commit 5c8e727b61f516ddb30d2400d6f3c97462443801
Author: Karsten Loesing <karsten.loesing(a)gmx.net>
Date: Thu Mar 1 12:27:07 2018 +0100
Refactor even more of the graphing code.
---
src/main/R/rserver/graphs.R | 428 +++++++++++++++++---------------------------
1 file changed, 167 insertions(+), 261 deletions(-)
diff --git a/src/main/R/rserver/graphs.R b/src/main/R/rserver/graphs.R
index 8847967..93ff919 100644
--- a/src/main/R/rserver/graphs.R
+++ b/src/main/R/rserver/graphs.R
@@ -329,28 +329,20 @@ stats_dir = "/srv/metrics.torproject.org/metrics/shared/stats/"
rdata_dir = "/srv/metrics.torproject.org/metrics/shared/RData/"
prepare_networksize <- function(start, end) {
- s <- read.csv(paste(stats_dir, "servers.csv", sep = ""),
- stringsAsFactors = FALSE)
- s <- s[s$date >= start & s$date <= end & s$flag == '' &
- s$country == '' & s$version == '' & s$platform == '' &
- s$ec2bridge == '', ]
- s <- data.frame(date = as.Date(s$date, "%Y-%m-%d"), relays = s$relays,
- bridges = s$bridges)
- s
+ read.csv(paste(stats_dir, "servers.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), flag == '',
+ country == '', version == '', platform == '', ec2bridge == '') %>%
+ select(date, relays, bridges)
}
plot_networksize <- function(start, end, path) {
- s <- prepare_networksize(start, end)
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by="1 day")
- missing <- setdiff(dates, as.Date(s$date, origin = "1970-01-01"))
- if (length(missing) > 0)
- s <- rbind(s,
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- relays = NA, bridges = NA))
- networksize <- gather(s, variable, value, -date)
- ggplot(networksize, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = variable)) + geom_line() +
+ prepare_networksize(start, end) %>%
+ gather(variable, value, -date) %>%
+ complete(date = full_seq(date, period = 1),
+ variable = c("relays", "bridges")) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
+ geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
@@ -367,14 +359,11 @@ write_networksize <- function(start, end, path) {
}
prepare_versions <- function(start, end) {
- s <- read.csv(paste(stats_dir, "servers.csv", sep = ""),
- stringsAsFactors = FALSE)
- s <- s[s$date >= start & s$date <= end & s$flag == '' &
- s$country == '' & s$version != '' & s$platform == '' &
- s$ec2bridge == '', ]
- s <- data.frame(date = as.Date(s$date, "%Y-%m-%d"), version = s$version,
- relays = s$relays)
- s
+ read.csv(paste(stats_dir, "servers.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), flag == '',
+ country == '', version != '', platform == '', ec2bridge == '') %>%
+ select(date, version, relays)
}
plot_versions <- function(start, end, path) {
@@ -389,8 +378,7 @@ plot_versions <- function(start, end, path) {
stringsAsFactors = FALSE)
versions <- s[s$version %in% known_versions, ]
visible_versions <- sort(unique(versions$version))
- ggplot(versions, aes(x = as.Date(date, "%Y-%m-%d"), y = relays,
- colour = version)) +
+ ggplot(versions, aes(x = date, y = relays, colour = version)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -410,21 +398,18 @@ write_versions <- function(start, end, path) {
}
prepare_platforms <- function(start, end) {
- s <- read.csv(paste(stats_dir, "servers.csv", sep = ""),
- stringsAsFactors = FALSE)
- s <- s[s$date >= start & s$date <= end & s$flag == '' &
- s$country == '' & s$version == '' & s$platform != '' &
- s$ec2bridge == '', ]
