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Contributing

0.2.6

Changelog

This release enhances usage of several functions by fine tuning their parameters. It allows to select which Haxby subject to fetch. It also refactors documentation to make it easier to understand. Sphinx-gallery has been updated and nilearn is ready for new nibabel 2.1 version. Several bugs related to masks in Searchlight and ABIDE fetching have been resolved.

Bug fix

  • Change default dtype in nilearn.image.concat_imgs to be the original type of the data (see #1238).
  • Fix SearchLight that did not run without process_mask or with one voxel mask.
  • Fix flipping of left hemisphere when plotting glass brain.
  • Fix bug when downloading ABIDE timeseries

Enhancements

API changes summary

  • The parameter ‘n_subjects’ is deprecated and will be removed in future release. Use ‘subjects’ instead in nilearn.datasets.fetch_haxby
  • The function nilearn.datasets.fetch_haxby will now fetch the data accepting input given in ‘subjects’ as a list than integer.
  • Replace get_affine by affine with recent versions of nibabel.

0.2.5.1

Changelog

This is a bugfix release. The new minimum required version of scikit-learn is 0.14.1

API changes summary

  • default option for dim argument in plotting functions which uses MNI template as a background image is now changed to ‘auto’ mode. Meaning that an automatic contrast setting on background image is applied by default.
  • Scikit-learn validation tools have been imported and are now used to check consistency of input data, in SpaceNet for example.

New features

  • Add an option to select only off-diagonal elements in sym_to_vec. Also, the scaling of matrices is modified: we divide the diagonal by sqrt(2) instead of multiplying the off-diagonal elements.
  • Connectivity examples rely on nilearn.connectome.ConnectivityMeasure

Bug fix

  • Scipy 0.18 introduces a bug in a corner-case of resampling. Nilearn 0.2.5 can give wrong results with scipy 0.18, but this is fixed in 0.2.6.
  • Broken links and references fixed in docs

0.2.5

Changelog

The 0.2.5 release includes plotting for connectomes and glass brain with hemisphere-specific projection, as well as more didactic examples and improved documentation.

New features

Contributors

Contributors (from git shortlog -ns 0.2.4..0.2.5):

55  Gael Varoquaux
39  Alexandre Abraham
26  Martin Perez-Guevara
20  Kamalakar Daddy
 8  amadeuskanaan
 3  Alexandre Abadie
 3  Arthur Mensch
 3  Elvis Dohmatob
 3  Loïc Estève
 2  Jerome Dockes
 1  Alexandre M. S
 1  Bertrand Thirion
 1  Ivan Gonzalez
 1  robbisg

0.2.4

Changelog

The 0.2.4 is a small release focused on documentation for teaching.

New features

  • The path given to the “memory” argument of object now have their “~” expanded to the homedir
  • Display object created by plotting now uniformely expose an “add_markers” method.
  • plotting plot_connectome with colorbar is now implemented in function nilearn.plotting.plot_connectome
  • New function nilearn.image.resample_to_img to resample one img on another one (just resampling / interpolation, no coregistration)

API changes summary

  • Atlas fetcher nilearn.datasets.fetch_atlas_msdl now returns directly labels of the regions in output variable ‘labels’ and its coordinates in output variable ‘region_coords’ and its type of network in ‘networks’.
  • The output variable name ‘regions’ is now changed to ‘maps’ in AAL atlas fetcher in nilearn.datasets.fetch_atlas_aal.
  • AAL atlas now returns directly its labels in variable ‘labels’ and its index values in variable ‘indices’.

0.2.3

Changelog

The 0.2.3 is a small feature release for BrainHack 2016.

New features

Bug fixes

  • Better dimming on white background for plotting

0.2.2

Changelog

The 0.2.2 is a bugfix + dependency update release (for sphinx gallery). It aims at preparing a renewal of the tutorials.

New features

  • Fetcher for Megatrawl Netmats dataset.

Enhancements

  • Flake8 is now run on pull requests.
  • Reworking of the documentation organization.
  • Sphinx-gallery updated to version 0.1.1
  • The default n_subjects=None in nilearn.datasets.fetch_adhd is now changed to n_subjects=30.

Bug fixes

API changes summary

  • Deprecated dataset downloading function have been removed.
  • Download progression message refreshing rate has been lowered to sparsify CircleCI logs.

