import argparse
import numpy as np
from plot_utils import METRICS, add_metric_argument, load_results
def main():
parser = argparse.ArgumentParser()
parser.add_argument("file", help="JSON file with benchmark results")
add_metric_argument(parser)
parser.add_argument(
"--time-unit",
help="Display unit for time metrics (default: second).",
choices=["second", "millisecond"],
)
args = parser.parse_args()
metric, [results] = load_results(parser, [args.file], args.metric)
description = METRICS[metric]
unit, scale = description.unit, description.scale
if args.time_unit is not None:
if not metric.startswith("time_"):
parser.error("--time-unit can only be used with a time metric")
if args.time_unit == "millisecond":
unit, scale = "ms", 0.001
def format_value(value):
suffix = f" {unit}" if unit else ""
return f"{value:.3f}{suffix}"
print(f"Metric: {description.label}\n")
for result in results:
summary = result["summary"][metric]
values = [m[metric]["value"] / scale for m in result["measurements"]]
p05, p25, p75, p95 = np.percentile(values, [5, 25, 75, 95])
iqr = p75 - p25
print(f"Command '{result.get('name', result['command'])}'")
print(f" runs: {summary['count']:8d}")
for statistic in ["mean", "stddev", "median", "min", "max"]:
value = summary[statistic]
formatted = "N/A" if value is None else format_value(value / scale)
print(f" {statistic + ':':<8}{formatted:>8}")
print()
print(" percentiles:")
print(f" P_05 .. P_95: {format_value(p05)} .. {format_value(p95)}")
print(
f" P_25 .. P_75: {format_value(p25)} .. {format_value(p75)}"
f" (IQR = {format_value(iqr)})"
)
print()
if __name__ == "__main__":
main()