- platforms <- data.frame(date = as.Date(s$date, "%Y-%m-%d"),
- variable = ifelse(s$platform == "Darwin", "macOS", s$platform),
- value = s$relays)
- platforms
+ read.csv(paste(stats_dir, "servers.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), flag == '',
+ country == '', version == '', platform != '', ec2bridge == '') %>%
+ select(date, platform, relays) %>%
+ mutate(platform = ifelse(platform == "Darwin", "macOS",
+ as.character(platform)))
}
plot_platforms <- function(start, end, path) {
- platforms <- prepare_platforms(start, end)
- ggplot(platforms, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = variable)) +
+ prepare_platforms(start, end) %>%
+ ggplot(aes(x = date, y = relays, colour = platform)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -439,33 +424,31 @@ plot_platforms <- function(start, end, path) {
write_platforms <- function(start, end, path) {
prepare_platforms(start, end) %>%
- spread(variable, value) %>%
+ spread(platform, relays) %>%
write.csv(path, quote = FALSE, row.names = FALSE)
}
prepare_bandwidth <- function(start, end) {
- b <- read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
- stringsAsFactors = FALSE)
- b <- b[b$date >= start & b$date <= end & b$isexit == '' &
- b$isguard == '', ]
- b <- data.frame(date = as.Date(b$date, "%Y-%m-%d"),
- bwadv = b$advbw * 8 / 1e9,
- bwhist = (b$bwread + b$bwwrite) * 8 / 2e9)
- b
+ read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), isexit == '',
+ isguard == '') %>%
+ mutate(advbw = advbw * 8 / 1e9) %>%
+ mutate(bwhist = (bwread + bwwrite) * 8 / 2e9) %>%
+ select(date, advbw, bwhist)
}
plot_bandwidth <- function(start, end, path) {
- b <- prepare_bandwidth(start, end)
- bandwidth <- gather(b, variable, value, -date)
- ggplot(bandwidth, aes(x = as.Date(date, "%Y-%m-%d"),
- y = value, colour = variable)) +
+ prepare_bandwidth(start, end) %>%
+ gather(variable, value, -date) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = unit_format(unit = "Gbit/s"),
limits = c(0, NA)) +
scale_colour_hue(name = "", h.start = 90,
- breaks = c("bwadv", "bwhist"),
+ breaks = c("advbw", "bwhist"),
labels = c("Advertised bandwidth", "Bandwidth history")) +
ggtitle("Total relay bandwidth") +
labs(caption = copyright_notice) +
@@ -479,37 +462,22 @@ write_bandwidth <- function(start, end, path) {
}
prepare_bwhist_flags <- function(start, end) {
- b <- read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
- stringsAsFactors = FALSE)
- b <- b[b$date >= start & b$date <= end & b$isexit != '' &
- b$isguard != '', ]
- bw <- data.frame(date = as.Date(b$date, "%Y-%m-%d"),
- isexit = b$isexit == 't', isguard = b$isguard == 't',
- read = b$bwread, written = b$bwwrite)
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by = "1 day")
- missing <- setdiff(dates, as.Date(bw$date, origin = "1970-01-01"))
- if (length(missing) > 0)
- bw <- rbind(bw,
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- isexit = FALSE, isguard = FALSE, read = NA, written = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- isexit = FALSE, isguard = TRUE, read = NA, written = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- isexit = TRUE, isguard = FALSE, read = NA, written = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- isexit = TRUE, isguard = TRUE, read = NA, written = NA))
- bw <- data.frame(date = bw$date, variable = ifelse(bw$isexit,
- ifelse(bw$isguard, "guard_and_exit", "exit_only"),
