OpenMC/scripts/openmc-get-jeff-data

#!/usr/bin/env python3

import os
from collections import defaultdict
import sys
import tarfile
import zipfile
import glob
import argparse
from string import digits
from urllib.request import urlopen

import openmc.data


description = """
Download JEFF 3.2 ACE data from OECD/NEA and convert it to a multi-temperature
HDF5 library for use with OpenMC.

"""

download_warning = """
WARNING: This script will download approximately 9 GB of data. Extracting and
processing the data may require as much as 40 GB of additional free disk
space. Note that if you don't need all 11 temperatures, you can modify the
'files' list in the script to download only the data you want.

Are you sure you want to continue? ([y]/n)
"""

class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter,
                      argparse.RawDescriptionHelpFormatter):
    pass

parser = argparse.ArgumentParser(
    description=description,
    formatter_class=CustomFormatter
)
parser.add_argument('-b', '--batch', action='store_true',
                    help='supresses standard in')
parser.add_argument('-d', '--destination', default='jeff-3.2-hdf5',
                    help='Directory to create new library in')
parser.add_argument('--libver', choices=['earliest', 'latest'],
                    default='latest', help="Output HDF5 versioning. Use "
                    "'earliest' for backwards compatibility or 'latest' for "
                    "performance")
args = parser.parse_args()

response = input(download_warning) if not args.batch else 'y'
if response.lower().startswith('n'):
    sys.exit()

base_url = 'https://www.oecd-nea.org/dbforms/data/eva/evatapes/jeff_32/Processed/'
files = ['JEFF32-ACE-293K.tar.gz',
         'JEFF32-ACE-400K.tar.gz',
         'JEFF32-ACE-500K.tar.gz',
         'JEFF32-ACE-600K.tar.gz',
         'JEFF32-ACE-700K.tar.gz',
         'JEFF32-ACE-800K.zip',
         'JEFF32-ACE-900K.tar.gz',
         'JEFF32-ACE-1000K.tar.gz',
         'JEFF32-ACE-1200K.tar.gz',
         'JEFF32-ACE-1500K.tar.gz',
         'JEFF32-ACE-1800K.tar.gz',
         'TSLs.tar.gz']

block_size = 16384

# ==============================================================================
# DOWNLOAD FILES FROM OECD SITE

files_complete = []
for f in files:
    # Establish connection to URL
    url = base_url + f
    req = urlopen(url)

    # Get file size from header
    if sys.version_info[0] < 3:
        file_size = int(req.info().getheaders('Content-Length')[0])
    else:
        file_size = req.length
    downloaded = 0

    # Check if file already downloaded
    if os.path.exists(f):
        if os.path.getsize(f) == file_size:
            print('Skipping {}, already downloaded'.format(f))
            files_complete.append(f)
            continue
        else:
            overwrite = input('Overwrite {}? ([y]/n) '.format(f))
            if overwrite.lower().startswith('n'):
                continue

    # Copy file to disk
    print('Downloading {}... '.format(f), end='')
    with open(f, 'wb') as fh:
        while True:
            chunk = req.read(block_size)
            if not chunk: break
            fh.write(chunk)
            downloaded += len(chunk)
            status = '{:10}  [{:3.2f}%]'.format(downloaded, downloaded * 100. / file_size)
            print(status + chr(8)*len(status), end='')
        print('')
        files_complete.append(f)

# ==============================================================================
# EXTRACT FILES FROM TGZ

for f in files:
    if f not in files_complete:
        continue

    # Extract files
    if f.endswith('.zip'):
        with zipfile.ZipFile(f, 'r') as zipf:
            print('Extracting {}...'.format(f))
            zipf.extractall('jeff-3.2')

    else:
        suffix = 'ACEs_293K' if '293' in f else ''
        with tarfile.open(f, 'r') as tgz:
            print('Extracting {}...'.format(f))
            tgz.extractall(os.path.join('jeff-3.2', suffix))

