| vis.group.morph.standard {fsbrain} | R Documentation | 
Plot standard space morphometry data for a group of subjects.
Description
Plot standard space morphometry data for a group of subjects and combine them into a single large image.
Usage
vis.group.morph.standard(
  subjects_dir,
  subject_id,
  measure,
  fwhm = "10",
  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  | 
measure | 
 vector of character strings, the morphometry measures, e.g.,   | 
fwhm | 
 vector of character strings, the smoothing kernel FWHM strings, e.g.,   | 
view_angles | 
 see   | 
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:   | 
... | 
 extra parameters passed to the subject level visualization function. Not all may make sense in this context. Example:   | 
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 'subject_id' parameter. This function is vectorized over 'subject_id', 'measure' and 'fwhm'.
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.data.on.group.standard(),
vis.group.annot(),
vis.group.coloredmeshes(),
vis.group.morph.native()