| """Explicit publication whitelist, generated summaries and figures.""" |
| from pathlib import Path |
| import json,gzip,shutil,hashlib,platform,importlib.metadata |
| import numpy as np |
| import matplotlib |
| matplotlib.use('Agg') |
| import matplotlib.pyplot as plt |
| R=Path(__file__).resolve().parents[1] |
|
|
| def main(): |
| rows=[json.loads(l) for l in (R/'data/equilibria.jsonl').open()] |
| dataset=R/'release/dataset';model=R/'release/model' |
| for root in [dataset,model]: |
| for d in ['src','tests','reports','assets']: (root/d).mkdir(parents=True,exist_ok=True) |
| for folder in ['src','tests']: |
| for p in (R/folder).glob('*.py'):shutil.copy2(p,root/folder/p.name) |
| for p in (R/'reports').glob('*.json'):shutil.copy2(p,root/'reports'/p.name) |
| for name in ['SCHEMA.md','requirements.txt','LICENSE-CODE','LICENSE-DATA']:shutil.copy2(R/name,root/name) |
| (dataset/'states').mkdir(exist_ok=True) |
| for split in ['train','validation','test','parameter_ood']: |
| with gzip.open(dataset/f'states/{split}.jsonl.gz','wt') as f: |
| for row in rows: |
| if row['split']==split:f.write(json.dumps(row,allow_nan=False,separators=(',',':'))+'\n') |
| (dataset/'validation').mkdir(exist_ok=True) |
| with gzip.open(dataset/'validation/paired_resolution.jsonl.gz','wt') as f:f.write((R/'data/paired_resolution.jsonl').read_text()) |
| (dataset/'validation/rejected_attempts.json').write_text('[]\n') |
| with gzip.open(dataset/'validation/discarded_seed_attempts.jsonl.gz','wt') as f:f.write((R/'data/discarded_seed_attempts.jsonl').read_text()) |
| native=R/'cases/fig9/outputs/003-downward-single-geometry' |
| for folder in ['paraview','xdmf','scientific','figures']: |
| shutil.copytree(native/folder,dataset/'native_fe'/folder,dirs_exist_ok=True) |
| for name in ['native_fe_metrics.csv','paraview_checks.json']:shutil.copy2(native/name,dataset/'native_fe'/name) |
| (dataset/'cases/fig9').mkdir(parents=True,exist_ok=True) |
| for name in ['case.py','paper_reference.py','agentfem.toml']:shutil.copy2(R/'cases/fig9'/name,dataset/'cases/fig9'/name) |
| shutil.copytree(R/'models',model/'models',dirs_exist_ok=True) |
| environment={name:importlib.metadata.version(name) for name in ['numpy','scipy','torch','safetensors','matplotlib','h5py']} |
| environment.update(python=platform.python_version(),platform=platform.platform(),agentfem_commit='36f4c1b06ce8a37988eea50bd139fd2d3513985d') |
| for root in [R,dataset,model]:(root/'reports/environment.json').write_text(json.dumps(environment,indent=2)) |
| plt.rcParams.update({'font.family':'DejaVu Sans','text.color':'#e6efed','axes.labelcolor':'#8fa5a7','xtick.color':'#61777c','ytick.color':'#61777c'}) |
| fig,axes=plt.subplots(1,3,figsize=(15,6),facecolor='#091317') |
| titles=['Driven by force','Programmed curvature','One load. Three branches.'] |
| families=['end_load','intrinsic_curvature','microforce'] |
| for ax,family,title in zip(axes,families,titles): |
| ax.set_facecolor('#091317');ax.set_aspect('equal');ax.set_xlim(-.55,1.1);ax.set_ylim(-1.05,1.05) |
| ax.set_xticks([]);ax.set_yticks([]) |
| for sp in ax.spines.values():sp.set_visible(False) |
| ax.axhline(0,color='#244048',lw=.5);ax.axvline(0,color='#244048',lw=.5) |
| if family=='microforce': |
| chosen=[v for v in rows if v['scene_id']=='microforce_000' and v['step']==16] |
| else: |
| chosen=[v for v in rows if v['family']==family and v['path_kind']=='ramp' and v['step']==24][::5][:12] |
| for i,v in enumerate(chosen): |
| xy=np.array(v['centerline']);color='#e3ac72' if v['branch']=='straight' else '#78d6ca' |
| ax.plot(*xy.T,color=color,alpha=.3+.7*(i+1)/len(chosen),lw=2.2) |
| ax.scatter(*xy[-1],s=12,color=color,zorder=4) |
| ax.scatter(0,0,s=40,color='#f1f5ed',zorder=5) |
| ax.set_title(title,fontsize=13,loc='left',pad=20,color='#eff6f1') |
| fig.text(.055,.93,'AgentFEM / MORPH LAB',color='#78d6ca',fontsize=12,weight='bold') |
| fig.text(.055,.055,'Programmable rods 路 Equilibrium branches 路 Inverse shape design',fontsize=15,color='#f1f5ed') |
| fig.subplots_adjust(top=.82,bottom=.15,wspace=.14,left=.055,right=.97) |
| for root in [dataset,model]:fig.savefig(root/'assets/overview.png',dpi=140,facecolor=fig.get_facecolor()) |
| plt.close(fig) |
| |
| |
| for root in [dataset,model]: |
| hashes={str(p.relative_to(root)):hashlib.sha256(p.read_bytes()).hexdigest() for p in sorted(root.rglob('*')) if p.is_file() and p.name!='SHA256SUMS.json'} |
| (root/'SHA256SUMS.json').write_text(json.dumps(hashes,indent=2)) |
| print('Packaged',len(rows),'states') |
|
|
| if __name__=='__main__':main() |
|
|
