mirror of
https://github.com/sharkdp/hyperfine.git
synced 2026-10-12 02:22:35 +00:00
86 lines
2.3 KiB
Python
Executable File
86 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python
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# /// script
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# requires-python = ">=3.10"
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# dependencies = [
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# "matplotlib",
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# "pyqt6",
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# "numpy",
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# ]
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# ///
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"""
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This script shows `hyperfine` benchmark results as a bar plot grouped by command.
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Note all the input files must contain results for all commands.
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"""
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import argparse
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import pathlib
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import matplotlib.pyplot as plt
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import numpy as np
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from plot_utils import METRICS, add_metric_argument, load_results
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parser = argparse.ArgumentParser(description=__doc__)
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add_metric_argument(parser)
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parser.add_argument(
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"files", nargs="+", type=pathlib.Path, help="JSON files with benchmark results"
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)
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parser.add_argument("--title", help="Plot Title")
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parser.add_argument(
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"--benchmark-names", nargs="+", help="Names of the benchmark groups"
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)
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parser.add_argument("-o", "--output", help="Save image to the given filename")
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args = parser.parse_args()
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metric, datasets = load_results(parser, args.files, args.metric)
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metric_info = METRICS[metric]
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commands = None
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data = []
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inputs = []
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if args.benchmark_names:
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assert len(args.files) == len(args.benchmark_names), (
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"Number of benchmark names must match the number of input files."
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)
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for i, (filename, results) in enumerate(zip(args.files, datasets)):
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benchmark_commands = [b.get("name", b["command"]) for b in results]
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if commands is None:
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commands = benchmark_commands
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else:
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assert commands == benchmark_commands, (
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f"Unexpected commands in {filename}: {benchmark_commands}, expected: {commands}"
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)
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data.append([b["summary"][metric]["mean"] / metric_info.scale for b in results])
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if args.benchmark_names:
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inputs.append(args.benchmark_names[i])
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else:
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inputs.append(filename.stem)
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data = np.transpose(data)
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x = np.arange(len(inputs)) # the label locations
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width = 0.25 # the width of the bars
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fig, ax = plt.subplots(layout="constrained")
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fig.set_figheight(5)
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fig.set_figwidth(10)
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for i, command in enumerate(commands):
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offset = width * (i + 1)
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rects = ax.bar(x + offset, data[i], width, label=command)
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ax.set_xticks(x + 0.5, inputs)
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ax.grid(visible=True, axis="y")
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if args.title:
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plt.title(args.title)
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plt.xlabel("Benchmark")
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plt.ylabel(metric_info.axis_label)
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plt.legend(title="Command")
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if args.output:
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plt.savefig(args.output)
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else:
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plt.show()
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