WIP my graph
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09ef754312
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0c959ac6b6
1 changed files with 155 additions and 13 deletions
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@ -236,10 +236,19 @@ t3 <- plot_grid(v8, v9, v10, v11, labels = c('A', 'B', 'C', 'D'), ncol=2)
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t3 + ggsave("thunder_packets.png", dpi=300, dev='png', height=12, width=15, units="cm")
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t3 + ggsave("thunder_packets.png", dpi=300, dev='png', height=12, width=15, units="cm")
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tor_multi_lat <- read.csv("tor_just_many_latencies.csv")
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tor_multi_lat <- read.csv("tor_just_many_latencies.csv")
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tor_drop <- sqldf("select run,conf,1.0*MAX(ident)/33 as last_one from tor_multi_lat group by run,conf")
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tor_multi_lat_100 <- read.csv("tor_just_many_latencies_100.csv")
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v12 <- ggplot(data=tor_drop,aes(x=last_one)) +
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tor_drop <- sqldf(
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"
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select run,conf,1.0*MAX(ident)/33 as last_one,'33' as pkt_sec from tor_multi_lat group by run,conf
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union
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select run,conf,1.0*MAX(ident)/10 as last_one, '10' as pkt_sec from tor_multi_lat_100 group by run,conf
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")
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v12 <- ggplot(data=tor_drop,aes(x=last_one, linetype=factor(pkt_sec, levels=c('33', '10')))) +
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stat_ecdf(pad = FALSE) +
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stat_ecdf(pad = FALSE) +
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ylab("% broken links") +
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ylab("% broken links") +
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labs(linetype="Pkt/sec") +
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coord_cartesian(xlim = c(0, 300), ylim = c(0,0.5)) +
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coord_cartesian(xlim = c(0, 300), ylim = c(0,0.5)) +
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scale_y_continuous(labels = scales::percent) +
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scale_y_continuous(labels = scales::percent) +
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xlab("Elapsed time (sec)") +
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xlab("Elapsed time (sec)") +
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@ -252,22 +261,155 @@ library(purrr)
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library(tidyr)
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library(tidyr)
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tor_lat_stack <- tor_multi_lat %>%
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tor_lat_stack <- tor_multi_lat %>%
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dplyr::mutate(latency = latency / 1000) %>%
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dplyr::group_by(run,conf) %>%
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dplyr::group_by(run,conf) %>%
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dplyr::summarise(
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dplyr::summarise(
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id = paste(first(run),first(conf)),
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id = paste(first(run),first(conf)),
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min = min(latency),
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min = min(latency),
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max = max(latency),
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q25 = quantile(latency,0.25) - min(latency),
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median = median(latency) - quantile(latency,0.25),
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q75 = quantile(latency,0.75) - median(latency),
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q95 = quantile(latency,0.95) - quantile(latency,0.75),
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q99 = quantile(latency,0.99) - quantile(latency,0.95),
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max = max(latency) - quantile(latency,0.99),
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max_sort = max(latency),
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max_sort = max(latency),
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q25 = quantile(latency,0.25),
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median_sort = median(latency)
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median = median(latency),
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median_sort = median(latency),
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q75 = quantile(latency,0.75),
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q95 = quantile(latency,0.95),
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q99 = quantile(latency,0.99)
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)
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)
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tor_lat_stack <- gather(tor_lat_stack, 'min', 'max', 'q25', 'median', 'q75', 'q95', 'q99', key="quantile_name", value="quantile_value")
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tor_lat_stack <- gather(tor_lat_stack, 'min', 'max', 'q25', 'median', 'q75', 'q95', 'q99', key="quantile_name", value="quantile_value")
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ggplot(tor_lat_stack, aes(x=id,y=quantile_value,fill=quantile_name)) +
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v13 <- ggplot(tor_lat_stack, aes(
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ylim(0,1000000) +
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x=reorder(id,median_sort),
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geom_bar(stat="identity", position="dodge")
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"))
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v14 <- ggplot(tor_lat_stack, aes(
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x=reorder(id,median_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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#coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(),axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"))
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v15 <- ggplot(tor_lat_stack, aes(
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x=reorder(id,max_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"), plot.tag.position='top')
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v16 <- ggplot(tor_lat_stack, aes(
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x=reorder(id,max_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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#coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"),plot.tag.position='bottom')
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t4 <- plot_grid(v16, v15, v14, v13, labels = c('A', 'B', 'C', 'D'), ncol=1)
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t4 + ggsave("tor_30ms.png", dpi=300, dev='png', height=20, width=15, units="cm")
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tor_lat_stack_100 <- tor_multi_lat_100 %>%
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dplyr::mutate(latency = latency / 1000) %>%
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dplyr::group_by(run,conf) %>%
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dplyr::summarise(
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id = paste(first(run),first(conf)),
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min = min(latency),
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q25 = quantile(latency,0.25) - min(latency),
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median = median(latency) - quantile(latency,0.25),
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q75 = quantile(latency,0.75) - median(latency),
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q95 = quantile(latency,0.95) - quantile(latency,0.75),
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q99 = quantile(latency,0.99) - quantile(latency,0.95),
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max = max(latency) - quantile(latency,0.99),
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max_sort = max(latency),
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median_sort = median(latency)
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)
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tor_lat_stack_100 <- gather(tor_lat_stack_100, 'min', 'max', 'q25', 'median', 'q75', 'q95', 'q99', key="quantile_name", value="quantile_value")
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v17 <- ggplot(tor_lat_stack_100, aes(
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x=reorder(id,median_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"))
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v18 <- ggplot(tor_lat_stack_100, aes(
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x=reorder(id,median_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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#coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(),axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"))
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v19 <- ggplot(tor_lat_stack_100, aes(
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x=reorder(id,max_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"), plot.tag.position='top')
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v20 <- ggplot(tor_lat_stack_100, aes(
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x=reorder(id,max_sort),
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y=quantile_value,
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fill=factor(quantile_name, levels=c('max','q99','q95','q75', 'median', 'q25', 'min')))
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) +
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#coord_cartesian(ylim = c(0,1500)) +
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labs(fill="quantile")+
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xlab("Tor circuits") +
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ylab("RTT (ms)") +
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geom_bar(stat="identity", position="stack",width=1) +
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scale_fill_grey() +
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theme_classic() +
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theme(axis.text.x=element_blank(), axis.ticks.x = element_blank(), legend.key.size = unit(0.2, "cm"),plot.tag.position='bottom')
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t5 <- plot_grid(v20, v19, v18, v17, labels = c('A', 'B', 'C', 'D'), ncol=1)
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t5 + ggsave("tor_100ms.png", dpi=300, dev='png', height=20, width=15, units="cm")
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