Predict new data points using an existing DiffusionMap. The resulting matrix can be used in the plot method for the DiffusionMap

Description

Predict new data points using an existing DiffusionMap. The resulting matrix can be used in the plot method for the DiffusionMap

Usage

dm.predict(dm, new.data)

Arguments

Value

A nrow(new.data) \times ncol(eigenvectors(dif)) matrix of projected diffusion components for the new data.

Examples

data(guo)
g1 <- guo[, guo$num.cells != 32L]
g2 <- guo[, guo$num.cells == 32L]
dm <- DiffusionMap(g1)
dc2 <- dm.predict(dm, g2)
plot(dm, new.dcs = dc2)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(destiny)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/destiny/dm.predict.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dm.predict
> ### Title: Predict new data points using an existing DiffusionMap. The
> ###   resulting matrix can be used in the plot method for the DiffusionMap
> ### Aliases: dm.predict
> 
> ### ** Examples
> 
> data(guo)
> g1 <- guo[, guo$num.cells != 32L]
> g2 <- guo[, guo$num.cells == 32L]
> dm <- DiffusionMap(g1)
> dc2 <- dm.predict(dm, g2)
> plot(dm, new.dcs = dc2)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>