Plot a NeuroSlice

Plot a NeuroSlice

plot an NeuroVol as a series of 2D slices

Usage

# S4 method for class 'NeuroSlice'
plot(
  x,
  cmap = gray(seq(0, 1, length.out = 255)),
  irange = range(x, na.rm = TRUE)
)

# S4 method for class 'NeuroVol'
plot(
  x,
  cmap = gray(seq(0, 1, length.out = 255)),
  zlevels = unique(round(seq(1, dim(x)[3], length.out = 6))),
  irange = range(x, na.rm = TRUE),
  thresh = c(0, 0),
  alpha = 1,
  bgvol = NULL,
  bgcmap = gray(seq(0, 1, length.out = 255))
)

Arguments

x

the object to display

cmap

a color map consisting of a vector of colors in hex format (e.g. gray(n=255))

irange

the intensity range indicating the low and high values of the color scale.

zlevels

the series of slice indices to display.

thresh

a 2-element vector indicating the lower and upper transparency thresholds.

alpha

the level of alpha transparency

bgvol

a background volume that serves as an image underlay (currently ignored).

bgcmap

a color map for backround layer consisting of a vector of colors in hex format (e.g. gray(n=255))

Details

The plot method uses ggplot2 to create a raster visualization of the slice data. The intensity values are mapped to colors using the specified colormap and range.

Examples

# Create example slice
slice_space <- NeuroSpace(c(100, 100))
slice_data <- matrix(rnorm(100*100), 100, 100)
slice <- NeuroSlice(slice_data, slice_space)

if (FALSE) { # \dontrun{
# Basic plot
plot(slice)

# Custom colormap
library(viridis)
plot(slice, cmap = viridis(255))

# Custom intensity range
plot(slice, irange = c(-2, 2))
} # }


dat <- matrix(rnorm(100*100), 100, 100)
slice <- NeuroSlice(dat, NeuroSpace(c(100,100)))
#plot(slice)