dimReduction

Overview

This vignette describes the usage of the dimReduction parameter in the pandemonium app and how new functions can be written for it.

what the function takes

mat = n x m matrix of coordinates to reduce dist = n x n distance matrix.

What the function should return:

dimReduction(mat = mat, ist = dist)$Y = n x 2 matrix or data frame with dimension reduced coordinates

How to write new functions

The standard way to write a new function to be passed to dimReduction is as a wrapper for a common dimension reduction algorithm. THe defined function must be able to take mat and dist as parameters. If only one of them is used it is best to write the function with space for additional parameters with ... as seen in the following example.

tSNE_mat <- function(mat,...) {
  coord_red = list()
  coord_red$Y = Rtsne::Rtsne(mat)$Y
  coord_red
}

tSNE_dist <- function(dist,...) {
  coord_red = list()
  coord_red$Y = Rtsne::Rtsne(dist, is.dist = TRUE)$Y
  coord_red
}

newPandemonium(df, dim_reduction = list(tSNE_mat = tSNE_mat, tSNE_dist = tSNE_dist))

Some algorithms may take a distances object instead of a distance matrix. This can be done by converting the distance matrix using stats::as.dist(). As done with umap.

umap <- function(dist,...) {
  ret <- list()
  ret$Y <- uwot::umap(stats::as.dist(dist))
  ret
}

newPandemonium(df, dim_reduction = list(umap = umap))