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[tor-commits] [metrics-web/master] Simplify Rserve setup.
commit e82de493279a0e74b55e5fd66a4056a1cecf19c5
Author: Karsten Loesing <karsten.loesing@xxxxxxx>
Date: Fri Jan 11 11:39:12 2019 +0100
Simplify Rserve setup.
---
src/main/R/rserver/Rserv.conf | 2 -
src/main/R/rserver/graphs.R | 1539 ------------------------------------
src/main/R/rserver/rserve-init.R | 1609 +++++++++++++++++++++++++++++++++++++-
src/main/R/rserver/tables.R | 58 --
4 files changed, 1600 insertions(+), 1608 deletions(-)
diff --git a/src/main/R/rserver/Rserv.conf b/src/main/R/rserver/Rserv.conf
deleted file mode 100644
index 1fb3039..0000000
--- a/src/main/R/rserver/Rserv.conf
+++ /dev/null
@@ -1,2 +0,0 @@
-workdir /srv/metrics.torproject.org/metrics/website/rserve/workdir
-source rserve-init.R
diff --git a/src/main/R/rserver/graphs.R b/src/main/R/rserver/graphs.R
deleted file mode 100644
index 0d7a90c..0000000
--- a/src/main/R/rserver/graphs.R
+++ /dev/null
@@ -1,1539 +0,0 @@
-countrylist <- list(
- "ad" = "Andorra",
- "ae" = "the United Arab Emirates",
- "af" = "Afghanistan",
- "ag" = "Antigua and Barbuda",
- "ai" = "Anguilla",
- "al" = "Albania",
- "am" = "Armenia",
- "an" = "the Netherlands Antilles",
- "ao" = "Angola",
- "aq" = "Antarctica",
- "ar" = "Argentina",
- "as" = "American Samoa",
- "at" = "Austria",
- "au" = "Australia",
- "aw" = "Aruba",
- "ax" = "the Aland Islands",
- "az" = "Azerbaijan",
- "ba" = "Bosnia and Herzegovina",
- "bb" = "Barbados",
- "bd" = "Bangladesh",
- "be" = "Belgium",
- "bf" = "Burkina Faso",
- "bg" = "Bulgaria",
- "bh" = "Bahrain",
- "bi" = "Burundi",
- "bj" = "Benin",
- "bl" = "Saint Bartelemey",
- "bm" = "Bermuda",
- "bn" = "Brunei",
- "bo" = "Bolivia",
- "bq" = "Bonaire, Sint Eustatius and Saba",
- "br" = "Brazil",
- "bs" = "the Bahamas",
- "bt" = "Bhutan",
- "bv" = "the Bouvet Island",
- "bw" = "Botswana",
- "by" = "Belarus",
- "bz" = "Belize",
- "ca" = "Canada",
- "cc" = "the Cocos (Keeling) Islands",
- "cd" = "the Democratic Republic of the Congo",
- "cf" = "Central African Republic",
- "cg" = "Congo",
- "ch" = "Switzerland",
- "ci" = "Côte d'Ivoire",
- "ck" = "the Cook Islands",
- "cl" = "Chile",
- "cm" = "Cameroon",
- "cn" = "China",
- "co" = "Colombia",
- "cr" = "Costa Rica",
- "cu" = "Cuba",
- "cv" = "Cape Verde",
- "cw" = "Curaçao",
- "cx" = "the Christmas Island",
- "cy" = "Cyprus",
- "cz" = "the Czech Republic",
- "de" = "Germany",
- "dj" = "Djibouti",
- "dk" = "Denmark",
- "dm" = "Dominica",
- "do" = "the Dominican Republic",
- "dz" = "Algeria",
- "ec" = "Ecuador",
- "ee" = "Estonia",
- "eg" = "Egypt",
- "eh" = "the Western Sahara",
- "er" = "Eritrea",
- "es" = "Spain",
- "et" = "Ethiopia",
- "fi" = "Finland",
- "fj" = "Fiji",
- "fk" = "the Falkland Islands (Malvinas)",
- "fm" = "the Federated States of Micronesia",
- "fo" = "the Faroe Islands",
- "fr" = "France",
- "ga" = "Gabon",
- "gb" = "the United Kingdom",
- "gd" = "Grenada",
- "ge" = "Georgia",
- "gf" = "French Guiana",
- "gg" = "Guernsey",
- "gh" = "Ghana",
- "gi" = "Gibraltar",
- "gl" = "Greenland",
- "gm" = "Gambia",
- "gn" = "Guinea",
- "gp" = "Guadeloupe",
- "gq" = "Equatorial Guinea",
- "gr" = "Greece",
- "gs" = "South Georgia and the South Sandwich Islands",
- "gt" = "Guatemala",
- "gu" = "Guam",
- "gw" = "Guinea-Bissau",
- "gy" = "Guyana",
- "hk" = "Hong Kong",
- "hm" = "Heard Island and McDonald Islands",
- "hn" = "Honduras",
- "hr" = "Croatia",
- "ht" = "Haiti",
- "hu" = "Hungary",
- "id" = "Indonesia",
- "ie" = "Ireland",
- "il" = "Israel",
- "im" = "the Isle of Man",
- "in" = "India",
- "io" = "the British Indian Ocean Territory",
- "iq" = "Iraq",
- "ir" = "Iran",
- "is" = "Iceland",
- "it" = "Italy",
- "je" = "Jersey",
- "jm" = "Jamaica",
- "jo" = "Jordan",
- "jp" = "Japan",
- "ke" = "Kenya",
- "kg" = "Kyrgyzstan",
- "kh" = "Cambodia",
- "ki" = "Kiribati",
- "km" = "Comoros",
- "kn" = "Saint Kitts and Nevis",
- "kp" = "North Korea",
- "kr" = "the Republic of Korea",
- "kw" = "Kuwait",
- "ky" = "the Cayman Islands",
- "kz" = "Kazakhstan",
- "la" = "Laos",
- "lb" = "Lebanon",
- "lc" = "Saint Lucia",
- "li" = "Liechtenstein",
- "lk" = "Sri Lanka",
- "lr" = "Liberia",
- "ls" = "Lesotho",
- "lt" = "Lithuania",
- "lu" = "Luxembourg",
- "lv" = "Latvia",
- "ly" = "Libya",
- "ma" = "Morocco",
- "mc" = "Monaco",
- "md" = "the Republic of Moldova",
- "me" = "Montenegro",
- "mf" = "Saint Martin",
- "mg" = "Madagascar",
- "mh" = "the Marshall Islands",
- "mk" = "Macedonia",
- "ml" = "Mali",
- "mm" = "Burma",
- "mn" = "Mongolia",
- "mo" = "Macau",
- "mp" = "the Northern Mariana Islands",
- "mq" = "Martinique",
- "mr" = "Mauritania",
- "ms" = "Montserrat",
- "mt" = "Malta",
- "mu" = "Mauritius",
- "mv" = "the Maldives",
- "mw" = "Malawi",
- "mx" = "Mexico",
- "my" = "Malaysia",
- "mz" = "Mozambique",
- "na" = "Namibia",
- "nc" = "New Caledonia",
- "ne" = "Niger",
- "nf" = "Norfolk Island",
- "ng" = "Nigeria",
- "ni" = "Nicaragua",
- "nl" = "the Netherlands",
- "no" = "Norway",
- "np" = "Nepal",
- "nr" = "Nauru",
- "nu" = "Niue",
- "nz" = "New Zealand",
- "om" = "Oman",
- "pa" = "Panama",
- "pe" = "Peru",
- "pf" = "French Polynesia",
- "pg" = "Papua New Guinea",
- "ph" = "the Philippines",
- "pk" = "Pakistan",
- "pl" = "Poland",
- "pm" = "Saint Pierre and Miquelon",
- "pn" = "the Pitcairn Islands",
- "pr" = "Puerto Rico",
- "ps" = "the Palestinian Territory",
- "pt" = "Portugal",
- "pw" = "Palau",
- "py" = "Paraguay",
- "qa" = "Qatar",
- "re" = "Reunion",
- "ro" = "Romania",
- "rs" = "Serbia",
- "ru" = "Russia",
- "rw" = "Rwanda",
- "sa" = "Saudi Arabia",
- "sb" = "the Solomon Islands",
- "sc" = "the Seychelles",
- "sd" = "Sudan",
- "se" = "Sweden",
- "sg" = "Singapore",
- "sh" = "Saint Helena",
- "si" = "Slovenia",
- "sj" = "Svalbard and Jan Mayen",
- "sk" = "Slovakia",
- "sl" = "Sierra Leone",
- "sm" = "San Marino",
- "sn" = "Senegal",
- "so" = "Somalia",
- "sr" = "Suriname",
- "ss" = "South Sudan",
- "st" = "São Tomé and PrÃncipe",
- "sv" = "El Salvador",
- "sx" = "Sint Maarten",
- "sy" = "the Syrian Arab Republic",
- "sz" = "Swaziland",
- "tc" = "Turks and Caicos Islands",
- "td" = "Chad",
- "tf" = "the French Southern Territories",
- "tg" = "Togo",
- "th" = "Thailand",
- "tj" = "Tajikistan",
- "tk" = "Tokelau",
- "tl" = "East Timor",
- "tm" = "Turkmenistan",
- "tn" = "Tunisia",
- "to" = "Tonga",
- "tr" = "Turkey",
- "tt" = "Trinidad and Tobago",
- "tv" = "Tuvalu",
- "tw" = "Taiwan",
- "tz" = "the United Republic of Tanzania",
- "ua" = "Ukraine",
- "ug" = "Uganda",
- "um" = "the United States Minor Outlying Islands",
- "us" = "the United States",
- "uy" = "Uruguay",
- "uz" = "Uzbekistan",
- "va" = "Vatican City",
- "vc" = "Saint Vincent and the Grenadines",
- "ve" = "Venezuela",
- "vg" = "the British Virgin Islands",
- "vi" = "the United States Virgin Islands",
- "vn" = "Vietnam",
- "vu" = "Vanuatu",
- "wf" = "Wallis and Futuna",
- "ws" = "Samoa",
- "xk" = "Kosovo",
- "ye" = "Yemen",
- "yt" = "Mayotte",
- "za" = "South Africa",
- "zm" = "Zambia",
- "zw" = "Zimbabwe")
-
-countryname <- function(country) {
- res <- countrylist[[country]]
- if (is.null(res))
- res <- "no-man's-land"
- res
-}
-
-# Helper function that takes date limits as input and returns major breaks as
-# output. The main difference to the built-in major breaks is that we're trying
-# harder to align major breaks with first days of weeks (Sundays), months,
-# quarters, or years.
-custom_breaks <- function(input) {
- scales_index <- cut(as.numeric(max(input) - min(input)),
- c(-1, 7, 12, 56, 180, 600, 2000, Inf), labels = FALSE)
- from_print_format <- c("%F", "%F", "%Y-W%U-7", "%Y-%m-01", "%Y-01-01",
- "%Y-01-01", "%Y-01-01")[scales_index]
- from_parse_format <- ifelse(scales_index == 3, "%Y-W%U-%u", "%F")
- by <- c("1 day", "2 days", "1 week", "1 month", "3 months", "1 year",
- "2 years")[scales_index]
- seq(as.Date(as.character(min(input), from_print_format),
- format = from_parse_format), max(input), by = by)
-}
-
-# Helper function that takes date limits as input and returns minor breaks as
-# output. As opposed to the built-in minor breaks, we're not just adding one
-# minor break half way through between two major breaks. Instead, we're plotting
-# a minor break for every day, week, month, or quarter between two major breaks.
-custom_minor_breaks <- function(input) {
- scales_index <- cut(as.numeric(max(input) - min(input)),
- c(-1, 7, 12, 56, 180, 600, 2000, Inf), labels = FALSE)
- from_print_format <- c("%F", "%F", "%F", "%Y-W%U-7", "%Y-%m-01", "%Y-01-01",
- "%Y-01-01")[scales_index]
- from_parse_format <- ifelse(scales_index == 4, "%Y-W%U-%u", "%F")
- by <- c("1 day", "1 day", "1 day", "1 week", "1 month", "3 months",
- "1 year")[scales_index]
- seq(as.Date(as.character(min(input), from_print_format),
- format = from_parse_format), max(input), by = by)
-}
-
-# Helper function that takes breaks as input and returns labels as output. We're
-# going all ISO-8601 here, though we're not just writing %Y-%m-%d everywhere,
-# but %Y-%m or %Y if all breaks are on the first of a month or even year.
-custom_labels <- function(breaks) {
- if (all(format(breaks, format = "%m-%d") == "01-01", na.rm = TRUE)) {
- format(breaks, format = "%Y")
- } else {
- if (all(format(breaks, format = "%d") == "01", na.rm = TRUE)) {
- format(breaks, format = "%Y-%m")
- } else {
- format(breaks, format = "%F")
- }
- }
-}
-
-# Helper function to format numbers in non-scientific notation with spaces as
-# thousands separator.
-formatter <- function(x, ...) {
- format(x, ..., scientific = FALSE, big.mark = " ")
-}
-
-theme_update(
- # Make plot title centered, and leave some room to the plot.
- plot.title = element_text(hjust = 0.5, margin = margin(b = 11)),
-
- # Leave a little more room to the right for long x axis labels.
- plot.margin = margin(5.5, 11, 5.5, 5.5)
-)
-
-# Set the default line size of geom_line() to 1.
-update_geom_defaults("line", list(size = 1))
-
-copyright_notice <- "The Tor Project - https://metrics.torproject.org/";
-
-stats_dir <- "/srv/metrics.torproject.org/metrics/shared/stats/"
-
-rdata_dir <- "/srv/metrics.torproject.org/metrics/shared/RData/"
-
-# Helper function that copies the appropriate no data object to filename.
-copy_no_data <- function(filename) {
- len <- nchar(filename)
- extension <- substr(filename, len - 3, len)
- if (".csv" == extension) {
- write("# No data available for the given parameters.", file=filename)
- } else {
- file.copy(paste(rdata_dir, "no-data-available", extension, sep = ""),
- filename)
- }
-}
-
-# Helper function wrapping calls into error handling.
