getStarsAtHighestDensityRegion: Perform cut in the membership list based on the 2D space...

In UPMASK: Unsupervised Photometric Membership Assignment in Stellar Clusters

Description

getStarsAtHighestDensityRegion will compute the 2D Kernel Density Estimation for the requested subset of data and will return only the stars in the most dense region.

Usage

getStarsAtHighestDensityRegion(ocdata_out, threshold=2, posIdx=c(1,2), 
plotAnalysis=FALSE, verbose=FALSE)

Arguments

ocdata_out	a data frame to use
threshold	a double with the thresholding level
posIdx	an array of integers indicating the columns of the data frame containing the spatial positions
plotAnalysis	a boolean indicating if the anaylsis should be plotted
verbose	a boolean indicating if the code should be verbose

Value

A data frame with the objects which were selected from ocdata_out

Author(s)

Alberto Krone-Martins, Andre Moitinho

Examples

# Create a simple data set
toyDataDF <- data.frame(x=runif(50, 0, 10), y=runif(50, 0, 10), resMclust.class=rep(1, 50))
toyDataDF <- rbind(toyDataDF, data.frame(x=rnorm(50, 2, 3), 
                   y=rnorm(50, 4, 3), resMclust.class=rep(1, 50)))

# Perform the XY density based cut
toyRes <- getStarsAtHighestDensityRegion(toyDataDF)

# Clean the environment
rm(list=c("toyDataDF", "toyRes"))
 

UPMASK documentation built on May 2, 2019, 2:39 p.m.