def get_subdomain_avg_library(self):
"""Construct a subdomain-averaged version of this library.
This routine averages each multi-group cross section across distribcell
instances. The method performs spatial homogenization to compute the
scalar flux-weighted average cross section across the subdomains.
NOTE: This method is only relevant for distribcell domain types and
simplys returns a deep copy of the library for all other domains types.
Returns
-------
openmc.mgxs.Library
A new multi-group cross section library averaged across subdomains
Raises
------
ValueError
When this method is called before a statepoint has been loaded
See also
--------
MGXS.get_subdomain_avg_xs(subdomains)
"""
if self.sp_filename is None:
msg = 'Unable to get a subdomain-averaged cross section ' \
'library since the statepoint has not yet been loaded'
raise ValueError(msg)
# Clone this Library to initialize the subdomain-averaged version
subdomain_avg_library = copy.deepcopy(self)
if subdomain_avg_library.domain_type == 'distribcell':
subdomain_avg_library.domain_type = 'cell'
else:
return subdomain_avg_library
# Subdomain average the MGXS for each domain and mgxs type
for domain in self.domains:
for mgxs_type in self.mgxs_types:
mgxs = subdomain_avg_library.get_mgxs(domain, mgxs_type)
if mgxs.domain_type == 'distribcell':
avg_mgxs = mgxs.get_subdomain_avg_xs()
subdomain_avg_library.all_mgxs[domain.id][mgxs_type] = avg_mgxs
return subdomain_avg_library
def build_hdf5_store(self,
filename='mgxs.h5',
directory='mgxs',
subdomains='all',
nuclides='all',
xs_type='macro'):
"""Export the multi-group cross section library to an HDF5 binary file.
This method constructs an HDF5 file which stores the library's
multi-group cross section data. The data is stored in a hierarchy of
HDF5 groups from the domain type, domain id, subdomain id (for
distribcell domains), nuclides and cross section types. Two datasets for
the mean and standard deviation are stored for each subdomain entry in
the HDF5 file. The number of groups is stored as a file attribute.
NOTE: This requires the h5py Python package.
Parameters
----------
filename : str
Filename for the HDF5 file. Defaults to 'mgxs.h5'.
directory : str
Directory for the HDF5 file. Defaults to 'mgxs'.
subdomains : {'all', 'avg'}
Report all subdomains or the average of all subdomain cross sections
in the report. Defaults to 'all'.
nuclides : {'all', 'sum'}
The nuclides of the cross-sections to include in the report. This
may be a list of nuclide name strings (e.g., ['U-235', 'U-238']).
The special string 'all' will report the cross sections for all
nuclides in the spatial domain. The special string 'sum' will report
the cross sections summed over all nuclides. Defaults to 'all'.
xs_type: {'macro', 'micro'}
Store the macro or micro cross section in units of cm^-1 or barns.
Defaults to 'macro'.
Raises
------
ValueError
When this method is called before a statepoint has been loaded
See also
--------
MGXS.build_hdf5_store(filename, directory, xs_type)
"""
if self.sp_filename is None:
msg = 'Unable to export multi-group cross section library ' \
'since a statepoint has not yet been loaded'
raise ValueError(msg)
cv.check_type('filename', filename, basestring)
cv.check_type('directory', directory, basestring)
import h5py
# Make directory if it does not exist
if not os.path.exists(directory):
os.makedirs(directory)
# Add an attribute for the number of energy groups to the HDF5 file
full_filename = os.path.join(directory, filename)
full_filename = full_filename.replace(' ', '-')
f = h5py.File(full_filename, 'w')
f.attrs["# groups"] = self.num_groups
f.close()
# Export MGXS for each domain and mgxs type to an HDF5 file
for domain in self.domains:
for mgxs_type in self.mgxs_types:
mgxs = self.all_mgxs[domain.id][mgxs_type]
if subdomains == 'avg':
mgxs = mgxs.get_subdomain_avg_xs()
mgxs.build_hdf5_store(filename,
directory,
xs_type=xs_type,
nuclides=nuclides)
def build_hdf5_store(self, filename='mgxs.h5', directory='mgxs',
subdomains='all', nuclides='all', xs_type='macro',
row_column='inout'):
"""Export the multi-group cross section library to an HDF5 binary file.
This method constructs an HDF5 file which stores the library's
multi-group cross section data. The data is stored in a hierarchy of
HDF5 groups from the domain type, domain id, subdomain id (for
distribcell domains), nuclides and cross section types. Two datasets for
the mean and standard deviation are stored for each subdomain entry in
the HDF5 file. The number of groups is stored as a file attribute.
NOTE: This requires the h5py Python package.
Parameters
----------
filename : str
Filename for the HDF5 file. Defaults to 'mgxs.h5'.
directory : str
Directory for the HDF5 file. Defaults to 'mgxs'.
subdomains : {'all', 'avg'}
Report all subdomains or the average of all subdomain cross sections
in the report. Defaults to 'all'.
nuclides : {'all', 'sum'}
The nuclides of the cross-sections to include in the report. This
may be a list of nuclide name strings (e.g., ['U-235', 'U-238']).
The special string 'all' will report the cross sections for all
nuclides in the spatial domain. The special string 'sum' will report
the cross sections summed over all nuclides. Defaults to 'all'.
xs_type: {'macro', 'micro'}
Store the macro or micro cross section in units of cm^-1 or barns.
Defaults to 'macro'.
row_column: {'inout', 'outin'}
Store scattering matrices indexed first by incoming group and
second by outgoing group ('inout'), or vice versa ('outin').
Defaults to 'inout'.
Raises
------
ValueError
When this method is called before a statepoint has been loaded
See also
--------
MGXS.build_hdf5_store(filename, directory, xs_type)
"""
if self.sp_filename is None:
msg = 'Unable to export multi-group cross section library ' \
'since a statepoint has not yet been loaded'
raise ValueError(msg)
cv.check_type('filename', filename, basestring)
cv.check_type('directory', directory, basestring)
import h5py
# Make directory if it does not exist
if not os.path.exists(directory):
os.makedirs(directory)
# Add an attribute for the number of energy groups to the HDF5 file
full_filename = os.path.join(directory, filename)
full_filename = full_filename.replace(' ', '-')
f = h5py.File(full_filename, 'w')
f.attrs['# groups'] = self.num_groups
f.close()
# Export MGXS for each domain and mgxs type to an HDF5 file
for domain in self.domains:
for mgxs_type in self.mgxs_types:
mgxs = self.all_mgxs[domain.id][mgxs_type]
if subdomains == 'avg':
mgxs = mgxs.get_subdomain_avg_xs()
mgxs.build_hdf5_store(filename, directory, xs_type=xs_type,
nuclides=nuclides, row_column=row_column)