-robust_call <- function(wrappee, filename) {
- tryCatch(eval(wrappee), error = function(e) copy_no_data(filename),
- finally = if (!file.exists(filename) || file.size(filename) == 0) {
- copy_no_data(filename)
- })
-}
-
-# Write the result of the given FUN, typically a prepare_ function, as .csv file
-# to the given path_p.
-write_data <- function(FUN, ..., path_p) {
- FUN(...) %>%
- write.csv(path_p, quote = FALSE, row.names = FALSE, na = "")
-}
-
-# Disable readr's automatic progress bar.
-options(readr.show_progress = FALSE)
-
-prepare_networksize <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "networksize.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- relays = col_double(),
- bridges = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
-}
-
-plot_networksize <- function(start_p, end_p, path_p) {
- prepare_networksize(start_p, end_p) %>%
- 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)) +
- scale_colour_hue("", breaks = c("relays", "bridges"),
- labels = c("Relays", "Bridges")) +
- ggtitle("Number of relays") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_versions <- function(start_p = NULL, end_p = NULL) {
- read_csv(paste(stats_dir, "versions.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- version = col_character(),
- relays = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
-}
-
-plot_versions <- function(start_p, end_p, path_p) {
- s <- prepare_versions(start_p, end_p)
- known_versions <- unique(s$version)
- getPalette <- colorRampPalette(brewer.pal(12, "Paired"))
- colours <- data.frame(breaks = known_versions,
- values = rep(brewer.pal(min(12, length(known_versions)), "Paired"),
- len = length(known_versions)),
- stringsAsFactors = FALSE)
- versions <- s[s$version %in% known_versions, ]
- visible_versions <- sort(unique(versions$version))
- versions <- versions %>%
- complete(date = full_seq(date, period = 1), nesting(version)) %>%
- ggplot(aes(x = date, y = relays, colour = version)) +
- geom_line() +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
- scale_colour_manual(name = "Tor version",
- values = colours[colours$breaks %in% visible_versions, 2],
- breaks = visible_versions) +
- ggtitle("Relay versions") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_platforms <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "platforms.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- platform = col_factor(levels = NULL),
- relays = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- mutate(platform = tolower(platform)) %>%
- spread(platform, relays)
-}
-
-plot_platforms <- function(start_p, end_p, path_p) {
- prepare_platforms(start_p, end_p) %>%
- gather(platform, relays, -date) %>%
- complete(date = full_seq(date, period = 1), nesting(platform)) %>%
- 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) +
- scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
- scale_colour_manual(name = "Platform",
- breaks = c("linux", "macos", "bsd", "windows", "other"),
- labels = c("Linux", "macOS", "BSD", "Windows", "Other"),
- values = c("linux" = "#56B4E9", "macos" = "#333333", "bsd" = "#E69F00",
- "windows" = "#0072B2", "other" = "#009E73")) +
- ggtitle("Relay platforms") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_dirbytes <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "bandwidth.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- isexit = col_logical(),
- isguard = col_logical(),
- bwread = col_skip(),
- bwwrite = col_skip(),
- dirread = col_double(),
- dirwrite = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(is.na(isexit)) %>%
- filter(is.na(isguard)) %>%
- mutate(dirread = dirread * 8 / 1e9,
- dirwrite = dirwrite * 8 / 1e9) %>%
- select(date, dirread, dirwrite)
-}
-
-plot_dirbytes <- function(start_p, end_p, path_p) {
- prepare_dirbytes(start_p, end_p) %>%
- gather(variable, value, -date) %>%
- complete(date = full_seq(date, period = 1), nesting(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) +
- scale_y_continuous(name = "", labels = unit_format(unit = "Gbit/s"),
- limits = c(0, NA)) +
- scale_colour_hue(name = "",
- breaks = c("dirwrite", "dirread"),
- labels = c("Written dir bytes", "Read dir bytes")) +
- ggtitle("Number of bytes spent on answering directory requests") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_relayflags <- function(start_p = NULL, end_p = NULL, flag_p = NULL) {
- read_csv(file = paste(stats_dir, "relayflags.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- flag = col_factor(levels = NULL),
- relays = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(flag_p)) flag %in% flag_p else TRUE)
-}
-
-plot_relayflags <- function(start_p, end_p, flag_p, path_p) {
- prepare_relayflags(start_p, end_p, flag_p) %>%
- complete(date = full_seq(date, period = 1), flag = unique(flag)) %>%
- ggplot(aes(x = date, y = relays, colour = 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)) +
- scale_colour_manual(name = "Relay flags", values = c("#E69F00",
- "#56B4E9", "#009E73", "#EE6A50", "#000000", "#0072B2"),
- breaks = flag_p, labels = flag_p) +
- ggtitle("Number of relays with relay flags assigned") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_torperf <- function(start_p = NULL, end_p = NULL, server_p = NULL,
- filesize_p = NULL) {
- read_csv(file = paste(stats_dir, "torperf-1.1.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- filesize = col_double(),
- source = col_character(),
- server = col_character(),
- q1 = col_double(),
- md = col_double(),
- q3 = col_double(),
- timeouts = col_skip(),
- failures = col_skip(),
- requests = col_skip())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(server_p)) server == server_p else TRUE) %>%
- filter(if (!is.null(filesize_p))
- filesize == ifelse(filesize_p == "50kb", 50 * 1024,
- ifelse(filesize_p == "1mb", 1024 * 1024, 5 * 1024 * 1024)) else
- TRUE) %>%
- transmute(date, filesize, source, server, q1 = q1 / 1e3, md = md / 1e3,
- q3 = q3 / 1e3)
-}
-
-plot_torperf <- function(start_p, end_p, server_p, filesize_p, path_p) {
- prepare_torperf(start_p, end_p, server_p, filesize_p) %>%
- filter(source != "") %>%
- complete(date = full_seq(date, period = 1), nesting(source)) %>%
- ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
- geom_ribbon(alpha = 0.5) +
- geom_line(aes(colour = source), size = 0.75) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = unit_format(unit = "s"),
- limits = c(0, NA)) +
- scale_fill_hue(name = "Source") +
- scale_colour_hue(name = "Source") +
- ggtitle(paste("Time to complete",
- ifelse(filesize_p == "50kb", "50 KiB",
- ifelse(filesize_p == "1mb", "1 MiB", "5 MiB")),
- "request to", server_p, "server")) +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_torperf_failures <- function(start_p = NULL, end_p = NULL,
- server_p = NULL, filesize_p = NULL) {
- read_csv(file = paste(stats_dir, "torperf-1.1.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- filesize = col_double(),
- source = col_character(),
- server = col_character(),
- q1 = col_skip(),
- md = col_skip(),
- q3 = col_skip(),
- timeouts = col_double(),
- failures = col_double(),
- requests = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(filesize_p))
- filesize == ifelse(filesize_p == "50kb", 50 * 1024,
- ifelse(filesize_p == "1mb", 1024 * 1024, 5 * 1024 * 1024)) else
- TRUE) %>%
- filter(if (!is.null(server_p)) server == server_p else TRUE) %>%
- filter(requests > 0) %>%
- transmute(date, filesize, source, server, timeouts = timeouts / requests,
- failures = failures / requests)
-}
-
-plot_torperf_failures <- function(start_p, end_p, server_p, filesize_p,
- path_p) {
- prepare_torperf_failures(start_p, end_p, server_p, filesize_p) %>%
- filter(source != "") %>%
- gather(variable, value, -c(date, filesize, source, server)) %>%
- mutate(variable = factor(variable, levels = c("timeouts", "failures"),
- labels = c("Timeouts", "Failures"))) %>%
- ggplot(aes(x = date, y = value, colour = source)) +
- geom_point(size = 2, alpha = 0.5) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = percent, limits = c(0, NA)) +
- scale_colour_hue(name = "Source") +
- facet_grid(variable ~ .) +
- ggtitle(paste("Timeouts and failures of",
- ifelse(filesize_p == "50kb", "50 KiB",
- ifelse(filesize_p == "1mb", "1 MiB", "5 MiB")),
- "requests to", server_p, "server")) +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_onionperf_buildtimes <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "buildtimes.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- source = col_character(),
- position = col_double(),
- q1 = col_double(),
- md = col_double(),
- q3 = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
-}
-
-plot_onionperf_buildtimes <- function(start_p, end_p, path_p) {
- prepare_onionperf_buildtimes(start_p, end_p) %>%
- filter(source != "") %>%
- mutate(date = as.Date(date),
- position = factor(position, levels = seq(1, 3, 1),
- labels = c("1st hop", "2nd hop", "3rd hop"))) %>%
- complete(date = full_seq(date, period = 1), nesting(source, position)) %>%
- ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
- geom_ribbon(alpha = 0.5) +
- geom_line(aes(colour = source), size = 0.75) +
- facet_grid(position ~ .) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = unit_format(unit = "ms"),
- limits = c(0, NA)) +
- scale_fill_hue(name = "Source") +
- scale_colour_hue(name = "Source") +
- ggtitle("Circuit build times") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_onionperf_latencies <- function(start_p = NULL, end_p = NULL,
- server_p = NULL) {
- read_csv(file = paste(stats_dir, "latencies.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- source = col_character(),
- server = col_character(),
- q1 = col_double(),
- md = col_double(),
- q3 = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(server_p)) server == server_p else TRUE)
-}
-
-plot_onionperf_latencies <- function(start_p, end_p, server_p, path_p) {
- prepare_onionperf_latencies(start_p, end_p, server_p) %>%
- filter(source != "") %>%
- complete(date = full_seq(date, period = 1), nesting(source)) %>%
- ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
- geom_ribbon(alpha = 0.5) +
- geom_line(aes(colour = source), size = 0.75) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = unit_format(unit = "ms"),
- limits = c(0, NA)) +
- scale_fill_hue(name = "Source") +
- scale_colour_hue(name = "Source") +
- ggtitle(paste("Circuit round-trip latencies to", server_p, "server")) +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_connbidirect <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "connbidirect2.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- direction = col_factor(levels = NULL),
- quantile = col_double(),
- fraction = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- mutate(quantile = paste("X", quantile, sep = ""),
- fraction = fraction / 100) %>%
- spread(quantile, fraction) %>%
- rename(q1 = X0.25, md = X0.5, q3 = X0.75)
-}
-
-plot_connbidirect <- function(start_p, end_p, path_p) {
- prepare_connbidirect(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1), nesting(direction)) %>%
- ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = direction)) +
- geom_ribbon(alpha = 0.5) +
- geom_line(aes(colour = direction), size = 0.75) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = percent, limits = c(0, NA)) +
- scale_colour_hue(name = "Medians and interquartile ranges",
- breaks = c("both", "write", "read"),
- labels = c("Both reading and writing", "Mostly writing",
- "Mostly reading")) +
- scale_fill_hue(name = "Medians and interquartile ranges",
- breaks = c("both", "write", "read"),
- labels = c("Both reading and writing", "Mostly writing",
- "Mostly reading")) +
- ggtitle("Fraction of connections used uni-/bidirectionally") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_bandwidth_flags <- function(start_p = NULL, end_p = NULL) {
- advbw <- read_csv(file = paste(stats_dir, "advbw.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- isexit = col_logical(),
- isguard = col_logical(),
- advbw = col_double())) %>%
- transmute(date, have_guard_flag = isguard, have_exit_flag = isexit,
- variable = "advbw", value = advbw * 8 / 1e9)
- bwhist <- read_csv(file = paste(stats_dir, "bandwidth.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- isexit = col_logical(),
- isguard = col_logical(),
