476 lines
33 KiB
Python
476 lines
33 KiB
Python
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#!/usr/bin/env python3
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"""Read completed/partial pressure diagnostics; never launch a solver or modify inputs."""
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import argparse
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import csv
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import json
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import math
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent
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ITERATIONS = (2, 3, 4, 7, 11)
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def rows(path):
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if not path.exists():
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return []
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with path.open() as stream:
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return [r for r in csv.DictReader(stream) if None not in r and all(v is not None for v in r.values())]
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def metrics(path):
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return {r['metric']: float(r['value']) for r in rows(path)}
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def metadata(path):
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if not path.exists():
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return {}
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return dict(line.split('=', 1) for line in path.read_text().splitlines() if '=' in line)
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def numeric(row):
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result = {}
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for key, value in row.items():
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try:
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result[key] = float(value)
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except ValueError:
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result[key] = value
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return result
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def negative_h_rejection(row):
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# Enums at source9e1b65d: thermodynamic_domain=2, pressure_force=6,
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# outside_domain=5. The prepared pressure operator emits this for h<0.
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return all(float(row.get(k, -999)) == v for k, v in
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[('admissible', 0), ('reason', 2), ('stage', 6), ('eos_code', 5)])
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def sanitize(value):
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if isinstance(value, float) and not math.isfinite(value):
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return None
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if isinstance(value, dict):
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return {k: sanitize(v) for k, v in value.items()}
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if isinstance(value, list):
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return [sanitize(v) for v in value]
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return value
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def case(iteration):
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folder = ROOT / 'focused' / f'n1_J0p10_iteration_{iteration}'
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capture = metadata(ROOT / 'captures/n1_J0p10_capture' / f'capture_{iteration}/capture.txt')
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bound = metrics(folder / 'frozen_enthalpy_bound.csv')
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inputs = metrics(folder / 'frozen_input_checks.csv')
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replay = rows(folder / 'replayed_candidate.csv')
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trial_rows = rows(folder / 'pressure_obstruction_trials.csv')
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limits = [numeric(r) for r in rows(folder / 'pressure_obstruction_limits.csv')]
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summary = metrics(folder / 'pressure_obstruction_summary.csv')
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live = next((r for r in rows(ROOT / 'captures/n1_J0p10_capture/newton.csv')
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if int(r['iteration']) == iteration), None)
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result = {'iteration': iteration, 'folder': str(folder), 'capture': capture,
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'bounds': bound, 'input_checks': inputs, 'limits': limits,
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'exact_candidate': numeric(replay[0]) if replay else None,
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'exact_candidate_confirms_pressure_negative_h': negative_h_rejection(replay[0]) if replay else None,
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'restoration_completed': 'final_restoration_residual_difference' in inputs,
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'pressure_trials_completed': len(trial_rows),
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'pressure_trials_expected': summary.get('candidate_trial_count'),
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'trial_checks': [], 'live_newton_step': numeric(live) if live else None}
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result['pressure_grid_complete'] = (summary.get('candidate_trial_count') is not None and
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len(trial_rows) == summary['candidate_trial_count'])
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if capture:
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result['direction_roundoff_relative_estimate'] = (
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float(capture['direction_roundoff_scale_estimate']) / float(capture['direction_norm']))
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if bound:
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result['closure_to_pressure_bound_ratio'] = bound['closure_alpha_h'] / bound['pressure_alpha_h']
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result['exact_first_trial_over_pressure_bound'] = float(capture['first_trial_alpha']) / bound['pressure_alpha_h']
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if live:
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result['accepted_alpha_over_union_bound'] = float(live['alpha']) / bound['alpha_thermodynamic']
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result['tightest_sampled_family'] = ('closure' if bound['closure_alpha_h'] < bound['pressure_alpha_h'] else
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'pressure' if bound['pressure_alpha_h'] < bound['closure_alpha_h'] else 'tie')
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midpoint = .5 * (bound['closure_alpha_h'] + bound['pressure_alpha_h'])
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result['between_bounds_midpoint'] = {
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'alpha': midpoint,
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'closure_limiting_h_prediction': bound['limiting_h'] + midpoint * bound['limiting_dh'],
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'pressure_limiting_h_prediction': bound['pressure_limiting_h'] + midpoint * bound['pressure_limiting_dh'],
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}
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for row in trial_rows:
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r = numeric(row)
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errors = [abs(r[f'{family}_limiting_h_evaluated'] - r[f'{family}_limiting_h_prediction'])
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for family in ('pressure', 'closure')]
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sign_checks = [((r[f'{family}_limiting_h_evaluated'] < 0) ==
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(r[f'{family}_limiting_h_prediction'] < 0)) for family in ('pressure', 'closure')]
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ratio = r['alpha_over_union_bound']
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r['maximum_limiting_h_evaluation_prediction_absolute_difference'] = max(errors)
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r['both_limiting_point_signs_match_prediction'] = all(sign_checks)
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r['confirms_pressure_negative_h'] = negative_h_rejection(row)
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# Descriptive expectation check for these fixed cases, not a general
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# assertion that h>=0 guarantees preparation or merit acceptance.
