R: add plot_auc_boxplots_by_chapter.R to compare AUC distributions by ICD-10 chapter for 1-year and no-gap datasets; outputs individual and grid plots

plot_auc_boxplots_by_chapter.R

@@ -0,0 +1,134 @@
+# Compare AUC distributions between models by ICD-10 chapter (1-year and no-gap)
+# Usage:
+#   Rscript plot_auc_boxplots_by_chapter.R [one_year_csv] [no_gap_csv] [output_dir]
+# Defaults:
+#   one_year_csv = "model_comparison_auc_1year.csv"
+#   no_gap_csv   = "model_comparison_auc_no_gap.csv"
+#   output_dir   = current working directory (".")
+
+suppressPackageStartupMessages({
+  library(ggplot2)
+  library(cowplot)
+})
+
+args <- commandArgs(trailingOnly = TRUE)
+one_year_csv <- if (length(args) >= 1) args[1] else "model_comparison_auc_1year.csv"
+no_gap_csv   <- if (length(args) >= 2) args[2] else "model_comparison_auc_no_gap.csv"
+out_dir      <- if (length(args) >= 3) args[3] else "."
+
+if (!dir.exists(out_dir)) {
+  dir.create(out_dir, recursive = TRUE, showWarnings = FALSE)
+}
+
+read_csv_safe <- function(path) {
+  tryCatch({
+    read.csv(path, check.names = FALSE)
+  }, error = function(e) {
+    stop(sprintf("Failed to read CSV at '%s': %s", path, e$message))
+  })
+}
+
+# Determine a chapter column name robustly
+get_chapter_col <- function(df) {
+  candidates <- c("ICD-10 Chapter (short)", "ICD-10 Chapter", "ICD10_chapter", "chapter", "ICD_chapter")
+  for (c in candidates) {
+    if (c %in% names(df)) return(c)
+  }
+  return(NA_character_)
+}
+
+# Build long-format data.frame with columns: chapter, model, auc
+# It will include any of the known model columns that exist in the input df
+build_long_df <- function(df) {
+  model_cols <- c(
+    auc_120     = "auc_120",
+    auc_120_l   = "auc_120_l",
+    auc_256     = "auc_256",
+    auc_256_l   = "auc_256_l",
+    auc_delphi  = "auc_delphi"
+  )
+  pretty_names <- c(
+    auc_120    = "GPT-2 120",
+    auc_120_l  = "GPT-2 120_L",
+    auc_256    = "GPT-2 256",
+    auc_256_l  = "GPT-2 256_L",
+    auc_delphi = "Delphi"
+  )
+  present <- model_cols[names(model_cols) %in% names(df)]
+  if (length(present) == 0) stop("No known AUC columns found in input data.")
+  chap_col <- get_chapter_col(df)
+  if (is.na(chap_col)) {
+    warning("No chapter column found; using a single 'All' group.")
+    chapters <- rep("All", nrow(df))
+  } else {
+    chapters <- df[[chap_col]]
+  }
+  out_list <- list()
+  for (key in names(model_cols)) {
+    col <- model_cols[[key]]
+    if (col %in% names(df)) {
+      out_list[[length(out_list) + 1]] <- data.frame(
+        chapter = chapters,
+        model   = pretty_names[[key]],
+        auc     = as.numeric(df[[col]]),
+        stringsAsFactors = FALSE
+      )
+    }
+  }
+  long_df <- do.call(rbind, out_list)
+  # Filter out-of-range or NA
+  long_df <- long_df[is.finite(long_df$auc) & long_df$auc >= 0 & long_df$auc <= 1, ]
+  long_df$model <- factor(long_df$model, levels = c("GPT-2 120", "GPT-2 120_L", "GPT-2 256", "GPT-2 256_L", "Delphi"))
+  return(long_df)
+}
+
+# Make the boxplot grouped by chapter
+make_boxplot <- function(long_df, title_text) {
+  # Order chapters by median AUC of Delphi if available, otherwise overall median
+  has_delphi <- any(long_df$model == "Delphi")
+  if (has_delphi) {
+    med <- aggregate(auc ~ chapter, data = subset(long_df, model == "Delphi"), median, na.rm = TRUE)
+  } else {
+    med <- aggregate(auc ~ chapter, data = long_df, median, na.rm = TRUE)
+  }
+  chap_levels <- med[order(med$auc, decreasing = TRUE), "chapter"]
+  long_df$chapter <- factor(long_df$chapter, levels = chap_levels)
+
+  ggplot(long_df, aes(x = chapter, y = auc, fill = model)) +
+    geom_boxplot(outlier.shape = 19, outlier.size = 0.7, width = 0.75, alpha = 0.95) +
+    coord_flip() +
+    scale_y_continuous(limits = c(0.3, 1.0), breaks = seq(0.3, 1.0, by = 0.1)) +
+    labs(title = title_text, x = "ICD-10 Chapter", y = "AUC") +
+    theme_minimal(base_size = 11) +
+    theme(
+      plot.title = element_text(hjust = 0.5),
+      panel.grid.minor = element_blank(),
+      legend.position = "bottom"
+    ) +
+    guides(fill = guide_legend(nrow = 1))
+}
+
+# Build plots for 1-year and no-gap
+one_year_df <- read_csv_safe(one_year_csv)
+no_gap_df   <- read_csv_safe(no_gap_csv)
+
+one_year_long <- build_long_df(one_year_df)
+no_gap_long   <- build_long_df(no_gap_df)
+
+p1 <- make_boxplot(one_year_long, "AUC by ICD-10 Chapter (1-year gap)")
+p2 <- make_boxplot(no_gap_long,   "AUC by ICD-10 Chapter (no gap)")
+
+# Save individual plots
+out_1year <- file.path(out_dir, "auc_boxplot_by_chapter_1year.png")
+ggsave(out_1year, p1, width = 12, height = 10, dpi = 300, bg = "white")
+cat(sprintf("Saved: %s\n", out_1year))
+
+out_nogap <- file.path(out_dir, "auc_boxplot_by_chapter_no_gap.png")
+ggsave(out_nogap, p2, width = 12, height = 10, dpi = 300, bg = "white")
+cat(sprintf("Saved: %s\n", out_nogap))
+
+# Save a side-by-side grid for quick comparison
+grid <- plot_grid(p1, p2, labels = c("A", "B"), ncol = 2, align = "hv")
+out_grid <- file.path(out_dir, "auc_boxplot_by_chapter_grid.png")
+ggsave(out_grid, grid, width = 18, height = 10, dpi = 250, bg = "white")
+cat(sprintf("Saved grid: %s\n", out_grid))