#!/usr/bin/env python # /// script # requires-python = ">=3.10" # dependencies = [ # "matplotlib", # "pyqt6", # "numpy", # ] # /// """ This script shows `hyperfine` benchmark results as a bar plot grouped by command. Note all the input files must contain results for all commands. """ import argparse import json import pathlib import matplotlib.pyplot as plt import numpy as np parser = argparse.ArgumentParser(description=__doc__) parser.add_argument( "files", nargs="+", type=pathlib.Path, help="JSON files with benchmark results" ) parser.add_argument("--title", help="Plot Title") parser.add_argument( "--benchmark-names", nargs="+", help="Names of the benchmark groups" ) parser.add_argument("-o", "--output", help="Save image to the given filename") args = parser.parse_args() commands = None data = [] inputs = [] if args.benchmark_names: assert len(args.files) == len( args.benchmark_names ), "Number of benchmark names must match the number of input files." for i, filename in enumerate(args.files): with open(filename) as f: results = json.load(f)["results"] benchmark_commands = [b["command"] for b in results] if commands is None: commands = benchmark_commands else: assert ( commands == benchmark_commands ), f"Unexpected commands in {filename}: {benchmark_commands}, expected: {commands}" data.append([round(b["mean"], 2) for b in results]) if args.benchmark_names: inputs.append(args.benchmark_names[i]) else: inputs.append(filename.stem) data = np.transpose(data) x = np.arange(len(inputs)) # the label locations width = 0.25 # the width of the bars fig, ax = plt.subplots(layout="constrained") fig.set_figheight(5) fig.set_figwidth(10) for i, command in enumerate(commands): offset = width * (i + 1) rects = ax.bar(x + offset, data[i], width, label=command) ax.set_xticks(x + 0.5, inputs) ax.grid(visible=True, axis="y") if args.title: plt.title(args.title) plt.xlabel("Benchmark") plt.ylabel("Time [s]") plt.legend(title="Command") if args.output: plt.savefig(args.output) else: plt.show()