- ifelse(bw$isguard, "guard_only", "middle_only")),
- value = (bw$read + bw$written) * 8 / 2e9)
- bw
+ read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), isexit != '',
+ isguard != '') %>%
+ mutate(variable = ifelse(isexit == 't',
+ ifelse(isguard == 't', "guard_and_exit", "exit_only"),
+ ifelse(isguard == 't', "guard_only", "middle_only")),
+ value = (bwread + bwwrite) * 8 / 2e9) %>%
+ select(date, variable, value)
}
plot_bwhist_flags <- function(start, end, path) {
- bw <- prepare_bwhist_flags(start, end)
- ggplot(bw, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = variable)) +
+ prepare_bwhist_flags(start, end) %>%
+ complete(date = full_seq(date, period = 1),
+ variable = unique(variable)) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -532,21 +500,19 @@ write_bwhist_flags <- function(start, end, path) {
}
prepare_dirbytes <- function(start, end, path) {
- b <- read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
- stringsAsFactors = FALSE)
- b <- b[b$date >= start & b$date <= end & b$isexit == '' &
- b$isguard == '', ]
- b <- data.frame(date = as.Date(b$date, "%Y-%m-%d"),
- dirread = b$dirread * 8 / 1e9,
- dirwrite = b$dirwrite * 8 / 1e9)
- b
+ read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), isexit == '',
+ isguard == '') %>%
+ mutate(dirread = dirread * 8 / 1e9,
+ dirwrite = dirwrite * 8 / 1e9) %>%
+ select(date, dirread, dirwrite)
}
plot_dirbytes <- function(start, end, path) {
- b <- prepare_dirbytes(start, end)
- dir <- gather(b, variable, value, -date)
- ggplot(dir, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = variable)) +
+ prepare_dirbytes(start, end) %>%
+ gather(variable, value, -date) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -567,33 +533,20 @@ write_dirbytes <- function(start, end, path) {
}
prepare_relayflags <- function(start, end, flags) {
- s <- read.csv(paste(stats_dir, "servers.csv", sep = ""),
- stringsAsFactors = FALSE)
- s <- s[s$date >= start & s$date <= end & s$country == '' &
- s$version == '' & s$platform == '' & s$ec2bridge == '', ]
- s <- data.frame(date = as.Date(s$date, "%Y-%m-%d"),
- variable = ifelse(s$flag == '', 'Running', s$flag),
- value = s$relays)
- networksize <- s[s$variable %in% flags, ]
- networksize
+ read.csv(paste(stats_dir, "servers.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end), country == '',
+ version == '', platform == '', ec2bridge == '') %>%
+ mutate(flag = ifelse(flag == '', 'Running', as.character(flag))) %>%
+ filter(flag %in% flags) %>%
+ select(date, flag, relays)
}
plot_relayflags <- function(start, end, flags, path) {
- networksize <- prepare_relayflags(start, end, flags)
- networksize <- rbind(data.frame(
- date = as.Date(end) + 1,
- variable = c("Running", "Exit", "Guard", "Fast", "Stable", "HSDir"),
- value = NA), networksize)
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by="1 day")
- missing <- setdiff(dates, networksize$date)
- if (length(missing) > 0)
- networksize <- rbind(data.frame(
- date = as.Date(rep(missing, 6), origin = "1970-01-01"),
- variable = c("Running", "Exit", "Guard", "Fast", "Stable", "HSDir"),
- value = rep(NA, length(missing) * 6)), networksize)
- ggplot(networksize, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = as.factor(variable))) + geom_line() +
+ prepare_relayflags(start, end, flags) %>%
+ complete(date = full_seq(date, period = 1), flag = unique(flag)) %>%