        # Remove thermal scattering tables from 293K data since they are
        # redundant
        if '293' in f:
            for path in glob.glob(os.path.join('jeff-3.2', 'ACEs_293K', '*-293.ACE')):
                os.remove(path)

# ==============================================================================
# CHANGE ZAID FOR METASTABLES

metastables = glob.glob(os.path.join('jeff-3.2', '**', '*M.ACE'))
for path in metastables:
    print('    Fixing {} (ensure metastable)...'.format(path))
    text = open(path, 'r').read()
    mass_first_digit = int(text[3])
    if mass_first_digit <= 2:
        text = text[:3] + str(mass_first_digit + 4) + text[4:]
        open(path, 'w').write(text)

# ==============================================================================
# GENERATE HDF5 LIBRARY -- NEUTRON FILES

# Get a list of all ACE files
neutron_files = glob.glob(os.path.join('jeff-3.2', '*', '*.ACE'))

# Group together tables for same nuclide
tables = defaultdict(list)
for filename in sorted(neutron_files):
    dirname, basename = os.path.split(filename)
    name = basename.split('.')[0]
    tables[name].append(filename)

# Sort temperatures from lowest to highest
for name, filenames in sorted(tables.items()):
    filenames.sort(key=lambda x: int(
        x.split(os.path.sep)[1].split('_')[1][:-1]))

# Create output directory if it doesn't exist
if not os.path.isdir(args.destination):
    os.mkdir(args.destination)

library = openmc.data.DataLibrary()

for name, filenames in sorted(tables.items()):
    # Convert first temperature for the table
    print('Converting: ' + filenames[0])
    data = openmc.data.IncidentNeutron.from_ace(filenames[0])

    # For each higher temperature, add cross sections to the existing table
    for filename in filenames[1:]:
        print('Adding: ' + filename)
        data.add_temperature_from_ace(filename)

    # Export HDF5 file
    h5_file = os.path.join(args.destination, data.name + '.h5')
    print('Writing {}...'.format(h5_file))
    data.export_to_hdf5(h5_file, 'w', libver=args.libver)

    # Register with library
    library.register_file(h5_file)

# ==============================================================================
# GENERATE HDF5 LIBRARY -- S(A,B) FILES

sab_files = glob.glob(os.path.join('jeff-3.2', 'ANNEX_6_3_STLs', '*', '*.ace'))

# Group together tables for same nuclide
tables = defaultdict(list)
for filename in sorted(sab_files):
    dirname, basename = os.path.split(filename)
    name = basename.split('-')[0]
    tables[name].append(filename)

# Sort temperatures from lowest to highest
for name, filenames in sorted(tables.items()):
    filenames.sort(key=lambda x: int(
        os.path.split(x)[1].split('-')[1].split('.')[0]))

for name, filenames in sorted(tables.items()):
    # Convert first temperature for the table
    print('Converting: ' + filenames[0])

    # Take numbers out of table name, e.g. lw10.32t -> lw.32t
    table = openmc.data.ace.get_table(filenames[0])
    name, xs = table.name.split('.')
    table.name = '.'.join((name.strip(digits), xs))
    data = openmc.data.ThermalScattering.from_ace(table)

    # For each higher temperature, add cross sections to the existing table
    for filename in filenames[1:]:
        print('Adding: ' + filename)
        table = openmc.data.ace.get_table(filename)
        name, xs = table.name.split('.')
        table.name = '.'.join((name.strip(digits), xs))
        data.add_temperature_from_ace(table)

    # Export HDF5 file
    h5_file = os.path.join(args.destination, data.name + '.h5')
    print('Writing {}...'.format(h5_file))
    data.export_to_hdf5(h5_file, 'w', libver=args.libver)

    # Register with library
    library.register_file(h5_file)

# Write cross_sections.xml
libpath = os.path.join(args.destination, 'cross_sections.xml')
library.export_to_xml(libpath)