Datasets:
Formats:
json
Languages:
English
Size:
< 1K
Tags:
recursive-self-improvement
self-modifying-systems
program-semantics
formal-methods
adaptive-validation
exact-arithmetic
License:
| """Generate manuscript tables and figures directly from released raw summaries.""" | |
| from pathlib import Path | |
| import json | |
| import matplotlib | |
| matplotlib.use('Agg') | |
| import matplotlib.pyplot as plt | |
| ROOT=Path(__file__).resolve().parents[1];M=ROOT/'manuscript';F=M/'figures';F.mkdir(exist_ok=True) | |
| def read(name):return json.loads((ROOT/'results'/name).read_text()) | |
| h=read('heredity_summary.json') | |
| fig,ax=plt.subplots(figsize=(7.2,3.6)) | |
| labels=['Literal programs','Hereditary classes','Current signature classes'] | |
| values=[h['literal_programs'],h['hereditary_classes'],h['static_evaluation_classes']] | |
| bars=ax.barh(labels,values) | |
| for b,n in zip(bars,values):ax.text(n+1200,b.get_y()+b.get_height()/2,f'{n:,}',va='center',fontsize=11) | |
| ax.set_xlim(0,98000);ax.set_xlabel('Number of distinguishable classes under each contract') | |
| ax.invert_yaxis();ax.spines[['top','right']].set_visible(False);fig.tight_layout();fig.savefig(F/'v4_catalog.pdf');plt.close(fig) | |
| c=read('corridor_summary.json')['aggregates'];labels={'raw':'Raw simulation','selfloop_skip':'Self-loop skipping','compiled':'Compiled exit'} | |
| rows=[] | |
| for key in ['raw','selfloop_skip','compiled']: | |
| x=c[key];rows.append(f"{labels[key]} & {x['setup_cpu']:.6f} & {x['execution_cpu']:.6f} & {x['total_cpu']:.6f} & {x['random_draws']:,} \\\\") | |
| (M/'tables_v4_corridor.tex').write_text(r'''\begin{table}[htbp]\centering\small | |
| \begin{tabular}{lrrrr}\toprule | |
| Method & Setup CPU & Execution CPU & Total CPU & Draws\\\midrule | |
| '''+ '\n'.join(rows)+r''' | |
| \bottomrule\end{tabular} | |
| \caption{Cold-per-batch corridor comparison. CPU values are seconds summed over the same 12,288 completed episodes per method. Setup is charged in every batch.} | |
| \end{table} | |
| ''') | |
| r=read('reinvestment_summary.json')['aggregate'];rows=[] | |
| for key in ['raw','selfloop_skip','compiled']: | |
| x=r[key];rows.append(f"{labels[key]} & {x['mean_candidates']:,.1f} & {x['mean_best_utility']:.9f} & {x['mean_regret']:.7f} \\\\") | |
| (M/'tables_v4_reinvestment.tex').write_text(r'''\begin{table}[htbp]\centering\small | |
| \begin{tabular}{lrrr}\toprule | |
| Method & Mean candidates & Mean best utility & Mean regret\\\midrule | |
| '''+ '\n'.join(rows)+r''' | |
| \bottomrule\end{tabular} | |
| \caption{Setup-paid synthetic search: 20 seeds and 0.08 CPU seconds per method and seed. Regret is measured against the unit upper bound, not a proved attained optimum.} | |
| \end{table} | |
| ''') | |
| print('Generated one plot and two tables from recorded JSON.') | |