Package index • fsbrain

All functions

alphablend(): Perform alpha blending for pairs of RGBA colors.
annot.outline(): Compute outline vertex colors from annotation.
annot.outline.border.vertices(): Compute the border vertices for each region in an annot.
apply.label.to.morphdata(): Load a label from file and apply it to morphometry data.
apply.labeldata.to.morphdata(): Apply a label to morphometry data.
apply.transform(): Apply matmult transformation to input.
arrange.brainview.images(): Combine several brainview images into a new figure.
arrange.brainview.images.grid(): Combine several brainview images as a grid into a new figure.
brainviews(): Show one or more views of the given meshes in rgl windows.
clip.data(): Clip data at quantiles to remove outliers.
clip_fun(): Get data clipping function.
cm.cbry(): Get cyan blue red yellow colormap function.
cm.div(): Return the standard fsbrain diverging colormap.
cm.heat(): Return the standard fsbrain heat colormap.
cm.qual(): Return the standard fsbrain qualitative colormap.
cm.seq(): Return the standard fsbrain sequential colormap.
collayer.bg(): Compute binarized mean curvature surface color layer.
collayer.bg.atlas(): Compute atlas or annotation surface color layer.
collayer.bg.meancurv(): Compute binarized mean curvature surface color layer.
collayer.bg.sulc(): Compute binarized sulcal depth surface color layer.
collayer.from.annot(): Compute surface color layer from annotation or atlas data.
collayer.from.annotdata(): Compute surface color layer from annotation or atlas data.
collayer.from.mask.data(): Compute surface color layer from morph-like data.
collayer.from.morphlike.data(): Compute surface color layer from morph-like data.
collayers.merge(): Merge two or more color layers based on their transparency values.
coloredmesh.from.annot(): Create a coloredmesh from an annotation of an atlas.
coloredmesh.from.label(): Create a coloredmesh from a label.
coloredmesh.from.mask(): Create a coloredmesh from a mask.
coloredmesh.from.morph.native(): Create a coloredmesh from native space morphometry data.
coloredmesh.from.morph.standard(): Create a coloredmesh from standard space morphometry data.
coloredmesh.from.morphdata(): Create a coloredmesh from arbitrary data.
coloredmesh.from.preloaded.data(): Generate coloredmesh from loaded data.
coloredmesh.plot.colorbar.separate(): Draw colorbar for coloredmeshes in separate 2D plot.
coloredmeshes.from.color(): Create coloredmeshes for both hemis using pre-defined colors.
colorlist.brain.clusters(): Return diverging color list
colors.are.grayscale(): Check for the given color strings whether they represent gray scale colors.
colors.have.transparency(): Check for the given color strings whether they have transparency, i.e., an alpha channel value != fully opaque.
combine.colorbar.with.brainview.animation(): Combine a colorbar and a brain animation in gif format into a new animation.
combine.colorbar.with.brainview.image(): Combine a colorbar and a brainview image into a new figure.
constant.pervertexdata(): Get vertex data for a single fs.surface or a hemilist of surfaces.
cube3D.tris(): Return triangles for a 3D cube or cuboid.
cubes3D.tris(): Vectorized version of cube3D.tris
delete_all_optional_data(): Delete all data in the package cache.
demographics.to.fsgd.file(): Write FreeSurfer Group Descriptor (FSGD) file from demographics dataframe.
demographics.to.qdec.table.dat(): Convert a dataframe containing demographics data to a qdec.table.dat file and related files.
desaturate(): Perform simple desaturation or grayscale conversion of RGBA colors.
download_fsaverage(): Download the FreeSurfer v6 fsaverage subject.
download_fsaverage3(): Download the FreeSurfer v6 low-resolution fsaverage3 subject.
download_fsaverage6(): Download the FreeSurfer v6 fsaverage6 subject.
download_fsaverage_minimal(): Download only essential FreeSurfer v6 fsaverage files for quick visualization.
download_optional_data(): Download optional data for this package if required.
download_optional_paper_data(): Download extra data to reproduce the figures from the fsbrain paper.
export(): Export high-quality brainview image with a colorbar.
export.coloredmesh.ply(): Export a coloredmeshes with vertexcolors in PLY format.
face.edges(): Enumerate all edges of the given faces or mesh.
find.freesurferhome(): Find the FREESURFER_HOME directory on disk.
find.subjectsdir.of(): Find the subject directory containing the fsaverage subject (or others) on disk.
