manifoldMap: Visualize an embedding by plotting with images

In elbamos/largeVis: High-Quality Visualizations of Large, High-Dimensional Datasets

Description

Makes a plot of n images sampled from images, positions at coordinates given by x.

Usage

manifoldMap(x, n = nrow(x), images, scale = 1, ...)

Arguments

x	A largeVis object or [N,D] matrix of coordinates.
n	The number of images to sample.
images	The images. A 3-D or 4-D array.
scale	Proportion to scale the images to.
...	Addiitional parameters passed to plot.

Details

The images can be passed in either as a list or a 3- or 4-dimensional array. The first dimension is n.

If the objects in the list are matrix objects, or the array is 3-dimensional, the images will be treated as greyscale. If there is an additional dimension, it must have a length of 3 and be RGB color layers.

References

Andrej Karpapthy. t-SNE Visualization of CNN Codes.

See Also

ggManifoldMap

Examples

## Not run: 
load("mnist.Rda")
load("mnistcoordinates.Rda")

flip <- function(x) apply(x,2,rev)
rotate <- function(x) t(flip(x))

mnistimages <- apply(mnist$images,
   MARGIN=1,
   FUN = function(x) as.array(rotate(flip(x))))
mnistimages <- t(mnistimages)
dim(mnistimages) <- c(42000, 28, 28)

manifoldMap(coords,
   1000,
   scale = 0.07,
   mnistimages)

## End(Not run)

elbamos/largeVis documentation built on May 16, 2019, 2:58 a.m.