plot2d: plot function

In WPKDE: Weighted Piecewise Kernel Density Estimation

Description

plot all the data points(black spots in the plot) and peaks(red spots in the plot) in one coordinate system

Usage

plot2d(x,matPeaks,evalpointsX,evalpointsY)

Arguments

x	data points in the format n*2 matrix
matPeaks	matrix returned by the findPeak function
evalpointsX	points at which the matPeaks is evaluated at x-axis direction
evalpointsY	points at which the matPeaks is evaluated at y-axis direction

Details

The function plot2d is mainly designed to make the result of functions kdeC and findPeak visual

Author(s)

Kunyu Ye

Examples

data.gen<-function(n.peaks=100, N=1e5, max.var=0.001, max.corr=0.5)
{
  library(mvtnorm)

  dat<-matrix(0, nrow=N, ncol=2)
  all.m<-c(NA,NA)

  for(i in 1:n.peaks)
  {
    this.m<-runif(2)
    this.var<-runif(2, min=0.1*max.var, max=max.var)
    this.cov<-runif(1, min=-1*max.corr, max=max.corr) * sqrt(this.var[1])* sqrt(this.var[2])
    this.s<-matrix(c(this.var[1], this.cov, this.cov, this.var[2]),ncol=2)

    dat[((i-1)*N/n.peaks+1):(i*N/n.peaks),]<-rmvnorm(N/n.peaks, mean=this.m, sigma=this.s)
    all.m<-rbind(all.m, this.m)
  }

  all.m[,1]<-(all.m[,1]-min(dat[,1]))/diff(range(dat[,1]))
  all.m[,2]<-(all.m[,2]-min(dat[,2]))/diff(range(dat[,2]))
  dat[,1]<-(dat[,1]-min(dat[,1]))/diff(range(dat[,1]))
  dat[,2]<-(dat[,2]-min(dat[,2]))/diff(range(dat[,2]))

  all.m<-all.m[-1,]
  return(list(dat=dat,m=all.m))
}

r<-data.gen(n.peaks=100, N=1e5, max.var=0.001, max.corr=0.5)

k1<-kdeC(r$dat, H=c(0.005,0.005),  gridsize = c(501,501), cutNum=c(1,1))

matPeaks<-findPeak(estimate=k1$estimate,filter=0)

plot2d(x=r$dat,matPeaks=matPeaks,evalpointsX=k1$evalpointsX,evalpointsY=k1$evalpointsY)

WPKDE documentation built on May 2, 2019, 10:33 a.m.