Changelog for python312-nilearn-0.10.3-40.2.noarch.rpm :

* Tue Feb 20 2024 Ben Greiner - Update to 0.10.3 [#]# Highlights
* API Allow passing arguments to first_level_from_bids to build first level models that include specific set of confounds by relying on the strategies from load_confounds (#4103 by Rémi Gau).
* Support passing t and F contrasts to compute_contrast that that have fewer columns than the number of estimated parameters. Remaining columns are padded with zero (#4067 by Rémi Gau).
* NiftiSpheresMasker now has generate_report method (#3102 by Yasmin Mzayek and Nicolas Gensollen).
* Update the CompCor strategy in load_confounds and load_confounds_strategy to support fmriprep 21.x series and above. (#3285 by Hao-Ting Wang).
* Allow setting vmin in plot_glass_brain and plot_stat_map (#3993 by Michelle Wang).
* When plotting thresholded statistical maps with a colorbar, the threshold value(s) will now be displayed as tick labels on the colorbar (##2833 by Nicolas Gensollen).
* Combine GLM examples plot_fixed_effect and plot_fiac_analysis into a a single example plot_two_runs_model (#3191 by Taylor Salo and Rémi Gau). [#]# New
* The temp_file_lifetime parameter of interactive plots’ open_in_browser method is deprecated and has no effect (#4180 by Jerome Dockes).. [#]# Fixes
* MultiNiftiMasker can now call generate_report which will generate a report for the first subject in the list of subjects (#4001 by Yasmin Mzayek).
* Make sure that all atlases and datasets fetchers return a description (#4215 Rémi Gau).
* Update the CompCor strategy in load_confounds and load_confounds_strategy to support fmriprep 21.x series and above. (#3285 by Hao-Ting Wang).
* Fix SimpleRegressionResults to accommodate for the lack of a model attribute (#4071 Rémi Gau)
* clean_img can now use kwargs clean__sample_mask argument to correctly reshape the nifti image to the dimensions of the mask in the output (#4051 by Mia Zwally).
* Fix plotting of an image with color bar when maximum value is exactly zero (#4204 by Rémi Gau).
* Code Fix PSC normalisation method applied by standardize_signal in signal (#4116 by Hao-Ting Wang and Yasmin Mzayek).
* Fixed inheritance of decoder classes to keep compatibility with scikit-learn>v1.3 (#4188 by Yasmin Mzayek).
* Make sure that all the fetchers for atlas and func from nilearn.datasets return a sklearn.utils.Bunch. Add new behavior to fetch_language_localizer_demo_dataset to return output as Bunch. This behavior will become the default in version 0.13.0 (#4233 by Rémi Gau). [#]# Enhancements
* NiftiSpheresMasker now has generate_report method (#3102 by Yasmin Mzayek and Nicolas Gensollen).
* Allow passing Pandas Series of image filenames to SecondLevelModel (#4070 by Rémi Gau).
* Allow passing arguments to first_level_from_bids to build first level models that include specific set of confounds by relying on the strategies from load_confounds (#4103 by Rémi Gau).
* Support passing t and F contrasts to compute_contrast that that have fewer columns than the number of estimated parameters. Remaining columns are padded with zero (#4067 by Rémi Gau).
* Multi-subject maskers’ generate_report method no longer fails with 5D data but instead shows report of first subject. User can index input list to show report for different subjects (#3935 by Yasmin Mzayek).
* Allow global_signal parameter in load_confounds_strategy in denoise_strategy=\'compcor\' (#4225 by Hao-Ting Wang).
* Add two_sided option for binarize_img (#4121 by Steven Meisler).
* generate_report now uses appropriate cut coordinates when functional image is provided (#4099 by Yasmin Mzayek and Nicolas Gensollen).
* Mention the classification type (all-vs-one) in Decoding of a dataset after GLM fit for signal extraction (#4122 by Tamer Gezici).
* Add backslash to homogenize Parcellations- Release 0.10.2 [#]# Higlights
* Volume plotting functions like plotting.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..
* Update Decoder objects to use the more efficient LogisticRegressionCV.
* Add LassoCV as a new estimator option for Decoder objects
* Add vmin and symmetric_cbar arguments to nilearn.plotting.plot_img_on_surf.
* Improve contrasts allowing fixed effects on F contrasts
* 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.. [#]# NEW
* Volume plotting functions like plotting.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..
* 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.. [#]# Fixes
* Fix bug in method transform_imgs of maskers.MultiNiftiMapsMasker and maskers.MultiNiftiLabelsMasker that would raise an error if a list of sample_mask was specified to fit_transform.
* Fix bug in nilearn.plotting.surf_plotting._plot_surf_matplotlib that would make vertices transparent when saving in PDF or SVG format.