- bwread = col_double(),
- bwwrite = col_double(),
- dirread = col_double(),
- dirwrite = col_double())) %>%
- transmute(date, have_guard_flag = isguard, have_exit_flag = isexit,
- variable = "bwhist", value = (bwread + bwwrite) * 8 / 2e9)
- rbind(advbw, bwhist) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(!is.na(have_exit_flag)) %>%
- filter(!is.na(have_guard_flag)) %>%
- spread(variable, value)
-}
-
-plot_bandwidth_flags <- function(start_p, end_p, path_p) {
- prepare_bandwidth_flags(start_p, end_p) %>%
- gather(variable, value, c(advbw, bwhist)) %>%
- unite(flags, have_guard_flag, have_exit_flag) %>%
- mutate(flags = factor(flags,
- levels = c("FALSE_TRUE", "TRUE_TRUE", "TRUE_FALSE", "FALSE_FALSE"),
- labels = c("Exit only", "Guard and Exit", "Guard only",
- "Neither Guard nor Exit"))) %>%
- mutate(variable = ifelse(variable == "advbw",
- "Advertised bandwidth", "Consumed bandwidth")) %>%
- ggplot(aes(x = date, y = value, fill = flags)) +
- geom_area() +
- 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_fill_manual(name = "",
- values = c("#03B3FF", "#39FF02", "#FFFF00", "#AAAA99")) +
- facet_grid(variable ~ .) +
- ggtitle("Advertised and consumed bandwidth by relay flags") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_userstats_relay_country <- function(start_p = NULL, end_p = NULL,
- country_p = NULL, events_p = NULL) {
- read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- node = col_character(),
- country = col_character(),
- transport = col_character(),
- version = col_character(),
- lower = col_double(),
- upper = col_double(),
- clients = col_double(),
- frac = col_double()),
- na = character()) %>%
- filter(node == "relay") %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(country_p))
- country == ifelse(country_p == "all", "", country_p) else TRUE) %>%
- filter(transport == "") %>%
- filter(version == "") %>%
- select(date, country, clients, lower, upper, frac) %>%
- rename(users = clients)
-}
-
-plot_userstats_relay_country <- function(start_p, end_p, country_p, events_p,
- path_p) {
- u <- prepare_userstats_relay_country(start_p, end_p, country_p, events_p) %>%
- complete(date = full_seq(date, period = 1))
- plot <- ggplot(u, aes(x = date, y = users))
- if (length(na.omit(u$users)) > 0 & events_p != "off" &
- country_p != "all") {
- upturns <- u[u$users > u$upper, c("date", "users")]
- downturns <- u[u$users < u$lower, c("date", "users")]
- if (events_p == "on") {
- u[!is.na(u$lower) & u$lower < 0, "lower"] <- 0
- plot <- plot +
- geom_ribbon(data = u, aes(ymin = lower, ymax = upper), fill = "gray")
- }
- if (length(upturns$date) > 0)
- plot <- plot +
- geom_point(data = upturns, aes(x = date, y = users), size = 5,
- colour = "dodgerblue2")
- if (length(downturns$date) > 0)
- plot <- plot +
- geom_point(data = downturns, aes(x = date, y = users), size = 5,
- colour = "firebrick2")
- }
- plot <- plot +
- 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)) +
- ggtitle(paste("Directly connecting users",
- ifelse(country_p == "all", "",
- paste(" from", countryname(country_p))), sep = "")) +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_userstats_bridge_country <- function(start_p = NULL, end_p = NULL,
- country_p = NULL) {
- read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- node = col_character(),
- country = col_character(),
- transport = col_character(),
- version = col_character(),
- lower = col_double(),
- upper = col_double(),
- clients = col_double(),
- frac = col_double()),
- na = character()) %>%
- filter(node == "bridge") %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(country_p))
- country == ifelse(country_p == "all", "", country_p) else TRUE) %>%
- filter(transport == "") %>%
- filter(version == "") %>%
- select(date, country, clients, frac) %>%
- rename(users = clients)
-}
-
-plot_userstats_bridge_country <- function(start_p, end_p, country_p, path_p) {
- prepare_userstats_bridge_country(start_p, end_p, country_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- ggplot(aes(x = date, y = users)) +
- 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)) +
- ggtitle(paste("Bridge users",
- ifelse(country_p == "all", "",
- paste(" from", countryname(country_p))), sep = "")) +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_userstats_bridge_transport <- function(start_p = NULL, end_p = NULL,
- transport_p = NULL) {
- u <- read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- node = col_character(),
- country = col_character(),
- transport = col_character(),
- version = col_character(),
- lower = col_double(),
- upper = col_double(),
- clients = col_double(),
- frac = col_double())) %>%
- filter(node == "bridge") %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(is.na(country)) %>%
- filter(is.na(version)) %>%
- filter(!is.na(transport)) %>%
- select(date, transport, clients, frac)
- if (is.null(transport_p) || "!<OR>" %in% transport_p) {
- n <- u %>%
- filter(transport != "<OR>") %>%
- group_by(date, frac) %>%
- summarize(clients = sum(clients))
- u <- rbind(u, data.frame(date = n$date, transport = "!<OR>",
- clients = n$clients, frac = n$frac))
- }
- u %>%
- filter(if (!is.null(transport_p)) transport %in% transport_p else TRUE) %>%
- select(date, transport, clients, frac) %>%
- rename(users = clients) %>%
- arrange(date, transport)
-}
-
-plot_userstats_bridge_transport <- function(start_p, end_p, transport_p,
- path_p) {
- if (length(transport_p) > 1) {
- title <- paste("Bridge users by transport")
- } else {
- title <- paste("Bridge users using",
- ifelse(transport_p == "<??>", "unknown pluggable transport(s)",
- ifelse(transport_p == "<OR>", "default OR protocol",
- ifelse(transport_p == "!<OR>", "any pluggable transport",
- ifelse(transport_p == "fte", "FTE",
- ifelse(transport_p == "websocket", "Flash proxy/websocket",
- paste("transport", transport_p)))))))
- }
- u <- prepare_userstats_bridge_transport(start_p, end_p, transport_p) %>%
- complete(date = full_seq(date, period = 1), nesting(transport))
- if (length(transport_p) > 1) {
- plot <- ggplot(u, aes(x = date, y = users, colour = transport))
- } else {
- plot <- ggplot(u, aes(x = date, y = users))
- }
- plot <- plot +
- 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)) +
- ggtitle(title) +
- labs(caption = copyright_notice)
- if (length(transport_p) > 1) {
- plot <- plot +
- scale_colour_hue(name = "", breaks = transport_p,
- labels = ifelse(transport_p == "<??>", "Unknown PT",
- ifelse(transport_p == "<OR>", "Default OR protocol",
- ifelse(transport_p == "!<OR>", "Any PT",
- ifelse(transport_p == "fte", "FTE",
- ifelse(transport_p == "websocket", "Flash proxy/websocket",
- transport_p))))))
- }
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_userstats_bridge_version <- function(start_p = NULL, end_p = NULL,
- version_p = NULL) {
- read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- node = col_character(),
- country = col_character(),
- transport = col_character(),
- version = col_character(),
- lower = col_double(),
- upper = col_double(),
- clients = col_double(),
- frac = col_double())) %>%
- filter(node == "bridge") %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(is.na(country)) %>%
- filter(is.na(transport)) %>%
- filter(if (!is.null(version_p)) version == version_p else TRUE) %>%
- select(date, version, clients, frac) %>%
- rename(users = clients)
-}
-
-plot_userstats_bridge_version <- function(start_p, end_p, version_p, path_p) {
- prepare_userstats_bridge_version(start_p, end_p, version_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- ggplot(aes(x = date, y = users)) +
- 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)) +
- ggtitle(paste("Bridge users using IP", version_p, sep = "")) +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_userstats_bridge_combined <- function(start_p = NULL, end_p = NULL,
- country_p = NULL) {
- if (!is.null(country_p) && country_p == "all") {
- prepare_userstats_bridge_country(start_p, end_p, country_p)
- } else {
- read_csv(file = paste(stats_dir, "userstats-combined.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- node = col_skip(),
- country = col_character(),
- transport = col_character(),
- version = col_skip(),
- frac = col_double(),
- low = col_double(),
- high = col_double()),
- na = character()) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(country_p)) country == country_p else TRUE) %>%
- select(date, country, transport, low, high, frac) %>%
- arrange(date, country, transport)
- }
-}
-
-plot_userstats_bridge_combined <- function(start_p, end_p, country_p, path_p) {
- if (country_p == "all") {
- plot_userstats_bridge_country(start_p, end_p, country_p, path_p)
- } else {
- top <- 3
- u <- prepare_userstats_bridge_combined(start_p, end_p, country_p)
- a <- aggregate(list(mid = (u$high + u$low) / 2),
- by = list(transport = u$transport), FUN = sum)
- a <- a[order(a$mid, decreasing = TRUE)[1:top], ]
- u <- u[u$transport %in% a$transport, ] %>%
- complete(date = full_seq(date, period = 1), nesting(country, transport))
- title <- paste("Bridge users by transport from ",
- countryname(country_p), sep = "")
- ggplot(u, aes(x = as.Date(date), ymin = low, ymax = high,
- fill = transport)) +
- geom_ribbon(alpha = 0.5, size = 0.5) +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", limits = c(0, NA), labels = formatter) +
- scale_colour_hue("Top-3 transports") +
- scale_fill_hue("Top-3 transports") +
- ggtitle(title) +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
- }
-}
-
-prepare_advbwdist_perc <- function(start_p = NULL, end_p = NULL, p_p = NULL) {
- read_csv(file = paste(stats_dir, "advbwdist.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- isexit = col_logical(),
- relay = col_skip(),
- percentile = col_integer(),
- advbw = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(p_p)) percentile %in% as.numeric(p_p) else
- percentile != "") %>%
- transmute(date, percentile = as.factor(percentile),
- variable = ifelse(is.na(isexit), "all", "exits"),
- advbw = advbw * 8 / 1e9) %>%
- spread(variable, advbw) %>%
- rename(p = percentile)
-}
-
-plot_advbwdist_perc <- function(start_p, end_p, p_p, path_p) {
- prepare_advbwdist_perc(start_p, end_p, p_p) %>%
- gather(variable, advbw, -c(date, p)) %>%
- mutate(variable = ifelse(variable == "all", "All relays",
- "Exits only")) %>%
- complete(date = full_seq(date, period = 1), nesting(p, variable)) %>%
- ggplot(aes(x = date, y = advbw, colour = p)) +
- 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") +
- ggtitle("Advertised bandwidth distribution") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_advbwdist_relay <- function(start_p = NULL, end_p = NULL, n_p = NULL) {
- read_csv(file = paste(stats_dir, "advbwdist.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- isexit = col_logical(),
- relay = col_integer(),
- percentile = col_skip(),
- advbw = col_double())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(if (!is.null(n_p)) relay %in% as.numeric(n_p) else
- relay != "") %>%
- transmute(date, relay = as.factor(relay),
- variable = ifelse(is.na(isexit), "all", "exits"),
- advbw = advbw * 8 / 1e9) %>%
- spread(variable, advbw) %>%
- rename(n = relay)
-}
-
-plot_advbwdist_relay <- function(start_p, end_p, n_p, path_p) {
- prepare_advbwdist_relay(start_p, end_p, n_p) %>%
- gather(variable, advbw, -c(date, n)) %>%
- mutate(variable = ifelse(variable == "all", "All relays",
- "Exits only")) %>%
- complete(date = full_seq(date, period = 1), nesting(n, variable)) %>%
- ggplot(aes(x = date, y = advbw, colour = n)) +
- 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") +
- ggtitle("Advertised bandwidth of n-th fastest relays") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_hidserv_dir_onions_seen <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "hidserv.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- type = col_factor(levels = NULL),
- wmean = col_skip(),
- wmedian = col_skip(),
- wiqm = col_double(),
- frac = col_double(),
- stats = col_skip())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(type == "dir-onions-seen") %>%
- transmute(date, onions = ifelse(frac >= 0.01, wiqm, NA), frac)
-}
-
-plot_hidserv_dir_onions_seen <- function(start_p, end_p, path_p) {
- prepare_hidserv_dir_onions_seen(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- ggplot(aes(x = date, y = onions)) +
