test: add bounded first-failure uniform SRT diagnostic

This commit is contained in:
2026-10-18 02:59:28 -07:00
parent 9805383f9c
commit 8e378aa047
5 changed files with 495 additions and 0 deletions
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unittest.case.FunctionTestCase (test_bounded_state_evidence) ... ok
unittest.case.FunctionTestCase (test_disjoint_complete_categories) ... ok
unittest.case.FunctionTestCase (test_exact_config_and_source) ... ok
unittest.case.FunctionTestCase (test_inactive_nonfinite_does_not_fail) ... ok
unittest.case.FunctionTestCase (test_original_safety_limits) ... ok
unittest.case.FunctionTestCase (test_population_macro_force_separate) ... ok
unittest.case.FunctionTestCase (test_source_guard_and_deadline) ... ok
----------------------------------------------------------------------
Ran 7 tests in 0.039s
OK
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"""Read-only observations of the exact failed SRT control, at most 320 steps.
Default is CPU preflight. Execution requires root admission and an external watchdog.
No solver, initialization, geometry or numerical parameter modifications.
"""
import argparse
import hashlib
import importlib
import json
import math
import os
from pathlib import Path
import sys
import time
from tempfile import TemporaryDirectory
import numpy as np
HERE=Path(__file__).resolve().parent
DEFAULT_SOURCE=HERE.parents[2]
LIMIT_BYTES=128*1024**2
def dump(path,value):
path.write_text(json.dumps(value,indent=2,allow_nan=False))
def number(value):
value=float(value)
return value if math.isfinite(value) else ('NaN' if math.isnan(value) else ('+Inf' if value>0 else '-Inf'))
def source_config(source):
manifest=json.loads((HERE/'source_manifest.json').read_text())
for name,digest in manifest['sha256'].items():
if hashlib.sha256((source/name).read_bytes()).hexdigest()!=digest:
raise ValueError('Pinned source mismatch: '+name)
sys.path.insert(0,str(source/'src')); sys.path.insert(0,str(source/'tests/validation'))
import CelerisLab
if Path(CelerisLab.__file__).resolve()!=source/'src/CelerisLab/__init__.py':
raise ValueError('Wrong CelerisLab import')
runner=importlib.import_module('run_refined_dfg')
if Path(runner.__file__).resolve()!=source/'tests/validation/run_refined_dfg.py':
raise ValueError('Wrong runner import')
h,_=runner.helpers(source)
cfg,body,p=runner.config(h,80) # Exact original config factory, not a reimplementation.
return cfg,body,p,manifest
def categories(flags,p):
"""Disjoint physical categories; subtype nibble is not a bitfield."""
from CelerisLab.lbm.descriptors import FLUID,SOLID,OBSTACLE
y,x=np.indices(flags.shape); fluid=(flags&FLUID)!=0
masks={}; left=fluid.copy()
for name,test in (
('body_near',(x-p['center'][0])**2+(y-p['center'][1])**2 <= (p['radius']+3)**2),
('outlet_near',x>=flags.shape[1]-4),('inlet_near',x<=3),
('wall_near',(y<=3)|(y>=flags.shape[0]-4))):
masks[name]=left&test; left &= ~test
masks['bulk']=left
subtype=flags&0xf0
masks['inlet_ghost']=(~fluid)&(subtype==0x20)
masks['outlet_ghost']=(~fluid)&(subtype==0x30)
masks['wall_ghost']=(~fluid)&(subtype==0x10)
assigned=np.logical_or.reduce(list(masks.values()))
masks['body_solid']=(~assigned)&(((flags&OBSTACLE)!=0)|((flags&SOLID)!=0))
assigned|=masks['body_solid']; masks['other_inactive']=~assigned
return fluid,masks
def finite_extrema(a,mask):
good=mask&np.isfinite(a)
if not good.any(): return dict(min=None,max=None)
idx=np.flatnonzero(good); values=a.ravel()[idx]
lo=int(idx[np.argmin(values)]); hi=int(idx[np.argmax(values)])
return dict(min=float(a.ravel()[lo]),max=float(a.ravel()[hi]),
min_yx=list(map(int,np.unravel_index(lo,a.shape))),
max_yx=list(map(int,np.unravel_index(hi,a.shape))))
def diagnose(g,macro,force,flags,p,step):
fluid,masks=categories(flags,p)
badpop=~np.isfinite(g); badnode=badpop.any(axis=0)
badmacro=np.logical_or.reduce([~np.isfinite(macro[k]) for k in ('rho','ux','uy')])
with np.errstate(over='ignore',invalid='ignore'):
mach=np.sqrt(3*(np.asarray(macro['ux'],np.float64)**2+np.asarray(macro['uy'],np.float64)**2))
rho=macro['rho']