* Fix bug that would prevent using symmetric_cmap=True or the avg_method argument with plotting.plot_surf_roi.
* Fixes a bug that would lead to an error when loading a fsaverage surface while relying on numpy >= 1.24.x.
* Fix bug that would prevent loading the confounds of a gifti file in actual fmriprep datasets.
* Fix bug that prevented using dataframes as input for second level GLM when computing contrasts.
* Fix bug in glm.first_level.first_level_from_bids that returned no confound files if the corresponding bold files contained derivatives BIDS entities.
* Fix bug in glm.first_level.first_level_from_bids that would throw a warning about slice_time_ref not being provided even when it was.
* Fix bug where the cv_params_ attribute of fitter Decoder objects sometimes had missing entries if grid_param is a sequence of dicts with different keys.
* Make the nilearn.interfaces.fmriprep.load_confounds confounds file selection more generic.
* Change default figure sizes to prevent titles from overlapping figure content
* Relax the nilearn.interfaces.fmriprep.load_confounds confounds selection on cosine as not all confound files contained the variables.
* Fix pathlib.Path not being counted as Niimg-like object in image.new_img_like.
* Fix fit_transform behavior to match when fit method is passed image data
* Allow using both vmin and threshold with \"plotly\" engine to be consistent with \"matplotlib\" behavior
* Set edgecolors to be the same as facecolors in plotting.plot_surf_contours so that ROI contours are rendered clearly
* Refactor deprecation of behavior of datasets.fetch_atlas_craddock_2012, datasets.fetch_atlas_smith_2009 and datasets.fetch_atlas_basc_multiscale_2015 fetchers including using API consistent maps key [#]# Enhancements
* Add cross-reference links to type definitions in public surface functions.
* Update Decoder objects to use the more efficient LogisticRegressionCV.
* Throw warning in glm.first_level.first_level_from_bids when using event.tsv files with no trial type column.
* Make return key names in the description file of destrieux surface consistent with datasets.fetch_atlas_surf_destrieux.
* Add LassoCV as a new estimator option for Decoder objects
* Add vmin and symmetric_cbar arguments to nilearn.plotting.plot_img_on_surf.
* Improve generate_report method of maskers by allowing users to pass a cmap argument for plotting image
* Improve contrasts allowing fixed effects on F contrasts [#]# Changes
* Validate the content of events files before plotting them.
* nilearn.glm.first_level.experimental_paradigm.check_events will now throw a warning if some events have a 0 second duration and will throw an error if an event has NaN onset or duration.
* Removed old files and test code from deprecated datasets COBRE and NYU resting state.
* PEP8 and isort compliance extended to the whole nilearn codebase..
* Finish applying black formatting to most of the codebase..
* Empty region signals resulting from applying mask_img in maskers.NiftiLabelsMasker will no longer be kept in release 0.15. Meanwhile, use keep_masked_labels parameter when initializing the maskers.NiftiLabelsMasker object to enable/disable this behavior..
* Empty region signals resulting from applying mask_img in maskers.NiftiMapsMasker will no longer be kept in release 0.15. Meanwhile, use keep_masked_maps parameter when initializing the maskers.NiftiMapsMasker object to enable/disable this behavior..
* Removed mention of license in \"header\".
* Configure plots in example gallery for better rendering
* Make one_mesh_info and full_brain_info into private functions _one_mesh_info and _full_brain_info
* Refactor error raising tests using context managers
* Added warning to deprecate darkness in surf_plotting._compute_facecolors_matplotlib and html_surface._get_vertexcolor
* Replace skipped doctests with default code-blocks
* Move the ~nilearn.plotting.html_surface._mix_colormaps to cm.py in nilearn.plotting
* Remove deprecation decorator from ~nilearn.glm.regression
* Expose standardize in plotting.plot_carpet and connectome.ConnectivityMeasure to handle \"zscore\" deprecation.
* Example :ref:sphx_glr_auto_examples_01_plotting_plot_prob_atlas.py is shortened to speed up build time- Drop numpy-1.25.patch- Drop warning-based-sklearn-version.patch
* Thu Aug 10 2023 Daniel Garcia - Add numpy-1.25.patch, upstream patch gh#nilearn/nilearn#3746- Add warning-based-sklearn-version.patch, upstream patch gh#nilearn/nilearn#3763
* Tue Jun 27 2023 Markéta Machová - Update to 0.10.1
* New function load_sample_motor_activation_image to load example contrast map
* fsaverage meshes accessed through fetch_surf_fsaverage now come with flat maps for all resolutions
* Improve how first_level_from_bids handles fetching slice timing metadata and add additional input validation. In release 0.12 the default slice_time_ref will be None instead of 0
* Fixes several bugs in first_level_from_bids.
