From 3c2a38fa4ec3a38c0527838aa2e628d966076438 Mon Sep 17 00:00:00 2001 From: "wbinventor@gmail.com" Date: Fri, 26 Feb 2016 20:38:42 -0500 Subject: [PATCH] Revised reporting of AggregateNuclides and AggregateScores in Pandas DataFrames --- openmc/arithmetic.py | 16 ++++++++++++++++ openmc/tallies.py | 19 ++++++++++++++++--- 2 files changed, 32 insertions(+), 3 deletions(-) diff --git a/openmc/arithmetic.py b/openmc/arithmetic.py index 5271e49a61..e9ba378d52 100644 --- a/openmc/arithmetic.py +++ b/openmc/arithmetic.py @@ -562,6 +562,13 @@ class AggregateScore(object): def aggregate_op(self): return self._aggregate_op + @property + def name(self): + + # Append each score in the aggregate to the string + string = '(' + ', '.join(map(str, self.scores)) + ')' + return string + @scores.setter def scores(self, scores): cv.check_iterable_type('scores', scores, basestring) @@ -649,6 +656,15 @@ class AggregateNuclide(object): def aggregate_op(self): return self._aggregate_op + @property + def name(self): + + # Append each nuclide in the aggregate to the string + names = [nuclide.name if isinstance(nuclide, Nuclide) else str(nuclide) + for nuclide in self.nuclides] + string = '(' + ', '.join(map(str, names)) + ')' + return string + @nuclides.setter def nuclides(self, nuclides): cv.check_iterable_type('nuclides', nuclides, diff --git a/openmc/tallies.py b/openmc/tallies.py index cba7ff9276..fb66eb77f8 100644 --- a/openmc/tallies.py +++ b/openmc/tallies.py @@ -1571,23 +1571,36 @@ class Tally(object): # Include DataFrame column for nuclides if user requested it if nuclides: nuclides = [] + column_name = 'nuclide' for nuclide in self.nuclides: - # Write Nuclide name if Summary info was linked with StatePoint if isinstance(nuclide, Nuclide): nuclides.append(nuclide.name) + elif isinstance(nuclide, AggregateNuclide): + nuclides.append(nuclide.name) + column_name = '{0}(nuclide)'.format(nuclide.aggregate_op) else: nuclides.append(nuclide) # Tile the nuclide bins into a DataFrame column nuclides = np.repeat(nuclides, len(self.scores)) tile_factor = data_size / len(nuclides) - df['nuclide'] = np.tile(nuclides, int(tile_factor)) + df[column_name] = np.tile(nuclides, int(tile_factor)) # Include column for scores if user requested it if scores: + scores = [] + column_name = 'score' + + for score in self.scores: + if isinstance(score, (basestring, CrossScore)): + scores.append(score) + elif isinstance(score, AggregateScore): + scores.append(score.name) + column_name = '{0}(score)'.format(score.aggregate_op) + tile_factor = data_size / len(self.scores) - df['score'] = np.tile(self.scores, int(tile_factor)) + df[column_name] = np.tile(scores, int(tile_factor)) # Append columns with mean, std. dev. for each tally bin df['mean'] = self.mean.ravel()