# License: CDDL 1.0
#
# Copyright 2014 Jens Elkner.

# Invoke as 'R CMD BATCH --slave show.R' in the directory, which contains the
# iostat -xrn output

w<-1024
h<-768
hw<-600
hh<-450
f<-120
ft<-"out.tiff"

process<-function(d) { # "c8t4d0"
	fname<-paste(d, ".io", sep="")
	if (! file.exists(fname)) {
		return(paste("Skipping", fname))
	}
	line<-paste(rep("=",70), collapse="")
	# Set the 1st fields of header lines to NA to be able to filter them out
	raw<-read.csv(fname, header=F, dec=".", sep=",", skip=2,
		na.strings=c("extended device statistics", "r/s"))
	raw<-subset(raw, !is.na(V1) , select = V1:V10, drop=T)
	data<-subset(raw, as.numeric(as.character(V6)) >= 1, drop=T)
	
	dt<-format(as.POSIXlt(nrow(data), origin = "1970-01-01", tz="GMT"), "%H:%M:%S")
	title<-paste(d, "-", dt);
	#plot(data[,5], type="p", xlab="time [s]", ylab="KiB/s", pch=".")

	out<-file(paste(d, "-summary.txt", sep=""), "wt")
	sink(out, type="output", split = FALSE)
	cat(title, "", "Data", line, sep="\n")
	print(summary(data))
	sink()
	
	# create timeseries for kw/s
	ts_kws<-ts(as.double(as.character(data$V4))/1024.0, start=1, frequency=f)
	# create seasonal series from timeseries
	ss_kws<-stl(ts_kws, s.window="periodic")
	# ss_kws$time.series[,1] .. seasonal component
	# ss_kws$time.series[,2] .. trend component
	# ss_kws$time.series[,3] .. remainder component
	# see attributes(ss_kws$time.series)
	
	# save as tiff - the only R supported px based format w/o loosing info
	tiff(filename = ft, width=w, height=h, units="px")
	# plot ss. One could rename "data","seasonal","trend","remainder" labels
	# on y-axis by adding soething like 'labels=c("l1", "l2", "l3", "l4")'
	pars = list(xaxt="n", mar = c(0, 6, 0, 6), oma = c(6, 0, 4, 0),
		tck = -0.01, mfrow = c(4, 1))
	plot(ss_kws, main=paste(title, "- throughput [MiB/s]"), set.pars=pars)
	v.pretty<-pretty(0:nrow(data)/f)
	axis(1, at=v.pretty, labels=v.pretty*f/60)
	dev.off()
	system(paste("convert ", ft, " ", d, "-throughput.gif", sep=""))
	tiff(filename = ft, width=hw, height=hh, units="px")
	hist(as.double(as.character(data$V4))/1024.0, main=title,
		xlab="throughput [MiB/s]", breaks=20)
	dev.off()
	system(paste("convert ", ft, " ", d, "-throughput-hist.gif", sep=""))
	
	# Zusammenfassung
	sink(out, type="output", split = FALSE)
	cat("", "Throughput [MiB/s]", line, sep="\n")
	print(summary(ss_kws$time.series))
	sink()
	
	# das gleiche für time/IOP
	speed<-(as.double(as.character(data$V8))/as.double(as.character(data$V6)))
	ts_speed<-ts(speed, start=1, frequency=f)
	ss_speed<-stl(ts_speed, s.window="periodic")
	tiff(filename = ft, width=w, height=h, units="px")
	plot(ss_speed, main=paste(title, "- latency [ms]"), set.pars=pars)
	v.pretty<-pretty(0:nrow(data)/f)
	axis(1, at=v.pretty, labels=v.pretty*f/60)
	dev.off()
	system(paste("convert ", ft, " ", d, "-latency.gif", sep=""))
	tiff(filename = ft, width=hw, height=hh, units="px")
	hist(speed, main=title, xlab="latency [ms]", breaks=20)
	dev.off()
	system(paste("convert ", ft, " ", d, "-latency-hist.gif", sep=""))
	
	sink(out, type="output", split = FALSE)
	cat("", "Latency [ms]", line, sep="\n")
	print(summary(ss_speed$time.series))
	sink()
	
	close(out)
	unlink(ft)
}

for (i in 3:8) {
	for (k in 0:7) {
		fn<-paste("c", i, "t", k, "d0", sep="")
		print(fn)
		process(fn)
	}
}

# tsf<-HoltWinters(ts_speed, beta=FALSE, gamma=FALSE)
# plot(tsf)
# plot(tsf$fitted)