vis.mask.on.subject | R Documentation |
A mask is a logical vector that contains one value per vertex. You can create it manually, or use functions like mask.from.labeldata.for.hemi
to create and modify it. Check the example for this function.
vis.mask.on.subject(
subjects_dir,
vis_subject_id,
mask_lh,
mask_rh,
surface = "white",
views = c("t4"),
rgloptions = rglo(),
rglactions = list(),
draw_colorbar = FALSE,
makecmap_options = list(colFn = label.colFn.inv),
style = "default"
)
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'. |
mask_lh |
logical vector or NULL, the mask to visualize on the left hemisphere surface. Must have the same length as the lh surface of the vis_subject_id has vertices. If NULL, this surface will not be rendered. Only one of mask_lh or mask_rh is allowed to be NULL. |
mask_rh |
logical vector or NULL, the mask to visualize on the right hemisphere surface. Must have the same length as the rh surface of the vis_subject_id has vertices. If NULL, this surface will not be rendered. Only one of mask_lh or mask_rh is allowed to be NULL. |
surface |
string. The display surface. E.g., "white", "pial", or "inflated". Defaults to "white". |
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 |
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: |
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 |
makecmap_options |
named list of parameters to pass to |
style |
character string, a rendering style, e.g., 'default', 'shiny' or 'semitransparent'. |
list of coloredmeshes. The coloredmeshes used for the visualization.
Drawing a colorbar for label data makes limited sense, use a legend instead. The colorbar can give a rough overview of the relative number of label and non-label vertices though, so it is possible to request one.
Other mask functions:
coloredmesh.from.mask()
,
mask.from.labeldata.for.hemi()
Other visualization functions:
highlight.vertices.on.subject()
,
highlight.vertices.on.subject.spheres()
,
vis.color.on.subject()
,
vis.data.on.fsaverage()
,
vis.data.on.subject()
,
vis.labeldata.on.subject()
,
vis.region.values.on.subject()
,
vis.subject.annot()
,
vis.subject.label()
,
vis.subject.morph.native()
,
vis.subject.morph.standard()
,
vis.subject.pre()
,
vis.symmetric.data.on.subject()
,
vislayout.from.coloredmeshes()
## Not run:
fsbrain::download_optional_data();
# Define the data to use:
subjects_dir = fsbrain::get_optional_data_filepath("subjects_dir");
subject_id = 'subject1';
surface = 'white';
hemi = 'both';
atlas = 'aparc';
region = 'bankssts';
# Create a mask from a region of an annotation:
lh_annot = subject.annot(subjects_dir, subject_id, 'lh', atlas);
rh_annot = subject.annot(subjects_dir, subject_id, 'rh', atlas);
lh_label = label.from.annotdata(lh_annot, region);
rh_label = label.from.annotdata(rh_annot, region);
lh_mask = mask.from.labeldata.for.hemi(lh_label, length(lh_annot$vertices));
rh_mask = mask.from.labeldata.for.hemi(rh_label, length(rh_annot$vertices));
# Edit the mask: add the vertices from another region to it:
region2 = 'medialorbitofrontal';
lh_label2 = label.from.annotdata(lh_annot, region2);
rh_label2 = label.from.annotdata(rh_annot, region2);
lh_mask2 = mask.from.labeldata.for.hemi(lh_label2, length(lh_annot$vertices),
existing_mask = lh_mask);
rh_mask2 = mask.from.labeldata.for.hemi(rh_label2, length(rh_annot$vertices),
existing_mask = rh_mask);
# Visualize the mask:
vis.mask.on.subject(subjects_dir, subject_id, lh_mask2, rh_mask2);
## End(Not run)
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