Reference API

neuromaps.datasets - Dataset fetchers

Functions for fetching datasets.

Functions to show all available annotations

neuromaps.datasets.available_annotations([...])

List datasets available via fetch_annotation().

neuromaps.datasets.available_tags([...])

Return available tags for querying annotations.

Functions to fetch and describe the annotations

neuromaps.datasets.fetch_annotation(*[, ...])

Download files for brain annotations matching requested variables.

neuromaps.datasets.describe_annotations(annots)

Return detailed descriptions for annotations as a pandas dataframe.

Functions to fetch the atlases

neuromaps.datasets.fetch_atlas(atlas, density)

Fetch specified atlas and density.

neuromaps.datasets.fetch_civet([density, ...])

Fetch CIVET surface atlas.

neuromaps.datasets.fetch_fsaverage([...])

Fetch fsaverage surface atlas.

neuromaps.datasets.fetch_fslr([density, ...])

Fetch fsLR surface atlas.

neuromaps.datasets.fetch_mni152([density, ...])

Fetch MNI152 atlas.

neuromaps.datasets.fetch_regfusion(atlas[, ...])

Fetch regfusion inputs for mapping MNI152 to specified surface atlas.

neuromaps.datasets.fetch_all_atlases([...])

Fetch (and cache) all available atlases.

neuromaps.datasets.get_atlas_dir(atlas[, ...])

Return filepath to specified atlas.

neuromaps.images - Image and surface handling

Functions for operating on images + surfaces.

Functions to load the images and surfaces

neuromaps.images.load_gifti(img)

Load gifti file img.

neuromaps.images.load_nifti(img)

Load nifti file img.

Functions to convert surfaces to GIFTI format

neuromaps.images.relabel_gifti(parcellation)

Update GIFTI images so label IDs are consecutive across hemispheres.

neuromaps.images.annot_to_gifti(parcellation)

Convert FreeSurfer-style annotation parcellation files to GIFTI images.

neuromaps.images.dlabel_to_gifti(parcellation)

Convert CIFTI dlabel file to GIFTI images.

neuromaps.images.obj_to_gifti(obj[, fn])

Convert CIVET obj surface file to GIFTI format.

neuromaps.images.fssurf_to_gifti(surf[, fn])

Convert FreeSurfer surf surface file to GIFTI format.

neuromaps.images.fsmorph_to_gifti(morph[, ...])

Convert FreeSurfer morph data file to GIFTI format.

Functions to work with surfaces

neuromaps.images.average_surfaces(*surfs)

Generate average surface from input surfs.

neuromaps.images.interp_surface(data, src, trg)

Interpolate data on src surface to trg surface.

neuromaps.images.vertex_areas(surface)

Calculate vertex areas from surface file.

neuromaps.nulls - Null models

Functions for computing null models.

Spatial permutation null models (for surface images only)

neuromaps.nulls.alexander_bloch(data[, ...])

Generate null maps from data using method from [SN1].

neuromaps.nulls.vazquez_rodriguez(data[, ...])

Generate null maps from data using method from [SN1].

neuromaps.nulls.vasa(data[, atlas, density, ...])

Generate null maps for parcellated data using method from [SN2].

neuromaps.nulls.hungarian(data[, atlas, ...])

Generate null maps for parcellated data using the Hungarian method ([SN3]).

neuromaps.nulls.baum(data[, atlas, density, ...])

Generate null maps for parcellated data using method from [SN4].

neuromaps.nulls.cornblath(data[, atlas, ...])

Generate null maps for parcellated data using method from [SN5].

Parametric spatial null models (for volumetric and surface images)

neuromaps.nulls.burt2018(data[, atlas, ...])

Generate null maps for data using method from [SN6].

neuromaps.nulls.burt2020(data[, atlas, ...])

Generate null maps for data using method from [SN7] and [SN8].

neuromaps.nulls.moran(data[, atlas, ...])

Generate null maps for data using method from [SN9].

neuromaps.parcellate - Parcellation utilities

Functionality for parcellating data.

neuromaps.parcellate.Parcellater(...[, ...])

Class for parcellating arbitrary volumetric / surface data.

neuromaps.plotting - Plotting functions

Functionality for plotting.

neuromaps.plotting.plot_surf_template(data, ...)

Plot data on template surface.

neuromaps.points - Triangle mesh utilities

Functions for working with triangle meshes + surfaces.

neuromaps.points.make_surf_graph(vertices, faces)

Construct adjacency graph from surf.

neuromaps.points.get_surface_distance(surface)

Calculate surface distance for vertices in surface.

neuromaps.resampling - Resampling workflows

Functions for comparing data.

neuromaps.resampling.resample_images(src, ...)

Resample images src and trg to same space/density with resampling method.

neuromaps.stats - Statistical functions

Functions for statistical analyses.

neuromaps.stats.compare_images(src, trg[, ...])

Compare images src and trg.

neuromaps.stats.permtest_metric(a, b[, ...])

Generate non-parameteric p-value of a and b for metric.

neuromaps.transforms - Transformations between spaces

Functionality for transforming files between spaces.

Volume-to-surface transformations

neuromaps.transforms.mni152_to_civet(img[, ...])

Project img in MNI152 space to CIVET surface.

neuromaps.transforms.mni152_to_fsaverage(img)

Project img in MNI152 space to fsaverage surface.

neuromaps.transforms.mni152_to_fslr(img[, ...])

Project img in MNI152 space to fsLR surface.

Volume-to-volume transformations

neuromaps.transforms.mni152_to_mni152(img[, ...])

Resample img to target image (if supplied) or target resolution.

Surface-to-surface transformations

neuromaps.transforms.civet_to_fslr(data[, ...])

Resample data on CIVET surface to the fsLR surface.

neuromaps.transforms.fslr_to_civet(data[, ...])

Resample data on fsLR surface to the CIVET surface.

neuromaps.transforms.civet_to_fsaverage(data)

Resample data on CIVET surface to the fsaverage surface.

neuromaps.transforms.fsaverage_to_civet(data)

Resample data on fsaverage surface to the CIVET surface.

neuromaps.transforms.civet_to_civet(data[, ...])

Resample data on CIVET surface to new density.

neuromaps.transforms.fslr_to_fsaverage(data)

Resample data on fsLR surface to the fsaverage surface.

neuromaps.transforms.fsaverage_to_fslr(data)

Resample data on fsaverage surface to the fsLR surface.

neuromaps.transforms.fslr_to_fslr(data[, ...])

Resample data on fsLR surface to new density.

neuromaps.transforms.fsaverage_to_fsaverage(data)

Resample data on fsaverage surface to new density.