| Title: | Diffusion Map and Spectral Map |
|---|---|
| Description: | Implements the diffusion map method of dimensionality reduction and spectral method of combining multiple diffusion maps, including creation of the spectra and visualization of maps. |
| Authors: | Tianhao Wu [aut, cre] |
| Maintainer: | Tianhao Wu <[email protected]> |
| License: | GNU General Public License version 2 |
| Version: | 1.0 |
| Built: | 2024-11-16 03:03:03 UTC |
| Source: | https://github.com/cran/SpectralMap |
Implements the diffusion map method of dimensionality reduction and spectral method of combining multiple diffusion maps, including creation of the spectra and visualization of maps.
SpectralMap(data, epsilon=0.1, range=1, Plot2D=FALSE, Plot3D=FALSE)SpectralMap(data, epsilon=0.1, range=1, Plot2D=FALSE, Plot3D=FALSE)
data |
a list of datasets and each column in each dataset is a variable |
epsilon |
parameter in the Gaussian kernel |
range |
indexes of the datasets in the data list to be combined and computed. If length(range)==1, only diffusion map will be computed. Otherwise, spectral map will be computed |
Plot2D |
a logical value indicating whether a 2-D map should be plotted |
Plot3D |
a logical value indicating whether a 3-D map should be plotted |
singularvector |
the spectra of either diffusion map or spectral map |
#generate two datasets n <- 100 theta <- 2*pi*seq(from=0, to=1-1/n, by=1/n) r = (1 + cos(6*theta)/4) # X is a circle X1 = cos(theta) X2 = sin(theta) X<-data.frame(X1,X2) #Y is a hexagon Y1 = r*cos(theta) Y2 = r*sin(theta) Y<-data.frame(Y1,Y2) #create data list Data<-list(X,Y) #create the diffusion map of X example1<-SpectralMap(Data, epsilon=0.1, range=1, Plot2D=TRUE, Plot3D=FALSE) #create the spectral map from X to Y example2<-SpectralMap(Data, epsilon=0.1, range=1:2, Plot2D=TRUE, Plot3D=FALSE)#generate two datasets n <- 100 theta <- 2*pi*seq(from=0, to=1-1/n, by=1/n) r = (1 + cos(6*theta)/4) # X is a circle X1 = cos(theta) X2 = sin(theta) X<-data.frame(X1,X2) #Y is a hexagon Y1 = r*cos(theta) Y2 = r*sin(theta) Y<-data.frame(Y1,Y2) #create data list Data<-list(X,Y) #create the diffusion map of X example1<-SpectralMap(Data, epsilon=0.1, range=1, Plot2D=TRUE, Plot3D=FALSE) #create the spectral map from X to Y example2<-SpectralMap(Data, epsilon=0.1, range=1:2, Plot2D=TRUE, Plot3D=FALSE)