# Exactly the original physical macro/reaction conditions, now sampled each step.
nonfinite_macro=bool(np.any(badmacro&fluid))
force_bad=force is not None and not np.isfinite(force).all()
density_bad=bool(np.any(fluid&((rho<.5)|(rho>1.5))))
mach_bad=bool(np.any(fluid&(mach>.2)))
population_bad=bool(np.any(badnode&fluid))
original_failure=nonfinite_macro or force_bad or density_bad or mach_bad
offending=fluid&(badnode|badmacro|(rho<.5)|(rho>1.5)|(mach>.2))
examples=[]
for y,x in np.argwhere(offending)[:16]:
examples.append(dict(y=int(y),x=int(x),physical_xy_m=[float(x*p['dx']),float((y-.5)*p['dx'])],
category=next(name for name,mask in masks.items() if mask[y,x]),flag=int(flags[y,x]),
nonfinite_q=np.flatnonzero(badpop[:,y,x]).tolist(),
populations=[number(v) for v in g[:,y,x]],
rho=number(rho[y,x]),ux=number(macro['ux'][y,x]),uy=number(macro['uy'][y,x])))
neighborhoods=[]
for node in examples[:4]:
y,x=node['y'],node['x']; y0,y1=max(0,y-2),min(flags.shape[0],y+3); x0,x1=max(0,x-2),min(flags.shape[1],x+3)
neighborhoods.append(dict(bounds_xy=[x0,y0,x1,y1],flags=flags[y0:y1,x0:x1].tolist(),
physical_populations=[[[number(v) for v in row] for row in plane] for plane in g[:,y0:y1,x0:x1]]))
return dict(step=step,tstar=step*p['mean_speed']/p['diameter'],
physical_failure=bool(original_failure or population_bad),
original_health_failure=bool(original_failure),
physical_population_nonfinite=population_bad,physical_macro_nonfinite=nonfinite_macro,
force_nonfinite=bool(force_bad),density_limit=density_bad,mach_limit=mach_bad,
force=None if force is None else [number(v) for v in force],
categories={name:dict(nodes=int(mask.sum()),nonfinite_population_nodes=int((mask&badnode).sum()),
nonfinite_populations=int(badpop[:,mask].sum()),nonfinite_macro_nodes=int((mask&badmacro).sum()))
for name,mask in masks.items()},
rho=finite_extrema(rho,fluid),mach=finite_extrema(mach,fluid),
first_physical_examples=examples,local_neighborhoods=neighborhoods)
def snapshot(sim,p):
# Public physical decode and original production macro path. No host reconstruction
# substitutes for the original health check. get_ddf shares its completed-step cache.
with np.errstate(all='ignore'):
macro={k:np.asarray(v).copy() for k,v in sim.get_macroscopic().items()}
g=sim.get_ddf().reshape(9,p['ny'],p['nx'])
import pycuda.driver as cuda
raw=np.empty_like(g,dtype=np.float32)
with sim.ctx.activate():
cuda.memcpy_dtoh(raw,sim.field.ddf_gpu)
return dict(raw=raw,g=g,macro=macro,step=int(sim.stepper.step_count))
def save_states(dest,previous,current,flags,diagnostic):
"""Two states only; raw shifted bits and decoded observations, no trajectory."""
arrays={'flags':flags}
for name,state in (('previous',previous),('current',current)):
if state is None: continue
arrays[name+'_raw_shifted']=state['raw']
arrays[name+'_physical']=state['g']
arrays[name+'_step']=np.array(state['step'],np.int64)
# At D80, raw+physical for two states ~84 MiB; reserve >4 MiB for JSON/NPZ overhead.
if sum(v.nbytes for v in arrays.values())>LIMIT_BYTES-4*1024**2:
raise ValueError('Evidence arrays exceed bounded artifact budget')
np.savez(dest/'states.npz',**arrays)
dump(dest/'diagnostics.json',diagnostic)
size=sum(p.stat().st_size for p in dest.iterdir() if p.is_file())
if size>LIMIT_BYTES: raise RuntimeError('Evidence directory exceeds 128 MiB')
return size
def deadline_check(deadline):
if time.monotonic()>=deadline: raise TimeoutError('Diagnostic wall ceiling reached')
def execute(a,cfg,body,p):
from CelerisLab.simulation import Simulation
started=time.monotonic(); deadline=started+a.wall_seconds
previous=None; prior_report=None; initial_report=None
with TemporaryDirectory() as temp:
temp=Path(temp); dump(temp/'lbm.json',cfg); dump(temp/'body.json',body)
with Simulation(str(temp/'lbm.json'),str(temp/'body.json'),device_id=0) as sim:
sim.initialize() # Exact original production initialization, unchanged.
