From 8e10d9e00fefb104692a9fc21978d8ae467b5cb2 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Mon, 17 Oct 2016 19:15:11 -0400
Subject: [PATCH 01/27] seem to have the input side for the MuFilter working,
 now on to the library generation side

---
 openmc/filter.py       | 313 +++++++++++++++++++++++++++++++----------
 openmc/mgxs/library.py |  82 +++++++++--
 openmc/mgxs/mgxs.py    | 210 ++++++++++++++++++---------
 openmc/mgxs_library.py |  39 +++--
 openmc/tallies.py      |   3 +-
 5 files changed, 474 insertions(+), 173 deletions(-)

diff --git a/openmc/filter.py b/openmc/filter.py
index d11af96f5..91ceb2931 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -105,7 +105,8 @@ class Filter(with_metaclass(FilterMeta, object)):
         """Return all subclasses and their subclasses, etc."""
         subs = cls.__subclasses__()
         subsubs = [grand for s in subs for grand in s.__subclasses__()]
-        return subs + subsubs
+        subsubsubs = [grand for s in subsubs for grand in s.__subclasses__()]
+        return subs + subsubs + subsubsubs
 
     @classmethod
     def from_hdf5(cls, group, **kwargs):
@@ -777,7 +778,116 @@ class MeshFilter(Filter):
         return df
 
 
-class EnergyFilter(Filter):
+class RealFilter(Filter):
+    """Tally modifier that describes phase-space and other characteristics
+
+    Parameters
+    ----------
+    bins : Iterable of Real
+        A grid of bin values.
+
+    Attributes
+    ----------
+    bins : Iterable of Real
+        A grid of bin values.
+    num_bins : Integral
+        The number of filter bins
+    stride : Integral
+        The number of filter, nuclide and score bins within each of this
+        filter's bins.
+
+    """
+
+    def __gt__(self, other):
+        if type(self) is type(other):
+            # Compare largest/smallest bin edges in filters
+            # This logic is used when merging tallies with real filters
+            return self.bins[0] >= other.bins[-1]
+        else:
+            return super(RealFilter, self).__gt__(other)
+
+    @property
+    def num_bins(self):
+        return len(self.bins) - 1
+
+    @num_bins.setter
+    def num_bins(self, num_bins):
+        cv.check_type('filter num_bins', num_bins, Integral)
+        cv.check_greater_than('filter num_bins', num_bins, 0, equality=True)
+        self._num_bins = num_bins
+
+    def can_merge(self, other):
+        if type(self) is not type(other):
+            return False
+
+        if self.bins[0] == other.bins[-1]:
+            # This low energy edge coincides with other's high edge
+            return True
+        elif self.bins[-1] == other.bins[0]:
+            # This high energy edge coincides with other's low edge
+            return True
+        else:
+            return False
+
+    def merge(self, other):
+        if not self.can_merge(other):
+            msg = 'Unable to merge "{0}" with "{1}" ' \
+                  'filters'.format(self.type, other.type)
+            raise ValueError(msg)
+
+        # Merge unique filter bins
+        merged_bins = np.concatenate((self.bins, other.bins))
+        merged_bins = np.unique(merged_bins)
+
+        # Create a new filter with these bins
+        return type(self)(sorted(merged_bins))
+
+    def is_subset(self, other):
+        """Determine if another filter is a subset of this filter.
+
+        If all of the bins in the other filter are included as bins in this
+        filter, then it is a subset of this filter.
+
+        Parameters
+        ----------
+        other : openmc.Filter
+            The filter to query as a subset of this filter
+
+        Returns
+        -------
+        bool
+            Whether or not the other filter is a subset of this filter
+
+        """
+
+        if type(self) is not type(other):
+            return False
+        elif len(self.bins) != len(other.bins):
+            return False
+        else:
+            return np.allclose(self.bins, other.bins)
+
+    def get_bin_index(self, filter_bin):
+        # Use lower energy bound to find index for RealFilters
+        deltas = np.abs(self.bins - filter_bin[1]) / filter_bin[1]
+        min_delta = np.min(deltas)
+        if min_delta < 1E-3:
+            return deltas.argmin() - 1
+        else:
+            msg = 'Unable to get the bin index for Filter since "{0}" ' \
+                  'is not one of the bins'.format(filter_bin)
+            raise ValueError(msg)
+
+    def get_bin(self, bin_index):
+        cv.check_type('bin_index', bin_index, Integral)
+        cv.check_greater_than('bin_index', bin_index, 0, equality=True)
+        cv.check_less_than('bin_index', bin_index, self.num_bins)
+
+        # Construct 2-tuple of lower, upper bins for real-valued filters
+        return (self.bins[bin_index], self.bins[bin_index + 1])
+
+
+class EnergyFilter(RealFilter):
     """Bins tally events based on incident particle energy.
 