- geom_line() +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", limits = c(0, NA), labels = formatter) +
- ggtitle("Unique .onion addresses") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_hidserv_rend_relayed_cells <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "hidserv.csv", sep = ""),
- col_types = cols(
- date = col_date(format = ""),
- type = col_factor(levels = NULL),
- wmean = col_skip(),
- wmedian = col_skip(),
- wiqm = col_double(),
- frac = col_double(),
- stats = col_skip())) %>%
- filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
- filter(type == "rend-relayed-cells") %>%
- transmute(date,
- relayed = ifelse(frac >= 0.01, wiqm * 8 * 512 / (86400 * 1e9), NA), frac)
-}
-
-plot_hidserv_rend_relayed_cells <- function(start_p, end_p, path_p) {
- prepare_hidserv_rend_relayed_cells(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- ggplot(aes(x = date, y = relayed)) +
- 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)) +
- ggtitle("Onion-service traffic") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_webstats_tb <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
- col_types = cols(
- log_date = col_date(format = ""),
- request_type = col_factor(levels = NULL),
- platform = col_skip(),
- channel = col_skip(),
- locale = col_skip(),
- incremental = col_skip(),
- count = col_double())) %>%
- filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
- filter(request_type %in% c("tbid", "tbsd", "tbup", "tbur")) %>%
- group_by(log_date, request_type) %>%
- summarize(count = sum(count)) %>%
- spread(request_type, count) %>%
- rename(date = log_date, initial_downloads = tbid,
- signature_downloads = tbsd, update_pings = tbup,
- update_requests = tbur)
-}
-
-plot_webstats_tb <- function(start_p, end_p, path_p) {
- prepare_webstats_tb(start_p, end_p) %>%
- gather(request_type, count, -date) %>%
- mutate(request_type = factor(request_type,
- levels = c("initial_downloads", "signature_downloads", "update_pings",
- "update_requests"),
- labels = c("Initial downloads", "Signature downloads", "Update pings",
- "Update requests"))) %>%
- ungroup() %>%
- complete(date = full_seq(date, period = 1), nesting(request_type)) %>%
- ggplot(aes(x = date, y = count)) +
- geom_point() +
- geom_line() +
- facet_grid(request_type ~ ., scales = "free_y") +
- 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)) +
- theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
- strip.background = element_rect(fill = NA)) +
- ggtitle("Tor Browser downloads and updates") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_webstats_tb_platform <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
- col_types = cols(
- log_date = col_date(format = ""),
- request_type = col_factor(levels = NULL),
- platform = col_factor(levels = NULL),
- channel = col_skip(),
- locale = col_skip(),
- incremental = col_skip(),
- count = col_double())) %>%
- filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
- filter(request_type %in% c("tbid", "tbup")) %>%
- group_by(log_date, platform, request_type) %>%
- summarize(count = sum(count)) %>%
- spread(request_type, count, fill = 0) %>%
- rename(date = log_date, initial_downloads = tbid, update_pings = tbup)
-}
-
-plot_webstats_tb_platform <- function(start_p, end_p, path_p) {
- prepare_webstats_tb_platform(start_p, end_p) %>%
- gather(request_type, count, -c(date, platform)) %>%
- mutate(request_type = factor(request_type,
- levels = c("initial_downloads", "update_pings"),
- labels = c("Initial downloads", "Update pings"))) %>%
- ungroup() %>%
- complete(date = full_seq(date, period = 1),
- nesting(platform, request_type)) %>%
- ggplot(aes(x = date, y = count, colour = platform)) +
- geom_point() +
- 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)) +
- scale_colour_hue(name = "Platform",
- breaks = c("w", "m", "l", "o", ""),
- labels = c("Windows", "macOS", "Linux", "Other", "Unknown")) +
- facet_grid(request_type ~ ., scales = "free_y") +
- theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
- strip.background = element_rect(fill = NA),
- legend.position = "top") +
- ggtitle("Tor Browser downloads and updates by platform") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_webstats_tb_locale <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
- col_types = cols(
- log_date = col_date(format = ""),
- request_type = col_factor(levels = NULL),
- platform = col_skip(),
- channel = col_skip(),
- locale = col_factor(levels = NULL),
- incremental = col_skip(),
- count = col_double())) %>%
- filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
- filter(request_type %in% c("tbid", "tbup")) %>%
- rename(date = log_date) %>%
- group_by(date, locale, request_type) %>%
- summarize(count = sum(count)) %>%
- mutate(request_type = factor(request_type, levels = c("tbid", "tbup"))) %>%
- spread(request_type, count, fill = 0) %>%
- rename(initial_downloads = tbid, update_pings = tbup)
-}
-
-plot_webstats_tb_locale <- function(start_p, end_p, path_p) {
- d <- prepare_webstats_tb_locale(start_p, end_p) %>%
- gather(request_type, count, -c(date, locale)) %>%
- mutate(request_type = factor(request_type,
- levels = c("initial_downloads", "update_pings"),
- labels = c("Initial downloads", "Update pings")))
- 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(date = d$date,
- request_type = d$request_type,
- locale = ifelse(d$locale %in% e$locale, d$locale, "(other)")), FUN = sum)
- d %>%
- complete(date = full_seq(date, period = 1),
- nesting(locale, request_type)) %>%
- ggplot(aes(x = date, y = count, colour = locale)) +
- geom_point() +
- geom_line() +
- scale_x_date(name = "", breaks = custom_breaks,
- labels = custom_labels, minor_breaks = custom_minor_breaks) +
- scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
- scale_colour_hue(name = "Locale",
- breaks = c(e$locale, "(other)"),
- labels = c(as.character(e$locale), "Other")) +
- facet_grid(request_type ~ ., scales = "free_y") +
- theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
- strip.background = element_rect(fill = NA),
- legend.position = "top") +
- guides(col = guide_legend(nrow = 1)) +
- ggtitle("Tor Browser downloads and updates by locale") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_webstats_tm <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
- col_types = cols(
- log_date = col_date(format = ""),
- request_type = col_factor(levels = NULL),
- platform = col_skip(),
- channel = col_skip(),
- locale = col_skip(),
- incremental = col_skip(),
- count = col_double())) %>%
- filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
- filter(request_type %in% c("tmid", "tmup")) %>%
- group_by(log_date, request_type) %>%
- summarize(count = sum(count)) %>%
- mutate(request_type = factor(request_type, levels = c("tmid", "tmup"))) %>%
- spread(request_type, count, drop = FALSE, fill = 0) %>%
- rename(date = log_date, initial_downloads = tmid, update_pings = tmup)
-}
-
-plot_webstats_tm <- function(start_p, end_p, path_p) {
- prepare_webstats_tm(start_p, end_p) %>%
- gather(request_type, count, -date) %>%
- mutate(request_type = factor(request_type,
- levels = c("initial_downloads", "update_pings"),
- labels = c("Initial downloads", "Update pings"))) %>%
- ungroup() %>%
- complete(date = full_seq(date, period = 1), nesting(request_type)) %>%
- ggplot(aes(x = date, y = count)) +
- geom_point() +
- geom_line() +
- facet_grid(request_type ~ ., scales = "free_y") +
- 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)) +
- theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
- strip.background = element_rect(fill = NA)) +
- ggtitle("Tor Messenger downloads and updates") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_relays_ipv6 <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
- col_types = cols(
- valid_after_date = col_date(format = ""),
- server = col_factor(levels = NULL),
- guard_relay = col_skip(),
- exit_relay = col_skip(),
- announced_ipv6 = col_logical(),
- exiting_ipv6_relay = col_logical(),
- reachable_ipv6_relay = col_logical(),
- server_count_sum_avg = col_double(),
- advertised_bandwidth_bytes_sum_avg = col_skip())) %>%
- filter(if (!is.null(start_p))
- valid_after_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p))
- valid_after_date <= as.Date(end_p) else TRUE) %>%
- filter(server == "relay") %>%
- group_by(valid_after_date) %>%
- summarize(total = sum(server_count_sum_avg),
- announced = sum(server_count_sum_avg[announced_ipv6]),
- reachable = sum(server_count_sum_avg[reachable_ipv6_relay]),
- exiting = sum(server_count_sum_avg[exiting_ipv6_relay])) %>%
- rename(date = valid_after_date)
-}
-
-plot_relays_ipv6 <- function(start_p, end_p, path_p) {
- prepare_relays_ipv6(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- gather(category, count, -date) %>%
- ggplot(aes(x = date, y = count, colour = category)) +
- 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)) +
- scale_colour_hue(name = "", h.start = 90,
- breaks = c("total", "announced", "reachable", "exiting"),
- labels = c("Total (IPv4) OR", "IPv6 announced OR", "IPv6 reachable OR",
- "IPv6 exiting")) +
- ggtitle("Relays by IP version") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_bridges_ipv6 <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
- col_types = cols(
- valid_after_date = col_date(format = ""),
- server = col_factor(levels = NULL),
- guard_relay = col_skip(),
- exit_relay = col_skip(),
- announced_ipv6 = col_logical(),
- exiting_ipv6_relay = col_skip(),
- reachable_ipv6_relay = col_skip(),
- server_count_sum_avg = col_double(),
- advertised_bandwidth_bytes_sum_avg = col_skip())) %>%
- filter(if (!is.null(start_p))
- valid_after_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p))
- valid_after_date <= as.Date(end_p) else TRUE) %>%
- filter(server == "bridge") %>%
- group_by(valid_after_date) %>%
- summarize(total = sum(server_count_sum_avg),
- announced = sum(server_count_sum_avg[announced_ipv6])) %>%
- rename(date = valid_after_date)
-}
-
-plot_bridges_ipv6 <- function(start_p, end_p, path_p) {
- prepare_bridges_ipv6(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- gather(category, count, -date) %>%
- ggplot(aes(x = date, y = count, colour = category)) +
- 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)) +
- scale_colour_hue(name = "", h.start = 90,
- breaks = c("total", "announced"),
- labels = c("Total (IPv4) OR", "IPv6 announced OR")) +
- ggtitle("Bridges by IP version") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top")
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_advbw_ipv6 <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
- col_types = cols(
- valid_after_date = col_date(format = ""),
- server = col_factor(levels = NULL),
- guard_relay = col_logical(),
- exit_relay = col_logical(),
- announced_ipv6 = col_logical(),
- exiting_ipv6_relay = col_logical(),
- reachable_ipv6_relay = col_logical(),
- server_count_sum_avg = col_skip(),
- advertised_bandwidth_bytes_sum_avg = col_double())) %>%
- filter(if (!is.null(start_p))
- valid_after_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p))
- valid_after_date <= as.Date(end_p) else TRUE) %>%
- filter(server == "relay") %>%
- mutate(advertised_bandwidth_bytes_sum_avg =
- advertised_bandwidth_bytes_sum_avg * 8 / 1e9) %>%
- group_by(valid_after_date) %>%
- summarize(total = sum(advertised_bandwidth_bytes_sum_avg),
- total_guard = sum(advertised_bandwidth_bytes_sum_avg[guard_relay]),
- total_exit = sum(advertised_bandwidth_bytes_sum_avg[exit_relay]),
- reachable_guard = sum(advertised_bandwidth_bytes_sum_avg[
- reachable_ipv6_relay & guard_relay]),
- reachable_exit = sum(advertised_bandwidth_bytes_sum_avg[
- reachable_ipv6_relay & exit_relay]),
- exiting = sum(advertised_bandwidth_bytes_sum_avg[
- exiting_ipv6_relay])) %>%
- rename(date = valid_after_date)
-}
-
-plot_advbw_ipv6 <- function(start_p, end_p, path_p) {
- prepare_advbw_ipv6(start_p, end_p) %>%
- complete(date = full_seq(date, period = 1)) %>%
- gather(category, advbw, -date) %>%
- ggplot(aes(x = date, y = advbw, colour = category)) +
- 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("total", "total_guard", "total_exit", "reachable_guard",
- "reachable_exit", "exiting"),
- labels = c("Total (IPv4) OR", "Guard total (IPv4)", "Exit total (IPv4)",
