Datasets:
Formats:
csv
Languages:
English
Size:
< 1K
Tags:
mathematics
homogenization
spectral-theory
variational-methods
matrix-analysis
scientific-computing
File size: 3,017 Bytes
9427ec0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | #!/usr/bin/env python3
"""Export three small Hub-viewable tables from the recorded verification JSON.
No solver is rerun and no numerical value is rounded or fabricated.
"""
from pathlib import Path
import csv
import json
ROOT = Path(__file__).resolve().parent
def write_csv(name, rows):
keys = list(dict.fromkeys(key for row in rows for key in row))
path = ROOT / 'data' / name
path.parent.mkdir(exist_ok=True)
with path.open('w', encoding='utf-8', newline='') as out:
writer = csv.DictWriter(out, fieldnames=keys, lineterminator='\n')
writer.writeheader()
writer.writerows(rows)
return len(rows)
def response_columns(response):
fields = {}
for i in range(2):
for j in range(2):
fields[f'Y{i+1}{j+1}_real'] = response['real_part'][i][j]
fields[f'Y{i+1}{j+1}_imag'] = response['imaginary_part'][i][j]
for i, value in enumerate(response['eigenvalues'], 1):
fields[f'response_eigenvalue_{i}'] = value
return fields
def main():
source = ROOT / 'research' / 'results'
critical = json.loads((source / 'critical.json').read_text(encoding='utf-8'))
rows = []
for case in critical['cases']:
for record in case['rows']:
row = dict(factor_kind=case['kind'], tau=case['tau'], n=record['n'],
rho=record['penalty'],
relative_response_error=record['relative_error_to_effective_response'])
row.update(response_columns(record['response']))
row.update(record['solver_metrics'])
rows.append(row)
counts = {'critical_crossover': write_csv('critical_crossover.csv', rows)}
ports = json.loads((source / 'nexus_uniform.json').read_text(encoding='utf-8'))
rows = []
for i, record in enumerate(ports['rows']):
row = dict(case_index=i, kind=record['kind'], epsilon=record['epsilon'],
lambda_finite='' if record['strength'] == 'infinity' else record['strength'],
hard_constraint=record['strength'] == 'infinity',
check=record.get('check', 'main'))
row.update({k: v for k, v in record.items()
if k not in {'kind', 'epsilon', 'strength', 'check'}})
rows.append(row)
counts['compact_ports'] = write_csv('compact_ports.csv', rows)
design = critical['finite_critical_compensation_design']
rows = []
for record in design['rows']:
row = dict(tau=design['tau'], n=record['n'], rho=record['penalty'],
relative_response_error=record['relative_error_to_prescribed_response'],
effective_potential_identity_error=design['effective_potential_identity_error'])
row.update(response_columns(record['response']))
row.update(record['solver_metrics'])
rows.append(row)
counts['critical_compensation'] = write_csv('critical_compensation.csv', rows)
print(json.dumps(counts, indent=2))
if __name__ == '__main__':
main()
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