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Make plotting scripts runnable with uv
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David Peter authored and David Peter committed
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commit
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@@ -17,105 +17,107 @@ import matplotlib.pyplot as plt
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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("file", help="JSON file with benchmark results", nargs="+")
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parser.add_argument(
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"--parameter-name",
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metavar="name",
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type=str,
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help="Deprecated; parameter names are now inferred from benchmark files",
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)
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parser.add_argument(
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"--log-x", help="Use a logarithmic x (parameter) axis", action="store_true"
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)
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parser.add_argument(
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"--log-y",
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"--log-time",
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dest="log_y",
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help="Use a logarithmic metric axis",
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action="store_true",
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)
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parser.add_argument(
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"--titles", help="Comma-separated list of titles 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, datasets = load_results(parser, args.file, args.metric)
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metric_info = METRICS[metric]
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if args.parameter_name is not None:
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sys.stderr.write(
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"warning: --parameter-name is deprecated; names are inferred from "
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"benchmark results\n"
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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", nargs="+")
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parser.add_argument(
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"--parameter-name",
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metavar="name",
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type=str,
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help="Deprecated; parameter names are now inferred from benchmark files",
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)
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parser.add_argument(
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"--log-x", help="Use a logarithmic x (parameter) axis", action="store_true"
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)
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parser.add_argument(
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"--log-y",
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"--log-time",
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dest="log_y",
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help="Use a logarithmic metric axis",
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action="store_true",
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)
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parser.add_argument(
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"--titles", help="Comma-separated list of titles 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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def die(msg):
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sys.stderr.write(f"fatal: {msg}\n")
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sys.exit(1)
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def extract_parameters(results):
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"""Return `(parameter_name: str, parameter_values: List[float])`."""
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if not results:
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die("no benchmark data to plot")
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(names, values) = zip(*(unique_parameter(b) for b in results))
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names = frozenset(names)
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if len(names) != 1:
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die(
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f"benchmarks must all have the same parameter name, but found: {sorted(names)}"
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args = parser.parse_args()
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metric, datasets = load_results(parser, args.file, args.metric)
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metric_info = METRICS[metric]
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if args.parameter_name is not None:
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sys.stderr.write(
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"warning: --parameter-name is deprecated; names are inferred from "
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"benchmark results\n"
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)
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return (next(iter(names)), list(values))
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def die(msg):
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sys.stderr.write(f"fatal: {msg}\n")
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sys.exit(1)
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def extract_parameters(results):
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"""Return `(parameter_name: str, parameter_values: List[float])`."""
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if not results:
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die("no benchmark data to plot")
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(names, values) = zip(*(unique_parameter(b) for b in results))
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names = frozenset(names)
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if len(names) != 1:
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die(
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f"benchmarks must all have the same parameter name, but found: {sorted(names)}"
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)
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return (next(iter(names)), list(values))
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def unique_parameter(benchmark):
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"""Return the unique parameter `(name: str, value: float)`, or die."""
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params_dict = benchmark.get("parameters", {})
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if not params_dict:
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die("benchmarks must have exactly one parameter, but found none")
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if len(params_dict) > 1:
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die(
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f"benchmarks must have exactly one parameter, but found multiple: {sorted(params_dict)}"
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)
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[(name, value)] = params_dict.items()
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return (name, float(value["value"]))
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parameter_name = None
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for results in datasets:
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(this_parameter_name, parameter_values) = extract_parameters(results)
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if parameter_name is not None and this_parameter_name != parameter_name:
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die(
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f"files must all have the same parameter name, but found {parameter_name!r} vs. {this_parameter_name!r}"
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)
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parameter_name = this_parameter_name
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summaries = [b["summary"][metric] for b in results]
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means = [s["mean"] / metric_info.scale for s in summaries]
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stddevs = [
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s["stddev"] / metric_info.scale if s["stddev"] is not None else float("nan")
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for s in summaries
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]
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plt.errorbar(x=parameter_values, y=means, yerr=stddevs, capsize=2)
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plt.xlabel(parameter_name)
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plt.ylabel(metric_info.axis_label)
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if args.log_y:
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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.log_x:
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plt.xscale("log")
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if args.titles:
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plt.legend(args.titles.split(","))
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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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def unique_parameter(benchmark):
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"""Return the unique parameter `(name: str, value: float)`, or die."""
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params_dict = benchmark.get("parameters", {})
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if not params_dict:
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die("benchmarks must have exactly one parameter, but found none")
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if len(params_dict) > 1:
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die(
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f"benchmarks must have exactly one parameter, but found multiple: {sorted(params_dict)}"
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)
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[(name, value)] = params_dict.items()
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return (name, float(value["value"]))
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parameter_name = None
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for results in datasets:
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(this_parameter_name, parameter_values) = extract_parameters(results)
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if parameter_name is not None and this_parameter_name != parameter_name:
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die(
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f"files must all have the same parameter name, but found {parameter_name!r} vs. {this_parameter_name!r}"
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)
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parameter_name = this_parameter_name
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summaries = [b["summary"][metric] for b in results]
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means = [s["mean"] / metric_info.scale for s in summaries]
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stddevs = [
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s["stddev"] / metric_info.scale if s["stddev"] is not None else float("nan")
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for s in summaries
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]
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plt.errorbar(x=parameter_values, y=means, yerr=stddevs, capsize=2)
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plt.xlabel(parameter_name)
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plt.ylabel(metric_info.axis_label)
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if args.log_y:
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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.log_x:
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plt.xscale("log")
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if args.titles:
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plt.legend(args.titles.split(","))
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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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