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Updated MGXS.get_pandas_dataframe(...) method to use distribcell_paths parameter

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This commit is contained in:
Will Boyd 2016-04-30 14:00:24 -04:00
parent 615cec9e96
commit 5e6de55a47
1 changed files with 17 additions and 20 deletions
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37
openmc/mgxs/mgxs.py
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@ -1346,7 +1346,7 @@ class MGXS(object):
modified.write('\n\\end{document}')
def get_pandas_dataframe(self, groups='all', nuclides='all',
xs_type='macro', summary=None):
xs_type='macro', distribcell_paths=False):
"""Build a Pandas DataFrame for the MGXS data.
This method leverages :meth:`openmc.Tally.get_pandas_dataframe`, but
@ -1366,12 +1366,9 @@ class MGXS(object):
xs_type: {'macro', 'micro'}
Return macro or micro cross section in units of cm^-1 or barns.
Defaults to 'macro'.
summary : None or openmc.Summary
An optional Summary object to be used to construct columns for
distribcell tally filters (default is None). The geometric
information in the Summary object is embedded into a multi-index
column with a geometric "path" to each distribcell intance.
NOTE: This option requires the OpenCG Python package.
distribcell_paths : list of str
The paths traversed through the CSG tree to reach each distribcell
instance (for 'distribcell' filters only)
Returns
-------
@ -1398,7 +1395,8 @@ class MGXS(object):
# Use tally summation to sum across all nuclides
query_nuclides = self.get_all_nuclides()
xs_tally = self.xs_tally.summation(nuclides=query_nuclides)
df = xs_tally.get_pandas_dataframe(summary=summary)
df = xs_tally.get_pandas_dataframe(
distribcell_paths=distribcell_paths)
# Remove nuclide column since it is homogeneous and redundant
df.drop('nuclide', axis=1, inplace=True)
@ -1406,14 +1404,16 @@ class MGXS(object):
# If the user requested a specific set of nuclides
elif self.by_nuclide and nuclides != 'all':
xs_tally = self.xs_tally.get_slice(nuclides=nuclides)
df = xs_tally.get_pandas_dataframe(summary=summary)
df = xs_tally.get_pandas_dataframe(
distribcell_paths=distribcell_paths)
# If the user requested all nuclides, keep nuclide column in dataframe
else:
df = self.xs_tally.get_pandas_dataframe(summary=summary)
df = self.xs_tally.get_pandas_dataframe(
distribcell_paths=distribcell_paths)
# Remove the score column since it is homogeneous and redundant
if summary and 'distribcell' in self.domain_type:
if distribcell_paths and 'distribcell' in self.domain_type:
df = df.drop('score', level=0, axis=1)
else:
df = df.drop('score', axis=1)
@ -2557,7 +2557,7 @@ class Chi(MGXS):
return xs
def get_pandas_dataframe(self, groups='all', nuclides='all',
xs_type='macro', summary=None):
xs_type='macro', distribcell_paths=False):
"""Build a Pandas DataFrame for the MGXS data.
This method leverages :meth:`openmc.Tally.get_pandas_dataframe`, but
@ -2577,12 +2577,9 @@ class Chi(MGXS):
xs_type: {'macro', 'micro'}
Return macro or micro cross section in units of cm^-1 or barns.
Defaults to 'macro'.
summary : None or openmc.Summary
An optional Summary object to be used to construct columns for
distribcell tally filters (default is None). The geometric
information in the Summary object is embedded into a multi-index
column with a geometric "path" to each distribcell intance.
NOTE: This option requires the OpenCG Python package.
distribcell_paths : list of str
The paths traversed through the CSG tree to reach each distribcell
instance (for 'distribcell' filters only)
Returns
-------
@ -2598,8 +2595,8 @@ class Chi(MGXS):
"""
# Build the dataframe using the parent class method
df = super(Chi, self).get_pandas_dataframe(groups, nuclides,
xs_type, summary)
df = super(Chi, self).get_pandas_dataframe(
groups, nuclides, xs_type, distribcell_paths=distribcell_paths)
# If user requested micro cross sections, multiply by the atom
# densities to cancel out division made by the parent class method