commit 519512c85d814985caffbbda93db00c5dd32b41f Author: Karsten Loesing karsten.loesing@gmx.net Date: Tue Feb 13 15:19:21 2018 +0100

Use complete() rather than merge() for missing dates.

The result is the same, but the code is much easier to read. --- src/main/R/rserver/graphs.R | 36 ++++++++++++------------------------ 1 file changed, 12 insertions(+), 24 deletions(-)

diff --git a/src/main/R/rserver/graphs.R b/src/main/R/rserver/graphs.R index c7ef2bd..ab1a60d 100644 --- a/src/main/R/rserver/graphs.R +++ b/src/main/R/rserver/graphs.R @@ -1095,20 +1095,16 @@ plot_webstats_tm <- function(start, end, path) { }

plot_relays_ipv6 <- function(start, end, path) { - all_relay_data <- read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), + read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), colClasses = c("valid_after_date" = "Date")) %>% - filter(server == "relay") - start_date <- max(as.Date(start), min(all_relay_data$valid_after_date)) - end_date <- min(as.Date(end), max(all_relay_data$valid_after_date)) - all_relay_data %>% - filter(valid_after_date >= start_date, valid_after_date <= end_date) %>% + filter(valid_after_date >= as.Date(start), + valid_after_date <= as.Date(end), server == "relay") %>% group_by(valid_after_date) %>% summarize(total = sum(server_count_sum_avg), announced = sum(server_count_sum_avg[announced_ipv6 == 't']), reachable = sum(server_count_sum_avg[reachable_ipv6_relay == 't']), exiting = sum(server_count_sum_avg[exiting_ipv6_relay == 't'])) %>% - merge(data.frame(valid_after_date = seq(start_date, end_date, - by = "1 day")), all = TRUE) %>% + complete(valid_after_date = full_seq(valid_after_date, period = 1)) %>% gather(total, announced, reachable, exiting, key = "category", value = "count") %>% ggplot(aes(x = valid_after_date, y = count, colour = category)) + @@ -1127,18 +1123,14 @@ plot_relays_ipv6 <- function(start, end, path) { }

plot_bridges_ipv6 <- function(start, end, path) { - all_bridge_data <- read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), + read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), colClasses = c("valid_after_date" = "Date")) %>% - filter(server == "bridge") - start_date <- max(as.Date(start), min(all_bridge_data$valid_after_date)) - end_date <- min(as.Date(end), max(all_bridge_data$valid_after_date)) - all_bridge_data %>% - filter(valid_after_date >= start_date, valid_after_date <= end_date) %>% + filter(valid_after_date >= as.Date(start), + valid_after_date <= as.Date(end), server == "bridge") %>% group_by(valid_after_date) %>% summarize(total = sum(server_count_sum_avg), announced = sum(server_count_sum_avg[announced_ipv6 == 't'])) %>% - merge(data.frame(valid_after_date = seq(start_date, end_date, - by = "1 day")), all = TRUE) %>% + complete(valid_after_date = full_seq(valid_after_date, period = 1)) %>% gather(total, announced, key = "category", value = "count") %>% ggplot(aes(x = valid_after_date, y = count, colour = category)) + geom_line() + @@ -1155,13 +1147,10 @@ plot_bridges_ipv6 <- function(start, end, path) { }

plot_advbw_ipv6 <- function(start, end, path) { - all_relay_data <- read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), + read.csv(paste(stats_dir, "ipv6servers.csv", sep = ""), colClasses = c("valid_after_date" = "Date")) %>% - filter(server == "relay") - start_date <- max(as.Date(start), min(all_relay_data$valid_after_date)) - end_date <- min(as.Date(end), max(all_relay_data$valid_after_date)) - all_relay_data %>% - filter(valid_after_date >= start_date, valid_after_date <= end_date) %>% + filter(valid_after_date >= as.Date(start), + valid_after_date <= as.Date(end), server == "relay") %>% group_by(valid_after_date) %>% summarize(total = sum(advertised_bandwidth_bytes_sum_avg), total_guard = sum(advertised_bandwidth_bytes_sum_avg[guard_relay != 'f']), @@ -1172,8 +1161,7 @@ plot_advbw_ipv6 <- function(start, end, path) { reachable_ipv6_relay != 'f' & exit_relay != 'f']), exiting = sum(advertised_bandwidth_bytes_sum_avg[ exiting_ipv6_relay != 'f'])) %>% - merge(data.frame(valid_after_date = seq(start_date, end_date, - by = "1 day")), all = TRUE) %>% + complete(valid_after_date = full_seq(valid_after_date, period = 1)) %>% gather(total, total_guard, total_exit, reachable_guard, reachable_exit, exiting, key = "category", value = "count") %>% ggplot(aes(x = valid_after_date, y = (count * 8) / 1e9,