fs.coloredmesh(): fs.coloredmesh constructor
fs.home(): Return FreeSurfer path.
fs.surface.as.adjacencylist(): Turn surface mesh into a igraph and return its adjacency list representation.
fs.surface.to.igraph(): Create igraph undirected graph from a brain surface mesh.
fs.surface.to.tmesh3d(): Get an rgl tmesh3d instance from a brain surface mesh.
fs.surface.vertex.neighbors(): Compute vertex neighborhoods or the full adjacency list for a mesh using the Rvcg or igraph library.
fsaverage.path(): Return path to fsaverage dir.
fsbrain.set.default.figsize(): Set default figure size for fsbrain visualization functions.
fup(): Transform first character of a string to uppercase.
gen.test.volume(): Generate test 3D volume of integers. The volume has an outer background area (intensity value 'bg') and an inner foreground areas (intensity value 200L).
geod.patches.color.overlay(): Generate color overlay from geodesic patches around several vertices.
geod.vert.neighborhood(): Compute all vertices within given geodesic distance on the mesh.
geodesic.circles(): Compute geodesic circles and ball stats for given vertices.
geodesic.dists.to.vertex(): Simple internal wrapper around Rvcg::vcgDijkstra with function check.
geodesic.path(): Compute geodesic path from a source vertex to one or more target vertices.
get.atlas.region.names(): Determine atlas region names from a subject.
get.rglstyle(): Get the default visualization style parameters as a named list.
get.view.angle.names(): Get list of valid view angle names.
getIn(): Retrieve values from nested named lists
get_optional_data_filepath(): Access a single file from the package cache by its file name.
group.agg.atlas.native(): Aggregate native space morphometry data over brain atlas regions and subjects for a group of subjects.
group.agg.atlas.standard(): Aggregate standard space morphometry data over brain atlas regions and subjects for a group of subjects.
group.annot(): Load annotations for a group of subjects.
group.concat.measures.native(): Concatenate native space data for a group of subjects.
group.concat.measures.standard(): Concatenate standard space data for a group of subjects.
group.label(): Retrieve label data for a group of subjects.
group.label.from.annot(): Extract a region from an atlas annotation as a label for a group of subjects.
group.morph.agg.native(): Aggregate native space morphometry data over one hemisphere for a group of subjects.
group.morph.agg.standard(): Aggregate standard space (fsaverage) morphometry data over one hemisphere for a group of subjects.
group.morph.agg.standard.vertex(): Aggregate standard space morphometry data over subjects.
group.morph.native(): Retrieve native space morphometry data for a group of subjects.
group.morph.standard(): Retrieve standard space morphometry data for a group of subjects.
group.morph.standard.sf(): Read combined data for a group from a single file.
group.multimorph.agg.native(): Aggregate native space morphometry data for multiple measures over hemispheres for a group of subjects.
group.multimorph.agg.standard(): Aggregate standard space (fsaverage) morphometry data for multiple measures over hemispheres for a group of subjects.
group.surface(): Retrieve surface mesh data for a group of subjects.
groupmorph.split.hemilist(): Split a per-vertex group data matrix for both hemispheres into a hemilist at given index.
hasIn(): Check for values in nested named lists
hemilist(): Create a hemilist from lh and rh data.
hemilist.derive.hemi(): Derive 'hemi' string from the data in a hemilist
hemilist.from.prefixed.list(): Create a hemilist from a named list with keys prefixed with 'lh_' and 'rh_'.
hemilist.get.combined.data(): Get combined data of hemi list
hemilist.unwrap(): Unwrap hemi data from a named hemi list.
hemilist.wrap(): Wrap data into a named hemi list.
highlight.points.spheres(): Draw small 3D spheres at given points.
highlight.vertices.on.subject(): Highlight vertices given by index on a subject's meshes by coloring faces.
highlight.vertices.on.subject.spheres(): Highlight vertices given by index on a subject's meshes by coloring faces.
highlight.vertices.spheres(): Draw small 3D spheres at given brain mesh vertices. Supports full brain (2 meshes) as well.
images.dimmax(): Compute max width and height of magick images.
is.fs.coloredmesh(): Check whether object is an fs.coloredmesh (S3)
is.fs.coloredvoxels(): Check whether object is an fs.coloredvoxels instance (S3)
is.fsbrain(): Check whether object is an fsbrain (S3)
is.hemilist(): Check whether x is a hemilist
label.border(): Compute border of a label.
label.colFn(): A simple colormap function for binary colors.