- "Reachable guard IPv6 OR", "Reachable exit IPv6 OR", "IPv6 exiting")) +
- ggtitle("Advertised bandwidth by IP version") +
- labs(caption = copyright_notice) +
- theme(legend.position = "top") +
- guides(colour = guide_legend(nrow = 2, byrow = TRUE))
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-prepare_totalcw <- function(start_p = NULL, end_p = NULL) {
- read_csv(file = paste(stats_dir, "totalcw.csv", sep = ""),
- col_types = cols(
- valid_after_date = col_date(format = ""),
- nickname = col_character(),
- have_guard_flag = col_logical(),
- have_exit_flag = col_logical(),
- measured_sum_avg = col_double())) %>%
- filter(if (!is.null(start_p))
- valid_after_date >= as.Date(start_p) else TRUE) %>%
- filter(if (!is.null(end_p))
- valid_after_date <= as.Date(end_p) else TRUE) %>%
- group_by(valid_after_date, nickname) %>%
- summarize(measured_sum_avg = sum(measured_sum_avg)) %>%
- rename(date = valid_after_date, totalcw = measured_sum_avg) %>%
- arrange(date, nickname)
-}
-
-plot_totalcw <- function(start_p, end_p, path_p) {
- prepare_totalcw(start_p, end_p) %>%
- mutate(nickname = ifelse(is.na(nickname), "consensus", nickname)) %>%
- mutate(nickname = factor(nickname,
- levels = c("consensus", unique(nickname[nickname != "consensus"])))) %>%
- ungroup() %>%
- complete(date = full_seq(date, period = 1), nesting(nickname)) %>%
- ggplot(aes(x = date, y = totalcw, colour = nickname)) +
- geom_line(na.rm = TRUE) +
- 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)) +
- scale_colour_hue(name = "") +
- ggtitle("Total consensus weights across bandwidth authorities") +
- labs(caption = copyright_notice)
- ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
-}
-
-
diff --git a/src/main/R/rserver/rserve-init.R b/src/main/R/rserver/rserve-init.R
index f160698..57e14f5 100644
--- a/src/main/R/rserver/rserve-init.R
+++ b/src/main/R/rserver/rserve-init.R
@@ -1,12 +1,1603 @@
-##Pre-loaded libraries and graphing functions to speed things up
+require(ggplot2)
+require(RColorBrewer)
+require(scales)
+require(dplyr)
+require(tidyr)
+require(readr)
-library("ggplot2")
-library("RColorBrewer")
-library("scales")
-library(dplyr)
-library(tidyr)
-library(readr)
+countrylist <- list(
+ "ad" = "Andorra",
+ "ae" = "the United Arab Emirates",
+ "af" = "Afghanistan",
+ "ag" = "Antigua and Barbuda",
+ "ai" = "Anguilla",
+ "al" = "Albania",
+ "am" = "Armenia",
+ "an" = "the Netherlands Antilles",
+ "ao" = "Angola",
+ "aq" = "Antarctica",
+ "ar" = "Argentina",
+ "as" = "American Samoa",
+ "at" = "Austria",
+ "au" = "Australia",
+ "aw" = "Aruba",
+ "ax" = "the Aland Islands",
+ "az" = "Azerbaijan",
+ "ba" = "Bosnia and Herzegovina",
+ "bb" = "Barbados",
+ "bd" = "Bangladesh",
+ "be" = "Belgium",
+ "bf" = "Burkina Faso",
+ "bg" = "Bulgaria",
+ "bh" = "Bahrain",
+ "bi" = "Burundi",
+ "bj" = "Benin",
+ "bl" = "Saint Bartelemey",
+ "bm" = "Bermuda",
+ "bn" = "Brunei",
+ "bo" = "Bolivia",
+ "bq" = "Bonaire, Sint Eustatius and Saba",
+ "br" = "Brazil",
+ "bs" = "the Bahamas",
+ "bt" = "Bhutan",
+ "bv" = "the Bouvet Island",
+ "bw" = "Botswana",
+ "by" = "Belarus",
+ "bz" = "Belize",
+ "ca" = "Canada",
+ "cc" = "the Cocos (Keeling) Islands",
+ "cd" = "the Democratic Republic of the Congo",
+ "cf" = "Central African Republic",
+ "cg" = "Congo",
+ "ch" = "Switzerland",
+ "ci" = "Côte d'Ivoire",
+ "ck" = "the Cook Islands",
+ "cl" = "Chile",
+ "cm" = "Cameroon",
+ "cn" = "China",
+ "co" = "Colombia",
+ "cr" = "Costa Rica",
+ "cu" = "Cuba",
+ "cv" = "Cape Verde",
+ "cw" = "Curaçao",
+ "cx" = "the Christmas Island",
+ "cy" = "Cyprus",
+ "cz" = "the Czech Republic",
+ "de" = "Germany",
+ "dj" = "Djibouti",
+ "dk" = "Denmark",
+ "dm" = "Dominica",
+ "do" = "the Dominican Republic",
+ "dz" = "Algeria",
+ "ec" = "Ecuador",
+ "ee" = "Estonia",
+ "eg" = "Egypt",
+ "eh" = "the Western Sahara",
+ "er" = "Eritrea",
+ "es" = "Spain",
+ "et" = "Ethiopia",
+ "fi" = "Finland",
+ "fj" = "Fiji",
+ "fk" = "the Falkland Islands (Malvinas)",
+ "fm" = "the Federated States of Micronesia",
+ "fo" = "the Faroe Islands",
+ "fr" = "France",
+ "ga" = "Gabon",
+ "gb" = "the United Kingdom",
+ "gd" = "Grenada",
+ "ge" = "Georgia",
+ "gf" = "French Guiana",
+ "gg" = "Guernsey",
+ "gh" = "Ghana",
+ "gi" = "Gibraltar",
+ "gl" = "Greenland",
+ "gm" = "Gambia",
+ "gn" = "Guinea",
+ "gp" = "Guadeloupe",
+ "gq" = "Equatorial Guinea",
+ "gr" = "Greece",
+ "gs" = "South Georgia and the South Sandwich Islands",
+ "gt" = "Guatemala",
+ "gu" = "Guam",
+ "gw" = "Guinea-Bissau",
+ "gy" = "Guyana",
+ "hk" = "Hong Kong",
+ "hm" = "Heard Island and McDonald Islands",
+ "hn" = "Honduras",
+ "hr" = "Croatia",
+ "ht" = "Haiti",
+ "hu" = "Hungary",
+ "id" = "Indonesia",
+ "ie" = "Ireland",
+ "il" = "Israel",
+ "im" = "the Isle of Man",
+ "in" = "India",
+ "io" = "the British Indian Ocean Territory",
+ "iq" = "Iraq",
+ "ir" = "Iran",
+ "is" = "Iceland",
+ "it" = "Italy",
+ "je" = "Jersey",
+ "jm" = "Jamaica",
+ "jo" = "Jordan",
+ "jp" = "Japan",
+ "ke" = "Kenya",
+ "kg" = "Kyrgyzstan",
+ "kh" = "Cambodia",
+ "ki" = "Kiribati",
+ "km" = "Comoros",
+ "kn" = "Saint Kitts and Nevis",
+ "kp" = "North Korea",
+ "kr" = "the Republic of Korea",
+ "kw" = "Kuwait",
+ "ky" = "the Cayman Islands",
+ "kz" = "Kazakhstan",
+ "la" = "Laos",
+ "lb" = "Lebanon",
+ "lc" = "Saint Lucia",
+ "li" = "Liechtenstein",
+ "lk" = "Sri Lanka",
+ "lr" = "Liberia",
+ "ls" = "Lesotho",
+ "lt" = "Lithuania",
+ "lu" = "Luxembourg",
+ "lv" = "Latvia",
+ "ly" = "Libya",
+ "ma" = "Morocco",
+ "mc" = "Monaco",
+ "md" = "the Republic of Moldova",
+ "me" = "Montenegro",
+ "mf" = "Saint Martin",
+ "mg" = "Madagascar",
+ "mh" = "the Marshall Islands",
+ "mk" = "Macedonia",
+ "ml" = "Mali",
+ "mm" = "Burma",
+ "mn" = "Mongolia",
+ "mo" = "Macau",
+ "mp" = "the Northern Mariana Islands",
+ "mq" = "Martinique",
+ "mr" = "Mauritania",
+ "ms" = "Montserrat",
+ "mt" = "Malta",
+ "mu" = "Mauritius",
+ "mv" = "the Maldives",
+ "mw" = "Malawi",
+ "mx" = "Mexico",
+ "my" = "Malaysia",
+ "mz" = "Mozambique",
+ "na" = "Namibia",
+ "nc" = "New Caledonia",
+ "ne" = "Niger",
+ "nf" = "Norfolk Island",
+ "ng" = "Nigeria",
+ "ni" = "Nicaragua",
+ "nl" = "the Netherlands",
+ "no" = "Norway",
+ "np" = "Nepal",
+ "nr" = "Nauru",
+ "nu" = "Niue",
+ "nz" = "New Zealand",
+ "om" = "Oman",
+ "pa" = "Panama",
+ "pe" = "Peru",
+ "pf" = "French Polynesia",
+ "pg" = "Papua New Guinea",
+ "ph" = "the Philippines",
+ "pk" = "Pakistan",
+ "pl" = "Poland",
+ "pm" = "Saint Pierre and Miquelon",
+ "pn" = "the Pitcairn Islands",
+ "pr" = "Puerto Rico",
+ "ps" = "the Palestinian Territory",
+ "pt" = "Portugal",
+ "pw" = "Palau",
+ "py" = "Paraguay",
+ "qa" = "Qatar",
+ "re" = "Reunion",
+ "ro" = "Romania",
+ "rs" = "Serbia",
+ "ru" = "Russia",
+ "rw" = "Rwanda",
+ "sa" = "Saudi Arabia",
+ "sb" = "the Solomon Islands",
+ "sc" = "the Seychelles",
+ "sd" = "Sudan",
+ "se" = "Sweden",
+ "sg" = "Singapore",
+ "sh" = "Saint Helena",
+ "si" = "Slovenia",
+ "sj" = "Svalbard and Jan Mayen",
+ "sk" = "Slovakia",
+ "sl" = "Sierra Leone",
+ "sm" = "San Marino",
+ "sn" = "Senegal",
+ "so" = "Somalia",
+ "sr" = "Suriname",
+ "ss" = "South Sudan",
+ "st" = "São Tomé and PrÃncipe",
+ "sv" = "El Salvador",
+ "sx" = "Sint Maarten",
+ "sy" = "the Syrian Arab Republic",
+ "sz" = "Swaziland",
+ "tc" = "Turks and Caicos Islands",
+ "td" = "Chad",
+ "tf" = "the French Southern Territories",
+ "tg" = "Togo",
+ "th" = "Thailand",
+ "tj" = "Tajikistan",
+ "tk" = "Tokelau",
+ "tl" = "East Timor",
+ "tm" = "Turkmenistan",
+ "tn" = "Tunisia",
+ "to" = "Tonga",
+ "tr" = "Turkey",
+ "tt" = "Trinidad and Tobago",
+ "tv" = "Tuvalu",
+ "tw" = "Taiwan",
+ "tz" = "the United Republic of Tanzania",
+ "ua" = "Ukraine",
+ "ug" = "Uganda",
+ "um" = "the United States Minor Outlying Islands",
+ "us" = "the United States",
+ "uy" = "Uruguay",
+ "uz" = "Uzbekistan",
+ "va" = "Vatican City",
+ "vc" = "Saint Vincent and the Grenadines",
+ "ve" = "Venezuela",
+ "vg" = "the British Virgin Islands",
+ "vi" = "the United States Virgin Islands",
+ "vn" = "Vietnam",
+ "vu" = "Vanuatu",
+ "wf" = "Wallis and Futuna",
+ "ws" = "Samoa",
+ "xk" = "Kosovo",
+ "ye" = "Yemen",
+ "yt" = "Mayotte",
+ "za" = "South Africa",
+ "zm" = "Zambia",
+ "zw" = "Zimbabwe")
-source('graphs.R')
-source('tables.R')
+countryname <- function(country) {
+ res <- countrylist[[country]]
+ if (is.null(res))
+ res <- "no-man's-land"
+ res
+}
+
+# Helper function that takes date limits as input and returns major breaks as
+# output. The main difference to the built-in major breaks is that we're trying
+# harder to align major breaks with first days of weeks (Sundays), months,
+# quarters, or years.
+custom_breaks <- function(input) {
+ scales_index <- cut(as.numeric(max(input) - min(input)),
+ c(-1, 7, 12, 56, 180, 600, 2000, Inf), labels = FALSE)
+ from_print_format <- c("%F", "%F", "%Y-W%U-7", "%Y-%m-01", "%Y-01-01",
+ "%Y-01-01", "%Y-01-01")[scales_index]
+ from_parse_format <- ifelse(scales_index == 3, "%Y-W%U-%u", "%F")
+ by <- c("1 day", "2 days", "1 week", "1 month", "3 months", "1 year",
+ "2 years")[scales_index]
+ seq(as.Date(as.character(min(input), from_print_format),
+ format = from_parse_format), max(input), by = by)
+}
+
+# Helper function that takes date limits as input and returns minor breaks as
+# output. As opposed to the built-in minor breaks, we're not just adding one
+# minor break half way through between two major breaks. Instead, we're plotting
+# a minor break for every day, week, month, or quarter between two major breaks.
+custom_minor_breaks <- function(input) {
+ scales_index <- cut(as.numeric(max(input) - min(input)),
+ c(-1, 7, 12, 56, 180, 600, 2000, Inf), labels = FALSE)
+ from_print_format <- c("%F", "%F", "%F", "%Y-W%U-7", "%Y-%m-01", "%Y-01-01",
+ "%Y-01-01")[scales_index]
+ from_parse_format <- ifelse(scales_index == 4, "%Y-W%U-%u", "%F")
+ by <- c("1 day", "1 day", "1 day", "1 week", "1 month", "3 months",
+ "1 year")[scales_index]
+ seq(as.Date(as.character(min(input), from_print_format),
+ format = from_parse_format), max(input), by = by)
+}
+
+# Helper function that takes breaks as input and returns labels as output. We're
+# going all ISO-8601 here, though we're not just writing %Y-%m-%d everywhere,
+# but %Y-%m or %Y if all breaks are on the first of a month or even year.
+custom_labels <- function(breaks) {
+ if (all(format(breaks, format = "%m-%d") == "01-01", na.rm = TRUE)) {
+ format(breaks, format = "%Y")
+ } else {
+ if (all(format(breaks, format = "%d") == "01", na.rm = TRUE)) {
+ format(breaks, format = "%Y-%m")
+ } else {
+ format(breaks, format = "%F")
+ }
+ }
+}
+
+# Helper function to format numbers in non-scientific notation with spaces as
+# thousands separator.
+formatter <- function(x, ...) {
+ format(x, ..., scientific = FALSE, big.mark = " ")
+}
+
+theme_update(
+ # Make plot title centered, and leave some room to the plot.
+ plot.title = element_text(hjust = 0.5, margin = margin(b = 11)),
+
+ # Leave a little more room to the right for long x axis labels.
+ plot.margin = margin(5.5, 11, 5.5, 5.5)
+)
+
+# Set the default line size of geom_line() to 1.
+update_geom_defaults("line", list(size = 1))
+
+copyright_notice <- "The Tor Project - https://metrics.torproject.org/";
+
+stats_dir <- "/srv/metrics.torproject.org/metrics/shared/stats/"
+
+rdata_dir <- "/srv/metrics.torproject.org/metrics/shared/RData/"
+
+# Helper function that copies the appropriate no data object to filename.
+copy_no_data <- function(filename) {
+ len <- nchar(filename)
+ extension <- substr(filename, len - 3, len)
+ if (".csv" == extension) {
+ write("# No data available for the given parameters.", file=filename)
+ } else {
+ file.copy(paste(rdata_dir, "no-data-available", extension, sep = ""),
+ filename)
+ }
+}
+
+# Helper function wrapping calls into error handling.
+robust_call <- function(wrappee, filename) {
+ tryCatch(eval(wrappee), error = function(e) copy_no_data(filename),
+ finally = if (!file.exists(filename) || file.size(filename) == 0) {
+ copy_no_data(filename)
+ })
+}
+
+# Write the result of the given FUN, typically a prepare_ function, as .csv file
+# to the given path_p.
+write_data <- function(FUN, ..., path_p) {
+ FUN(...) %>%
+ write.csv(path_p, quote = FALSE, row.names = FALSE, na = "")
+}
+
+# Disable readr's automatic progress bar.
