Create a CIFTI-2 axis for scalar or label maps.

A scalars axis holds a set of maps (e.g. the myelin map and the cortical thickness of a subject in one .dscalar file), a labels axis holds a set of label maps (one per parcellation in a .dlabel file). Both are described by their map names; a labels axis can additionally have a label table per map, which maps the integer label keys in the data to names and colors.

Usage

cifti.axis.scalars(names = NULL, metadata = NULL)

Arguments

names

character vector or NULL, the map names. The number of maps is the number of names, so this has to be given (use empty strings for unnamed maps).

metadata

list of metadata lists or NULL, one per map. Each metadata list is a named list of character strings, as returned for a map by read.cifti.header. This is used for the palette information that Connectome Workbench stores per map.

Value

a named list with the entries 'type' and 'named_maps', an axis to be passed to cifti.header.from.axes or write.cifti.

See also

Other cifti functions: cifti.axis.brain.models(), cifti.axis.from.template(), cifti.axis.labels(), cifti.axis.parcels(), cifti.axis.parcels.from.annot(), cifti.axis.series(), cifti.brain.model.surface(), cifti.brain.model.volume(), cifti.dim.labels(), cifti.file.type.for.axes(), cifti.grayordinates(), cifti.header.from.axes(), cifti.label.table(), cifti.parcel(), cifti.parcels(), cifti.series.info(), cifti.structure.data(), cifti.structures(), cifti.volume(), print.fs.cifti(), print.fs.cifti.data(), print.fs.connectome(), read.cifti(), read.cifti.header(), read.cifti.rows(), read.fs.connectome.cifti(), write.cifti(), write.fs.connectome.cifti(), write.fs.morph.cifti(), write.fs.parcellated.cifti(), write.fs.parcellation.cifti(), write.fs.series.cifti()

Examples

axis <- cifti.axis.scalars(c("thickness", "area"))
length(axis$named_maps)
#> [1] 2