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expected = (r['direction'] == 'shape_only' or ratio < 1)
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r['admissibility_matches_enthalpy_only_prediction'] = bool(r['admissible']) == expected
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result['trial_checks'].append(r)
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if trial_rows:
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result['all_limiting_sign_predictions_match'] = all(r['both_limiting_point_signs_match_prediction']
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for r in result['trial_checks'])
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result['all_admissibility_matches_enthalpy_only_prediction'] = all(
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r['admissibility_matches_enthalpy_only_prediction'] for r in result['trial_checks'])
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result['mapping_rejections'] = sum(r['admissible'] == 0 and r['reason'] in (0, 1)
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for r in result['trial_checks'])
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result['maximum_limiting_h_absolute_disagreement'] = max(
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r['maximum_limiting_h_evaluation_prediction_absolute_difference'] for r in result['trial_checks'])
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shape_rows = [r for r in result['trial_checks'] if r['direction'] == 'shape_only']
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h_crossing_rows = [r for r in result['trial_checks']
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if r['direction'] == 'enthalpy_only' and r['alpha_over_union_bound'] > 1]
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result['shape_only_all_prepared'] = all(r['admissible'] == 1 for r in shape_rows) if len(shape_rows) == 4 else None
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result['enthalpy_only_crossing_failures_all_pressure_negative_h'] = (
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all(r['confirms_pressure_negative_h'] for r in h_crossing_rows) if len(h_crossing_rows) == 2 else None)
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return result
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def fmt(value):
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return 'pending' if value is None else f'{value:.9g}'
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def vector_entries(path, indices):
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"""Read only selected zero-based entries; reject an incompatible saved vector."""
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if not path.exists():
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return None
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selected = set(indices)
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found = {}
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with path.open() as stream:
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size = int(next(stream).strip())
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if not selected or min(selected) < 0 or max(selected) >= size:
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raise ValueError(f'Carrier indices incompatible with {path}')
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count = 0
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for index, line in enumerate(stream):
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value = float(line)
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count += 1
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if index in selected:
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found[index] = value
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if count != size or len(found) != len(selected):
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raise ValueError(f'Incomplete vector {path}')
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return [found[index] for index in indices]
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def extrema(values):
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return {'count': len(values), 'minimum': min(values), 'maximum': max(values),
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'maximum_absolute': max(abs(x) for x in values),
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'l2_norm': math.sqrt(math.fsum(x*x for x in values)),
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'negative_count': sum(x < 0 for x in values),
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'nonzero_count': sum(x != 0 for x in values)}
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def supplemental(cases):
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"""Find the two supplemental case IDs without imposing an output-parent name."""
