--- /dev/null
+source("functions.r");
+
+
+
+median_time_to_resolve_window <- function (t, tg, window)
+{
+ hbreaks<-tg$week_ts
+
+ xx<-NULL;
+ yy<-NULL;
+ yy_sd_high<-NULL;
+ yy_sd_low<-NULL;
+ date_index <- NULL;
+ q_list <- NULL;
+
+ x<-seq(-20,20,0.01)
+
+ for ( i in seq(1,length(hbreaks)-window-1) )
+ {
+ print (sprintf("round %s of %s", i, length(hbreaks)-window-1))
+ # get range from t
+ t_sub <- t[which(t$start > hbreaks[i] & t$start<= hbreaks[i+window]),]
+ if ( length(t_sub$start) <= 1 ) { next }
+ # take log, then sn.mle -> h
+ d <- (t_sub$lastreply - t_sub$start)/(60*60) # hours
+ d <- log(d) # log(hours)
+ # sn.mle
+ print (sprintf("length: %s", length(d)))
+ q<-quantile(d)
+ print(q)
+
+ date_index <- c(date_index, round(i+window/2))
+
+ xx<- c(xx, hbreaks[round(i+window/2)])
+ q_list <- rbind(q_list, q)
+
+ }
+ return (cbind(xx,q_list))
+}
+
+available_nodes <- function (ns, from, to, type, fmt="%b")
+{
+ # find 'type' range of days
+ dates <-seq(as.Date(from), as.Date(to), type)
+ months <- format(dates, fmt)
+ hbreaks<-unclass(as.POSIXct(dates))
+
+ xx<-NULL;
+ yy<-NULL;
+
+ for ( i in seq(1,length(hbreaks)-1) )
+ {
+ # get range from ns
+ ns_sub <- ns[which(ns$date > hbreaks[i] & ns$date <= hbreaks[i+1] & ns$status == 'BOOT'),]
+ nodes <- length(ns_sub$date)
+
+ xx<- c(xx, hbreaks[i])
+ yy<- c(yy, nodes)
+
+ }
+ m<- months[1:length(months)-1]
+ return (rbind(xx,yy,m))
+}
+
+
+open_tickets <- function (t, tg)
+{
+ xx<-NULL;
+ yy<-NULL;
+
+ hbreaks<-tg$day_ts
+
+ for ( i in seq(1,length(hbreaks)-1) )
+ {
+ # identify any tickets with a start time in range, lastreply in range
+ # or where both start is less and lastreply is greater than the range
+ t_sub <- t[which( (t$start < hbreaks[i] & t$lastreply > hbreaks[i+1]) |
+ (t$start > hbreaks[i] & t$start <= hbreaks[i+1]) |
+ (t$lastreply > hbreaks[i] & t$lastreply <= hbreaks[i+1]) ),]
+ tickets <- length(t_sub$start)
+
+ xx<- c(xx, hbreaks[i])
+ yy<- c(yy, tickets)
+ }
+ return (rbind(xx,yy))
+}
+
+online_nodes <- function (fb)
+{
+ breaks <- unique(fb$timestamp)
+ n<-NULL
+ o<-NULL
+ x<-NULL
+ for (i in seq(1,length(breaks)) )
+ {
+ ts <- breaks[i]
+ sub <- fb[which(fb$timestamp == ts),]
+ node_count <- length(unique(sub$hostname))
+ online_count <- length(unique(sub$hostname[which(sub$state=='BOOT')]))
+ x<-c(x,ts)
+ n<-c(n,node_count)
+ o<-c(o,online_count)
+ }
+ print(length(x))
+ print(length(n))
+ print(length(o))
+ return (rbind(x,n,o))
+}
+
+#####
+
+# system("rt_s1_raw_dump.py --runsql");
+# system("rt_s2_parse_raw.py 3 > rt_data.csv");