+ ggplot(aes(x = date, y = relays, colour = as.factor(flag))) +
+ geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
@@ -616,32 +569,24 @@ plot_torperf <- function(start, end, source, server, filesize, path) {
filesizeVal <- ifelse(filesize == '50kb', 50 * 1024,
ifelse(filesize == '1mb', 1024 * 1024, 5 * 1024 * 1024))
t <- read.csv(paste(stats_dir, "torperf-1.1.csv", sep = ""),
- stringsAsFactors = FALSE)
+ colClasses = c("date" = "Date"))
known_sources <- c("all", unique(t[t$source != "", "source"]))
colours <- data.frame(source = known_sources,
colour = brewer.pal(length(known_sources), "Paired"),
stringsAsFactors = FALSE)
- t <- t[t$date >= start & t$date <= end & t$filesize == filesizeVal &
- t$source == ifelse(source == 'all', '', source) &
- t$server == server, ]
- torperf <- data.frame(date = as.Date(t$date, "%Y-%m-%d"),
- q1 = t$q1, md = t$md, q3 = t$q3)
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by="1 day")
- missing <- setdiff(dates, torperf$date)
- if (length(missing) > 0)
- torperf <- rbind(torperf,
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- q1 = NA, md = NA, q3 = NA))
colour <- colours[colours$source == source, "colour"]
filesizes <- data.frame(filesizes = c("5mb", "1mb", "50kb"),
label = c("5 MiB", "1 MiB", "50 KiB"), stringsAsFactors = FALSE)
filesizeStr <- filesizes[filesizes$filesize == filesize, "label"]
- ggplot(torperf, aes(x = as.Date(date, "%Y-%m-%d"), y = md/1e3,
- fill = "line")) +
+ t[t$date >= as.Date(start) & t$date <= as.Date(end) &
+ t$filesize == filesizeVal &
+ t$source == ifelse(source == 'all', '', source) &
+ t$server == server, ] %>%
+ transmute(date, q1 = q1 / 1e3, md = md / 1e3, q3 = q3 / 1e3) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ ggplot(aes(x = date, y = md, fill = "line")) +
geom_line(colour = colour, size = 0.75) +
- geom_ribbon(data = torperf, aes(x = date, ymin = q1/1e3,
- ymax = q3/1e3, fill = "ribbon")) +
+ geom_ribbon(aes(x = date, ymin = q1, ymax = q3, fill = "ribbon")) +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = unit_format(unit = "s"),
@@ -671,8 +616,7 @@ write_torperf <- function(start, end, source_, server_, filesize_, path) {
ifelse(filesize_ == '1mb', 1024 * 1024, 5 * 1024 * 1024)),
source == ifelse(source_ == 'all', '', source_),
server == server_) %>%
- select(date, q1, md, q3) %>%
- mutate(q1 = q1 / 1e3, md = md / 1e3, q3 = q3 / 1e3) %>%
+ transmute(date, q1 = q1 / 1e3, md = md / 1e3, q3 = q3 / 1e3) %>%
write.csv(path, quote = FALSE, row.names = FALSE)
}
@@ -680,31 +624,21 @@ prepare_torperf_failures <- function(start, end, source, server, filesize) {
filesizeVal <- ifelse(filesize == '50kb', 50 * 1024,
ifelse(filesize == '1mb', 1024 * 1024, 5 * 1024 * 1024))
t <- read.csv(paste(stats_dir, "torperf-1.1.csv", sep = ""),
- stringsAsFactors = FALSE)
- t <- t[t$date >= start & t$date <= end & t$filesize == filesizeVal &
+ colClasses = c("date" = "Date"))
+ t[t$date >= start & t$date <= end & t$filesize == filesizeVal &
t$source == ifelse(source == 'all', '', source) &
- t$server == server & t$requests > 0, ]
- torperf <- data.frame(date = as.Date(t$date, "%Y-%m-%d"),
- timeouts = t$timeouts / t$requests,
- failures = t$failures / t$requests)
- torperf
+ t$server == server & t$requests > 0, ] %>%
+ transmute(date, timeouts = timeouts / requests,
+ failures = failures / requests)
}
plot_torperf_failures <- function(start, end, source, server, filesize, path) {
