library(cplog) library(dplyr) library(ggplot2) library(magrittr) library(stringr) library(tidyr) log_dir_root <- system.file("extdata", "051816_3661_Q3Q4_subset/", package = "cplog") aws_logs <- lapply( list.dirs(log_dir_root, recursive = F, full.names = F), function(log_dir) { logdf <- parse_log_dir(paste0(log_dir_root, log_dir, sep = "/")) logdf %>% mutate(log_dir = log_dir) } ) %>% bind_rows() aws_logs %<>% rename(group = log_dir)
plot_runtimes <- function(df) { df %<>% group_by(group) %>% summarize(calculated = sum(runtime_calc, na.rm = T), reported = sum(runtime), date = min(date)) %>% select(date, calculated, reported) %>% gather(estimate_type, runtime, -date) p <- ggplot(df, aes(date, runtime, color = estimate_type)) + geom_line(alpha = 0.9) + geom_point(alpha = 0.3) + xlab("time") + ggtitle("Runtimes for each group of images") print(p) } aws_logs %>% plot_runtimes() aws_logs %>% filter(module != "NamesAndTypes") %>% plot_runtimes()
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