flags=sim.get_flags().reshape(p['ny'],p['nx'])
current=snapshot(sim,p)
initial_report=diagnose(current['g'],current['macro'],None,flags,p,0)
report=initial_report; status='initial_physical_failure' if report['physical_failure'] else 'step_cap_reached'
try:
deadline_check(deadline)
if not report['physical_failure']:
for _ in range(320):
deadline_check(deadline)
previous=current; prior_report=report
sim.run(1) # Same solver; observation buffers reset/read once per step.
force=sim.read_force(0).astype(np.float64)
current=snapshot(sim,p)
report=diagnose(current['g'],current['macro'],force,flags,p,current['step'])
if current['step']==1:
print('READY '+json.dumps(dict(step=1,all_observation_paths_exercised=True,
physical_healthy=not report['physical_failure']),allow_nan=False),flush=True)
if report['physical_failure']:
status='first_physical_failure'; break
deadline_check(deadline)
except TimeoutError:
status='wall_time_limit'
details=dict(status=status,executed_steps=int(sim.stepper.step_count),
observation_step=current['step'],previous_observation_step=None if previous is None else previous['step'],
initial=initial_report,preceding=prior_report,current=report,
wall_seconds=time.monotonic()-started,
storage='raw_shifted FP32 is exact active-buffer data; physical is production FP32 decoded G. Both are diagnostic snapshots, not complete restart checkpoints.',
health_scope='Physical FLUID nodes and force only; ghost/body categories cannot independently trigger physical failure.',
interpretation='Near-region labels locate symptoms, not the root cause. Per-step inspection changes observation cadence only. No physical acceptance.')
size=save_states(a.output,previous,current,flags,details)
print(json.dumps(dict(status=status,executed_steps=int(sim.stepper.step_count),evidence_bytes=size),allow_nan=False),flush=True)
return 0 if status=='step_cap_reached' else 2
def main():
parser=argparse.ArgumentParser(description=__doc__)
parser.add_argument('--source',type=Path,default=DEFAULT_SOURCE)
parser.add_argument('--output',type=Path,required=True)
parser.add_argument('--execute',action='store_true')
parser.add_argument('--gpu-admitted',action='store_true')
parser.add_argument('--wall-seconds',type=float)
a=parser.parse_args(); a.source=a.source.resolve()
cfg,body,p,manifest=source_config(a.source)
if a.output.exists() and any(a.output.iterdir()): raise ValueError('Use a new/empty output directory')
if a.execute and (not a.gpu_admitted or not os.environ.get('CUDA_VISIBLE_DEVICES') or
a.wall_seconds is None or not math.isfinite(a.wall_seconds) or a.wall_seconds<=0):
raise ValueError('Explicit root admission, device selection and finite wall ceiling required')
a.output.mkdir(parents=True,exist_ok=True)
dump(a.output/'preflight.json',dict(source=manifest,config=cfg,body=body,parameters=p,
diagnostic_sha256=hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),max_steps=320,
max_evidence_bytes=LIMIT_BYTES,executed=False))
if not a.execute: return 0
return execute(a,cfg,body,p)
if __name__=='__main__': raise SystemExit(main())
@@ -0,0 +1,112 @@
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}
}
@@ -0,0 +1,100 @@
"""CPU-only synthetic diagnostic and source-contract tests; no simulation results."""
