Make plotting scripts runnable with uv

scripts/plot_benchmark_comparison.py

@@ -21,65 +21,71 @@ import numpy as np
 
 from plot_utils import METRICS, add_metric_argument, load_results
 
-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."
+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 = []
 
-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])
+        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))  # the label locations
+    width = 0.25  # the width of the bars
+
+    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:
-        inputs.append(filename.stem)
+        plt.show()
 
-data = np.transpose(data)
-x = np.arange(len(inputs))  # the label locations
-width = 0.25  # the width of the bars
 
-fig, ax = plt.subplots(layout="constrained")
-fig.set_figheight(5)
-fig.set_figwidth(10)
-for i, command in enumerate(commands):
-    offset = width * (i + 1)
-    rects = 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()