julian.kunkel/mistral-io-datasets
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Cleanup

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Julian M. Kunkel 2020-08-17 18:15:35 +01:00
parent 6c8d2db495
commit 9ce020ae5e
1 changed files with 2 additions and 72 deletions
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plot.R
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@ -33,78 +33,8 @@ ggsave("ecdf-0.5.png")
ggplot(data, aes(similarity), group=alg_name) + geom_histogram(color="black", binwidth=0.025) + aes(fill = alg_name) + facet_grid(alg_name ~ ., switch = 'y') + scale_y_continuous(limits=c(0, 100), oob=squish) + scale_color_brewer(palette = "Set2") + ylab("Count (cropped at 100)")
ggsave("hist-sim.png")
# + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x)))
# scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x)))
#+ ylim(0, 250) + stat_summary(aes(linetype = alg_id), fun.y=mean, geom="line") +
# stat_summary(aes(linetype = alg_id), fun.y=mean, geom="line")
exit(0)
########### merged
both = rbind(i[ , (names(i) %in% names(d))], d[ , (names(d) %in% names(i))])
both$tpGiB = both$tpMiBs / 1024
both$PPN = as.factor(both$PPN)
e = both %>% filter(nodes == 500)
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_boxplot() + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom") + ylim(0, 250)
ggsave("500-nodes.png")
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_boxplot(position=pd) + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("500-nodes-all.png")
e = both %>% filter(nodes == 200)
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_point(position=pd) + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom") + ylim(0, 250)
ggsave("200-nodes.png")
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_point(position=pd) + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("200-nodes-all.png")
e = both %>% filter(nodes == 100)
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_point(position=pd) + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom") + ylim(0, 250)
ggsave("100-nodes.png")
ggplot(e, aes(PPN, tpGiB, color=config, group=config)) + geom_point(position=pd) + facet_grid(op + dim ~ ., switch = 'y') + xlab("PPN") + ylab("Performance in GiB/s") + stat_summary(aes(linetype = config), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("100-nodes-all.png")
########### End merged plots
d$tpGiB = d$tpMiBs / 1024
d$nodes = as.factor(d$nodes)
d$PPN = as.factor(d$PPN)
d$volume = as.factor(round(d$sizeMiB/1024,1))
# Compare:
# scale_colour_gradientn(colours=rainbow(3))
# d %>% filter(tpGiB > 100)
e = d %>% filter(nodes==5) # , size>100
ggplot(e, aes(volume, tpGiB, color=PPN, group=PPN)) + geom_point(position=pd) + facet_grid(op + config ~ ., switch = 'y') + xlab("Volume in GiB") + ylab("Performance in GiB/s") + stat_summary(aes(), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("5nodes-write-size-compare.png", width=4, height=3)
ggplot(e, aes(volume, tpGiB, color=PPN, group=PPN)) + geom_point(position=pd) + facet_grid(type ~ ., switch = 'y') + xlab("Volume in GiB") + ylab("Performance in GiB/s") + stat_summary(aes(), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("5nodes-read-size-compare.png", width=4, height=3)
e = d %>% filter(size==60000)
ggplot(e, aes(nodes, tpGiB, color=PPN, group=PPN)) + geom_point(position=pd) + facet_grid(type ~ ., switch = 'y') + xlab("Nodes") + ylab("Performance in GiB/s") + stat_summary(aes(), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("write-60000.png", width=4, height=3)
ggplot(e, aes(nodes, tpGiB, color=PPN, group=PPN)) + geom_point(position=pd) + facet_grid(type ~ ., switch = 'y') + xlab("Nodes") + ylab("Performance in GiB/s") + stat_summary(aes(), fun.y=mean, geom="line") + theme(legend.position="bottom")
ggsave("read-60000.png", width=4, height=3)
e = d %>% filter(size==60000, PPN==12)
ggplot(e, aes(nodes, write, color=type, group=type)) + geom_point(position=pd) + xlab("Nodes") + ylab("Performance in GiB/s") + theme(legend.position="bottom") + stat_summary(aes(group=type), fun.y=mean, geom="line")
ggsave("compare-write-12.png", width=4, height=3)
e = d %>% filter(size==60000, PPN==4)
ggplot(e, aes(nodes, write, color=type, group=type)) + geom_point(position=pd) + xlab("Nodes") + ylab("Performance in GiB/s") + theme(legend.position="bottom") + stat_summary(aes(group=type), fun.y=mean, geom="line")
ggsave("compare-write-4.png", width=4, height=3)