128 lines
3.1 KiB
R
128 lines
3.1 KiB
R
library(ggplot2)
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library(dplyr)
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library(readr)
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library(stringr)
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# Usage: Rscript combined_fault_rates_per_instruction.r exp1 exp2 ... queries_dir charts_dir [faults_file]
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args <- commandArgs(trailingOnly = TRUE)
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csv_suffix <- if (grepl("\\.csv$", args[length(args)])) {
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args[length(args)]
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} else {
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"faults.csv"
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}
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tail_args <- if (grepl("\\.csv$", args[length(args)])) {
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args[-length(args)]
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} else {
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args
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}
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if (length(tail_args) < 3) {
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stop(paste(
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"Usage: combined_fault_rates_per_instruction.r",
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"<exp1> <exp2> ... <queries_dir> <charts_dir> [faults_file]"
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))
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}
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charts_dir <- tail_args[length(tail_args)]
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queries_dir <- tail_args[length(tail_args) - 1]
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exp_args <- tail_args[-c(length(tail_args) - 1, length(tail_args))]
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# Faults / instruction count, per experiment
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rates <- data.frame()
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for (arg in exp_args) {
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faults_file <- file.path(queries_dir, paste0(arg, "_", csv_suffix))
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mnem_file <- file.path(queries_dir, paste0(arg, "_mnemonics.csv"))
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if (!file.exists(faults_file)) {
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warning(paste("Missing:", faults_file))
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next
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}
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if (!file.exists(mnem_file)) {
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warning(paste("Missing:", mnem_file))
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next
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}
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df <- read_csv(faults_file, col_types = cols())
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mdf <- read_csv(mnem_file, col_types = cols())
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total_faults <- df |>
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filter(resulttype != "OK_MARKER") |>
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summarise(faults = sum(faults, na.rm = TRUE)) |>
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pull(faults)
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total_instrs <- sum(mdf$count, na.rm = TRUE)
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if (is.na(total_instrs) || total_instrs == 0) {
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warning(paste("Zero instruction count for", arg))
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next
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}
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match <- str_match(
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basename(arg),
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"^\\d{2}-\\d{2}_\\d{2}-\\d{2}-\\d{2}_(.+?)_(c|aot|interp)_"
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)
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if (is.na(match[1, 1])) {
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base_name <- basename(arg)
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variant <- "unknown"
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} else {
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base_name <- match[1, 2]
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variant <- match[1, 3]
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}
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rates <- bind_rows(
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rates,
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data.frame(
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base_name = base_name,
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variant = variant,
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fault_rate = total_faults / total_instrs
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)
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)
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}
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if (nrow(rates) == 0) {
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stop("No data loaded")
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}
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# Order base_names by their max fault rate
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base_order <- rates |>
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group_by(base_name) |>
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summarise(max_rate = max(fault_rate), .groups = "drop") |>
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arrange(desc(max_rate)) |>
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pull(base_name)
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rates <- rates |>
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mutate(
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base_name = factor(base_name, levels = base_order),
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variant = factor(variant, levels = c("c", "aot", "interp", "unknown"))
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)
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plot <- ggplot(
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rates,
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aes(x = base_name, y = fault_rate, fill = variant)
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) +
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geom_col(position = position_dodge(preserve = "single")) +
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scale_y_log10() +
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labs(
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title = "Fault Rate per Instruction",
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x = "Experiment",
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y = "Faults / Instruction Count",
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fill = "Variant"
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) +
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theme_minimal() +
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theme(
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axis.text.x = element_text(angle = 90, hjust = 1),
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plot.title = element_text(size = 14, face = "bold")
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)
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suffix <- gsub("^faults|\\.csv$", "", csv_suffix)
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dir.create(charts_dir, showWarnings = FALSE, recursive = TRUE)
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outfile <- file.path(
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charts_dir,
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paste0("fault_rates_per_instruction", suffix, ".svg")
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)
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ggsave(outfile, plot = plot, width = 12, height = 6)
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print(paste("Saved", outfile))
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