* Add correct “zscore_sample” strategy to signal._standardize which will replace the default “zscore” strategy in release 0.13
* Moved packaging from setup.py and setuptools build backend to pyproject.toml and hatchling backend.
* Restore resample_img compatibility with all nibabel.spatialimages.SpatialImage objects
* Fri Apr 14 2023 Steve Kowalik - Skip a failing array test.
* Mon Feb 06 2023 Daniel Garcia - Update to 0.10.0
* New classes MultiNiftiLabelsMasker and MultiNiftiMapsMasker create maskers to extract signals from a list of subjects with 4D images using parallelization (#3237 by Yasmin Mzayek).
* Updated docs with a new theme using furo (#3125 by Alexis Thual).
* permuted_ols and non_parametric_inference now support TFCE statistic (#3196 by Taylor Salo).
* permuted_ols and non_parametric_inference now support cluster-level Family-wise error correction (#3181 by Taylor Salo).
* save_glm_to_bids has been added, which writes model outputs to disk according to BIDS convention (#2715 by Taylor Salo).
* Tue Oct 11 2022 John Vandenberg - Remove fix-test-decoder.patch merged upstream- Remove use of pytest-xdist which makes failures harder to see- Update to v0.9.2
* save_glm_to_bids has been added, which writes model outputs to disk according to BIDS convention
* permuted_ols and non_parametric_inference now support TFCE statistic
* permuted_ols and non_parametric_inference now support cluster-level Family-wise error correction
* Updated docs with a new theme using furo
* Fix _NEUROVAULT_BASE_URL and _NEUROSYNTH_FETCH_WORDS_URL in nilearn/datasets/neurovault.py by using https instead of http
* Convert references in nilearn/mass_univariate/permuted_least_squares.py to use bibtex format
* Update Craddock 2012 parcellation url in nilearn/datasets/atlas.py
* plot_roi failed before when used with the “contours” view type and passing a list of cut coordinates in display mode “x”, “y” or “z”; this has been corrected
* plot_markers can now plot a single scatter point
* Fix title display for plot_surf_stat_map. The title argument does not set the figure title anymore but the axis title.
* load_surf_mesh loaded FreeSurfer specific surface files (e.g. .pial) with a shift in the coordinates. This is fixed by adding the c_ras coordinates to the mesh coordinates
* Function nilearn.glm.second_level.second_level._check_second_level_input now raises an error when flm_object argument is False and second_level_input is a list of FirstLevelModel
* Function resample_img now warns the user if the provided image has an sform code equal to 0 or None
* Fix usage of scipy.stats.gamma.pdf in _gamma_difference_hrf function under nilearn/glm/first_level/hemodynamic_models.py, which resulted in slight distortion of HRF
* Fix bug introduced due to a fix in the pre-release version of scipy (1.9.0rc1) which now enforces that elements of a band-pass filter must meet condition Wn[0] < Wn[1]. Now if band-pass elements are equal butterworth returns an unfiltered signal with a warning
* The parameter alpha is now correctly passed to plot_glass_brain in plot_connectome
* Fix plotting of background image in view_img when the background is not the MNI template
* Fix the typographic error on the page Default Mode Network extraction of ADHD dataset
* Add sample_masks to fit for censoring time points
* Function run_glm and class FirstLevelModel now accept a random_state parameter, which allows users to seed the KMeans cluster model used to estimate AR coefficients
* Conform seeding and docstrings in module _utils.data_gen
* Docstrings of module second_level were improved
* In get_clusters_table, when the center of mass of a binary cluster falls outside the cluster, report the nearest within-cluster voxel instead
* Add n_elements_ attribute to masker classes
* Functions expecting string filesystem paths now also accept path-like objects
* Contributing guidelines now include a recommendation to run flake8 locally on the branch diff with main
* Improvements to permuted_ols and non_parametric_inference with TFCE statistic runtime
* NiftiLabelsMasker now accepts 1-dimensional arrays in its inverse_transform method
* Function plot_carpet argument cmap now respects behaviour specified by docs and changes the color of the carpet_plot. Changing the label colors is now delegated to a new variable cmap_labels
* Function fetch_surf_fsaverage no longer supports the previously deprecated option fsaverage5_sphere
* Classes RegressionResults, SimpleRegressionResults, OLSModel, and LikelihoodModelResults no longer support deprecated shortened attribute names, including df_resid, wdesign, wresid, norm_resid, resid, and wY
* Function fetch_openneuro_dataset_index is now deprecated in favor of the new fetch_ds000030_urls function
* 64-bit integers in Nifti files: some tools such as FSL, SPM and AFNI cannot handle Nifti images containing 64-bit integers. To avoid compatibility issues, it is best to avoid writing such images and in the future trying to create them with nibabel without explicitly specifying a data type will result in an error. To avoid this, new_img_like now warns when given int64 arrays and converts them to int32 when possible (ie when it would not result in an overflow). Moreover, any atlas fetcher that returned int64 images now produces images containing smaller ints.