label.colFn.inv(): A simple colormap function for binary colors.
label.from.annotdata(): Extract a region from an annotation as a label.
label.to.annot(): Merge several labels into an annotation
labeldata.from.mask(): Create labeldata from a mask.
limit_fun(): Get data limiting function.
limit_fun_na(): Get data limiting function to NA.
limit_fun_na_inside(): Get data limiting function, setting values inside range to NA.
list_optional_data(): Get file names available in package cache.
mask.from.labeldata.for.hemi(): Create a binary mask from labels.
mesh.vertex.neighbors(): Compute neighborhood of a vertex
mkco.cluster(): Return recommended 'makecmap_options' for diverging cluster data.
mkco.div(): Return recommended 'makecmap_options' for diverging data.
mkco.heat(): Return recommended 'makecmap_options' for sequential data with heatmap style.
mkco.seq(): Return recommended 'makecmap_options' for sequential data.
numverts.lh(): Determine vertex count of left hemi from hemilist of surfaces or the count itself.
numverts.rh(): Determine vertex count of right hemi from hemilist of surfaces or the count itself.
principal.curvatures(): Computes principal curvatures according to 2 definitions from raw k1 and k2 values.
print(<fs.coloredmesh>): Print description of a brain coloredmesh (S3).
print(<fs.coloredvoxels>): Print description of fs.coloredvoxels (S3).
print(<fsbrain>): Print description of an fsbrain (S3).
qc.for.group(): Perform data quality check based on computed region stats.
qc.from.regionwise.df(): Perform data quality check based on a dataframe containing aggregated region-wise data.
qc.from.segstats.tables(): Perform data quality check based on a segstats table.
qc.vis.failcount.by.region(): Visualize the number of outlier subjects per region in your dataset.
qdec.table.skeleton(): Generate skeleton dataframe for FreeSurfer QDEC long file from subjects list.
ras2vox_tkr(): The FreeSurfer default ras2vox_tkr matrix.
read.colorcsv(): Read colors from CSV file.
read.md.demographics(): Read demographics file
read.md.subjects(): Read subjects file
read.md.subjects.from.fsgd(): Read subjects list from an FSGD file.
regions.to.ignore(): Give suggestions for regions to ignore for an atlas.
report.on.demographics(): Print a demographics report
rglactions(): Create rglactions list, suitable to be passed as parameter to vis functions.
rglo(): Get rgloptions and consider global options.
rglot(): Get rgloptions for testing.
rglvoxels(): Draw 3D boxes at locations using rgl.
scale01(): Scale given values to range 0..1.
shape.descriptor.names(): Get all shape descriptor names.
shape.descriptors(): Computes geometric curvature-based descriptors.
shift.hemis.apart(): Shift hemispheres apart.
sjd.demo(): Download optional demo data if needed and return its path.
sjld(): Get subjects list from subjects.txt file in dir.
spread.values.over.annot(): Spread a single value for a region to all region vertices.
spread.values.over.hemi(): Spread the values in the region_value_list and return them for one hemisphere.
spread.values.over.subject(): Spread the values in the region_value_list and return them for one hemisphere.
subject.annot(): Load an annotation for a subject.
subject.annot.border(): Compute annot border vertices.
subject.atlas.agg(): Aggregate morphometry data over brain atlas regions for a subject.
subject.filepath.morph.native(): Construct filepath of native space morphometry data file.
subject.filepath.morph.standard(): Construct filepath of standard space morphometry data file.
subject.label(): Retrieve label data for a single subject.
subject.label.from.annot(): Extract a region from an atlas annotation as a label for a subject.
subject.lobes(): Load labels representing brain lobes.
subject.mask(): Compute a mask for a subject.
subject.morph.native(): Retrieve native space morphometry data for a single subject.
subject.morph.standard(): Retrieve standard space morphometry data for a single subject.
subject.num.verts(): Get subjects vertex count.
subject.surface(): Load a surface for a subject.
subject.volume(): Read a brain volume.
surface.curvatures(): Compute the k1 and k2 principal curvatures of a mesh.
tmesh3d.to.fs.surface(): Get an fs.surface brain mesh from an rgl tmesh3d instance.
vdata.split.by.hemi(): Split morph data vector at hemisphere boundary.
vertex.coords(): Return coordinates for vertices, supporting entire brain via hemilist.
vertex.hemis(): Return the proper hemi string ('lh' or 'rh') for each vertex.
