fsbrain (version 0.4.3)

vis.labeldata.on.subject: Visualize a label on the surface of a subject.

Description

Visualizes a label. Note that a label is just a set of vertices, and that you can use this function to visualize sets of vertices, e.g., to see where on the mesh a certain vertex lies. It may be helpful the visualize the vertex with its neighbors, because otherwise it may be too small to spot. Use the function [fsbrain::mesh.vertex.neighbors] to get them. It is advisable to set the view to the interactive 'si' mode and use the 'inflated' surface to identify single vertices.

Usage

vis.labeldata.on.subject(
  subjects_dir,
  vis_subject_id,
  lh_labeldata,
  rh_labeldata,
  surface = "white",
  colormap = NULL,
  views = c("t4"),
  rgloptions = rglo(),
  rglactions = list(),
  draw_colorbar = FALSE,
  makecmap_options = list(colFn = label.colFn.inv),
  ...
)

Arguments

subjects_dir

string. The FreeSurfer SUBJECTS_DIR, i.e., a directory containing the data for all your subjects, each in a subdir named after the subject identifier.

vis_subject_id

string. The subject identifier from which to obtain the surface for data visualization. Example: 'fsaverage'.

lh_labeldata

integer vector of vertex indices for the left hemisphere

rh_labeldata

integer vector of vertex indices for the right hemisphere

surface

string. The display surface. E.g., "white", "pial", or "inflated". Defaults to "white".

colormap

a colormap function. **DEPRECATED**: use parameter 'makecmap_options' instead, like this: makecmap_options=list('colFn'=terrain.colors).

views

list of strings. Valid entries include: 'si': single interactive view. 't4': tiled view showing the brain from 4 angles. 't9': tiled view showing the brain from 9 angles.

rgloptions

option list passed to par3d. Example: rgloptions = list("windowRect"=c(50,50,1000,1000)).

rglactions

named list. A list in which the names are from a set of pre-defined actions. The values can be used to specify parameters for the action. The following example clips outliers in the data before plotting and writes a screenshot in PNG format: rglactions = list("snapshot_png"="~/fsbrain.png", "clip_data"=c(0.05, 0.95)). See rglactions.

draw_colorbar

logical or one of the character strings 'vertical' or 'horizontal', whether to draw a colorbar. Notice: the colorbar is drawn to a separate subplot, and this only works if there is enough space for it, i.e., the plot resolution must be high enough. You may have to increase the plot size for the colorbar to show up, see the vignette for instructions. Defaults to `FALSE`. See coloredmesh.plot.colorbar.separate for an alternative.

makecmap_options

named list of parameters to pass to makecmap. Must not include the unnamed first parameter, which is derived from 'measure'. Should include at least a colormap function as name 'colFn'.

...

extra arguments to pass to coloredmesh.from.label.

Value

list of coloredmeshes. The coloredmeshes used for the visualization.

See Also

Other label functions: apply.label.to.morphdata(), apply.labeldata.to.morphdata(), subject.lobes(), subject.mask(), vis.subject.label()

Other visualization functions: highlight.vertices.on.subject(), vis.color.on.subject(), vis.data.on.fsaverage(), vis.data.on.subject(), vis.mask.on.subject(), vis.region.values.on.subject(), vis.subject.annot(), vis.subject.label(), vis.subject.morph.native(), vis.subject.morph.standard(), vis.symmetric.data.on.subject(), vislayout.from.coloredmeshes()

Examples

# NOT RUN {
   fsbrain::download_optional_data();

  # Define the data to use:
  subjects_dir = fsbrain::get_optional_data_filepath("subjects_dir");
  lh_labeldata = c(1000, 1001, 1002);   # only the vertices, will be tiny.
  subject_id = 'subject1';
  surface = 'white'; # Should use 'inflated', but we do not currently
                     # ship it for the example subject to reduce download size.

  # For the right hemi, extend them to neighborhood for better visibility:
  rh_labeldata = c(500, 5000);
  rh_surface = subject.surface(subjects_dir, subject_id, surface, 'rh');
  rh_labeldata_neighborhood = mesh.vertex.neighbors(rh_surface, rh_labeldata);
  vis.labeldata.on.subject(subjects_dir, subject_id, lh_labeldata,
   rh_labeldata_neighborhood$vertices, surface=surface, views=c('si'));
# }
# NOT RUN {
# }