* Refactors fmriprep confound loading such that that the parsing of the relevant image file and the loading of the confounds are done in separate steps
* Private submodules, functions, and classes from the decomposition module now start with a “_” character to make it clear that they are not part of the public API
* Convert references in nilearn/glm/regression.py and nilearn/glm/thresholding.py to use footcite/footbibliography
* Boolean input data in new_img_like now defaults to np.uint8 instead of np.int8
* The current behavior of maskers’ transform on 3D niimg inputs, in which a 2D array is returned, is deprecated, and 1D arrays will be returned starting in version 0.12
* Fri Sep 16 2022 Guillaume GARDET - Disable multi-thread tests until fixed upstream -- gh#nilearn/nilearn#3359
* Tue Jul 12 2022 Markéta Machová - Update to 0.9.1
* Python 3.6 is deprecated and will be removed in release 0.10
* Nibabel 2.x is no longer supported
* Surface plotting functions can now produce interactive plots with Plotly
* New module nilearn.interfaces to implement loading and saving utilities with various interfaces
* New functions load_confounds and load_confounds_strategy to load confound variables easily from fMRIPrep outputs
* New class HierarchicalKMeans which yields more balanced clusters than KMeans. It is also callable through Parcellations using method=hierarchical_kmeans
* Masker objects like NiftiMasker now belong to the new module nilearn.maskers. The old import style, through the module input_data, still works but has been deprecated
* Class NiftiMapsMasker can now generate HTML reports in the same way as NiftiMasker and NiftiLabelsMasker
* The contributing documentation and maintenance pages were improved
* many more changes, see upstream changelog- Add upstream patch fix-test-decoder.patch- Delete upstreamed patches:
* nilearn-pr3136-pythoncall.patch
* nilearn-pr3094-py310.patch
* Thu Jan 20 2022 Ben Greiner - Update to 0.8.1
* New atlas fetcher nilearn.datasets.fetch_atlas_juelich to download Juelich atlas from FSL.
* New grey and white-matter template and mask loading functions: nilearn.datasets.load_mni152_gm_template, nilearn.datasets.load_mni152_wm_template, nilearn.datasets.load_mni152_gm_mask, and nilearn.datasets.load_mni152_wm_mask
* Nilearn development process has been reworked. It now provides insights on nilearn organization as a project as well as more explicit Contribution Guidelines.
* nilearn.image.binarize_img binarizes images into 0 and 1.
* nilearn.input_data.NiftiLabelsMasker can now generate HTML reports in the same way as nilearn.input_data.NiftiMasker.
* nilearn.signal.clean accepts new parameter sample_mask. shape: (number of scans - number of volumes removed, )
* All inherent classes of nilearn.input_data.BaseMasker can use parameter sample_mask for sub-sample masking.
* Fetcher nilearn.datasets.fetch_surf_fsaverage now accepts fsaverage3, fsaverage4 and fsaverage6 as values for parameter mesh, so that all resolutions of fsaverage from 3 to 7 are now available.
* Fetcher nilearn.datasets.fetch_surf_fsaverage now provides attributes {area, curv, sphere, thick}_{left, right} for all fsaverage resolutions.
* nilearn.glm.first_level.run_glm now allows auto regressive noise models of order greater than one.
* Support for Nibabel 2.x is deprecated and will be removed in the 0.9 release.- Add nilearn-pr3094-py310.patch -- gh#nilearn/nilearn#3094- Add nilearn-pr3136-pythoncall.patch -- gh#nilearn/nilearn#3136- Only test on 64-bit platforms - - http://nilearn.github.io/introduction.html#installation
* Fri Apr 09 2021 Markéta Machová - Update to 0.7.1
* New atlas fetcher nilearn.datasets.fetch_atlas_difumo to download Dictionaries of Functional Modes, or “DiFuMo”, that can serve as atlases to extract functional signals with different dimensionalities.
* nilearn.decoding.Decoder and nilearn.decoding.DecoderRegressor is now implemented with random predictions to estimate a chance level.
* Some functions are now implemented with new display mode Mosaic. That implies plotting 3D maps in multiple columns and rows in a single axes.- Drop nilearn-fix-aarch64.patch
* Fri Jan 29 2021 Ben Greiner - Skip python36 build because Tumbleweed updates to SciPy 1.6.0 which dropped support for Python 3.6 (NEP 29)