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result = {'cases': [], 'offline_surface_checks': []}
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case_ids = [('n1_J0p10_onset_between_bounds', 2), ('n1_J0p10_late_surface_trace', 11)]
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reference_rows = None
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for name, iteration in case_ids:
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candidates = [path.parent for path in ROOT.glob(f'**/{name}/surface_trace_summary.csv')]
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if len(candidates) > 1:
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raise ValueError(f'Ambiguous duplicate supplemental case: {name}')
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if not candidates:
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result['cases'].append({'id': name, 'iteration': iteration, 'available': False})
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continue
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folder = candidates[0]
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carrier_rows = [numeric(r) for r in rows(folder / 'surface_trace_rows.csv')]
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summary = metrics(folder / 'surface_trace_summary.csv')
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if 'pressure_alpha_h' not in summary:
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result['cases'].append({'id': name, 'iteration': iteration, 'available': False})
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continue
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contribution_rows = [numeric(r) for r in rows(folder / 'surface_trace_limits.csv')]
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node_rows = [numeric(r) for r in rows(folder / 'surface_trace_nodes.csv')]
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replay_rows = rows(folder / 'replayed_candidate.csv')
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source_case = next(c for c in cases if c['iteration'] == iteration)
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details = {'id': name, 'iteration': iteration, 'available': True, 'folder': str(folder),
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'summary': summary, 'contributions': contribution_rows,
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'replayed_candidate': numeric(replay_rows[0]) if replay_rows else None,
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'carrier_rows_complete': len(carrier_rows) == summary.get('surface_row_count'),
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'nodal_checks': [],
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'restoration': metrics(folder / 'frozen_input_checks.csv')}
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provenance = folder.parent / 'provenance.json'
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if provenance.exists():
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p = json.loads(provenance.read_text())
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details['provenance'] = {key: p.get(key) for key in ('commit', 'branch', 'mesh_sha256')}
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if carrier_rows and details['carrier_rows_complete']:
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indices = [int(r['root_index']) for r in carrier_rows]
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if len(set(indices)) != len(indices):
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raise ValueError(f'Duplicate surface indices in {folder}')
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if reference_rows is not None and indices != reference_rows:
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raise ValueError('Supplemental surface carrier maps differ')
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reference_rows = indices
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for family in ('closure', 'pressure'):
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nodal = [r for r in node_rows if r['family'] == family]
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if not nodal:
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continue
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if len(nodal) != nodal[0]['node_count']:
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continue # A live CSV may not yet have all nodal rows.
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union = nodal[0]['alpha_union']
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factors = [('base', 0), ('near_below_union', .99*union),
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('near_above_union', 1.01*union), ('unit_step', 1)]
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if source_case['capture']:
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factors.append(('captured_first_alpha', float(source_case['capture']['first_trial_alpha'])))
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if source_case['live_newton_step']:
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factors.append(('accepted_alpha', source_case['live_newton_step']['alpha']))
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scale = max(abs(r[k]) for r in nodal for k in ('h', 'dh'))
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tolerance = 64 * math.ulp(1.0) * scale
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limit = next((r for r in contribution_rows if r['family'] == family), None)
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if limit is None:
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continue
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for label, alpha in factors:
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values = [r['h'] + alpha*r['dh'] for r in nodal]
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stats = extrema(values)
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stats.update({'family': family, 'element': nodal[0]['element'], 'fe_order': nodal[0]['fe_order'],
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'label': label, 'alpha': alpha, 'roundoff_scale_estimate': tolerance,
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'negative_beyond_roundoff_count': sum(v < -tolerance for v in values),
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'limiting_point_h': limit['full_h'] + alpha*limit['full_dh']})
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details['nodal_checks'].append(stats)
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if name.endswith('between_bounds') and details['replayed_candidate']:
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r = details['replayed_candidate']
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details['replay_confirms_closure_outside_domain'] = all(r.get(k) == v for k, v in
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[('admissible', 0), ('reason', 2), ('stage', 3), ('eos_code', 5)])
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details['candidate_derivation'] = json.loads((ROOT / 'supplemental_inputs/between_bounds_derivation.json').read_text())
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result['cases'].append(details)
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if reference_rows is not None:
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result['surface_root_indices'] = reference_rows
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for c in cases:
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folder = ROOT / 'captures/n1_J0p10_capture' / f"capture_{c['iteration']}"
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base = vector_entries(folder / 'physical_base.txt', reference_rows)
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candidate = vector_entries(folder / 'physical_candidate.txt', reference_rows)
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if base is None or candidate is None:
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continue
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alpha = float(c['capture']['first_trial_alpha'])
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dh = [(v-b)/alpha for b, v in zip(base, candidate)]
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result['offline_surface_checks'].append({'iteration': c['iteration'], 'first_trial_alpha': alpha,
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'base_h': extrema(base), 'exact_candidate_h': extrema(candidate),
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'reconstructed_direction_dh': extrema(dh),
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'base_and_exact_candidate_entire_surface_identically_zero': all(v == 0 for v in base + candidate)})
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return result
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def main():
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global ROOT
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('campaign_root', nargs='?', type=Path, default=ROOT,
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help='Campaign artifact directory (default: directory containing this script).')