import json
from pathlib import Path
import sys
from tempfile import TemporaryDirectory
import unittest
import numpy as np
sys.path.insert(0,str(Path(__file__).resolve().parent))
import diagnose_uniform_srt as d
cfg,body,p,manifest=d.source_config(d.DEFAULT_SOURCE)
def fixture():
flags=np.ones((12,20),np.uint16)
flags[:,0]=2|0x20; flags[:,-1]=2|0x30
flags[[0,-1]]=2|0x10; flags[5,6]=2|0x40|0x200
g=np.full((9,12,20),1/9,np.float32)
macro=dict(rho=np.ones((12,20)),ux=np.zeros((12,20)),uy=np.zeros((12,20)))
params=dict(center=[6,5],radius=1,dx=.1,mean_speed=.01,diameter=80)
return g,macro,flags,params
def test_exact_config_and_source():
assert manifest['commit']=='9805383f9c50d867e8555471baf5dbda8333a652'
assert p['diameter']==80 and p['mean_speed']==.01 and p['nx']==1761 and p['ny']==330
assert cfg['method']['collision']=='SRT' and cfg['method']['ddf_shifting']
assert cfg['method']['outlet']['srt_neq_damp']==.5
assert np.isclose(3*p['viscosity']+.5,.524)
assert body['objects'][0]['center']==[160,160.5]
def test_inactive_nonfinite_does_not_fail():
g,m,f,p=fixture(); fluid,_=d.categories(f,p)
g[:,~fluid]=np.nan
for a in m.values(): a[~fluid]=np.nan
r=d.diagnose(g,m,np.zeros(2),f,p,1)
assert not r['physical_failure']
assert r['categories']['body_solid']['nonfinite_population_nodes']==1
assert r['categories']['outlet_ghost']['nodes']==10
assert r['categories']['inlet_ghost']['nodes']==10
json.dumps(r,allow_nan=False)
def test_population_macro_force_separate():
g,m,f,p=fixture(); g[4,6,17]=np.inf
r=d.diagnose(g,m,np.zeros(2),f,p,27)
assert r['physical_failure'] and r['physical_population_nonfinite']
assert not r['original_health_failure'] and not r['force_nonfinite']
assert r['first_physical_examples'][0]['category']=='outlet_near'
assert r['first_physical_examples'][0]['nonfinite_q']==[4]
assert r['first_physical_examples'][0]['populations'][4]=='+Inf'
json.dumps(r,allow_nan=False)
g,m,f,p=fixture(); m['ux'][6,10]=np.nan
r=d.diagnose(g,m,np.zeros(2),f,p,28)
assert r['physical_macro_nonfinite'] and not r['physical_population_nonfinite']
assert not r['force_nonfinite'] and r['original_health_failure']
g,m,f,p=fixture(); r=d.diagnose(g,m,np.array([np.nan,0]),f,p,29)
assert r['force_nonfinite'] and not r['physical_macro_nonfinite']
assert not r['first_physical_examples']
def test_original_safety_limits():
g,m,f,p=fixture(); m['rho'][5,7]=.49
r=d.diagnose(g,m,[0,0],f,p,1)
assert r['density_limit'] and r['first_physical_examples'][0]['category']=='body_near'
g,m,f,p=fixture(); m['ux'][6,10]=.2
assert d.diagnose(g,m,[0,0],f,p,1)['mach_limit']
def test_disjoint_complete_categories():
_,_,f,p=fixture(); fluid,masks=d.categories(f,p)
np.testing.assert_array_equal(sum(mask.astype(int) for mask in masks.values()),np.ones(f.shape))
physical=sum(masks[k].astype(int) for k in ('body_near','inlet_near','outlet_near','wall_near','bulk'))
np.testing.assert_array_equal(physical,fluid.astype(int))
def test_bounded_state_evidence():
g,m,f,p=fixture(); state=dict(raw=g.copy(),g=g,macro=m,step=1)
with TemporaryDirectory() as tmp:
dest=Path(tmp); size=d.save_states(dest,state,state,f,{'status':'synthetic_test'})
assert size<d.LIMIT_BYTES
with np.load(dest/'states.npz') as saved:
np.testing.assert_array_equal(saved['previous_raw_shifted'],g)
np.testing.assert_array_equal(saved['current_physical'],g)
assert sorted(x.name for x in dest.iterdir())==['diagnostics.json','states.npz']
actual_bytes=4*(9*330*1761*4)+(330*1761*2)+16
assert actual_bytes<d.LIMIT_BYTES-4*1024**2
def test_source_guard_and_deadline():
with TemporaryDirectory() as tmp:
with unittest.TestCase().assertRaises((ValueError,FileNotFoundError)):
d.source_config(Path(tmp))
with unittest.TestCase().assertRaises(TimeoutError): d.deadline_check(0)
if __name__=='__main__':
result=unittest.TextTestRunner(verbosity=2).run(unittest.TestSuite(
unittest.FunctionTestCase(fn) for name,fn in sorted(globals().items()) if name.startswith('test_')))
raise SystemExit(not result.wasSuccessful())