- torperf <- prepare_torperf_failures(start, end, source, server, filesize)
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by="1 day")
- missing <- setdiff(dates, torperf$date)
- if (length(missing) > 0)
- torperf <- rbind(torperf,
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- timeouts = NA, failures = NA))
- torperf <- gather(torperf, variable, value, -date)
filesizes <- data.frame(filesizes = c("5mb", "1mb", "50kb"),
label = c("5 MiB", "1 MiB", "50 KiB"), stringsAsFactors = FALSE)
filesizeStr <- filesizes[filesizes$filesize == filesize, "label"]
- ggplot(torperf, aes(x = as.Date(date, "%Y-%m-%d"), y = value,
- colour = variable)) +
+ prepare_torperf_failures(start, end, source, server, filesize) %>%
+ gather(variable, value, -date) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
geom_point(size = 2) +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -726,21 +660,17 @@ write_torperf_failures <- function(start, end, source, server, filesize, path) {
}
prepare_connbidirect <- function(start, end) {
- c <- read.csv(paste(stats_dir, "connbidirect2.csv", sep = ""),
- stringsAsFactors = FALSE)
- c <- c[c$date >= start & c$date <= end, ]
- c <- data.frame(date = as.Date(c$date),
- direction = factor(c$direction,
- levels = c("both", "write", "read")),
- quantile = paste("X", c$quantile, sep = ""),
- fraction = c$fraction / 100)
- c <- spread(c, quantile, fraction)
- c
+ read.csv(paste(stats_dir, "connbidirect2.csv", sep = ""),
+ colClasses = c("date" = "Date", "direction" = "factor")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end)) %>%
+ mutate(quantile = paste("X", quantile, sep = ""),
+ fraction = fraction / 100) %>%
+ spread(quantile, fraction)
}
plot_connbidirect <- function(start, end, path) {
- c <- prepare_connbidirect(start, end)
- ggplot(c, aes(x = date, y = X0.5, colour = direction)) +
+ prepare_connbidirect(start, end) %>%
+ ggplot(aes(x = date, y = X0.5, colour = direction)) +
geom_line(size = 0.75) +
geom_ribbon(aes(x = date, ymin = X0.25, ymax = X0.75,
fill = direction), alpha = 0.5, show.legend = FALSE) +
@@ -772,10 +702,10 @@ write_connbidirect <- function(start, end, path) {
prepare_bandwidth_flags <- function(start, end) {
b <- read.csv(paste(stats_dir, "bandwidth.csv", sep = ""),
- stringsAsFactors = FALSE)
+ colClasses = c("date" = "Date"))
b <- b[b$date >= start & b$date <= end & b$isexit != '' &
b$isguard != '', ]
- b <- data.frame(date = as.Date(b$date, "%Y-%m-%d"),
+ b <- data.frame(date = b$date,
isexit = b$isexit == 't', isguard = b$isguard == 't',
advbw = b$advbw * 8 / 1e9,
bwhist = (b$bwread + b$bwwrite) * 8 / 2e9)
@@ -789,21 +719,6 @@ prepare_bandwidth_flags <- function(start, end) {
na.rm = TRUE, na.action = NULL)
b <- gather(b, type, value, -c(date, flag))
bandwidth <- b[b$value > 0, ]
- dates <- seq(from = as.Date(start, "%Y-%m-%d"),
- to = as.Date(end, "%Y-%m-%d"), by = "1 day")
- missing <- setdiff(dates, as.Date(bandwidth$date,
- origin = "1970-01-01"))
- if (length(missing) > 0) {
- bandwidth <- rbind(bandwidth,
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- type = "advbw", flag = "exit", value = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- type = "bwhist", flag = "exit", value = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- type = "advbw", flag = "guard", value = NA),
- data.frame(date = as.Date(missing, origin = "1970-01-01"),
