Expanded visualizer; filled table in report

src/aarch64-linux-flush-dcache/visualizer/ftrace2pyplot/arguments.py

@@ -32,4 +32,15 @@ parser.add_argument(
 parser.add_argument(
     "-i", "--interactive", type=bool, help="show pyplot when finished drawing",
     default=True
+)
+
+# Customizability
+parser.add_argument(
+    "--x-label", type=str, help="X axis label", default="Runtime (μs)"
+)
+parser.add_argument(
+    "--y-label", type=str, help="Y axis label", default="Write amount (KiB)"
+)
+parser.add_argument(
+    "--gen-title", type=bool, help="Generate title (legacy)", default=True
 )

src/aarch64-linux-flush-dcache/visualizer/ftrace2pyplot/core.py

@@ -3,6 +3,7 @@ from argparse import Namespace
 import glob
 from typing import List, Tuple, Union, Optional
 import re
+import sys # stderr
 
 import trappy
 import pandas as pd
@@ -92,9 +93,17 @@ def run(args: Namespace):
         if fngraph_df is None:
             print("No entry -- pass")
             continue
-        size_in_kb = parse_basename_to_kibs(
-            str(path.basename(ftrace_dat_path).split(".")[:-1]))
-        ftrace_dfs.append((size_in_kb, fngraph_df))
+        try:
+            label = parse_basename_to_kibs(
+                path.basename(ftrace_dat_path).split(".")[:-1])
+        except Exception:
+            label = str(path.basename(ftrace_dat_path))
+            print(
+                f"Cannot parse size in basename '{label}', using basename...",
+                file=sys.stderr
+            )
+
+        ftrace_dfs.append((label, fngraph_df))
 
     ftrace_dfs.sort(key=lambda tp: tp[0])
 
@@ -109,16 +118,27 @@ def run(args: Namespace):
     plot_df = pd.concat(series, axis=1, keys=indices) # In long-form
     print("Plot shape: {}; head: \n{}"
         .format(plot_df.shape, plot_df.head()))
+    print("Quantiles | 25p: \n{} | 50p: \n{} | 75p: \n{} | 99p: \n{}".format(
+        plot_df.quantile(.25, interpolation="nearest"),
+        plot_df.quantile(.50, interpolation="nearest"),
+        plot_df.quantile(.75, interpolation="nearest"),
+        plot_df.quantile(.99, interpolation="nearest"),
+    ))
 
     # plot violin plot
     fig, ax = plt.subplots(figsize=(12, 8))
     sns.violinplot(
         data=plot_df, orient="h", fill=False, log_scale=args.use_log_scale,
         inner="quart")
-    ax.set_xlabel("Runtime (μs)")
-    ax.set_ylabel("Write amount (KiB)")
-    ax.set_title("Percentile: {}{}"
-        .format(args.percentile, ", log scale" if args.use_log_scale else ""))
+    ax.set_xlabel(args.x_label)
+    ax.set_ylabel(args.y_label)
+    if args.gen_title:
+        ax.set_title("Percentile: {}{}"
+            .format(
+                args.percentile,
+                ", log scale" if args.use_log_scale else ""
+            )
+        )
     fig.savefig(args.output)
 
     if args.interactive: