vis.data.on.group.standard: Visualize standard space data for a group on template.

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

Visualize standard space data for a group on template.

Description

Plot standard space data for a group of subjects onto a template brain and combine the tiles into a single large image.

Usage

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

Arguments

subjects_dir	character string, the path to the SUBJECTS_DIR containing the template subject
vis_subject_id	character string, the template subject name. A typical choice is 'fsaverage'.
morph_data_both	named list of numerical vectors, 4D array or dataframe, the morph data for both hemispheres of all subjects. Can be loaded with group.morph.standard or group.morph.standard.sf.
captions	optional vector of character strings, the short text annotations for the individual tiles. Typically used to plot the subject identifier.
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.
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 subject data are plotted row-wise, in the order in which they appear in the 'morph_data_both' parameter.

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.native(), 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.