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ROOT = parser.parse_args().campaign_root.expanduser().resolve()
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if not ROOT.is_dir():
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parser.error(f'Campaign directory does not exist: {ROOT}')
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cases = [case(i) for i in ITERATIONS]
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transitions = []
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for first, second in zip(cases, cases[1:]):
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if second['iteration'] != first['iteration'] + 1 or not first['bounds'] or not second['bounds']:
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continue
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alpha = first['live_newton_step']['alpha']
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for family, prefix in [('closure', ''), ('pressure', 'pressure_')]:
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b, c = first['bounds'], second['bounds']
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same = all(b[prefix + key] == c[prefix + key] for key in ['limiting_element', 'limiting_point'])
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predicted = b[prefix + 'limiting_h'] + alpha * b[prefix + 'limiting_dh']
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observed = c[prefix + 'limiting_h']
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transitions.append({'from_iteration': first['iteration'], 'to_iteration': second['iteration'],
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'family': family, 'same_limiting_point': same, 'accepted_alpha': alpha,
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'predicted_next_h': predicted, 'observed_next_h': observed,
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'absolute_disagreement': abs(predicted - observed) if same else None})
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supplements = supplemental(cases)
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provenance_file = ROOT / 'focused/provenance.json'
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source_revision = json.loads(provenance_file.read_text()).get('commit', '9e1b65d') if provenance_file.exists() else '9e1b65d'
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report = {'schema_version': 2, 'source_revision': source_revision,
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'interpretation': 'Exact candidate replay is authoritative; direction probes include reconstruction roundoff.',
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'cases': cases, 'consecutive_captured_step_checks': transitions, 'supplemental': supplements}
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polynomial_path = ROOT / 'pressure_polynomial_checks.json'
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polynomial = json.loads(polynomial_path.read_text()) if polynomial_path.exists() else None
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if polynomial:
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report['offline_polynomial_artifacts'] = ['pressure_polynomial_checks.json', 'pressure_polynomial_analysis.md']
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(ROOT / 'pressure_checks.json').write_text(json.dumps(sanitize(report), indent=2, allow_nan=False) + '\n')
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lines = ['# Pressure obstruction analysis', '',
|
|||
|
|
'Read-only analysis of the frozen n=1, J=.1 direction captures. This script launches no solver and does not modify case data. '
|
|||
|
|
f'The original focused source is {source_revision}; iteration numbers are zero-based. '
|
|||
|
|
'Supplemental source revisions are recorded per case in pressure_checks.json. Partial cases are explicitly pending.', '',
|
|||
|
|
'| Iteration | Exact first alpha | Pressure bound | Closure bound | Limiting pressure h | dh | Element / point | Exact replay |',
|
|||
|
|
'|---:|---:|---:|---:|---:|---:|---|---|']
|
|||
|
|
for c in cases:
|
|||
|
|
b = c['bounds']
|
|||
|
|
loc = f"{int(b['pressure_limiting_element'])} / {int(b['pressure_limiting_point'])}" if b else 'pending'
|
|||
|
|
replay = ('pressure negative h' if c['exact_candidate_confirms_pressure_negative_h'] else
|
|||
|
|
('other; inspect JSON' if c['exact_candidate'] else 'pending'))
|
|||
|
|
alpha = float(c['capture']['first_trial_alpha']) if c['capture'] else None
|
|||
|
|
lines.append(f"| {c['iteration']} | {fmt(alpha)} | {fmt(b.get('pressure_alpha_h'))} | "
|
|||
|
|
f"{fmt(b.get('closure_alpha_h'))} | {fmt(b.get('pressure_limiting_h'))} | "
|
|||
|
|
f"{fmt(b.get('pressure_limiting_dh'))} | {loc} | {replay} |")
|
|||
|
|
if all(c['exact_candidate_confirms_pressure_negative_h'] for c in cases):
|
|||
|
|
lines += ['', '**All five exact saved first candidates reproduce finite negative enthalpy in pressure preparation.** '
|
|||
|
|
'These failures are thermodynamic-domain rejections, not geometry rejections. The saved candidates are '
|
|||
|
|
'replayed directly, so this conclusion does not depend on reconstructing the Newton direction.']
