###################################################################################
# Date: 2014-04-30
# Time series analysis
# listening to Climate history
###################################################################################
source("scripts/rmean.R")
library(audio)

# interpolated 10-year resolution
# CO2 concentrations
buffer<-read.csv("data/norm.daily.pna.index.b500101.current.ascii_20140226")
x<-buffer$pnai
n<-length(x)
# approximate time scale
dt<-(2014-1950+1)/n
time<-seq(1,n,1)*dt+1950

plot(time,x,xlab="time [years]",
     ylab="PNA index",
     typ='l')

#wait<-readline("press enter to listen to the time series")  
#rate<-22050


#play(x,rate=rate)
#wait<-readline("press enter to continue")  

# how does weather variability sound?

window<-c(5,11,31,51,181,365,(7*365+1))
nw<-length(window)
xmean<-matrix(NA,n,nw)
tmean<-matrix(NA,n,nw)
xoff<-(-2)
plot(time,x+xoff,xlab="time [years]",
     ylab="PNA index",
     typ='l',
     ylim=c(-5,20))
for (m in 1:nw) {
  xmean[,m]<-rmean(x,w=window[m])
  tmean[,m]<-rmean(time,w=window[m])
  lines(tmean[,m],xmean[,m]+2*m,col=m+1)
}