+options(readr.show_progress = FALSE)
+
+prepare_networksize <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "networksize.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ relays = col_double(),
+ bridges = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
+}
+
+plot_networksize <- function(start_p, end_p, path_p) {
+ prepare_networksize(start_p, end_p) %>%
+ 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)) +
+ scale_colour_hue("", breaks = c("relays", "bridges"),
+ labels = c("Relays", "Bridges")) +
+ ggtitle("Number of relays") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_versions <- function(start_p = NULL, end_p = NULL) {
+ read_csv(paste(stats_dir, "versions.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ version = col_character(),
+ relays = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
+}
+
+plot_versions <- function(start_p, end_p, path_p) {
+ s <- prepare_versions(start_p, end_p)
+ known_versions <- unique(s$version)
+ getPalette <- colorRampPalette(brewer.pal(12, "Paired"))
+ colours <- data.frame(breaks = known_versions,
+ values = rep(brewer.pal(min(12, length(known_versions)), "Paired"),
+ len = length(known_versions)),
+ stringsAsFactors = FALSE)
+ versions <- s[s$version %in% known_versions, ]
+ visible_versions <- sort(unique(versions$version))
+ versions <- versions %>%
+ complete(date = full_seq(date, period = 1), nesting(version)) %>%
+ ggplot(aes(x = date, y = relays, colour = version)) +
+ 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)) +
+ scale_colour_manual(name = "Tor version",
+ values = colours[colours$breaks %in% visible_versions, 2],
+ breaks = visible_versions) +
+ ggtitle("Relay versions") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_platforms <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "platforms.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ platform = col_factor(levels = NULL),
+ relays = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ mutate(platform = tolower(platform)) %>%
+ spread(platform, relays)
+}
+
+plot_platforms <- function(start_p, end_p, path_p) {
+ prepare_platforms(start_p, end_p) %>%
+ gather(platform, relays, -date) %>%
+ complete(date = full_seq(date, period = 1), nesting(platform)) %>%
+ 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) +
+ scale_y_continuous(name = "", labels = formatter, limits = c(0, NA)) +
+ scale_colour_manual(name = "Platform",
+ breaks = c("linux", "macos", "bsd", "windows", "other"),
+ labels = c("Linux", "macOS", "BSD", "Windows", "Other"),
+ values = c("linux" = "#56B4E9", "macos" = "#333333", "bsd" = "#E69F00",
+ "windows" = "#0072B2", "other" = "#009E73")) +
+ ggtitle("Relay platforms") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_dirbytes <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "bandwidth.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ isexit = col_logical(),
+ isguard = col_logical(),
+ bwread = col_skip(),
+ bwwrite = col_skip(),
+ dirread = col_double(),
+ dirwrite = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(is.na(isexit)) %>%
+ filter(is.na(isguard)) %>%
+ mutate(dirread = dirread * 8 / 1e9,
+ dirwrite = dirwrite * 8 / 1e9) %>%
+ select(date, dirread, dirwrite)
+}
+
+plot_dirbytes <- function(start_p, end_p, path_p) {
+ prepare_dirbytes(start_p, end_p) %>%
+ gather(variable, value, -date) %>%
+ complete(date = full_seq(date, period = 1), nesting(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) +
+ scale_y_continuous(name = "", labels = unit_format(unit = "Gbit/s"),
+ limits = c(0, NA)) +
+ scale_colour_hue(name = "",
+ breaks = c("dirwrite", "dirread"),
+ labels = c("Written dir bytes", "Read dir bytes")) +
+ ggtitle("Number of bytes spent on answering directory requests") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_relayflags <- function(start_p = NULL, end_p = NULL, flag_p = NULL) {
+ read_csv(file = paste(stats_dir, "relayflags.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ flag = col_factor(levels = NULL),
+ relays = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(flag_p)) flag %in% flag_p else TRUE)
+}
+
+plot_relayflags <- function(start_p, end_p, flag_p, path_p) {
+ prepare_relayflags(start_p, end_p, flag_p) %>%
+ complete(date = full_seq(date, period = 1), flag = unique(flag)) %>%
+ ggplot(aes(x = date, y = relays, colour = 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)) +
+ scale_colour_manual(name = "Relay flags", values = c("#E69F00",
+ "#56B4E9", "#009E73", "#EE6A50", "#000000", "#0072B2"),
+ breaks = flag_p, labels = flag_p) +
+ ggtitle("Number of relays with relay flags assigned") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_torperf <- function(start_p = NULL, end_p = NULL, server_p = NULL,
+ filesize_p = NULL) {
+ read_csv(file = paste(stats_dir, "torperf-1.1.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ filesize = col_double(),
+ source = col_character(),
+ server = col_character(),
+ q1 = col_double(),
+ md = col_double(),
+ q3 = col_double(),
+ timeouts = col_skip(),
+ failures = col_skip(),
+ requests = col_skip())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(server_p)) server == server_p else TRUE) %>%
+ filter(if (!is.null(filesize_p))
+ filesize == ifelse(filesize_p == "50kb", 50 * 1024,
+ ifelse(filesize_p == "1mb", 1024 * 1024, 5 * 1024 * 1024)) else
+ TRUE) %>%
+ transmute(date, filesize, source, server, q1 = q1 / 1e3, md = md / 1e3,
+ q3 = q3 / 1e3)
+}
+
+plot_torperf <- function(start_p, end_p, server_p, filesize_p, path_p) {
+ prepare_torperf(start_p, end_p, server_p, filesize_p) %>%
+ filter(source != "") %>%
+ complete(date = full_seq(date, period = 1), nesting(source)) %>%
+ ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
+ geom_ribbon(alpha = 0.5) +
+ geom_line(aes(colour = source), size = 0.75) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", labels = unit_format(unit = "s"),
+ limits = c(0, NA)) +
+ scale_fill_hue(name = "Source") +
+ scale_colour_hue(name = "Source") +
+ ggtitle(paste("Time to complete",
+ ifelse(filesize_p == "50kb", "50 KiB",
+ ifelse(filesize_p == "1mb", "1 MiB", "5 MiB")),
+ "request to", server_p, "server")) +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_torperf_failures <- function(start_p = NULL, end_p = NULL,
+ server_p = NULL, filesize_p = NULL) {
+ read_csv(file = paste(stats_dir, "torperf-1.1.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ filesize = col_double(),
+ source = col_character(),
+ server = col_character(),
+ q1 = col_skip(),
+ md = col_skip(),
+ q3 = col_skip(),
+ timeouts = col_double(),
+ failures = col_double(),
+ requests = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(filesize_p))
+ filesize == ifelse(filesize_p == "50kb", 50 * 1024,
+ ifelse(filesize_p == "1mb", 1024 * 1024, 5 * 1024 * 1024)) else
+ TRUE) %>%
+ filter(if (!is.null(server_p)) server == server_p else TRUE) %>%
+ filter(requests > 0) %>%
+ transmute(date, filesize, source, server, timeouts = timeouts / requests,
+ failures = failures / requests)
+}
+
+plot_torperf_failures <- function(start_p, end_p, server_p, filesize_p,
+ path_p) {
+ prepare_torperf_failures(start_p, end_p, server_p, filesize_p) %>%
+ filter(source != "") %>%
+ gather(variable, value, -c(date, filesize, source, server)) %>%
+ mutate(variable = factor(variable, levels = c("timeouts", "failures"),
+ labels = c("Timeouts", "Failures"))) %>%
+ ggplot(aes(x = date, y = value, colour = source)) +
+ geom_point(size = 2, alpha = 0.5) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", labels = percent, limits = c(0, NA)) +
+ scale_colour_hue(name = "Source") +
+ facet_grid(variable ~ .) +
+ ggtitle(paste("Timeouts and failures of",
+ ifelse(filesize_p == "50kb", "50 KiB",
+ ifelse(filesize_p == "1mb", "1 MiB", "5 MiB")),
+ "requests to", server_p, "server")) +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_onionperf_buildtimes <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "buildtimes.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ source = col_character(),
+ position = col_double(),
+ q1 = col_double(),
+ md = col_double(),
+ q3 = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE)
+}
+
+plot_onionperf_buildtimes <- function(start_p, end_p, path_p) {
+ prepare_onionperf_buildtimes(start_p, end_p) %>%
+ filter(source != "") %>%
+ mutate(date = as.Date(date),
+ position = factor(position, levels = seq(1, 3, 1),
+ labels = c("1st hop", "2nd hop", "3rd hop"))) %>%
+ complete(date = full_seq(date, period = 1), nesting(source, position)) %>%
+ ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
+ geom_ribbon(alpha = 0.5) +
+ geom_line(aes(colour = source), size = 0.75) +
+ facet_grid(position ~ .) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", labels = unit_format(unit = "ms"),
+ limits = c(0, NA)) +
+ scale_fill_hue(name = "Source") +
+ scale_colour_hue(name = "Source") +
+ ggtitle("Circuit build times") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_onionperf_latencies <- function(start_p = NULL, end_p = NULL,
+ server_p = NULL) {
+ read_csv(file = paste(stats_dir, "latencies.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ source = col_character(),
+ server = col_character(),
+ q1 = col_double(),
+ md = col_double(),
+ q3 = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(server_p)) server == server_p else TRUE)
+}
+
+plot_onionperf_latencies <- function(start_p, end_p, server_p, path_p) {
+ prepare_onionperf_latencies(start_p, end_p, server_p) %>%
+ filter(source != "") %>%
+ complete(date = full_seq(date, period = 1), nesting(source)) %>%
+ ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = source)) +
+ geom_ribbon(alpha = 0.5) +
+ geom_line(aes(colour = source), size = 0.75) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", labels = unit_format(unit = "ms"),
+ limits = c(0, NA)) +
+ scale_fill_hue(name = "Source") +
+ scale_colour_hue(name = "Source") +
+ ggtitle(paste("Circuit round-trip latencies to", server_p, "server")) +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_connbidirect <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "connbidirect2.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ direction = col_factor(levels = NULL),
+ quantile = col_double(),
+ fraction = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ mutate(quantile = paste("X", quantile, sep = ""),
+ fraction = fraction / 100) %>%
+ spread(quantile, fraction) %>%
+ rename(q1 = X0.25, md = X0.5, q3 = X0.75)
+}
+
+plot_connbidirect <- function(start_p, end_p, path_p) {
+ prepare_connbidirect(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1), nesting(direction)) %>%
+ ggplot(aes(x = date, y = md, ymin = q1, ymax = q3, fill = direction)) +
+ geom_ribbon(alpha = 0.5) +
+ geom_line(aes(colour = direction), size = 0.75) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", labels = percent, limits = c(0, NA)) +
+ scale_colour_hue(name = "Medians and interquartile ranges",
+ breaks = c("both", "write", "read"),
+ labels = c("Both reading and writing", "Mostly writing",
+ "Mostly reading")) +
+ scale_fill_hue(name = "Medians and interquartile ranges",
+ breaks = c("both", "write", "read"),
+ labels = c("Both reading and writing", "Mostly writing",
+ "Mostly reading")) +
+ ggtitle("Fraction of connections used uni-/bidirectionally") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_bandwidth_flags <- function(start_p = NULL, end_p = NULL) {
+ advbw <- read_csv(file = paste(stats_dir, "advbw.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ isexit = col_logical(),
+ isguard = col_logical(),
+ advbw = col_double())) %>%
+ transmute(date, have_guard_flag = isguard, have_exit_flag = isexit,
+ variable = "advbw", value = advbw * 8 / 1e9)
+ bwhist <- read_csv(file = paste(stats_dir, "bandwidth.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ isexit = col_logical(),
+ isguard = col_logical(),
+ bwread = col_double(),
+ bwwrite = col_double(),
+ dirread = col_double(),
+ dirwrite = col_double())) %>%
+ transmute(date, have_guard_flag = isguard, have_exit_flag = isexit,
+ variable = "bwhist", value = (bwread + bwwrite) * 8 / 2e9)
+ rbind(advbw, bwhist) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(!is.na(have_exit_flag)) %>%
+ filter(!is.na(have_guard_flag)) %>%
+ spread(variable, value)
+}
+
+plot_bandwidth_flags <- function(start_p, end_p, path_p) {
+ prepare_bandwidth_flags(start_p, end_p) %>%
+ gather(variable, value, c(advbw, bwhist)) %>%
+ unite(flags, have_guard_flag, have_exit_flag) %>%
+ mutate(flags = factor(flags,
+ levels = c("FALSE_TRUE", "TRUE_TRUE", "TRUE_FALSE", "FALSE_FALSE"),
+ labels = c("Exit only", "Guard and Exit", "Guard only",
+ "Neither Guard nor Exit"))) %>%
+ mutate(variable = ifelse(variable == "advbw",
+ "Advertised bandwidth", "Consumed bandwidth")) %>%
+ ggplot(aes(x = date, y = value, fill = flags)) +
+ geom_area() +
+ 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_fill_manual(name = "",
+ values = c("#03B3FF", "#39FF02", "#FFFF00", "#AAAA99")) +
+ facet_grid(variable ~ .) +
+ ggtitle("Advertised and consumed bandwidth by relay flags") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_userstats_relay_country <- function(start_p = NULL, end_p = NULL,
+ country_p = NULL, events_p = NULL) {
+ read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ node = col_character(),
+ country = col_character(),
+ transport = col_character(),
+ version = col_character(),
+ lower = col_double(),
+ upper = col_double(),
+ clients = col_double(),
+ frac = col_double()),
+ na = character()) %>%
+ filter(node == "relay") %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(country_p))
+ country == ifelse(country_p == "all", "", country_p) else TRUE) %>%
+ filter(transport == "") %>%
+ filter(version == "") %>%
+ select(date, country, clients, lower, upper, frac) %>%
+ rename(users = clients)
+}
+
+plot_userstats_relay_country <- function(start_p, end_p, country_p, events_p,
+ path_p) {
+ u <- prepare_userstats_relay_country(start_p, end_p, country_p, events_p) %>%
+ complete(date = full_seq(date, period = 1))
+ plot <- ggplot(u, aes(x = date, y = users))
+ if (length(na.omit(u$users)) > 0 & events_p != "off" &
+ country_p != "all") {
+ upturns <- u[u$users > u$upper, c("date", "users")]
+ downturns <- u[u$users < u$lower, c("date", "users")]
+ if (events_p == "on") {
+ u[!is.na(u$lower) & u$lower < 0, "lower"] <- 0
