Learn R Programming

nat.templatebrains (version 0.6.2)

bridging_graph: Make or query connected graph of bridging registrations

Description

These functions are designed for expert use. In general it is recommended to use xform_brain.

bridging_graph creates an igraph::graph representing all known template brains (vertices) and the bridging registrations connecting them (edges).

shortest_bridging_seq finds the shortest bridging sequence on a graph of all available bridging registrations, subject to constraints defined by graph connectivity and the reciprocal parameter.

Usage

bridging_graph(regdirs = getOption("nat.templatebrains.regdirs"), reciprocal = NA)
shortest_bridging_seq(sample, reference, checkboth = TRUE, imagedata = FALSE, reciprocal = NA, ...)

Arguments

regdirs
Character vector of directories to search for registrations (see details)
reciprocal
Sets the weight of reciprocal edges in the graph (and thereby whether inverse registrations will be considered).
sample
Source template brain (e.g. IS2) that data is currently in.
reference
Target template brain (e.g. IS2) that data should be transformed into.
checkboth
When TRUE will look for registrations in both directions. See details.
imagedata
Whether x should be treated as image data (presently only supported as a file on disk or 3D object vertices - see details).
...
extra arguments to pass to xform.

Details

When reciprocal != NAwe create a graph where each forward transformation is matched by a corresponding inverse transformation with the specified edge weight. The edge weight for forward transforms will always be 1.0.

By default regdirs is set to getOption('nat.templatebrains.regdirs')

See Also

allreg_dataframe

Examples

Run this code
## Not run: 
# plot(bridging_graph(reciprocal=3), vertex.size=25)
# # the same including
# plot(bridging_graph(), vertex.size=25)
# ## End(Not run)
## Not run: 
# shortest_bridging_seq(FCWB, IS2)
# # or
# shortest_bridging_seq('FCWB', 'IS2')
# ## End(Not run)

Run the code above in your browser using DataLab