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https://github.com/sharkdp/hyperfine.git
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ef9e1409c6
* add: legend modification parameters and output DPI This commit adds a CLI parameter to plot_histogram in order to position the legend of the plot on the diagram. It also defines the output DPI for the plot to 600 dpi. Plot_progression gets a CLI paramter to add a custom label and to overwrite the default one. --------- Co-authored-by: dbv <jt@dbv03.linpro.no> Co-authored-by: dbv <spreadcat.github@micronarrativ.org>
84 lines
2.3 KiB
Python
Executable File
84 lines
2.3 KiB
Python
Executable File
#!/usr/bin/env python
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"""This program shows `hyperfine` benchmark results as a histogram."""
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import argparse
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import json
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.font_manager
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parser = argparse.ArgumentParser(description=__doc__)
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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(
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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("--bins", help="Number of bins (default: auto)")
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parser.add_argument(
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"--legend-location", help="Location of the legend on plot (default: upper center)",
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choices=["upper center", "lower center", "right", "left", "best", "upper left", "upper right", "lower left", "lower right", "center left", "center right", "center"],
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default="upper center"
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)
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parser.add_argument(
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"--type", help="Type of histogram (*bar*, barstacked, step, stepfilled)"
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)
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parser.add_argument("-o", "--output", help="Save image to the given filename.")
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parser.add_argument(
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"--t-min", metavar="T", help="Minimum time to be displayed (seconds)"
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)
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parser.add_argument(
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"--t-max", metavar="T", help="Maximum time to be displayed (seconds)"
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)
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parser.add_argument(
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"--log-count",
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help="Use a logarithmic y-axis for the event count",
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action="store_true",
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)
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args = parser.parse_args()
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with open(args.file) as f:
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results = json.load(f)["results"]
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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["command"] for b in results]
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all_times = [b["times"] for b in results]
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t_min = float(args.t_min) if args.t_min else np.min(list(map(np.min, all_times)))
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t_max = float(args.t_max) if args.t_max else np.max(list(map(np.max, all_times)))
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bins = int(args.bins) if args.bins else "auto"
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histtype = args.type if args.type else "bar"
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plt.figure(figsize=(10, 5))
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plt.hist(
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all_times,
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label=labels,
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bins=bins,
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histtype=histtype,
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range=(t_min, t_max),
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)
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plt.legend(
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loc=args.legend_location,
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fancybox=True,
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shadow=True,
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prop={"size": 7, "family": ["Source Code Pro", "Fira Mono", "Courier New"]}
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)
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plt.xlabel("Time [s]")
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if args.title:
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plt.title(args.title)
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if args.log_count:
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plt.yscale("log")
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else:
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plt.ylim(0, None)
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if args.output:
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plt.savefig(args.output, dpi=600)
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else:
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plt.show()
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