|
|||
|
|
populated = [c for c in cases if c['bounds']]
|
|||
|
|
if populated:
|
|||
|
|
lines += ['', 'The family attaining the smaller sampled bound is ' + ', '.join(
|
|||
|
|
f"iteration {c['iteration']}: {c['tightest_sampled_family']}" for c in populated) + '.', '',
|
|||
|
|
'| Iteration | Live accepted alpha | Accepted alpha / union bound |', '|---:|---:|---:|']
|
|||
|
|
for c in populated:
|
|||
|
|
lines.append(f"| {c['iteration']} | {fmt(c['live_newton_step']['alpha'])} | {fmt(c['accepted_alpha_over_union_bound'])} |")
|
|||
|
|
if cases[-1]['bounds'] and cases[0]['bounds']:
|
|||
|
|
first, last = cases[0]['bounds'], cases[-1]['bounds']
|
|||
|
|
lines += ['', f"From iteration 2 to 11 the pressure bound shrinks by "
|
|||
|
|
f"{first['pressure_alpha_h']/last['pressure_alpha_h']:.6g} times. The limiting pressure sample remains "
|
|||
|
|
f"element {int(last['pressure_limiting_element'])}, point {int(last['pressure_limiting_point'])}; "
|
|||
|
|
'its h approaches zero while dh remains negative. '
|
|||
|
|
f"At iteration 11 the closure bound is {last['closure_alpha_h']/last['pressure_alpha_h']:.6g} times larger. "
|
|||
|
|
'The mechanism of the step-length collapse is established along these directions; why the Newton '
|
|||
|
|
'directions continue to decrease this h remains unresolved.']
|
|||
|
|
if transitions:
|
|||
|
|
maximum = max(r['absolute_disagreement'] for r in transitions if r['absolute_disagreement'] is not None)
|
|||
|
|
lines += ['', f"For consecutive captured states at the same limiting point, h_next = h + alpha_accepted*dh "
|
|||
|
|
f"agrees with the independently scanned next base to at most {maximum:.3g} absolute. "
|
|||
|
|
'The pointwise approach to the enthalpy boundary is therefore directly tied to the accepted steps.']
|
|||
|
|
lines += ['', '## Crossing controls', '',
|
|||
|
|
'| Iteration | Candidate rows / expected | Shape-only all prepared | h-only crossing rejects negative h | Geometry rejections | Max h prediction/evaluation difference | Restored |',
|
|||
|
|
'|---:|---:|---|---|---:|---:|---|']
|
|||
|
|
for c in cases:
|
|||
|
|
if c['iteration'] not in (2, 11):
|
|||
|
|
continue
|
|||
|
|
lines.append(f"| {c['iteration']} | {c['pressure_trials_completed']} / {fmt(c['pressure_trials_expected'])} | "
|
|||
|
|
f"{c.get('shape_only_all_prepared') if c.get('shape_only_all_prepared') is not None else 'pending'} | "
|
|||
|
|
f"{c.get('enthalpy_only_crossing_failures_all_pressure_negative_h') if c.get('enthalpy_only_crossing_failures_all_pressure_negative_h') is not None else 'pending'} | "
|
|||
|
|
f"{c.get('mapping_rejections', 'pending')} | {fmt(c.get('maximum_limiting_h_absolute_disagreement'))} | "
|
|||
|
|
f"{c['restoration_completed']} |")
|
|||
|
|
onset = cases[0]
|
|||
|
|
if onset['bounds']:
|
|||
|
|
b = onset['bounds']
|
|||
|
|
midpoint = onset['between_bounds_midpoint']
|
|||
|
|
midpoint_case = next(c for c in supplements['cases'] if c['iteration'] == 2)
|
|||
|
|
measured_midpoint = midpoint_case.get('replay_confirms_closure_outside_domain')
|
|||
|
|
midpoint_outcome = ('The supplemental candidate reproduces thermodynamic-domain rejection at the closure stage '
|
|||
|
|
'(reason=2, stage=3, EOS code=5), confirming pressure preparation passes at this alpha before closure fails.'
|
|||
|
|
if measured_midpoint is True else
|
|||
|
|
'The supplemental replay has a different outcome; inspect pressure_checks.json.'
|
|||
|
|
if measured_midpoint is False else
|
|||
|
|
'Its production outcome is pending; the supplemental replay can separate closure from pressure.')