+ plot <- plot +
+ geom_ribbon(data = u, aes(ymin = lower, ymax = upper), fill = "gray")
+ }
+ if (length(upturns$date) > 0)
+ plot <- plot +
+ geom_point(data = upturns, aes(x = date, y = users), size = 5,
+ colour = "dodgerblue2")
+ if (length(downturns$date) > 0)
+ plot <- plot +
+ geom_point(data = downturns, aes(x = date, y = users), size = 5,
+ colour = "firebrick2")
+ }
+ plot <- plot +
+ 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)) +
+ ggtitle(paste("Directly connecting users",
+ ifelse(country_p == "all", "",
+ paste(" from", countryname(country_p))), sep = "")) +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_userstats_bridge_country <- function(start_p = NULL, end_p = NULL,
+ country_p = NULL) {
+ read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ node = col_character(),
+ country = col_character(),
+ transport = col_character(),
+ version = col_character(),
+ lower = col_double(),
+ upper = col_double(),
+ clients = col_double(),
+ frac = col_double()),
+ na = character()) %>%
+ filter(node == "bridge") %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(country_p))
+ country == ifelse(country_p == "all", "", country_p) else TRUE) %>%
+ filter(transport == "") %>%
+ filter(version == "") %>%
+ select(date, country, clients, frac) %>%
+ rename(users = clients)
+}
+
+plot_userstats_bridge_country <- function(start_p, end_p, country_p, path_p) {
+ prepare_userstats_bridge_country(start_p, end_p, country_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ ggplot(aes(x = date, y = users)) +
+ 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)) +
+ ggtitle(paste("Bridge users",
+ ifelse(country_p == "all", "",
+ paste(" from", countryname(country_p))), sep = "")) +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_userstats_bridge_transport <- function(start_p = NULL, end_p = NULL,
+ transport_p = NULL) {
+ u <- read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ node = col_character(),
+ country = col_character(),
+ transport = col_character(),
+ version = col_character(),
+ lower = col_double(),
+ upper = col_double(),
+ clients = col_double(),
+ frac = col_double())) %>%
+ filter(node == "bridge") %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(is.na(country)) %>%
+ filter(is.na(version)) %>%
+ filter(!is.na(transport)) %>%
+ select(date, transport, clients, frac)
+ if (is.null(transport_p) || "!<OR>" %in% transport_p) {
+ n <- u %>%
+ filter(transport != "<OR>") %>%
+ group_by(date, frac) %>%
+ summarize(clients = sum(clients))
+ u <- rbind(u, data.frame(date = n$date, transport = "!<OR>",
+ clients = n$clients, frac = n$frac))
+ }
+ u %>%
+ filter(if (!is.null(transport_p)) transport %in% transport_p else TRUE) %>%
+ select(date, transport, clients, frac) %>%
+ rename(users = clients) %>%
+ arrange(date, transport)
+}
+
+plot_userstats_bridge_transport <- function(start_p, end_p, transport_p,
+ path_p) {
+ if (length(transport_p) > 1) {
+ title <- paste("Bridge users by transport")
+ } else {
+ title <- paste("Bridge users using",
+ ifelse(transport_p == "<??>", "unknown pluggable transport(s)",
+ ifelse(transport_p == "<OR>", "default OR protocol",
+ ifelse(transport_p == "!<OR>", "any pluggable transport",
+ ifelse(transport_p == "fte", "FTE",
+ ifelse(transport_p == "websocket", "Flash proxy/websocket",
+ paste("transport", transport_p)))))))
+ }
+ u <- prepare_userstats_bridge_transport(start_p, end_p, transport_p) %>%
+ complete(date = full_seq(date, period = 1), nesting(transport))
+ if (length(transport_p) > 1) {
+ plot <- ggplot(u, aes(x = date, y = users, colour = transport))
+ } else {
+ plot <- ggplot(u, aes(x = date, y = users))
+ }
+ plot <- plot +
+ 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)) +
+ ggtitle(title) +
+ labs(caption = copyright_notice)
+ if (length(transport_p) > 1) {
+ plot <- plot +
+ scale_colour_hue(name = "", breaks = transport_p,
+ labels = ifelse(transport_p == "<??>", "Unknown PT",
+ ifelse(transport_p == "<OR>", "Default OR protocol",
+ ifelse(transport_p == "!<OR>", "Any PT",
+ ifelse(transport_p == "fte", "FTE",
+ ifelse(transport_p == "websocket", "Flash proxy/websocket",
+ transport_p))))))
+ }
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_userstats_bridge_version <- function(start_p = NULL, end_p = NULL,
+ version_p = NULL) {
+ read_csv(file = paste(stats_dir, "clients.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ node = col_character(),
+ country = col_character(),
+ transport = col_character(),
+ version = col_character(),
+ lower = col_double(),
+ upper = col_double(),
+ clients = col_double(),
+ frac = col_double())) %>%
+ filter(node == "bridge") %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(is.na(country)) %>%
+ filter(is.na(transport)) %>%
+ filter(if (!is.null(version_p)) version == version_p else TRUE) %>%
+ select(date, version, clients, frac) %>%
+ rename(users = clients)
+}
+
+plot_userstats_bridge_version <- function(start_p, end_p, version_p, path_p) {
+ prepare_userstats_bridge_version(start_p, end_p, version_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ ggplot(aes(x = date, y = users)) +
+ 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)) +
+ ggtitle(paste("Bridge users using IP", version_p, sep = "")) +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_userstats_bridge_combined <- function(start_p = NULL, end_p = NULL,
+ country_p = NULL) {
+ if (!is.null(country_p) && country_p == "all") {
+ prepare_userstats_bridge_country(start_p, end_p, country_p)
+ } else {
+ read_csv(file = paste(stats_dir, "userstats-combined.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ node = col_skip(),
+ country = col_character(),
+ transport = col_character(),
+ version = col_skip(),
+ frac = col_double(),
+ low = col_double(),
+ high = col_double()),
+ na = character()) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(country_p)) country == country_p else TRUE) %>%
+ select(date, country, transport, low, high, frac) %>%
+ arrange(date, country, transport)
+ }
+}
+
+plot_userstats_bridge_combined <- function(start_p, end_p, country_p, path_p) {
+ if (country_p == "all") {
+ plot_userstats_bridge_country(start_p, end_p, country_p, path_p)
+ } else {
+ top <- 3
+ u <- prepare_userstats_bridge_combined(start_p, end_p, country_p)
+ a <- aggregate(list(mid = (u$high + u$low) / 2),
+ by = list(transport = u$transport), FUN = sum)
+ a <- a[order(a$mid, decreasing = TRUE)[1:top], ]
+ u <- u[u$transport %in% a$transport, ] %>%
+ complete(date = full_seq(date, period = 1), nesting(country, transport))
+ title <- paste("Bridge users by transport from ",
+ countryname(country_p), sep = "")
+ ggplot(u, aes(x = as.Date(date), ymin = low, ymax = high,
+ fill = transport)) +
+ geom_ribbon(alpha = 0.5, size = 0.5) +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", limits = c(0, NA), labels = formatter) +
+ scale_colour_hue("Top-3 transports") +
+ scale_fill_hue("Top-3 transports") +
+ ggtitle(title) +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+ }
+}
+
+prepare_advbwdist_perc <- function(start_p = NULL, end_p = NULL, p_p = NULL) {
+ read_csv(file = paste(stats_dir, "advbwdist.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ isexit = col_logical(),
+ relay = col_skip(),
+ percentile = col_integer(),
+ advbw = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(p_p)) percentile %in% as.numeric(p_p) else
+ percentile != "") %>%
+ transmute(date, percentile = as.factor(percentile),
+ variable = ifelse(is.na(isexit), "all", "exits"),
+ advbw = advbw * 8 / 1e9) %>%
+ spread(variable, advbw) %>%
+ rename(p = percentile)
+}
+
+plot_advbwdist_perc <- function(start_p, end_p, p_p, path_p) {
+ prepare_advbwdist_perc(start_p, end_p, p_p) %>%
+ gather(variable, advbw, -c(date, p)) %>%
+ mutate(variable = ifelse(variable == "all", "All relays",
+ "Exits only")) %>%
+ complete(date = full_seq(date, period = 1), nesting(p, variable)) %>%
+ ggplot(aes(x = date, y = advbw, colour = p)) +
+ 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") +
+ ggtitle("Advertised bandwidth distribution") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_advbwdist_relay <- function(start_p = NULL, end_p = NULL, n_p = NULL) {
+ read_csv(file = paste(stats_dir, "advbwdist.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ isexit = col_logical(),
+ relay = col_integer(),
+ percentile = col_skip(),
+ advbw = col_double())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(if (!is.null(n_p)) relay %in% as.numeric(n_p) else
+ relay != "") %>%
+ transmute(date, relay = as.factor(relay),
+ variable = ifelse(is.na(isexit), "all", "exits"),
+ advbw = advbw * 8 / 1e9) %>%
+ spread(variable, advbw) %>%
+ rename(n = relay)
+}
+
+plot_advbwdist_relay <- function(start_p, end_p, n_p, path_p) {
+ prepare_advbwdist_relay(start_p, end_p, n_p) %>%
+ gather(variable, advbw, -c(date, n)) %>%
+ mutate(variable = ifelse(variable == "all", "All relays",
+ "Exits only")) %>%
+ complete(date = full_seq(date, period = 1), nesting(n, variable)) %>%
+ ggplot(aes(x = date, y = advbw, colour = n)) +
+ 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") +
+ ggtitle("Advertised bandwidth of n-th fastest relays") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_hidserv_dir_onions_seen <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "hidserv.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ type = col_factor(levels = NULL),
+ wmean = col_skip(),
+ wmedian = col_skip(),
+ wiqm = col_double(),
+ frac = col_double(),
+ stats = col_skip())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(type == "dir-onions-seen") %>%
+ transmute(date, onions = ifelse(frac >= 0.01, wiqm, NA), frac)
+}
+
+plot_hidserv_dir_onions_seen <- function(start_p, end_p, path_p) {
+ prepare_hidserv_dir_onions_seen(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ ggplot(aes(x = date, y = onions)) +
+ geom_line() +
+ scale_x_date(name = "", breaks = custom_breaks,
+ labels = custom_labels, minor_breaks = custom_minor_breaks) +
+ scale_y_continuous(name = "", limits = c(0, NA), labels = formatter) +
+ ggtitle("Unique .onion addresses") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_hidserv_rend_relayed_cells <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "hidserv.csv", sep = ""),
+ col_types = cols(
+ date = col_date(format = ""),
+ type = col_factor(levels = NULL),
+ wmean = col_skip(),
+ wmedian = col_skip(),
+ wiqm = col_double(),
+ frac = col_double(),
+ stats = col_skip())) %>%
+ filter(if (!is.null(start_p)) date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) date <= as.Date(end_p) else TRUE) %>%
+ filter(type == "rend-relayed-cells") %>%
+ transmute(date,
+ relayed = ifelse(frac >= 0.01, wiqm * 8 * 512 / (86400 * 1e9), NA), frac)
+}
+
+plot_hidserv_rend_relayed_cells <- function(start_p, end_p, path_p) {
+ prepare_hidserv_rend_relayed_cells(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ ggplot(aes(x = date, y = relayed)) +
+ 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)) +
+ ggtitle("Onion-service traffic") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_webstats_tb <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
+ col_types = cols(
+ log_date = col_date(format = ""),
+ request_type = col_factor(levels = NULL),
+ platform = col_skip(),
+ channel = col_skip(),
+ locale = col_skip(),
+ incremental = col_skip(),
+ count = col_double())) %>%
+ filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
+ filter(request_type %in% c("tbid", "tbsd", "tbup", "tbur")) %>%
+ group_by(log_date, request_type) %>%
+ summarize(count = sum(count)) %>%
+ spread(request_type, count) %>%
+ rename(date = log_date, initial_downloads = tbid,
+ signature_downloads = tbsd, update_pings = tbup,
+ update_requests = tbur)
+}
+
+plot_webstats_tb <- function(start_p, end_p, path_p) {
+ prepare_webstats_tb(start_p, end_p) %>%
+ gather(request_type, count, -date) %>%
+ mutate(request_type = factor(request_type,
+ levels = c("initial_downloads", "signature_downloads", "update_pings",
+ "update_requests"),
+ labels = c("Initial downloads", "Signature downloads", "Update pings",
+ "Update requests"))) %>%
+ ungroup() %>%
+ complete(date = full_seq(date, period = 1), nesting(request_type)) %>%
+ ggplot(aes(x = date, y = count)) +
+ geom_point() +
+ geom_line() +
+ facet_grid(request_type ~ ., scales = "free_y") +
+ 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)) +
+ theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
+ strip.background = element_rect(fill = NA)) +
+ ggtitle("Tor Browser downloads and updates") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_webstats_tb_platform <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
+ col_types = cols(
+ log_date = col_date(format = ""),
+ request_type = col_factor(levels = NULL),
+ platform = col_factor(levels = NULL),
+ channel = col_skip(),
+ locale = col_skip(),
+ incremental = col_skip(),
+ count = col_double())) %>%
+ filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
+ filter(request_type %in% c("tbid", "tbup")) %>%
+ group_by(log_date, platform, request_type) %>%
+ summarize(count = sum(count)) %>%
+ spread(request_type, count, fill = 0) %>%
+ rename(date = log_date, initial_downloads = tbid, update_pings = tbup)
+}
+
+plot_webstats_tb_platform <- function(start_p, end_p, path_p) {
+ prepare_webstats_tb_platform(start_p, end_p) %>%
+ gather(request_type, count, -c(date, platform)) %>%
+ mutate(request_type = factor(request_type,
+ levels = c("initial_downloads", "update_pings"),
+ labels = c("Initial downloads", "Update pings"))) %>%
+ ungroup() %>%
+ complete(date = full_seq(date, period = 1),
+ nesting(platform, request_type)) %>%
+ ggplot(aes(x = date, y = count, colour = platform)) +
+ geom_point() +
+ 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)) +
+ scale_colour_hue(name = "Platform",
+ breaks = c("w", "m", "l", "o", ""),
+ labels = c("Windows", "macOS", "Linux", "Other", "Unknown")) +
+ facet_grid(request_type ~ ., scales = "free_y") +
+ theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
+ strip.background = element_rect(fill = NA),
+ legend.position = "top") +
+ ggtitle("Tor Browser downloads and updates by platform") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_webstats_tb_locale <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
+ col_types = cols(
+ log_date = col_date(format = ""),