     Parameters
@@ -797,24 +907,6 @@ class EnergyFilter(Filter):
 
     """
 
-    def __gt__(self, other):
-        if type(self) is type(other):
-            # Compare largest/smallest energy bin edges in energy filters
-            # This logic is used when merging tallies with energy filters
-            return self.bins[0] >= other.bins[-1]
-        else:
-            return super(EnergyFilter, self).__gt__(other)
-
-    @property
-    def num_bins(self):
-        return len(self.bins) - 1
-
-    @num_bins.setter
-    def num_bins(self, num_bins):
-        cv.check_type('filter num_bins', num_bins, Integral)
-        cv.check_greater_than('filter num_bins', num_bins, 0, equality=True)
-        self._num_bins = num_bins
-
     def check_bins(self, bins):
         for edge in bins:
             if not isinstance(edge, Real):
@@ -835,59 +927,6 @@ class EnergyFilter(Filter):
                       'increasing'.format(bins, self.type)
                 raise ValueError(msg)
 
-    def can_merge(self, other):
-        if type(self) is not type(other):
-            return False
-
-        if self.bins[0] == other.bins[-1]:
-            # This low energy edge coincides with other's high energy edge
-            return True
-        elif self.bins[-1] == other.bins[0]:
-            # This high energy edge coincides with other's low energy edge
-            return True
-        else:
-            return False
-
-    def merge(self, other):
-        if not self.can_merge(other):
-            msg = 'Unable to merge "{0}" with "{1}" ' \
-                  'filters'.format(self.type, other.type)
-            raise ValueError(msg)
-
-        # Merge unique filter bins
-        merged_bins = np.concatenate((self.bins, other.bins))
-        merged_bins = np.unique(merged_bins)
-
-        # Create a new filter with these bins
-        return type(self)(sorted(merged_bins))
-
-    def is_subset(self, other):
-        if type(self) is not type(other):
-            return False
-        elif len(self.bins) != len(other.bins):
-            return False
-        else:
-            return np.allclose(self.bins, other.bins)
-
-    def get_bin_index(self, filter_bin):
-        # Use lower energy bound to find index for energy Filters
-        deltas = np.abs(self.bins - filter_bin[1]) / filter_bin[1]
-        min_delta = np.min(deltas)
-        if min_delta < 1E-3:
-            return deltas.argmin() - 1
-        else:
-            msg = 'Unable to get the bin index for Filter since "{0}" ' \
-                  'is not one of the bins'.format(filter_bin)
-            raise ValueError(msg)
-
-    def get_bin(self, bin_index):
-        cv.check_type('bin_index', bin_index, Integral)
-        cv.check_greater_than('bin_index', bin_index, 0, equality=True)
-        cv.check_less_than('bin_index', bin_index, self.num_bins)
-
-        # Construct 2-tuple of lower, upper energies for energy(out) filters
-        return (self.bins[bin_index], self.bins[bin_index+1])
-
     def get_pandas_dataframe(self, data_size, **kwargs):
         """Builds a Pandas DataFrame for the Filter's bins.
 
@@ -1231,7 +1270,7 @@ class DistribcellFilter(Filter):
         return df
 
 
-class MuFilter(Filter):
+class MuFilter(RealFilter):
     """Bins tally events based on particle scattering angle.
 