- type = "bwhist", flag = "guard", value = NA))
- }
bandwidth <- data.frame(date = bandwidth$date,
variable = as.factor(paste(bandwidth$flag, "_", bandwidth$type,
sep = "")), value = bandwidth$value)
@@ -813,9 +728,10 @@ prepare_bandwidth_flags <- function(start, end) {
}
plot_bandwidth_flags <- function(start, end, path) {
- bandwidth <- prepare_bandwidth_flags(start, end)
- ggplot(bandwidth, aes(x = as.Date(date, "%Y-%m-%d"),
- y = value, colour = variable)) +
+ prepare_bandwidth_flags(start, end) %>%
+ complete(date = full_seq(date, period = 1),
+ variable = unique(variable)) %>%
+ ggplot(aes(x = date, y = value, colour = variable)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -1107,29 +1023,27 @@ write_userstats_bridge_combined <- function(start, end, country, path) {
}
prepare_advbwdist_perc <- function(start, end, p) {
- t <- read.csv(paste(stats_dir,
- "advbwdist.csv", sep = ""), stringsAsFactors = FALSE)
- t <- t[t$date >= start & t$date <= end &
- t$percentile %in% as.numeric(p), ]
- t <- data.frame(date = t$date, percentile = as.factor(t$percentile),
- variable = ifelse(t$isexit != "t", "all", "exits"),
- advbw = t$advbw * 8 / 1e9)
- t
+ read.csv(paste(stats_dir, "advbwdist.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end),
+ percentile %in% as.numeric(p)) %>%
+ transmute(date, percentile = as.factor(percentile),
+ variable = ifelse(isexit != "t", "all", "exits"),
+ advbw = advbw * 8 / 1e9)
}
plot_advbwdist_perc <- function(start, end, p, path) {
- t <- prepare_advbwdist_perc(start, end, p)
- t$variable <- ifelse(t$variable == "all", "All relays",
- "Exits only")
- ggplot(t, aes(x = as.Date(date), y = advbw, colour = percentile)) +
+ prepare_advbwdist_perc(start, end, p) %>%
+ mutate(variable = ifelse(variable == "all", "All relays",
+ "Exits only")) %>%
+ ggplot(aes(x = date, y = advbw, colour = percentile)) +
facet_grid(variable ~ .) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = unit_format(unit = "Gbit/s"),
limits = c(0, NA)) +
- scale_colour_hue(name = "Percentile",
- breaks = rev(levels(t$percentile))) +
+ scale_colour_hue(name = "Percentile") +
ggtitle("Advertised bandwidth distribution") +
labs(caption = copyright_notice)
ggsave(filename = path, width = 8, height = 5, dpi = 150)
@@ -1143,27 +1057,27 @@ write_advbwdist_perc <- function(start, end, p, path) {
}
prepare_advbwdist_relay <- function(start, end, n) {
- t <- read.csv(paste(stats_dir, "advbwdist.csv", sep = ""),
- stringsAsFactors = FALSE)
- t <- t[t$date >= start & t$date <= end & t$relay %in% as.numeric(n), ]
- t <- data.frame(date = t$date, relay = as.factor(t$relay),
- variable = ifelse(t$isexit != "t", "all", "exits"),
- advbw = t$advbw * 8 / 1e9)
- t
+ read.csv(paste(stats_dir, "advbwdist.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end),
+ relay %in% as.numeric(n)) %>%
+ transmute(date, relay = as.factor(relay),
+ variable = ifelse(isexit != "t", "all", "exits"),
+ advbw = advbw * 8 / 1e9)
}
plot_advbwdist_relay <- function(start, end, n, path) {
- t <- prepare_advbwdist_relay(start, end, n)
- t$variable <- ifelse(t$variable == "all", "All relays",
- "Exits only")
- ggplot(t, aes(x = as.Date(date), y = advbw, colour = relay)) +
+ prepare_advbwdist_relay(start, end, n) %>%
+ mutate(variable = ifelse(variable == "all", "All relays",
+ "Exits only")) %>%
+ ggplot(aes(x = date, y = advbw, colour = relay)) +
facet_grid(variable ~ .) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
