move some files around

scripts/charts/combined_sankey.r

@@ -0,0 +1,80 @@
+library(ggplot2)
+library(ggalluvial)
+
+# Usage: Rscript combined_comparion.r exp_abspath1 exp_abspath2 ...
+
+args <- commandArgs(trailingOnly = TRUE)
+argc <- length(args)
+
+if (argc != 2) {
+  print("Expecting two input files")
+  stop()
+}
+
+for (experiment in args) {
+  datafile <- paste(experiment, "/faults.csv", sep = "")
+  if (!file.exists(datafile)) {
+    print(paste("Input file", datafile, "is missing"))
+    stop()
+  }
+}
+
+resulttype_labels <- c(
+  OK_MARKER = "OK",
+  FAIL_MARKER = "FAIL",
+  DETECTED_MARKER = "DETECTED",
+  TIMEOUT = "TIMEOUT",
+  TRAP = "TRAP",
+  ACCESS_OUTERSPACE = "OUTERSPC",
+  WRITE_TEXTSEGMENT = "WRITETXT"
+)
+
+# Read data
+datafile1 <- paste(args[1], "/faults.csv", sep = "")
+data1 <- readr::read_csv(datafile1)
+data1$fault_address <- strtoi(data1$fault_address)
+data1$resulttype <- resulttype_labels[data1$resulttype]
+# tibble::glimpse(data1)
+
+datafile2 <- paste(args[2], "/faults.csv", sep = "")
+data2 <- readr::read_csv(datafile2)
+data2$fault_address <- strtoi(data2$fault_address)
+data2$resulttype <- resulttype_labels[data2$resulttype]
+# tibble::glimpse(data2)
+
+# https://corybrunson.github.io/ggalluvial/
+joined <- merge(
+  data1[, c("fault_address", "resulttype", "faults")],
+  data2[, c("fault_address", "resulttype", "faults")],
+  by = "fault_address",
+  suffixes = c("_bench1", "_bench2")
+)
+
+streams <- aggregate(
+  faults_bench2 ~ resulttype_bench1 + resulttype_bench2,
+  data = joined,
+  sum
+)
+names(streams) <- c("bench1", "bench2", "faults")
+
+plot <- ggplot(
+  data = streams,
+  aes(axis1 = bench1, axis2 = bench2, y = faults)
+) +
+  scale_x_discrete(
+    # TODO: Name the benchmarks
+    # limits = c(args[1], args[2])
+    limits = c("Bench A", "Bench B")
+  ) +
+  labs(x = "Benchmark", y = "Faults") +
+  geom_alluvium(aes(fill = bench1)) +
+  geom_stratum() +
+  geom_text(stat = "stratum", aes(label = after_stat(stratum))) +
+  theme_minimal() +
+  theme(legend.position = "none")
+
+# TODO: Name the file according to the benchmarks
+ggsave(
+  paste(args[2], "/../sankey.svg", sep = ""),
+  plot = plot,
+)

scripts/charts/single_result.r

@@ -0,0 +1,26 @@
+library(ggplot2)
+
+# Usage: Rscript single_result.r exp_abspath
+
+args <- commandArgs(trailingOnly = TRUE)
+experiment <- args[1]
+datafile <- paste(experiment, "/resultsdata.csv", sep = "")
+
+if (!file.exists(datafile)) {
+  print(paste("Input file", datafile, "is missing"))
+  stop()
+}
+
+data <- readr::read_csv(datafile)
+tibble::glimpse(data)
+
+plot <- ggplot(data, aes(x = benchmark, y = faults, fill = resulttype)) +
+  geom_col(position = "dodge") +
+  scale_y_log10() +
+  labs(x = "Benchmark", y = "Faults", fill = "Result Type") +
+  theme_minimal()
+
+ggsave(
+  paste(experiment, "/single_result.svg", sep = ""),
+  plot = plot,
+)

scripts/charts/single_scatter.r

@@ -0,0 +1,32 @@
+library(ggplot2)
+
+# Usage: Rscript single_scatter.r exp_abspath
+
+# TODO: Allow filtering resulttypes (or at least exclude OK_MARKER)
+
+args <- commandArgs(trailingOnly = TRUE)
+experiment <- args[1]
+datafile <- paste(experiment, "/faults.csv", sep = "")
+
+if (!file.exists(datafile)) {
+  print(paste("Input file", datafile, "is missing"))
+  stop()
+}
+
+data <- readr::read_csv(datafile)
+data$fault_address <- strtoi(data$fault_address)
+tibble::glimpse(data)
+
+plot <- ggplot(data, aes(x = fault_address, y = faults)) +
+  geom_point(aes(color = resulttype)) +
+  scale_x_continuous(
+    labels = function(x) sprintf("0x%X", as.integer(x))
+  ) +
+  scale_y_log10() +
+  labs(x = "Address", y = "Faults", color = "Type") +
+  theme_minimal()
+
+ggsave(
+  paste(experiment, "/scatter.svg", sep = ""),
+  plot = plot,
+)