d1 <- read.table("CalphaNMA.dat")
d2 <- read.table("allAtomNMA.dat")
d3 <- read.table("PCA.dat")


pdf("methods_compare_overlap.pdf", onefile=TRUE)
#postscript("methods_compare_overlap.ps", paper='special', width=6, height=6, horizontal=FALSE)
par(mfrow=c(1,1))

plot(d1[,1], d1[,2], type='o', xlab="PCA mode number", ylab="Squared Overlap", main="Overlap values for NMA and PCA", ylim=c(0,0.7), xlim=c(0,20))

lines(d2[,1], d2[,2], col=2, type='o')
lines(d3[,1], d3[,2], col=3, type='o')

legend(12,0.7, c("C-alpha NMA", "All atom NMA", "PCA"), col=c(1,2,3), lty=c(1,1,1))


d1 <- read.table("CalphaNMA.CUM.dat")
d2 <- read.table("allAtomNMA.CUM.dat")
d3 <- read.table("PCA.CUM.dat")

pdf("methods_compare_overlap.CUM.pdf", onefile=TRUE)
#postscript("methods_compare_overlap.CUM.ps", paper='special', width=6, height=6, horizontal=FALSE)
par(mfrow=c(1,1))
plot(d1[,1], d1[,2], type='o', xlab="PCA mode number", ylab="Cumulative Squared Overlap", main="Cumulative Overlap values for NMA and PCA", ylim=c(0,1), xlim=c(0,20))

lines(d2[,1], d2[,2], col=2, type='o')
lines(d3[,1], d3[,2], col=3, type='o')


#legend(30,0.7, c("1-5ns", "1-10ns", "1-20ns", "1-30ns", "1-40ns", "1-50ns", "1-60ns", "1-70ns", "1-80ns", "1-90ns", "1-100ns", "1-200ns"),
#       col=c(1,2,3,4,5,6,1,2,3,4,5,6), lty=c(1,1,1,1,1,1,2,2,2,2,2,2))

legend(12,0.7, c("C-alpha NMA", "All atom NMA", "PCA"), col=c(1,2,3), lty=c(1,1,1))

dev.off()
graphics.off()