scale_y_continuous(name = "", labels = unit_format(unit = "Gbit/s"),
limits = c(0, NA)) +
- scale_colour_hue(name = "n", breaks = levels(t$relay)) +
+ scale_colour_hue(name = "n") +
ggtitle("Advertised bandwidth of n-th fastest relays") +
labs(caption = copyright_notice)
ggsave(filename = path, width = 8, height = 5, dpi = 150)
@@ -1177,17 +1091,16 @@ write_advbwdist_relay <- function(start, end, n, path) {
}
prepare_hidserv_dir_onions_seen <- function(start, end) {
- h <- read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
- stringsAsFactors = FALSE)
- h <- h[h$date >= start & h$date <= end & h$type == "dir-onions-seen", ]
- h <- data.frame(date = as.Date(h$date, "%Y-%m-%d"),
- onions = ifelse(h$frac >= 0.01, h$wiqm, NA))
- h
+ read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end),
+ type == "dir-onions-seen") %>%
+ transmute(date = date, onions = ifelse(frac >= 0.01, wiqm, NA))
}
plot_hidserv_dir_onions_seen <- function(start, end, path) {
- h <- prepare_hidserv_dir_onions_seen(start, end)
- ggplot(h, aes(x = as.Date(date, origin = "1970-01-01"), y = onions)) +
+ prepare_hidserv_dir_onions_seen(start, end) %>%
+ ggplot(aes(x = date, y = onions)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -1203,19 +1116,17 @@ write_hidserv_dir_onions_seen <- function(start, end, path) {
}
prepare_hidserv_rend_relayed_cells <- function(start, end) {
- h <- read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
- stringsAsFactors = FALSE)
- h <- h[h$date >= start & h$date <= end &
- h$type == "rend-relayed-cells", ]
- h <- data.frame(date = as.Date(h$date, "%Y-%m-%d"),
- relayed = ifelse(h$frac >= 0.01,
- h$wiqm * 8 * 512 / (86400 * 1e9), NA))
- h
+ read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end),
+ type == "rend-relayed-cells") %>%
+ transmute(date,
+ relayed = ifelse(frac >= 0.01, wiqm * 8 * 512 / (86400 * 1e9), NA))
}
plot_hidserv_rend_relayed_cells <- function(start, end, path) {
- h <- prepare_hidserv_rend_relayed_cells(start, end)
- ggplot(h, aes(x = as.Date(date, origin = "1970-01-01"), y = relayed)) +
+ prepare_hidserv_rend_relayed_cells(start, end) %>%
+ ggplot(aes(x = date, y = relayed)) +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
labels = custom_labels, minor_breaks = custom_minor_breaks) +
@@ -1232,18 +1143,15 @@ write_hidserv_rend_relayed_cells <- function(start, end, path) {
}
prepare_hidserv_frac_reporting <- function(start, end) {
- h <- read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
- stringsAsFactors = FALSE)
- h <- h[h$date >= start & h$date <= end, ]
- h <- data.frame(date = as.Date(h$date, "%Y-%m-%d"),
- frac = h$frac, type = h$type)
- h
+ read.csv(paste(stats_dir, "hidserv.csv", sep = ""),
+ colClasses = c("date" = "Date")) %>%
+ filter(date >= as.Date(start), date <= as.Date(end)) %>%
+ select(date, frac, type)
}
plot_hidserv_frac_reporting <- function(start, end, path) {
- h <- prepare_hidserv_frac_reporting(start, end)
- ggplot(h, aes(x = as.Date(date, origin = "1970-01-01"), y = frac,
- colour = type)) +
+ prepare_hidserv_frac_reporting(start, end) %>%
+ ggplot(aes(x = date, y = frac, colour = type)) +
geom_line() +
geom_hline(yintercept = 0.01, linetype = 2) +
scale_x_date(name = "", breaks = custom_breaks,
@@ -1269,10 +1177,9 @@ write_hidserv_frac_reporting <- function(start, end, path) {
prepare_webstats_tb <- function(start, end) {