|
|||
|
|
lines += ['', '## Onset interpretation', '',
|
|||
|
|
f"The onset has a tighter **{onset['tightest_sampled_family']}** bound: closure {b['closure_alpha_h']:.12g}, "
|
|||
|
|
f"pressure {b['pressure_alpha_h']:.12g}. The original alpha=1 trial crosses both. "
|
|||
|
|
'Pressure is prepared before closure, so the recorded pressure-stage rejection identifies the first failing stage at that alpha; '
|
|||
|
|
'it does not establish the pressure quadrature as the tightest restriction.', '',
|
|||
|
|
f"A midpoint alpha={midpoint['alpha']:.12g} predicts closure h="
|
|||
|
|
f"{midpoint['closure_limiting_h_prediction']:.9g} and pressure h="
|
|||
|
|
f"{midpoint['pressure_limiting_h_prediction']:.9g} at the respective limiting points. "
|
|||
|
|
'This midpoint is outside the original probe grid. ' + midpoint_outcome, '']
|
|||
|
|
populated_limits = [c for c in cases if c['limits']]
|
|||
|
|
if populated_limits:
|
|||
|
|
lines += ['', '## Limiting-point locations', '',
|
|||
|
|
'| Iteration | Family | Surface-adjacent element | Reference radius | Physical base (x, y, z) |',
|
|||
|
|
'|---:|---|---|---:|---|']
|
|||
|
|
for c in populated_limits:
|
|||
|
|
for r in c['limits']:
|
|||
|
|
xyz = ', '.join(fmt(r[f'physical_{d}']) for d in 'xyz')
|
|||
|
|
lines.append(f"| {c['iteration']} | {r['family']} | {int(r['element'])}; "
|
|||
|
|
f"{bool(r['element_touches_stellar_surface'])} | {fmt(r['reference_radius'])} | ({xyz}) |")
|
|||
|
|
lines += ['', '## Surface trace is an enforced equation', '',
|
|||
|
|
'The runtime isobaric condition is not absent merely because the field registry has no essential constraint. '
|
|||
|
|
'The root constructs an enthalpy boundary map on StellarSurface (prepared_stellar_equilibrium.cpp:407), '
|
|||
|
|
'replaces surface hydrostatic residual rows (lines 809–810), and replaces their Jacobian rows (904–908). '
|
|||
|
|
'The compiled constraint is h−h(P_surface), with identity h Jacobian for fixed pressure '
|
|||
|
|
'(surface/compiled.cppm:47–59). At P_surface=0 the polytropic EOS gives h=0. '
|
|||
|
|
'The radial seed explicitly sets these boundary coefficients to zero '
|
|||
|
|
'(seed/stellar_equilibrium_projection.cppm:203–208).', '',
|
|||
|
|
'This is algebraic enforcement, not a per-trial coefficient projection. Source inspection alone does not '
|
|||
|
|
'establish exact zero in every captured iterate under an inexact linear solve. Even a zero polynomial '
|
|||
|
|
'boundary trace does not guarantee nonnegative enthalpy within the adjacent high-order element. '
|
|||
|
|
'The observed near-surface wall therefore does not establish a missing boundary condition or interpolation '
|
|||
|
|
'as the cause of the Newton direction.']
|
|||
|
|
trace_cases = [c for c in supplements['cases'] if c['available']]
|
|||
|
|
if trace_cases:
|
|||
|
|
lines += ['', '## Supplemental surface carrier and nodal checks', '',
|
|||
|
|
'The actual surface carrier indices come from GetPressureSurfaceRows(), then select entries in each '
|
|||
|
|
'saved physical state. Boundary-only fields retain those coefficients and zero every other enthalpy '
|
|||
|
|
'coefficient; evaluating this field at a limiting interior point gives the boundary contribution to '
|
|||
|
|
'that polynomial value, not a separate trace sample on the stellar surface.', '',
|
|||
|
|
'| Iteration | Carrier rows | Base max abs h | Direction max abs dh | Unit-step max abs h |',
|
|||
|
|
'|---:|---:|---:|---:|---:|']
|
|||
|
|
for c in trace_cases:
|
|||
|
|
m = c['summary']
|
|||
|
|
lines.append(f"| {c['iteration']} | {fmt(m.get('surface_row_count'))} | {fmt(m.get('base_h_maximum_absolute'))} | "
|
|||
|
|
f"{fmt(m.get('direction_dh_maximum_absolute'))} | {fmt(m.get('h_plus_dh_maximum_absolute'))} |")
|
|||
|
|
offline = supplements['offline_surface_checks']
|
|||
|
|
if len(offline) == len(ITERATIONS) and all(c['base_and_exact_candidate_entire_surface_identically_zero'] for c in offline):
|
|||
|
|
lines += ['', '**All actual surface enthalpy coefficients are exactly zero in all five saved bases and all '
|
|||
|
|
'five exact first candidates.** Their reconstructed boundary directions are therefore also zero. '
|
|||
|
|
'Boundary-row leakage is ruled out for these captured directions, independently of the inexact '
|
|||
|
|
'linear-solve possibility from source inspection.']