Contributors

Contributors (from git shortlog -ns 0.2.1..0.2.2):

39  Kamalakar Daddy
22  Alexandre Abraham
21  Loïc Estève
19  Gael Varoquaux
12  Alexandre Abadie
 7  Salma
 3  Danilo Bzdok
 1  Arthur Mensch
 1  Ben Cipollini
 1  Elvis Dohmatob
 1  Óscar Nájera

0.2.1

Changelog

Small bugfix for more flexible input types (targetter in particular at making code easier in nistats).

0.2

Changelog

The new minimum required version of scikit-learn is 0.13

New features

Enhancements

  • Making website a bit elaborated & modernise by using sphinx-gallery.
  • Documentation enhancement by integrating sphinx-gallery notebook style examples.
  • Documentation about nilearn.input_data.NiftiSpheresMasker.

Bug fixes

API changes summary

Contributors

Contributors (from git shortlog -ns 0.1.4..0.2.0):

822  Elvis Dohmatob
142  Gael Varoquaux
119  Alexandre Abraham
 90  Loïc Estève
 85  Kamalakar Daddy
 65  Alexandre Abadie
 43  Chris Filo Gorgolewski
 39  Salma BOUGACHA
 29  Danilo Bzdok
 20  Martin Perez-Guevara
 19  Mehdi Rahim
 19  Óscar Nájera
 17  martin
  8  Arthur Mensch
  8  Ben Cipollini
  4  ainafp
  4  juhuntenburg
  2  Martin_Perez_Guevara
  2  Michael Hanke
  2  arokem
  1  Bertrand Thirion
  1  Dimitri Papadopoulos Orfanos

0.1.4

Changelog

Highlights:

  • NiftiSpheresMasker: extract signals from balls specified by their coordinates
  • Obey Debian packaging rules
  • Add the Destrieux 2009 and Power 2011 atlas
  • Better caching in maskers

Contributors (from git shortlog -ns 0.1.3..0.1.4):

141  Alexandre Abraham
 15  Gael Varoquaux
 10  Loïc Estève
  2  Arthur Mensch
  2  Danilo Bzdok
  2  Michael Hanke
  1  Mehdi Rahim

0.1.3

Changelog

The 0.1.3 release is a bugfix release that fixes a lot of minor bugs. It also includes a full rewamp of the documentation, and support for Python 3.

Minimum version of supported packages are now:

  • numpy 1.6.1
  • scipy 0.9.0
  • scikit-learn 0.12.1
  • Matplotlib 1.1.1 (optional)

A non exhaustive list of issues fixed:

  • Dealing with NaNs in plot_connectome
  • Fix extreme values in colorbar were sometimes brok
  • Fix confounds removal with single confounds
  • Fix frequency filtering
  • Keep header information in images
  • add_overlay finds vmin and vmax automatically
  • vmin and vmax support in plot_connectome
  • detrending 3D images no longer puts them to zero

Contributors (from git shortlog -ns 0.1.2..0.1.3):

129  Alexandre Abraham
 67  Loïc Estève
 57  Gael Varoquaux
 44  Ben Cipollini
 37  Danilo Bzdok
 20  Elvis Dohmatob
 14  Óscar Nájera
  9  Salma BOUGACHA
  8  Alexandre Gramfort
  7  Kamalakar Daddy
  3  Demian Wassermann
  1  Bertrand Thirion

0.1.2

Changelog

The 0.1.2 release is a bugfix release, specifically to fix the NiftiMapsMasker.

0.1.1

Changelog

The main change compared to 0.1 is the addition of connectome plotting via the nilearn.plotting.plot_connectome function. See the plotting documentation for more details.

Contributors (from git shortlog -ns 0.1..0.1.1):

81  Loïc Estève
18  Alexandre Abraham
18  Danilo Bzdok
14  Ben Cipollini
 2  Gaël Varoquaux

0.1

Changelog

First release of nilearn.

Contributors (from git shortlog -ns 0.1):

600  Gaël Varoquaux
483  Alexandre Abraham
302  Loïc Estève
254  Philippe Gervais
122  Virgile Fritsch
 83  Michael Eickenberg
 59  Jean Kossaifi
 57  Jaques Grobler
 46  Danilo Bzdok
 35  Chris Filo Gorgolewski
 28  Ronald Phlypo
 25  Ben Cipollini
 15  Bertrand Thirion
 13  Alexandre Gramfort
 12  Fabian Pedregosa
 11  Yannick Schwartz
  9  Mehdi Rahim
  7  Óscar Nájera
  6  Elvis Dohmatob
  4  Konstantin Shmelkov
  3  Jason Gors
  3  Salma Bougacha
  1  Alexandre Savio
  1  Jan Margeta
  1  Matthias Ekman
  1  Michael Waskom
  1  Vincent Michel