+ request_type = col_factor(levels = NULL),
+ platform = col_skip(),
+ channel = col_skip(),
+ locale = col_factor(levels = NULL),
+ incremental = col_skip(),
+ count = col_double())) %>%
+ filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
+ filter(request_type %in% c("tbid", "tbup")) %>%
+ rename(date = log_date) %>%
+ group_by(date, locale, request_type) %>%
+ summarize(count = sum(count)) %>%
+ mutate(request_type = factor(request_type, levels = c("tbid", "tbup"))) %>%
+ spread(request_type, count, fill = 0) %>%
+ rename(initial_downloads = tbid, update_pings = tbup)
+}
+
+plot_webstats_tb_locale <- function(start_p, end_p, path_p) {
+ d <- prepare_webstats_tb_locale(start_p, end_p) %>%
+ gather(request_type, count, -c(date, locale)) %>%
+ mutate(request_type = factor(request_type,
+ levels = c("initial_downloads", "update_pings"),
+ labels = c("Initial downloads", "Update pings")))
+ 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$count), by = list(date = d$date,
+ request_type = d$request_type,
+ locale = ifelse(d$locale %in% e$locale, d$locale, "(other)")), FUN = sum)
+ d %>%
+ complete(date = full_seq(date, period = 1),
+ nesting(locale, request_type)) %>%
+ ggplot(aes(x = date, y = count, colour = locale)) +
+ geom_point() +
+ 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)) +
+ scale_colour_hue(name = "Locale",
+ breaks = c(e$locale, "(other)"),
+ labels = c(as.character(e$locale), "Other")) +
+ facet_grid(request_type ~ ., scales = "free_y") +
+ theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
+ strip.background = element_rect(fill = NA),
+ legend.position = "top") +
+ guides(col = guide_legend(nrow = 1)) +
+ ggtitle("Tor Browser downloads and updates by locale") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_webstats_tm <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "webstats.csv", sep = ""),
+ col_types = cols(
+ log_date = col_date(format = ""),
+ request_type = col_factor(levels = NULL),
+ platform = col_skip(),
+ channel = col_skip(),
+ locale = col_skip(),
+ incremental = col_skip(),
+ count = col_double())) %>%
+ filter(if (!is.null(start_p)) log_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p)) log_date <= as.Date(end_p) else TRUE) %>%
+ filter(request_type %in% c("tmid", "tmup")) %>%
+ group_by(log_date, request_type) %>%
+ summarize(count = sum(count)) %>%
+ mutate(request_type = factor(request_type, levels = c("tmid", "tmup"))) %>%
+ spread(request_type, count, drop = FALSE, fill = 0) %>%
+ rename(date = log_date, initial_downloads = tmid, update_pings = tmup)
+}
+
+plot_webstats_tm <- function(start_p, end_p, path_p) {
+ prepare_webstats_tm(start_p, end_p) %>%
+ gather(request_type, count, -date) %>%
+ mutate(request_type = factor(request_type,
+ levels = c("initial_downloads", "update_pings"),
+ labels = c("Initial downloads", "Update pings"))) %>%
+ ungroup() %>%
+ complete(date = full_seq(date, period = 1), nesting(request_type)) %>%
+ ggplot(aes(x = date, y = count)) +
+ geom_point() +
+ geom_line() +
+ facet_grid(request_type ~ ., scales = "free_y") +
+ 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)) +
+ theme(strip.text.y = element_text(angle = 0, hjust = 0, size = rel(1.5)),
+ strip.background = element_rect(fill = NA)) +
+ ggtitle("Tor Messenger downloads and updates") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_relays_ipv6 <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
+ col_types = cols(
+ valid_after_date = col_date(format = ""),
+ server = col_factor(levels = NULL),
+ guard_relay = col_skip(),
+ exit_relay = col_skip(),
+ announced_ipv6 = col_logical(),
+ exiting_ipv6_relay = col_logical(),
+ reachable_ipv6_relay = col_logical(),
+ server_count_sum_avg = col_double(),
+ advertised_bandwidth_bytes_sum_avg = col_skip())) %>%
+ filter(if (!is.null(start_p))
+ valid_after_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p))
+ valid_after_date <= as.Date(end_p) else TRUE) %>%
+ filter(server == "relay") %>%
+ group_by(valid_after_date) %>%
+ summarize(total = sum(server_count_sum_avg),
+ announced = sum(server_count_sum_avg[announced_ipv6]),
+ reachable = sum(server_count_sum_avg[reachable_ipv6_relay]),
+ exiting = sum(server_count_sum_avg[exiting_ipv6_relay])) %>%
+ rename(date = valid_after_date)
+}
+
+plot_relays_ipv6 <- function(start_p, end_p, path_p) {
+ prepare_relays_ipv6(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ gather(category, count, -date) %>%
+ ggplot(aes(x = date, y = count, colour = category)) +
+ 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)) +
+ scale_colour_hue(name = "", h.start = 90,
+ breaks = c("total", "announced", "reachable", "exiting"),
+ labels = c("Total (IPv4) OR", "IPv6 announced OR", "IPv6 reachable OR",
+ "IPv6 exiting")) +
+ ggtitle("Relays by IP version") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_bridges_ipv6 <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
+ col_types = cols(
+ valid_after_date = col_date(format = ""),
+ server = col_factor(levels = NULL),
+ guard_relay = col_skip(),
+ exit_relay = col_skip(),
+ announced_ipv6 = col_logical(),
+ exiting_ipv6_relay = col_skip(),
+ reachable_ipv6_relay = col_skip(),
+ server_count_sum_avg = col_double(),
+ advertised_bandwidth_bytes_sum_avg = col_skip())) %>%
+ filter(if (!is.null(start_p))
+ valid_after_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p))
+ valid_after_date <= as.Date(end_p) else TRUE) %>%
+ filter(server == "bridge") %>%
+ group_by(valid_after_date) %>%
+ summarize(total = sum(server_count_sum_avg),
+ announced = sum(server_count_sum_avg[announced_ipv6])) %>%
+ rename(date = valid_after_date)
+}
+
+plot_bridges_ipv6 <- function(start_p, end_p, path_p) {
+ prepare_bridges_ipv6(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ gather(category, count, -date) %>%
+ ggplot(aes(x = date, y = count, colour = category)) +
+ 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)) +
+ scale_colour_hue(name = "", h.start = 90,
+ breaks = c("total", "announced"),
+ labels = c("Total (IPv4) OR", "IPv6 announced OR")) +
+ ggtitle("Bridges by IP version") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top")
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_advbw_ipv6 <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "ipv6servers.csv", sep = ""),
+ col_types = cols(
+ valid_after_date = col_date(format = ""),
+ server = col_factor(levels = NULL),
+ guard_relay = col_logical(),
+ exit_relay = col_logical(),
+ announced_ipv6 = col_logical(),
+ exiting_ipv6_relay = col_logical(),
+ reachable_ipv6_relay = col_logical(),
+ server_count_sum_avg = col_skip(),
+ advertised_bandwidth_bytes_sum_avg = col_double())) %>%
+ filter(if (!is.null(start_p))
+ valid_after_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p))
+ valid_after_date <= as.Date(end_p) else TRUE) %>%
+ filter(server == "relay") %>%
+ mutate(advertised_bandwidth_bytes_sum_avg =
+ advertised_bandwidth_bytes_sum_avg * 8 / 1e9) %>%
+ group_by(valid_after_date) %>%
+ summarize(total = sum(advertised_bandwidth_bytes_sum_avg),
+ total_guard = sum(advertised_bandwidth_bytes_sum_avg[guard_relay]),
+ total_exit = sum(advertised_bandwidth_bytes_sum_avg[exit_relay]),
+ reachable_guard = sum(advertised_bandwidth_bytes_sum_avg[
+ reachable_ipv6_relay & guard_relay]),
+ reachable_exit = sum(advertised_bandwidth_bytes_sum_avg[
+ reachable_ipv6_relay & exit_relay]),
+ exiting = sum(advertised_bandwidth_bytes_sum_avg[
+ exiting_ipv6_relay])) %>%
+ rename(date = valid_after_date)
+}
+
+plot_advbw_ipv6 <- function(start_p, end_p, path_p) {
+ prepare_advbw_ipv6(start_p, end_p) %>%
+ complete(date = full_seq(date, period = 1)) %>%
+ gather(category, advbw, -date) %>%
+ ggplot(aes(x = date, y = advbw, colour = category)) +
+ 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("total", "total_guard", "total_exit", "reachable_guard",
+ "reachable_exit", "exiting"),
+ labels = c("Total (IPv4) OR", "Guard total (IPv4)", "Exit total (IPv4)",
+ "Reachable guard IPv6 OR", "Reachable exit IPv6 OR", "IPv6 exiting")) +
+ ggtitle("Advertised bandwidth by IP version") +
+ labs(caption = copyright_notice) +
+ theme(legend.position = "top") +
+ guides(colour = guide_legend(nrow = 2, byrow = TRUE))
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+prepare_totalcw <- function(start_p = NULL, end_p = NULL) {
+ read_csv(file = paste(stats_dir, "totalcw.csv", sep = ""),
+ col_types = cols(
+ valid_after_date = col_date(format = ""),
+ nickname = col_character(),
+ have_guard_flag = col_logical(),
+ have_exit_flag = col_logical(),
+ measured_sum_avg = col_double())) %>%
+ filter(if (!is.null(start_p))
+ valid_after_date >= as.Date(start_p) else TRUE) %>%
+ filter(if (!is.null(end_p))
+ valid_after_date <= as.Date(end_p) else TRUE) %>%
+ group_by(valid_after_date, nickname) %>%
+ summarize(measured_sum_avg = sum(measured_sum_avg)) %>%
+ rename(date = valid_after_date, totalcw = measured_sum_avg) %>%
+ arrange(date, nickname)
+}
+
+plot_totalcw <- function(start_p, end_p, path_p) {
+ prepare_totalcw(start_p, end_p) %>%
+ mutate(nickname = ifelse(is.na(nickname), "consensus", nickname)) %>%
+ mutate(nickname = factor(nickname,
+ levels = c("consensus", unique(nickname[nickname != "consensus"])))) %>%
+ ungroup() %>%
+ complete(date = full_seq(date, period = 1), nesting(nickname)) %>%
+ ggplot(aes(x = date, y = totalcw, colour = nickname)) +
+ geom_line(na.rm = TRUE) +
+ 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)) +
+ scale_colour_hue(name = "") +
+ ggtitle("Total consensus weights across bandwidth authorities") +
+ labs(caption = copyright_notice)
+ ggsave(filename = path_p, width = 8, height = 5, dpi = 150)
+}
+
+countrynames <- function(countries) {
+ sapply(countries, countryname)
+}
+
+write_userstats <- function(start, end, node, path) {
+ end <- min(end, as.character(Sys.Date()))
+ c <- read.csv(paste("/srv/metrics.torproject.org/metrics/shared/stats/",
+ "clients.csv", sep = ""), stringsAsFactors = FALSE)
+ c <- c[c$date >= start & c$date <= end & c$country != '' &
+ c$transport == '' & c$version == '' & c$node == node, ]
+ u <- data.frame(country = c$country, users = c$clients,
+ stringsAsFactors = FALSE)
+ u <- u[!is.na(u$users), ]
+ u <- aggregate(list(users = u$users), by = list(country = u$country),
+ mean)
+ total <- sum(u$users)
+ u <- u[!(u$country %in% c("zy", "??", "a1", "a2", "o1", "ap", "eu")), ]
+ u <- u[order(u$users, decreasing = TRUE), ]
+ u <- u[1:10, ]
+ u <- data.frame(
+ cc = as.character(u$country),
+ country = sub('the ', '', countrynames(as.character(u$country))),
+ abs = round(u$users),
+ rel = sprintf("%.2f", round(100 * u$users / total, 2)))
+ write.csv(u, path, quote = FALSE, row.names = FALSE)
+}
+
+write_userstats_relay <- function(start, end, path) {
+ write_userstats(start, end, 'relay', path)
+}
+
+write_userstats_bridge <- function(start, end, path) {
+ write_userstats(start, end, 'bridge', path)
+}
+
+write_userstats_censorship_events <- function(start, end, path) {
+ end <- min(end, as.character(Sys.Date()))
+ c <- read.csv(paste("/srv/metrics.torproject.org/metrics/shared/stats/",
+ "clients.csv", sep = ""), stringsAsFactors = FALSE)
+ c <- c[c$date >= start & c$date <= end & c$country != '' &
+ c$transport == '' & c$version == '' & c$node == 'relay', ]
+ r <- data.frame(date = c$date, country = c$country,
+ upturn = ifelse(!is.na(c$upper) &
+ c$clients > c$upper, 1, 0),
+ downturn = ifelse(!is.na(c$lower) &
+ c$clients < c$lower, 1, 0))
+ r <- aggregate(r[, c("upturn", "downturn")],
+ by = list(country = r$country), sum)
+ r <- r[(r$country %in% names(countrylist)), ]
+ r <- r[order(r$downturn, r$upturn, decreasing = TRUE), ]
+ r <- r[1:10, ]
+ r <- data.frame(cc = r$country,
+ country = sub('the ', '', countrynames(as.character(r$country))),
+ downturns = r$downturn,
+ upturns = r$upturn)
+ write.csv(r, path, quote = FALSE, row.names = FALSE)
+}
diff --git a/src/main/R/rserver/tables.R b/src/main/R/rserver/tables.R
deleted file mode 100644
index 28bd3d5..0000000
--- a/src/main/R/rserver/tables.R
+++ /dev/null
@@ -1,58 +0,0 @@
-countrynames <- function(countries) {
- sapply(countries, countryname)
-}
-
-write_userstats <- function(start, end, node, path) {
- end <- min(end, as.character(Sys.Date()))
- c <- read.csv(paste("/srv/metrics.torproject.org/metrics/shared/stats/",
- "clients.csv", sep = ""), stringsAsFactors = FALSE)
- c <- c[c$date >= start & c$date <= end & c$country != '' &
- c$transport == '' & c$version == '' & c$node == node, ]
- u <- data.frame(country = c$country, users = c$clients,
- stringsAsFactors = FALSE)
- u <- u[!is.na(u$users), ]
- u <- aggregate(list(users = u$users), by = list(country = u$country),
- mean)
- total <- sum(u$users)
- u <- u[!(u$country %in% c("zy", "??", "a1", "a2", "o1", "ap", "eu")), ]
- u <- u[order(u$users, decreasing = TRUE), ]
- u <- u[1:10, ]
- u <- data.frame(
- cc = as.character(u$country),
- country = sub('the ', '', countrynames(as.character(u$country))),
- abs = round(u$users),
- rel = sprintf("%.2f", round(100 * u$users / total, 2)))
- write.csv(u, path, quote = FALSE, row.names = FALSE)
-}
-
-write_userstats_relay <- function(start, end, path) {
- write_userstats(start, end, 'relay', path)
-}
-
-write_userstats_bridge <- function(start, end, path) {
- write_userstats(start, end, 'bridge', path)
-}
-
-write_userstats_censorship_events <- function(start, end, path) {
- end <- min(end, as.character(Sys.Date()))
- c <- read.csv(paste("/srv/metrics.torproject.org/metrics/shared/stats/",
- "clients.csv", sep = ""), stringsAsFactors = FALSE)
- c <- c[c$date >= start & c$date <= end & c$country != '' &
- c$transport == '' & c$version == '' & c$node == 'relay', ]
- r <- data.frame(date = c$date, country = c$country,
- upturn = ifelse(!is.na(c$upper) &
- c$clients > c$upper, 1, 0),
- downturn = ifelse(!is.na(c$lower) &
- c$clients < c$lower, 1, 0))
- r <- aggregate(r[, c("upturn", "downturn")],
- by = list(country = r$country), sum)
- r <- r[(r$country %in% names(countrylist)), ]
- r <- r[order(r$downturn, r$upturn, decreasing = TRUE), ]
- r <- r[1:10, ]
- r <- data.frame(cc = r$country,
- country = sub('the ', '', countrynames(as.character(r$country))),
- downturns = r$downturn,
- upturns = r$upturn)
- write.csv(r, path, quote = FALSE, row.names = FALSE)
-}
-
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