|
|||
|
|
else:
|
|||
|
|
lines += ['', 'Offline surface checks (including nonzero and negative counts) are recorded per capture in '
|
|||
|
|
'pressure_checks.json; inspect them before inferring exact trace enforcement in captured states.']
|
|||
|
|
lines += ['', '| Iteration | Family | Full h | Boundary contribution h | Full dh | Boundary contribution dh |',
|
|||
|
|
'|---:|---|---:|---:|---:|---:|']
|
|||
|
|
for c in trace_cases:
|
|||
|
|
for r in c['contributions']:
|
|||
|
|
lines.append(f"| {c['iteration']} | {r['family']} | {fmt(r['full_h'])} | {fmt(r['boundary_h'])} | "
|
|||
|
|
f"{fmt(r['full_dh'])} | {fmt(r['boundary_dh'])} |")
|
|||
|
|
lines += ['', 'Full physical fields are scattered through the production field adapter, then evaluated at FE '
|
|||
|
|
'GetNodes() coordinates. These values do not assume that raw signed local DOF indices are nodal values. '
|
|||
|
|
'The same element is intentionally exported separately for each limiting rule family.', '',
|
|||
|
|
'| Iteration | Family | Step | Nodal minimum h | Negative nodes | Limiting interior-point h |',
|
|||
|
|
'|---:|---|---|---:|---:|---:|']
|
|||
|
|
for c in trace_cases:
|
|||
|
|
for r in c['nodal_checks']:
|
|||
|
|
if r['label'] in ('base', 'near_above_union', 'unit_step'):
|
|||
|
|
lines.append(f"| {c['iteration']} | {r['family']} | {r['label']} | {fmt(r['minimum'])} | "
|
|||
|
|
f"{r['negative_count']} | {fmt(r['limiting_point_h'])} |")
|
|||
|
|
undershoots = [(c['iteration'], r['family']) for c in trace_cases for r in c['nodal_checks']
|
|||
|
|
if r['label'] == 'near_above_union' and r['minimum'] >= 0 and r['limiting_point_h'] < 0]
|
|||
|
|
if undershoots:
|
|||
|
|
lines += ['', 'At 1.01 times the union bound, nonnegative values at every FE node coexist with negative '
|
|||
|
|
'enthalpy at the limiting interior point in ' + ', '.join(f'iteration {i} {family}' for i, family in undershoots) +
|
|||
|
|
'. This demonstrates an interior polynomial undershoot in these trial directions. It does not '
|
|||
|
|
'establish an interpolation implementation error or explain why Newton selects this direction.']
|
|||
|
|
lines += ['', 'Nodal nonnegativity is not a certificate of positivity between nodes. The JSON includes strict '
|
|||
|
|
'negative counts and a separate 64-epsilon times nodal-value-scale estimate, which is descriptive '
|
|||
|
|
'rather than a certified rounding bound. Equality exactly at the union bound is deliberately not '
|
|||
|
|
'used to decide a crossing. The production quadrature union bound also does not certify positivity '
|
|||
|
|
'at unsampled points; these results do not establish the minimum enthalpy over an entire element.']
|
|||
|
|
if polynomial:
|
|||
|
|
lines += ['', '## Offline interior polynomial check', '',
|
|||
|
|
'A separate independently validated tensor-Q3 reconstruction samples 495,264 strictly interior '
|
|||
|
|
'reference points in each exported limiting element, including logarithmic distances to its zero '
|
|||
|
|
'face. It reconstructs all 64 nodes exactly and both production limit points to roundoff.']
