `Percent Signal Change`, which can be a meaningful metric for BOLD.
    * Class :class:`nilearn.input_data.NiftiLabelsMasker` now accepts an optional
      `strategy` parameter which allows it to change the function used to reduce
      values within each labelled ROI. Available functions include mean, median,
      minimum, maximum, standard_deviation and variance.
      This change is also introduced in :func:`nilearn.regions.img_to_signals_labels`.
    * :func:`nilearn.plotting.view_surf` now accepts surface data provided as a file
      path.
    + CHANGES
    * :func:`nilearn.plotting.plot_img` now has explicit keyword arguments `bg_img`,
      `vmin` and `vmax` to control the background image and the bounds of the
      colormap. These arguments were already accepted in `kwargs` but not documented
      before.
    + FIXES
    * :class:`nilearn.input_data.NiftiLabelsMasker` no longer truncates region means to their integral part
      when input images are of integer type.
    * The arg `version='det'` in :func:`nilearn.datasets.fetch_atlas_pauli_2017` now  works as expected.
    * `pip install nilearn` now installs the necessary dependencies.
    * Lots of other fixes in documentation and examples. More detailed change list follows:
  - Drop python2 support
* Fri Jul 26 2019 Todd R <toddrme2178@gmail.com>
  - Initial version

Files

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Fabrice Bellet, Tue Apr 9 14:50:04 2024