Setting tag Monitor-3.0-34
[monitor.git] / statistics / site_scores.r
1
2 source("functions.r");
3
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 > ./out_resources.csv ")
6
7 mdrc <- read.csv("out_resources.csv", TRUE, sep=",")
8
9 # replace all weird numbers with defaults of 100mbps 
10 mdrc$bwlimit <- replace(mdrc$bwlimit, which(mdrc$bwlimit==0 | mdrc$bwlimit==1), 100000)
11
12 f<-slices_2
13
14 s2<- f(mdrc, FALSE);
15 mdrc$score <- s2;
16 b<-30;
17
18 # ----------------------
19 ### LOGINBASE
20 unique_loginbase_length <- length(unique(mdrc$loginbase));
21 unique_lb <- list(loginbase=array(0,c(unique_loginbase_length)), 
22                                   score=array(0,c(unique_loginbase_length)),
23                                   memsize=array(0,c(unique_loginbase_length)),
24                                   disksize=array(0,c(unique_loginbase_length)),
25                                   cpuspeed=array(0,c(unique_loginbase_length))
26                           )
27
28 for ( i in 1:length(mdrc$loginbase) )
29 {
30     r <- mdrc[i,];
31         unique_lb$loginbase[r$loginbase] <- r$loginbase;
32         unique_lb$score[r$loginbase]     <- unique_lb$score[r$loginbase] + r$score;
33
34         v <- f(r, TRUE);
35         unique_lb$memsize[r$loginbase]  <- unique_lb$memsize[r$loginbase]  + v[1];
36         unique_lb$disksize[r$loginbase] <- unique_lb$disksize[r$loginbase]  + v[2];
37         unique_lb$cpuspeed[r$loginbase] <- unique_lb$cpuspeed[r$loginbase]  + v[3];
38 }
39
40 df<- data.frame(unique_lb)
41
42 h<- hist(df$score, breaks=b);
43 bins<-length(h$breaks);
44 c<- array(0,c(bins));
45 d<- array(0,c(bins));
46 m<- array(0,c(bins));
47 b<- array(0,c(bins));
48 # foreach score value, find which range it falls into, 
49 # then in three columns for cpu, mem, disk, record the fraction of each.
50 # then plot each sequence in a stacked graph, perhaps beside h$counts
51 for ( i in 1:length(df$cpuspeed) )
52 {
53     r <- df[i,];
54     s <- index_of_bin(h, r$score); # find bin position...
55     # take fraction that each component contributes to the total, and add to sum
56
57     m[s] <- m[s] + unique_lb$memsize[r$loginbase]/r$score;
58     d[s] <- d[s] + unique_lb$disksize[r$loginbase]/r$score;
59     c[s] <- c[s] + unique_lb$cpuspeed[r$loginbase]/r$score;
60 }
61
62 a <- array(c(c,d,m), dim=c(bins, 3));
63
64 png("/Users/soltesz/Downloads/slice_policy_3.png")
65 par(mfrow=c(2,1))
66 par(mai=c(0.5,1,0.5,0.2))
67 barplot(c(0,h$counts), 
68     xlab="slice count", 
69     main="Distribution of Site Scores", 
70     ylab="Total Frequency", 
71     ylim=c(0,70))
72 par(mai=c(1.0,1,0,0.2));
73 barplot(t(a), 
74     legend=c("CPUspeed (GHz)", "DISKsize (GB)", "MEMsize (GB)"), 
75     col=c("pink", "lightblue", "lightgreen"), 
76     ylim=c(0,70),
77     ylab="Break-down by Resource",
78     xlab="Site Score",
79     names.arg=c(0,h$breaks[1:length(h$breaks)-1]),
80 );
81 dev.off()
82
83