82 lines
4.7 KiB
Python
82 lines
4.7 KiB
Python
#!/usr/bin/env python3
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"""Reuse V1 ideal kernels; compare hypothesis with R3 native reconstruction order.
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CONTRACT: no GLSL/native precision equivalence, FBO contents or causal proof.
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INVARIANT: model prediction is fixed before fitting; no kernel/offset fitting.
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"""
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import ast
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import hashlib
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import json
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import re
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import sys
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from pathlib import Path
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import numpy as np
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from PIL import Image
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lab=Path(sys.argv[1]).resolve()
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fixture=Path(__file__).resolve().parent
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historical=fixture.parent/'step20c-optimized-blur-cache/edge-model.py'
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source=historical.read_text()
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# WHY: reuse the exact reviewed functions without executing the historical writer.
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# CONTRACT: retain only function definitions/imports and W,H constants from its AST.
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module=ast.parse(source)
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selected=[node for node in module.body if isinstance(node,(ast.Import,ast.ImportFrom,ast.FunctionDef))
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or (isinstance(node,ast.Assign) and any(isinstance(t,ast.Tuple) for t in node.targets))]
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context={}
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exec(compile(ast.Module(body=selected,type_ignores=[]),str(historical),'exec'),context)
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rebuild=context['rebuild'];pattern=context['pattern']
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run=lab/'runs/R3'
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lines=(run/'compositor.log').read_text().splitlines()
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commits=[]
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for line in (run/'background.log').read_text().splitlines():
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if line.startswith('CLIENT_COMMIT '):
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commits.append((int(re.search(r'ns=(\d+)',line)[1]),re.search(r'pattern=([AB])',line)[1]))
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rebuilds=[int(re.search(r'ns=(\d+)',line)[1]) for line in lines
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if line.startswith('OPT_GPU_REBUILD ') and 'output=HEADLESS-1' in line]
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ping=np.zeros((600,800,3));pong=ping.copy();states=[]
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for ns in rebuilds:
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current=next((c for t,c in reversed(commits) if t<ns),None)
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image=pattern(current) if current else np.zeros((600,800,3))
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cache=rebuild(image,ping,pong)
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states.append((ns,current,cache))
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events=[json.loads(line) for line in (run/'events.jsonl').read_text().splitlines()]
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metrics={};predictions={};actuals={}
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for event in events:
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if event['kind']!='capture' or event['output']!='HEADLESS-1' or event['tag']=='P0-FX0':continue
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ns,current,cache=next(s for s in reversed(states) if s[0]<event['before_ns'])
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predicted=np.round(cache*(119/255)+[68,32,16])
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actual=np.array(Image.open(run/event['path']).convert('RGB')).astype(float)
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predictions[event['tag']]=predicted;actuals[event['tag']]=actual
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rois={'center':(520,100,720,500),'boundary':(720,50,800,550),
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'physical_right':(750,0,800,600),'glass_bottom':(480,550,800,600)}
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measurements={}
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for name,(l,t,r,b) in rois.items():
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d=np.abs(predicted[t:b,l:r]-actual[t:b,l:r])
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measurements[name]={'mean_abs_channel_error':float(d.mean()),
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'max_channel_error':float(d.max()),'within_one_channel':float((d<=1).mean())}
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metrics[event['tag']]={'source':current,'model_rebuild_ns':ns,'ROIs':measurements}
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distribution={}
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for first,second in [('P1-B-natural','P2-B-explicit'),('P0-FX2','P3-A-natural')]:
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pd=predictions[second]-predictions[first];nd=actuals[second]-actuals[first]
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# Model applies only to the measured glass, not the entire composited source.
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pd[:,:480]=0;pm=np.any(pd!=0,axis=2);nm=np.any(nd!=0,axis=2)
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union=(pm|nm).sum();intersection=(pm&nm).sum()
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disagreement=np.abs(pd-nd)
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distribution[first+' -> '+second]={
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'predicted_changed_pixels_in_visible_glass':int(pm.sum()),'native_changed_pixels':int(nm.sum()),
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'mask_intersection':int(intersection),'mask_union':int(union),
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'mask_jaccard':float(intersection/union) if union else 1,
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'predicted_max_channel':float(np.abs(pd).max()),'native_max_channel':float(np.abs(nd).max()),
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'delta_residual_mean_abs_channel':float(disagreement[:,480:].mean()),
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'predicted_columns':pm.sum(axis=0).astype(int).tolist(),
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'predicted_rows':pm.sum(axis=1).astype(int).tolist(),
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'native_columns':nm.sum(axis=0).astype(int).tolist(),'native_rows':nm.sum(axis=1).astype(int).tolist(),
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'interpretation':'fixed-kernel history compatibility only; native FBO tail and mediump behavior unobserved'}
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(lab/'results/edge-model-comparison.json').write_text(json.dumps({
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'model_source':str(historical),'model_sha256':hashlib.sha256(historical.read_bytes()).hexdigest(),
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'native_schedule':'R3 OPT_GPU_REBUILD timestamps only; no invented timestamps for untraced runs',
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'rebuild_count':len(rebuilds),'metrics':metrics,'distributions':distribution,
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'causality':'NOT DEMONSTRATED; no GPU readback or intervention'},indent=2)+'\n')
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print(json.dumps({'rebuild_count':len(rebuilds),'metrics':metrics,
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'distributions':{k:{n:v for n,v in d.items() if not n.endswith(('columns','rows'))}
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for k,d in distribution.items()}},indent=2))
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