multiband (version 0.1.0)

cepii: Light curve data from two bands

Description

A dataset containing band I and V data from OGLE-LMC-T2CEP-009. There are two data frames, iband and vband, each of which has three columns. (time,magnitude,magnitude error).

Format

Two data frames with 3 variables, and 554 (iband) and 65 (vband) rows.

Examples

## Load I and V bands
iband <- cepii[[1]]
vband <- cepii[[2]]

## Try finer grid sizes as well, e.g. 'nOmega <- 500'
nOmega <- 10
omega_seq <- seq(3.5,3.65,length.out=nOmega)
sol_ls <- vector(mode="list",length=nOmega)
RSS_ls <- double(nOmega)

## Drastically subsample the data and see if the methods can find the period.
subi <- seq(1,nrow(iband),by=20)

## 1. Lomb Scargle on I band and V band separately
for (i in 1:nOmega) {
  sol_ls[[i]] <- lomb_scargle(iband[subi,1],iband[subi,2],iband[subi,3],omega_seq[i])
  RSS_ls[i] <- sol_ls[[i]]$RSS
}
plot(omega_seq,RSS_ls,xlab=expression(omega),ylab='RSS',main='I band',pch=16)

subv <- seq(1,nrow(vband),by=4)
for (i in 1:nOmega) {
  sol_ls[[i]] <- lomb_scargle(vband[subv,1],vband[subv,2],vband[subv,3],omega_seq[i])
  RSS_ls[i] <- sol_ls[[i]]$RSS
}
plot(omega_seq,RSS_ls,xlab=expression(omega),ylab='RSS',main='V band',pch=16)

## 2. Naive pooled Lomb Scargle versus Fused
tms <- vector(mode="list",length=2)
tms[[1]] <- iband[subi,,drop=FALSE]
tms[[2]] <- vband[subv,,drop=FALSE]
B <- length(tms)
t <- c(); m <- c(); sigma <- c()
for (b in 1:B) {
  t <- c(t,tms[[b]][,1])
  m <- c(m,tms[[b]][,2])
  sigma <- c(sigma,tms[[b]][,3])
}

sol_ls <- vector(mode="list",length=nOmega)
sol_bcd <- vector(mode="list",length=nOmega)
RSS_seq <- double(nOmega)
RSS_ls_seq <- double(nOmega)
gamma1 <- 1000
gamma2 <- 10
for (i in 1:nOmega) {
  sol_ls[[i]] <- lomb_scargle(t,m,sigma,omega_seq[i])
  RSS_ls_seq[i] <- sol_ls[[i]]$RSS
  beta0_ls <- rep(sol_ls[[i]]$beta0,B)
  A_ls <- rep(sol_ls[[i]]$A,B)
  rho_ls <- rep(sol_ls[[i]]$rho,B)
  sol_bcd[[i]] <- bcd_inexact(tms,beta0_ls,A_ls,rep(1,B),rho_ls,omega_seq[i],gamma1,gamma2,
    max_iter=1e4,tol=1e-10)
  RSS_seq[i] <- pnll(tms,sol_bcd[[i]]$beta0,sol_bcd[[i]]$A,rep(1,B),
    sol_bcd[[i]]$rho,omega_seq[i],0,0)
  print(paste0("Completed ", i))
}

plot(omega_seq,RSS_seq,xlab=expression(omega),ylab='RSS',main='I & V band fusion',pch=16)
plot(omega_seq,RSS_ls_seq,xlab=expression(omega),ylab='RSS',main='naive Lomb-Scargle',pch=16)
ix_min <- which(RSS_seq==min(RSS_seq))
sol_bcd_final <- sol_bcd[[ix_min]]