import argparse
import pathlib
import matplotlib.pyplot as plt
import numpy as np
from plot_utils import METRICS, add_metric_argument, load_results
def main():
parser = argparse.ArgumentParser(description=__doc__)
add_metric_argument(parser)
parser.add_argument(
"files", nargs="+", type=pathlib.Path, help="JSON files with benchmark results"
)
parser.add_argument("--title", help="Plot Title")
parser.add_argument(
"--benchmark-names", nargs="+", help="Names of the benchmark groups"
)
parser.add_argument("-o", "--output", help="Save image to the given filename")
args = parser.parse_args()
metric, datasets = load_results(parser, args.files, args.metric)
metric_info = METRICS[metric]
commands = None
data = []
inputs = []
if args.benchmark_names:
assert len(args.files) == len(args.benchmark_names), (
"Number of benchmark names must match the number of input files."
)
for i, (filename, results) in enumerate(zip(args.files, datasets)):
benchmark_commands = [b.get("name", b["command"]) for b in results]
if commands is None:
commands = benchmark_commands
else:
assert commands == benchmark_commands, (
f"Unexpected commands in {filename}: {benchmark_commands}, expected: {commands}"
)
data.append([b["summary"][metric]["mean"] / metric_info.scale for b in results])
if args.benchmark_names:
inputs.append(args.benchmark_names[i])
else:
inputs.append(filename.stem)
data = np.transpose(data)
x = np.arange(len(inputs)) width = 0.25
fig, ax = plt.subplots(layout="constrained")
fig.set_figheight(5)
fig.set_figwidth(10)
for i, command in enumerate(commands):
offset = width * (i + 1)
ax.bar(x + offset, data[i], width, label=command)
ax.set_xticks(x + 0.5, inputs)
ax.grid(visible=True, axis="y")
if args.title:
plt.title(args.title)
plt.xlabel("Benchmark")
plt.ylabel(metric_info.axis_label)
plt.legend(title="Command")
if args.output:
plt.savefig(args.output)
else:
plt.show()
if __name__ == "__main__":
main()