mirror of
https://github.com/sharkdp/hyperfine.git
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77 lines
2.4 KiB
Python
Executable File
77 lines
2.4 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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# ]
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# ///
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"""This program shows `hyperfine` benchmark results as a box and whisker plot.
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Quoting from the matplotlib documentation:
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The box extends from the lower to upper quartile values of the data, with
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a line at the median. The whiskers extend from the box to show the range
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of the data. Flier points are those past the end of the whiskers.
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"""
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import argparse
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import matplotlib.pyplot as plt
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from plot_utils import METRICS, add_metric_argument, load_results
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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add_metric_argument(parser)
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parser.add_argument("file", help="JSON file with benchmark results")
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parser.add_argument("--title", help="Plot Title")
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parser.add_argument("--sort-by", choices=["median"], help="Sort method")
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parser.add_argument(
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"--labels", help="Comma-separated list of entries for the plot legend"
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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, [results] = load_results(parser, [args.file], args.metric)
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metric_info = METRICS[metric]
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if args.labels:
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labels = args.labels.split(",")
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else:
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labels = [b.get("name", b["command"]) for b in results]
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values = [
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[m[metric]["value"] / metric_info.scale for m in b["measurements"]]
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for b in results
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]
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if args.sort_by == "median":
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medians = [b["summary"][metric]["median"] for b in results]
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indices = sorted(range(len(labels)), key=lambda k: medians[k])
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labels = [labels[i] for i in indices]
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values = [values[i] for i in indices]
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plt.figure(figsize=(10, 6), constrained_layout=True)
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boxplot = plt.boxplot(values, vert=True, patch_artist=True)
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cmap = plt.get_cmap("rainbow")
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colors = [cmap(val / len(values)) for val in range(len(values))]
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for patch, color in zip(boxplot["boxes"], colors):
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patch.set_facecolor(color)
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if args.title:
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plt.title(args.title)
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plt.legend(handles=boxplot["boxes"], labels=labels, loc="best", fontsize="medium")
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plt.ylabel(metric_info.axis_label)
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plt.ylim(0, None)
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plt.xticks(list(range(1, len(labels) + 1)), labels, rotation=45)
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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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if __name__ == "__main__":
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main()
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