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skills/scientific-visual-table-style/examples/example_openai_visuals.py
4.09 KB · Oct 4, 2026 · 12:32 UTC
#!/usr/bin/env python3
"""Generate three smoke-test figures using the shared visual template.
The data are synthetic and exist only to verify the implementation and export
workflow. Outputs are written to the directory supplied with ``--out``.
"""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
ROOT = Path(__file__).resolve().parents[1]
TEMPLATES = ROOT / "templates"
if str(TEMPLATES) not in sys.path:
sys.path.insert(0, str(TEMPLATES))
from openai_visuals import ( # noqa: E402
DEFAULT_THEME,
metric_axis_label,
new_figure,
plot_horizontal_comparison,
plot_line_series,
plot_pareto_frontier,
save_figure,
)
def build_model_comparison(output_dir: Path) -> list[Path]:
"""Create a compact direct-labeled model comparison."""
labels = ["External baseline", "Prior model", "Focal model"]
values = [68.2, 74.6, 81.3]
errors = [1.5, 1.1, 0.9]
fig, ax = new_figure(width_mm=85, height_mm=55)
plot_horizontal_comparison(
ax,
labels,
values,
focal_label="Focal model",
baseline_labels={"External baseline"},
errors=errors,
value_formatter="{:.1f}",
title="Accuracy improves by 6.7 points",
xlabel=metric_axis_label("Accuracy", "%", "higher"),
)
ax.set_xlim(0, 94)
ax.set_xticks([0, 20, 40, 60, 80])
saved, _ = save_figure(
fig,
output_dir / "model_comparison",
formats=("svg", "png"),
metadata={"Title": "Synthetic OpenAI-style model comparison"},
)
return saved
def build_reliability_curve(output_dir: Path) -> list[Path]:
"""Create a worst-of-k reliability curve with endpoint labels."""
k = [1, 2, 4, 8, 16]
series = {
"External baseline": [76, 69, 60, 49, 35],
"Prior model": [82, 77, 70, 61, 49],
"Focal model": [88, 85, 81, 75, 67],
}
fig, ax = new_figure(width_mm=85, height_mm=55)
plot_line_series(
ax,
k,
series,
focal="Focal model",
baselines={"External baseline"},
title="Reliability degrades more slowly",
xlabel="Attempts, k",
ylabel=metric_axis_label("Score", "%", "higher"),
)
ax.set_xticks(k)
ax.set_xlim(0.5, 19)
ax.set_ylim(25, 94)
ax.set_yticks([30, 45, 60, 75, 90])
saved, _ = save_figure(
fig,
output_dir / "reliability_curve",
formats=("svg", "png"),
metadata={"Title": "Synthetic OpenAI-style reliability curve"},
)
return saved
def build_cost_frontier(output_dir: Path) -> list[Path]:
"""Create a cost/performance frontier with computed nondominated points."""
labels = ["Baseline A", "Baseline B", "Prior low", "Prior high", "Focal low", "Focal high"]
cost = [0.02, 0.05, 0.08, 0.18, 0.06, 0.14]
score = [51, 61, 67, 76, 72, 84]
fig, ax = new_figure(width_mm=120, height_mm=68)
plot_pareto_frontier(
ax,
cost,
score,
labels,
x_preference="lower",
y_preference="higher",
focal_labels={"Focal low", "Focal high"},
title="The focal model shifts the frontier",
xlabel=metric_axis_label("Cost per task", "USD", "lower", scale="log10"),
ylabel=metric_axis_label("Task score", "%", "higher"),
)
ax.set_xscale("log")
ax.set_xlim(0.015, 0.27)
ax.set_ylim(45, 90)
saved, _ = save_figure(
fig,
output_dir / "cost_frontier",
formats=("svg", "png"),
metadata={"Title": "Synthetic OpenAI-style cost frontier"},
)
return saved
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--out", type=Path, default=Path("openai_visual_examples"))
args = parser.parse_args()
args.out.mkdir(parents=True, exist_ok=True)
paths: list[Path] = []
paths.extend(build_model_comparison(args.out))
paths.extend(build_reliability_curve(args.out))
paths.extend(build_cost_frontier(args.out))
for path in paths:
print(path)
return 0
if __name__ == "__main__":
raise SystemExit(main())
SHA-256: 94512555a8d3a528071e51c2f2dee2fa40acd451e9e3c62c587a889163c0854d