|
|||
|
|
for c in polynomial['cases']:
|
|||
|
|
minimum = c['sampled_extrema']['base']['minimum']
|
|||
|
|
if minimum < -c['roundoff_scale_estimate']:
|
|||
|
|
point = ', '.join(fmt(x) for x in c['sampled_extrema']['base']['minimum_reference_point'])
|
|||
|
|
lines += ['', f"**The saved iteration {c['iteration']} base already has negative enthalpy between "
|
|||
|
|
f"production quadrature points:** sampled h={minimum:.9g} at reference ({point}). "
|
|||
|
|
'This base-state finding is independent of Newton-direction reconstruction. The surface '
|
|||
|
|
'coefficients and all 64 FE node values remain nonnegative; production quadrature positivity '
|
|||
|
|
'therefore misses a real polynomial undershoot in this accepted state.']
|
|||
|
|
else:
|
|||
|
|
lines += ['', f"Iteration {c['iteration']} has no negative base samples on this grid; its sampled "
|
|||
|
|
f"directional bound {c['directional_bound']['sampled_admissible_step_bound']:.12g} is tighter "
|
|||
|
|
f"than the production bound {c['union_production_bound']:.12g}. Absence of negative samples "
|
|||
|
|
'does not certify positivity everywhere.']
|
|||
|
|
lines += ['', 'See pressure_polynomial_analysis.md and pressure_polynomial_checks.json for interpolation '
|
|||
|
|
'validation, minima, locations and limitations. No solver or preparation rule was changed.']
|
|||
|
|
lines += ['', '## Scope and interpretation', '',
|
|||
|
|
'A replay with reason=2, stage=6, EOS code=5 is the production pressure operator’s finite h<0 branch. '
|
|||
|
|
'It resolves the old CSV ambiguity with inverted geometry. Missing determinant/F data on rejection are not measured nonfinite residuals.', '',
|
|||
|
|
'The bound scans the exact production pressure/closure quadrature points using pointwise polynomial contractions. '
|
|||
|
|
'The independently re-evaluated h values in the crossing table concern the two frozen limiting points, not a full search for each trial’s most negative point. '
|
|||
|
|
'Optimized tensor contractions can differ at roundoff; .99/1.01 factors deliberately avoid equality at the crossing.', '',
|
|||
|
|
'Element-to-surface adjacency, when available in pressure_obstruction_limits.csv, is an exact topology flag. '
|
|||
|
|
'It is not distance to the surface. Physical/reference Cartesian coordinates and element-local integration coordinates are distinct.', '',
|
|||
|
|
'At iteration 11 the supplied direction is reconstructed from a first-trial difference at alpha=1.9073486328125e-6; '
|
|||
|
|
'its relative subtraction-roundoff scale estimate is approximately 4.88e-7, not a certified error bound. '
|
|||
|
|
'The exact saved candidate is replayed without that reconstruction and is authoritative for the observed rejection.', '',
|
|||
|
|
'Preparation success in a frozen probe does not establish line-search merit acceptance, physical equilibrium, or eventual Newton convergence. '
|
|||
|
|
'No requested stopping test, enthalpy admissibility rule, or solver was changed. '
|
|||
|
|
'The evolving bound is directional: a falling h/dh bound does not by itself identify why the nonlinear correction keeps pointing outward from the admissible set.', '',
|
|||
|
|
'Machine-readable evidence and all individual trial checks: pressure_checks.json. '
|
|||
|
|
'Reproduce this analysis with `python3 analyze_pressure.py /path/to/campaign_artifacts`; '
|
|||
|
|
'the optional campaign path defaults to the script directory.']
|
|||
|
|
(ROOT / 'pressure_analysis.md').write_text('\n'.join(lines) + '\n')
|
|||
|
|
print(json.dumps({'cases_with_exact_replay': sum(c['exact_candidate'] is not None for c in cases),
|
|||
|
|
'cases_fully_restored': sum(c['restoration_completed'] for c in cases),
|
|||
|
|
'supplemental_available': sum(c['available'] for c in supplements['cases']),
|
|||
|
|
'supplemental_fully_restored': sum('final_restoration_residual_difference' in c.get('restoration', {})
|
|||
|
|
for c in supplements['cases']),
|
|||
|
|
'candidate_rows': {c['iteration']: c['pressure_trials_completed'] for c in cases}}, sort_keys=True))
|
|||
|
|
|
|||
|
|
|
|||
|
|
if __name__ == '__main__':
|
|||
|
|
main()
|