4 #system("../nodequery.py --nodelist > ../nodelist.txt")
5 #system("../comonquery.py --cache --nodelist ../nodelist.txt --select 'resptime>0' --fields='name,cpuspeed,numcores,memsize,disksize,bwlimit' | grep -v null | ./hn2lb.py | ./hn2pcustatus.py | sed -e "s/none/0/g" -e "s/Not_Run/0.5/g" -e "s/error/0.5/g" -e "s/Ok/1/g" > ./out_resources.csv ")
7 mdrc <- read.csv("out_resources.csv", TRUE, sep=",")
9 # replace all weird numbers with defaults of 100mbps
10 mdrc$bwlimit <- replace(mdrc$bwlimit, which(mdrc$bwlimit==0 | mdrc$bwlimit==1), 100000)
11 #mdrc$pcus <- replace(mdrc$pcustatus, which(mdrc$pcustatus=="none"), 0);
12 #mdrc$pcus <- replace(mdrc$pcus, which(mdrc$pcus=="error" | mdrc$pcusu=="Not_Run"), 0.5);
13 #mdrc$pcus <- replace(mdrc$pcus, which(mdrc$pcus=="Ok"), 1);
21 # ----------------------
23 unique_loginbase_length <- length(unique(mdrc$loginbase));
24 unique_lb <- list(loginbase=array(0,c(unique_loginbase_length)),
25 score=array(0,c(unique_loginbase_length)),
26 memsize=array(0,c(unique_loginbase_length)),
27 disksize=array(0,c(unique_loginbase_length)),
28 cpuspeed=array(0,c(unique_loginbase_length)),
29 bwlimit=array(0,c(unique_loginbase_length)),
30 pcustatus=array(0,c(unique_loginbase_length))
33 for ( i in 1:length(mdrc$loginbase) )
36 unique_lb$loginbase[r$loginbase] <- r$loginbase;
37 unique_lb$score[r$loginbase] <- unique_lb$score[r$loginbase] + r$score;
40 unique_lb$memsize[r$loginbase] <- unique_lb$memsize[r$loginbase] + v[1];
41 unique_lb$disksize[r$loginbase] <- unique_lb$disksize[r$loginbase] + v[2];
42 unique_lb$cpuspeed[r$loginbase] <- unique_lb$cpuspeed[r$loginbase] + v[3];
43 unique_lb$bwlimit[r$loginbase] <- unique_lb$bwlimit[r$loginbase] + v[4];
44 unique_lb$pcustatus[r$loginbase] <- unique_lb$pcustatus[r$loginbase] + v[5];
47 df<- data.frame(unique_lb)
49 h<- hist(df$score, breaks=b);
50 bins<-length(h$breaks);
56 # foreach score value, find which range it falls into,
57 # then in three columns for cpu, mem, disk, record the fraction of each.
58 # then plot each sequence in a stacked graph, perhaps beside h$counts
59 for ( i in 1:length(df$cpuspeed) )
62 s <- index_of_bin(h, r$score); # find bin position...
63 # take fraction that each component contributes to the total, and add to sum
65 m[s] <- m[s] + unique_lb$memsize[r$loginbase]/r$score;
66 d[s] <- d[s] + unique_lb$disksize[r$loginbase]/r$score;
67 c[s] <- c[s] + unique_lb$cpuspeed[r$loginbase]/r$score;
68 b[s] <- b[s] + unique_lb$bwlimit[r$loginbase]/r$score;
69 p[s] <- p[s] + unique_lb$pcustatus[r$loginbase]/r$score;
72 #vals <- list(bwlimit=b,cpuspeed=c,disksize=d,memsize=m)
73 a <- array(c(p,b,c,d,m), dim=c(bins, 5));
75 #png("/Users/soltesz/Downloads/slice_policy_5.png")
77 par(mai=c(0.5,1,0.5,0.2))
78 barplot(c(0,h$counts),
80 main="Distribution of Site Scores",
81 ylab="Total Frequency",
83 par(mai=c(1.0,1,0,0.2));
85 legend=c("PCU Status", "BWlimit (Mbps)", "CPUspeed (GHz)", "DISKsize (GB)", "MEMsize (GB)"),
86 col=c("orange", "lightyellow", "pink", "lightblue", "lightgreen"),
88 ylab="Break-down by Resource",
90 names.arg=c(0,h$breaks[1:length(h$breaks)-1]),