nat.templatebrains (version 1.1)

mirror_brain: Mirror 3D object around a given axis, optionally using a warping registration

Description

Mirror 3D object around a given axis, optionally using a warping registration

Usage

mirror_brain(
  x,
  brain = regtemplate(x),
  mirrorAxis = c("X", "Y", "Z"),
  transform = c("warp", "affine", "flip"),
  ...
)

Value

A transformed version of x

Arguments

x

the 3D object to be mirrored.

brain

source template brain (e.g. IS2) that data is in.

mirrorAxis

the axis to mirror (default "X").

transform

whether to use warp (default) or affine component of registration, or simply flip about midplane of axis.

...

extra arguments to pass to mirror.

See Also

xform_brain, regtemplate

Examples

data(FCWB.demo)
# Simple mirror along the x i.e. medio-lateral axis
kcs20.flip=mirror_brain(kcs20, FCWB.demo, transform='flip')

## Full non-rigid mirroring to account for differences in shape/centering of
## template brain.
## Depends on nat.flybrains package and system CMTK installation
if (FALSE) {
library(nat.flybrains)
kcs20.right=mirror_brain(kcs20, FCWB, .progress='text')
plot3d(kcs20, col='red')
plot3d(kcs20.right, col='green')
# include surface plot of brain
plot3d(FCWB)

# Compare simple flip with full mirror
# This template brain is highly symmetric so these are almost identical
clear3d()
plot3d(kcs20.flip, col='blue')
plot3d(kcs20.right, col='green')

# Convert to JFRC2 and do the same
kcs20.jfrc2=xform_brain(kcs20, sample = FCWB, reference=JFRC2, .progress='text')
kcs20.jfrc2.right=mirror_brain(kcs20.jfrc2, JFRC2, .progress='text')
kcs20.jfrc2.flip=mirror_brain(kcs20.jfrc2, JFRC2, transform='flip')
clear3d()
# This time there is a bigger difference between the two transformations
plot3d(kcs20.jfrc2.flip, col='blue')
plot3d(kcs20.jfrc2.right, col='green')
# plot mushroom body neuropils as well
plot3d(JFRC2NP.surf, "MB.*_R", alpha=0.3, col='grey')

# Compare Euclidean distance between corresponding points in all neurons
diffs=xyzmatrix(kcs20.jfrc2.flip)-xyzmatrix(kcs20.jfrc2.right)
hist(sqrt(rowSums(diffs^2)), xlab='Distance /microns')
}

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