load(paste(rdata_dir, "webstats-tb.RData", sep = ""))
- d <- data
- d <- d[d$log_date >= start & d$log_date <= end, ]
- d$request_type <- factor(d$request_type)
- d
+ data %>%
+ filter(log_date >= as.Date(start), log_date <= as.Date(end)) %>%
+ mutate(request_type = factor(request_type))
}
plot_webstats_tb <- function(start, end, path) {
@@ -1306,17 +1213,17 @@ write_webstats_tb <- function(start, end, path) {
}
prepare_webstats_tb_platform <- function(start, end) {
- d <- read.csv(paste(stats_dir, "webstats.csv", sep = ""),
- stringsAsFactors = FALSE)
- d <- d[d$log_date >= start & d$log_date <= end & d$request_type == 'tbid', ]
- d <- aggregate(list(count = d$count), by = list(log_date = as.Date(d$log_date),
- platform = d$platform), FUN = sum)
- d
+ read.csv(paste(stats_dir, "webstats.csv", sep = ""),
+ colClasses = c("log_date" = "Date")) %>%
+ filter(log_date >= as.Date(start), log_date <= as.Date(end),
+ request_type == 'tbid') %>%
+ group_by(log_date, platform) %>%
+ summarize(count = sum(count))
}
plot_webstats_tb_platform <- function(start, end, path) {
- d <- prepare_webstats_tb_platform(start, end)
- ggplot(d, aes(x = log_date, y = count, colour = platform)) +
+ prepare_webstats_tb_platform(start, end) %>%
+ ggplot(aes(x = log_date, y = count, colour = platform)) +
geom_point() +
geom_line() +
scale_x_date(name = "", breaks = custom_breaks,
@@ -1342,13 +1249,13 @@ write_webstats_tb_platform <- function(start, end, path) {
plot_webstats_tb_locale <- function(start, end, path) {
d <- read.csv(paste(stats_dir, "webstats.csv", sep = ""),
- stringsAsFactors = FALSE)
+ colClasses = c("log_date" = "Date"))
d <- d[d$log_date >= start & d$log_date <= end & d$request_type == 'tbid', ]
e <- d
e <- aggregate(list(count = e$count), by = list(locale = e$locale), FUN = sum)
e <- e[order(e$count, decreasing = TRUE), ]
e <- e[1:5, ]
- d <- aggregate(list(count = d$count), by = list(log_date = as.Date(d$log_date),
+ d <- aggregate(list(count = d$count), by = list(log_date = d$log_date,
locale = ifelse(d$locale %in% e$locale, d$locale, '(other)')), FUN = sum)
ggplot(d, aes(x = log_date, y = count, colour = locale)) +
geom_point() +
@@ -1373,13 +1280,13 @@ plot_webstats_tb_locale <- function(start, end, path) {
# breaks and labels. Left as future work.
write_webstats_tb_locale <- function(start, end, path) {
d <- read.csv(paste(stats_dir, "webstats.csv", sep = ""),
- stringsAsFactors = FALSE)
+ colClasses = c("log_date" = "Date"))
d <- d[d$log_date >= start & d$log_date <= end & d$request_type == 'tbid', ]
e <- d
e <- aggregate(list(count = e$count), by = list(locale = e$locale), FUN = sum)
e <- e[order(e$count, decreasing = TRUE), ]
e <- e[1:5, ]
- d <- aggregate(list(count = d$count), by = list(log_date = as.Date(d$log_date),
+ d <- aggregate(list(count = d$count), by = list(log_date = d$log_date,
locale = ifelse(d$locale %in% e$locale, d$locale, 'other')), FUN = sum)
d %>%
mutate(locale = tolower(locale)) %>%
@@ -1390,10 +1297,9 @@ write_webstats_tb_locale <- function(start, end, path) {
prepare_webstats_tm <- function(start, end) {
load(paste(rdata_dir, "webstats-tm.RData", sep = ""))
- d <- data
- d <- d[d$log_date >= start & d$log_date <= end, ]
- d$request_type <- factor(d$request_type)
- d
+ data %>%
+ filter(log_date >= as.Date(start), log_date <= as.Date(end)) %>%
+ mutate(request_type = factor(request_type))
}
plot_webstats_tm <- function(start, end, path) {
