vis.data.on.group.native: Visualize native space data on a group of subjects.

In dfsp-spirit/fsbrain: Managing and Visualizing Brain Surface Data

Visualize native space data on a group of subjects.

Description

Plot surface data on the native space surfaces of a group of subjects and combine the tiles into a single large image.

Usage

vis.data.on.group.native(
  subjects_dir,
  subject_id,
  morph_data_both,
  view_angles = "sd_dorsal",
  output_img = "fsbrain_group_morph.png",
  num_per_row = 5L,
  captions = subject_id,
  rglactions = list(no_vis = TRUE),
  ...
)

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.
subject_id	vector of character strings, the subject identifiers
morph_data_both	named list of numerical vectors, the morph data for both hemispheres of all subjects. Can be loaded with group.morph.native.
view_angles	see get.view.angle.names.
output_img	character string, the file path for the output image. Should end with '.png'.
num_per_row	positive integer, the number of tiles per row.
captions	optional vector of character strings, the short text annotations for the individual tiles. Typically used to plot the subject identifier.
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.
...	extra parameters passed to the subject level visualization function. Not all may make sense in this context. Example: surface='pial'.

Value

named list, see the return value of arrange.brainview.images.grid for details.

Note

The subjects are plotted row-wise, in the order in which they appear in the 'morph_data_both' parameter. The surfaces are loaded in the order of the 'subject_id' parameter, so the order in both must match.

You can force an identical plot range for all subjects, so that one color represents identical values across subjects, via 'makecmap_options'. E.g., for the ... parameter, pass makecmap_options=list('colFn'=viridis::viridis, 'range'=c(0, 4))).

See Also

Other group visualization functions: vis.data.on.group.standard(), vis.group.annot(), vis.group.coloredmeshes(), vis.group.morph.native(), vis.group.morph.standard()

dfsp-spirit/fsbrain documentation built on Nov. 28, 2024, 10:29 a.m.