vis.color.on.subject(): Visualize pre-defined vertex colors on a subject.
vis.coloredmeshes(): Visualize a list of colored meshes in a single scene.
vis.coloredmeshes.rotating(): Visualize a list of colored meshes in a single scene and rotate them, movie-style.
vis.colortable.legend(): Create a separate legend plot for a colortable or an annotation.
vis.data.on.fsaverage(): Visualize arbitrary data on the fsaverage template subject, if available.
vis.data.on.group.native(): Visualize native space data on a group of subjects.
vis.data.on.group.standard(): Visualize standard space data for a group on template.
vis.data.on.subject(): Visualize arbitrary data on the surface of any subject.
vis.dti.trk(): Visualize DTI tracks from Diffusion Toolkit/TrackVis TRK format file.
vis.export.from.coloredmeshes(): Export high-quality brainview image with a colorbar.
vis.fs.surface(): Visualize fs.surface mesh
vis.group.annot(): Plot atlas annotations for a group of subjects.
vis.group.coloredmeshes(): Plot coloredmeshes for a group of subjects.
vis.group.morph.native(): Plot native space morphometry data for a group of subjects.
vis.group.morph.standard(): Plot standard space morphometry data for a group of subjects.
vis.labeldata.on.subject(): Visualize a label on the surface of a subject.
vis.mask.on.subject(): Visualize a vertex mask on the surface of a subject.
vis.path.along.verts(): Draw a 3D line from vertex to vertex
vis.paths(): Visualize many paths.
vis.paths.along.verts(): Visualize several paths in different colors.
vis.region.values.on.subject(): Visualize arbitrary data, one value per atlas region, on the surface of any subject (including template subjects).
vis.rglwidget(): Visualize coloredmeshes as an interactive rgl WebGL widget for use in R Shiny apps and RMarkdown documents.
vis.seg.legend(): Plot legend for a brain volume segmentation based on colorLUT.
vis.subject.annot(): Visualize an annotation for a subject.
vis.subject.label(): Visualize a binary label for a subject.
vis.subject.morph.native(): Visualize native space morphometry data for a subject.
vis.subject.morph.standard(): Visualize native space morphometry data for a subject or a group.
vis.subject.pre(): Visualize pre-loaded data.
vis.symmetric.data.on.subject(): Visualize clusters or activation data on the surface of any subject.
vis.volume.on.surface(): Visualize a brain volume overlaid on a cortical surface in 3D.
vislayout.from.coloredmeshes(): Visualize coloredmeshes from several angles and combine the images into a new figure.
vol.boundary.box(): Compute 3D bounding box of a volume.
vol.boundary.box.apply(): Apply a boundary box to a volume, returning the inner volume part
vol.hull(): Retain only the outer hull voxels of the foreground.
vol.imagestack(): Turn volume into an ImageMagick image stack.
vol.intensity.to.color(): Convert integer intensity image to RGB color string form.
vol.mask.from.segmentation(): Extract subset from a volume by value.
vol.merge(): Merge background volume and overlay to new colors.
vol.overlay.colors.from.activation(): Generate colors for a 3D volume, based on the activation data and a colormap.
vol.overlay.colors.from.colortable(): Compute voxel colors based on colortable.
vol.planes(): Translate names and indices of planes.
vol.slice(): Extract a slice of a 3D image stack.
vol.vox.from.crs(): Compute R voxel index for FreeSurfer CRS voxel index.
volvis.contour(): Visualize contour of a volume.
volvis.lb(): Show continuous 3D voxel/volume data as a lightbox, optionally with a background brain volume and colormap.
volvis.lb.with.surface(): Visualize volume slices with surface mesh contours overlaid in lightbox view.
volvis.lightbox(): Draw a lightbox view from volume slices.
volvis.slices.with.surface(): Export individual volume slices with surface contours to image files.
volvis.voxels(): Voxel-based visualization of volume mask at surface RAS positions.
vox2ras_tkr(): The FreeSurfer default vox2ras_tkr matrix.
write.group.morph.standard(): Write standard space group data to a standard FreeSurfer directory stucture.
write.group.morph.standard.mf(): Write per-vertex standard space data for a group of subjects to given file names.
write.group.morph.standard.sf(): Reshape and write combined per-vertex data for a group to a single MGH file.
write.region.aggregated(): Write data aggregated over regions to morphometry file for group.
write.region.values(): Write one value per atlas region for a subject.
write.region.values.fsaverage(): Write one value per atlas region for a template subject.