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Code Issues Projects Releases Packages Wiki Activity Actions 5

HDF5 stores now working for MultiGroupXS in Python API

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This commit is contained in:
Will Boyd 2015-09-13 17:14:29 -04:00
parent 6d2a87fd35
commit 2ad9ac9932
3 changed files with 95 additions and 30 deletions
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2
openmc/filter.py
View file

@ -511,7 +511,7 @@ class Filter(object):
try:
import pandas as pd
except ImportError:
msg = 'The pandas Python package must be installed on your system'
msg = 'The Pandas Python package must be installed on your system'
raise ImportError(msg)
# Initialize Pandas DataFrame

119
openmc/mgxs/mgxs.py
View file

@ -542,20 +542,99 @@ class MultiGroupXS(object):
self._xs_tally = xs_results['xs_tally']
self._offset = xs_results['offset']
def build_hdf5_store(self, filename='mgxs', directory='mgxs',
append=True, key=None):
def build_hdf5_store(self, filename='mgxs', directory='mgxs', append=True):
"""Export the multi-group cross-section data into an HDF5 binary file.
This routine constructs an HDF5 file which stores the multi-group
cross-section data. The data is be stored in a hierarchy of HDF5 groups
from the domain type, domain id, subdomain id (for distribcell domains),
and cross-section type. Two datasets for the mean and standard deviation
are stored for each subddomain entry in the HDF5 file.
NOTE: This requires the h5py Python package.
Parameters
----------
filename : str
Filename for the HDF5 file (default is 'mgxs')
directory : str
Directory for the HDF5 file (default is 'mgxs')
append : boolean
If true, appends to an existing HDF5 file with the same filename
directory (if one exists)
Raises
------
ValueError
When this method is called before the multi-group cross-section is
computed from tally data.
ImportError
When h5py is not installed.
"""
:param filename:
:param directory:
:param append:
:param key:
:return:
"""
if self.xs_tally is None:
msg = 'Unable to get build HDF5 store since the ' \
'cross-section has not been computed'
raise ValueError(msg)
# FIXME:
import h5py
raise NotImplementedError('HDF5 storage is not yet implemented')
# Attempt to import h5py
try:
import h5py
except ImportError:
msg = 'The h5py Python package must be installed on your system'
raise ImportError(msg)
filename = directory + '/' + filename + '.h5'
filename = filename.replace(' ', '-')
if append:
xs_results = h5py.File(filename, 'a')
else:
xs_results = h5py.File(filename, 'w')
# Create an HDF5 group within the file for the domain
domain_type_group = xs_results.require_group(self.domain_type)
group_name = '{0} {1}'.format(self.domain_type, self.domain.id)
domain_group = domain_type_group.require_group(group_name)
if self.domain_type == 'distribcell':
subdomains = np.arange(self.num_subdomains, dtype=np.int)
else:
subdomains = [self.domain.id]
# Determine number of digits to pad subdomain group keys
num_digits = len(str(self.num_subdomains))
# Create a separate HDF5 dataset for each subdomain
for i, subdomain in enumerate(subdomains):
# Create an HDF5 group for the subdomain
if self.domain_type == 'distribcell':
group_name = str(subdomain).zfill(num_digits)
subdomain_group = domain_group.require_group(group_name)
else:
subdomain_group = domain_group
# Create a separate HDF5 group for the xs type
xs_group = subdomain_group.require_group(self.xs_type)
# Extract the cross-section for this
average = self.get_xs(subdomains=[subdomain], value='mean')
std_dev = self.get_xs(subdomains=[subdomain], value='std_dev')
average = average.squeeze()
std_dev = std_dev.squeeze()
# Add MultiGroupXS results data to the HDF5 group
xs_group.require_dataset('average', dtype=np.float64,
shape=average.shape, data=average)
xs_group.require_dataset('std. dev.', dtype=np.float64,
shape=std_dev.shape, data=std_dev)
# Close the MultiGroup results HDF5 file
xs_results.close()
def export_xs_data(self, filename='mgxs', directory='mgxs', format='csv'):
"""Export the multi-group cross-section data to a file.
@ -1082,6 +1161,7 @@ class ScatterMatrixXS(MultiGroupXS):
# Query the multi-group cross-section tally for the data
xs = self.xs_tally.get_values(filters=filters,
filter_bins=filter_bins, value=value)
xs = np.nan_to_num(xs)
return xs
def print_xs(self, subdomains='all'):
@ -1217,17 +1297,7 @@ class Chi(MultiGroupXS):
nu_fission_in = self.tallies['nu-fission-in']
nu_fission_out = self.tallies['nu-fission-out']
# FIXME: Make filter bins simpler in Tally.summation(...)
# Construct energy group filter bins to sum across
'''
filter_bins = []
for group in range(1, self.num_groups+1):
group_bounds = self.energy_groups.get_group_bounds(group)
filter_bins.append((group_bounds,))
energy_bins = [filter_bins]
'''
energy_bins = []
for group in range(1, self.num_groups+1):
energy_bins.append(self.energy_groups.get_group_bounds(group))
@ -1235,9 +1305,6 @@ class Chi(MultiGroupXS):
sum_nu_fission_in = nu_fission_in.summation(filter='energy',
filter_bins=energy_bins)
# FIXME: Need ability to override energy groups with group numbers
# FIXME: Reverse from fast to thermal with energy groups
# FIXME: CrossFilter for energy + energy messes up tally arithmetic
sum_nu_fission_in.remove_filter(sum_nu_fission_in.filters[-1])
@ -1256,6 +1323,4 @@ class Chi(MultiGroupXS):
self._xs_tally /= norm
self._xs_tally._mean = np.nan_to_num(self.xs_tally.mean)
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)
# FIXME: Does this need to reset NaNs to zero?
self._xs_tally._std_dev = np.nan_to_num(self.xs_tally.std_dev)

4
openmc/tallies.py
View file

@ -1075,11 +1075,11 @@ class Tally(object):
'Summary info'.format(self.id)
raise KeyError(msg)
# Attempt to import the pandas package
# Attempt to import Pandas
try:
import pandas as pd
except ImportError:
msg = 'The pandas Python package must be installed on your system'
msg = 'The Pandas Python package must be installed on your system'
raise ImportError(msg)
# Initialize a pandas dataframe for the tally data