130 lines
3.2 KiB
R
130 lines
3.2 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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library(tidyr)
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# Usage: Rscript combined_fault_probability_merged.r exp1 exp2 ... queries_dir charts_dir [resultsdata_file]
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args <- commandArgs(trailingOnly = TRUE)
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csv_suffix <- if (grepl("\\.csv$", args[length(args)])) {
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args[length(args)]
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} else {
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"resultsdata.csv"
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}
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tail_args <- if (grepl("\\.csv$", 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) < 4) {
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stop(paste(
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"Usage: combined_fault_probability_merged.r",
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"<exp1> <exp2> ... <queries_dir> <charts_dir> [resultsdata_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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extract_info <- function(path) {
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dir_name <- basename(path)
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match <- str_match(
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dir_name,
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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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warning(paste("Could not parse:", dir_name))
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return(NULL)
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}
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# "tacle-kernel-bsort" -> "bsort", otherwise it doesn't fit
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base_name <- sub("^tacle-[^-]+-", "", match[1, 2])
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list(base_name = base_name, variant = match[1, 3], path = path)
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}
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# Load data
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all_data <- data.frame()
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for (arg in exp_args) {
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info <- extract_info(arg)
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if (is.null(info)) {
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next
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}
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csv_file <- file.path(queries_dir, paste0(arg, "_", csv_suffix))
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if (!file.exists(csv_file)) {
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warning(paste("Missing:", csv_file))
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next
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}
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df <- read_csv(csv_file, col_types = cols())
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df$base_name <- info$base_name
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df$variant <- info$variant
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all_data <- bind_rows(all_data, df)
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}
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# TODO: Finally put all the bullshit before this in some shared space
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if (nrow(all_data) == 0) {
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stop("No data loaded")
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}
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marker_order <- c(
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"OK_MARKER",
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"DETECTED_MARKER",
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"GROUP1_MARKER",
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"TRAP",
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"TIMEOUT",
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"WRITE_TEXTSEGMENT",
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"ACCESS_OUTERSPACE",
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"FAIL_MARKER"
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)
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# Merge ip/mem/regs, then divide by the merged faultspace area
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# Don't merge GROUP1_MARKER into TRAP for this chart
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# Also keep the OK_MARKERs, so the "sum to 100%" is accurate
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probability <- all_data |>
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group_by(base_name, variant, resulttype) |>
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summarise(faults = sum(faults, na.rm = TRUE), .groups = "drop") |>
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group_by(base_name, variant) |>
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mutate(frac = faults / sum(faults, na.rm = TRUE)) |>
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ungroup()
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# Don't print alphabetically
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probability$resulttype <- factor(probability$resulttype, levels = marker_order)
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probability$variant <- factor(
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probability$variant,
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levels = c("c", "aot", "interp")
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)
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plot <- ggplot(
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probability,
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aes(x = variant, y = frac, fill = resulttype)
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) +
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geom_col() +
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facet_wrap(~base_name) +
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scale_y_continuous(labels = scales::percent) +
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labs(
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title = "Fault Probability (merged ip + mem + regs)",
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x = NULL,
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y = "Probability of Failure",
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fill = "Fault Type"
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) +
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theme_minimal() +
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theme(
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plot.title = element_text(size = 13, face = "bold"),
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axis.text.x = element_text(angle = 45, hjust = 1)
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)
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out_suffix <- gsub("^resultsdata|\\.csv$", "", csv_suffix)
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dir.create(charts_dir, showWarnings = FALSE, recursive = TRUE)
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filename <- file.path(
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charts_dir,
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paste0("fault_probability_merged", out_suffix, ".svg")
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)
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ggsave(filename, plot = plot, width = 13, height = 8)
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