+# t <- read.csv('rt_data_2004-2011.csv', sep=',', header=TRUE)
+#t <- read.csv(, sep=',', header=TRUE)
+
+draw_rt_data <- function (input_filename, output_filename, start_date, end_date, draw=TRUE, one=FALSE)
+{
+ t <- read.csv(input_filename, sep=',', header=TRUE)
+ t2 <- t[which(t$complete == 1),]
+
+ tg <- time_graph_setup(start_date, end_date)
+ ot <- open_tickets(t2, tg)
+
+ if ( draw == TRUE ) {
+ start_image(output_filename, width=600, height=400)
+ }
+ if ( one == TRUE )
+ {
+ par(mfrow=c(1,1))
+ par(mai=c(0.8,1,0.4,0.1))
+ } else {
+ par(mfrow=c(2,1))
+ par(mai=c(0,1,0.3,0.1))
+ }
+
+ x1<-as.numeric(ot[1,])
+ y1<-as.numeric(ot[2,])
+
+ a_ot<-lowess_smooth(x1, y1)
+
+ plot(x1, y1, col='grey80', type='l', axes=F,
+ ylab="a) Open Tickets (tickets/day)", xlab="Date",
+ ylim=c(0,120)) # , ylim=c(0,260))
+ lines(a_ot$x, round(a_ot$y), col='black')
+
+ axis(2, las=1)
+ if ( one == TRUE ) {
+ axis(1, labels=tg$month_str, at=tg$month_ts, cex.axis=0.7)
+ axis(1, labels=tg$year_str, at=tg$year_ts, cex.axis=0.7, line=1, lwd=0)
+ }
+
+
+ abline(h=15, lty=3, col='grey80')
+ abline(h=25, lty=3, col='grey80')
+ abline(h=40, lty=3, col='grey80')
+
+ plc_releases(120)
+ if ( one == FALSE )
+ {
+ par(mai=c(1,1,0.1,0.1))
+ for ( s in c(5) )
+ {
+ d <- median_time_to_resolve_window(t2, tg, s) # "2004/1/1", "2011/1/28", s, "%b")
+ plot(d[,1], exp(as.numeric(d[,5]))/24, type='l', lty=1, xlab="",
+ axes=F, ylim=c(0.01, 15), ylab="b) Resolution Time by", col='black',
+ xlim=c(min(x1), max(x1)))
+ mtext("Quartile (days)", 2, 2)
+ lines(d[,1], exp(as.numeric(d[,4]))/24, lty=1, col='grey50')
+ lines(d[,1], exp(as.numeric(d[,3]))/24, lty=1, col='grey75')
+ axis(1, labels=tg$month_str, at=tg$month_ts, cex.axis=0.7)
+ axis(1, labels=tg$year_str, at=tg$year_ts, cex.axis=0.7, line=1, lwd=0)
+ axis(2, labels=c(0,1,4,7,14), at=c(0,1,4,7,14), las=1)
+ m<-round(max(exp(as.numeric(d[,4]))/24), 2)
+ }
+
+ abline(h=1, lty=3, col='grey80')
+ abline(h=4, lty=3, col='grey80')
+ abline(h=7, lty=3, col='grey80')
+
+ planetlab_releases(15)
+ }
+
+ if ( draw == TRUE ) {
+ end_image()
+ }
+}
+
+#system("./rt_s2_parse_raw.py 3 > rt_data_2004-2011.csv");
+draw_rt_data('rt_data_2004-2011.csv', "rt_operator_support_2004-2011.png", "2004/1/1", "2011/6/1", TRUE, TRUE)
+#draw_rt_data('rt_data_monitor_2004-2011.csv',"rt_operator_monitor_2004-2011.png", "2004/1/1", "2011/4/1")
+
+#draw_rt_data('short_support_20110101.csv',"rt_short_2011.png", "2010/11/1", "2011/4/1", FALSE)
git://git.onelab.eu / monitor.git / blobdiff