     Parameters
@@ -1259,8 +1298,82 @@ class MuFilter(Filter):
 
     """
 
+    def check_bins(self, bins):
+        for edge in bins:
+            if not isinstance(edge, Real):
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is a non-integer or floating point ' \
+                      'value'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge < -1.:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is less than -1'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge > 1.:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is greater than 1'.format(edge, type(self))
+                raise ValueError(msg)
 
-class PolarFilter(Filter):
+        # Check that bin edges are monotonically increasing
+        for index in range(1, len(bins)):
+            if bins[index] < bins[index-1]:
+                msg = 'Unable to add bin edges "{0}" to a "{1}" Filter ' \
+                      'since they are not monotonically ' \
+                      'increasing'.format(bins, self.type)
+                raise ValueError(msg)
+
+    def get_pandas_dataframe(self, data_size, **kwargs):
+        """Builds a Pandas DataFrame for the Filter's bins.
+
+        This method constructs a Pandas DataFrame object for the filter with
+        columns annotated by filter bin information. This is a helper method
+        for :meth:`Tally.get_pandas_dataframe`.
+
+        Parameters
+        ----------
+        data_size : Integral
+            The total number of bins in the tally corresponding to this filter
+
+        Returns
+        -------
+        pandas.DataFrame
+            A Pandas DataFrame with one column of the lower energy bound and one
+            column of upper energy bound for each filter bin.  The number of
+            rows in the DataFrame is the same as the total number of bins in the
+            corresponding tally, with the filter bin appropriately tiled to map
+            to the corresponding tally bins.
+
+        Raises
+        ------
+        ImportError
+            When Pandas is not installed
+
+        See also
+        --------
+        Tally.get_pandas_dataframe(), CrossFilter.get_pandas_dataframe()
+
+        """
+
+        # Initialize Pandas DataFrame
+        import pandas as pd
+        df = pd.DataFrame()
+
+        # Extract the lower and upper energy bounds, then repeat and tile
+        # them as necessary to account for other filters.
+        lo_bins = np.repeat(self.bins[:-1], self.stride)
+        hi_bins = np.repeat(self.bins[1:], self.stride)
+        tile_factor = data_size / len(lo_bins)
+        lo_bins = np.tile(lo_bins, tile_factor)
+        hi_bins = np.tile(hi_bins, tile_factor)
+
+        # Add the new energy columns to the DataFrame.
+        df.loc[:, self.short_name.lower() + ' low'] = lo_bins
+        df.loc[:, self.short_name.lower() + ' high'] = hi_bins
+
+        return df
+
+
+class PolarFilter(RealFilter):
     """Bins tally events based on the incident particle's direction.
 
     Parameters
@@ -1288,6 +1401,30 @@ class PolarFilter(Filter):
 
     """
 
+    def check_bins(self, bins):
+        for edge in bins:
+            if not isinstance(edge, Real):
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is a non-integer or floating point ' \
+                      'value'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge < 0.:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is less than 0'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge > np.pi:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is greater than pi'.format(edge, type(self))
+                raise ValueError(msg)
+
+        # Check that bin edges are monotonically increasing
+        for index in range(1, len(bins)):
+            if bins[index] < bins[index-1]:
+                msg = 'Unable to add bin edges "{0}" to a "{1}" Filter ' \
+                      'since they are not monotonically ' \
+                      'increasing'.format(bins, self.type)
+                raise ValueError(msg)
+
     def get_pandas_dataframe(self, data_size, **kwargs):
         """Builds a Pandas DataFrame for the Filter's bins.
 
@@ -1338,7 +1475,7 @@ class PolarFilter(Filter):
         return df
 
 
-class AzimuthalFilter(Filter):
+class AzimuthalFilter(RealFilter):
     """Bins tally events based on the incident particle's direction.
 
     Parameters
@@ -1366,6 +1503,30 @@ class AzimuthalFilter(Filter):
 
     """
 
+    def check_bins(self, bins):
+        for edge in bins:
+            if not isinstance(edge, Real):
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is a non-integer or floating point ' \
+                      'value'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge < -np.pi:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is less than -pi'.format(edge, type(self))
+                raise ValueError(msg)
+            elif edge > np.pi:
+                msg = 'Unable to add bin edge "{0}" to a "{1}" ' \
+                      'since it is greater than pi'.format(edge, type(self))
+                raise ValueError(msg)
+
+        # Check that bin edges are monotonically increasing
+        for index in range(1, len(bins)):
+            if bins[index] < bins[index-1]:
+                msg = 'Unable to add bin edges "{0}" to a "{1}" Filter ' \
+                      'since they are not monotonically ' \
+                      'increasing'.format(bins, self.type)
+                raise ValueError(msg)
+
     def get_pandas_dataframe(self, data_size, distribcell_paths=True):
         """Builds a Pandas DataFrame for the Filter's bins.
 
diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py
index c03aa7877..96bfa6fab 100644
--- a/openmc/mgxs/library.py
+++ b/openmc/mgxs/library.py
@@ -62,15 +62,23 @@ class Library(object):
         The spatial domain(s) for which MGXS in the Library are computed
     correction : {'P0', None}
         Apply the P0 correction to scattering matrices if set to 'P0'
+    scatter_format : {'legendre', or 'histogram'}
+        Representation of the angular scattering distribution (default is
+        'legendre')
     legendre_order : int
-        The highest legendre moment in the scattering matrices (default is 0)
+        The highest Legendre moment in the scattering matrix; this is used if
+        :attr:`ScatterMatrixXS.scatter_format` is 'legendre'. (default is 0)
+    histogram_bins : int
+        The number of equally-spaced bins for the histogram representation of
+        the angular scattering distribution; this is used if
+        :attr:`ScatterMatrixXS.scatter_format` is 'histogram'. (default is 16)
     energy_groups : openmc.mgxs.EnergyGroups
         Energy group structure for energy condensation
     delayed_groups : list of int
         Delayed groups to filter out the xs
     estimator : str or None
-        The tally estimator used to compute multi-group cross sections. If None,
-        the default for each MGXS type is used.
+        The tally estimator used to compute multi-group cross sections.
+        If None, the default for each MGXS type is used.
     tally_trigger : openmc.Trigger
         An (optional) tally precision trigger given to each tally used to
         compute the cross section
@@ -104,7 +112,9 @@ class Library(object):
         self._energy_groups = None
         self._delayed_groups = None
         self._correction = 'P0'
+        self._scatter_format = 'legendre'
         self._legendre_order = 0
+        self._histogram_bins = 16
         self._tally_trigger = None
         self._all_mgxs = OrderedDict()
         self._sp_filename = None
@@ -133,7 +143,9 @@ class Library(object):
             clone._domain_type = self.domain_type
             clone._domains = copy.deepcopy(self.domains)
             clone._correction = self.correction
+            clone._scatter_format = self.scatter_format
             clone._legendre_order = self.legendre_order
+            clone._histogram_bins = self.histogram_bins
             clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
             clone._delayed_groups = copy.deepcopy(self.delayed_groups, memo)
             clone._tally_trigger = copy.deepcopy(self.tally_trigger, memo)
@@ -212,10 +224,18 @@ class Library(object):
     def correction(self):
         return self._correction
 
+    @property
+    def scatter_format(self):
+        return self._scatter_format
+
     @property
     def legendre_order(self):
         return self._legendre_order
 
+    @property
+    def histogram_bins(self):
+        return self._histogram_bins
+
     @property
     def tally_trigger(self):
         return self._tally_trigger
@@ -355,26 +375,57 @@ class Library(object):
     def correction(self, correction):
         cv.check_value('correction', correction, ('P0', None))
 
-        if correction == 'P0' and self.legendre_order > 0:
-            warn('The P0 correction will be ignored since the scattering '
-                 'order "{}" is greater than zero'.format(self.legendre_order))
+        if self.scatter_format == 'legendre':
+            if correction == 'P0' and self.legendre_order > 0:
+                msg = 'The P0 correction will be ignored since the ' \
+                      'scattering order {} is greater than '\
+                      'zero'.format(self.legendre_order)
+                warn(msg)
+        elif self.scatter_format == 'histogram':
+            msg = 'The P0 correction will be ignored since the ' \
+                  'scatter format is set to histogram'
+            warn(msg)
 
         self._correction = correction
 
+    @scatter_format.setter
+    def scatter_format(self, scatter_format):
+        cv.check_value('scatter_format', scatter_format, openmc.mgxs.MU_TREATMENTS)
+        self._scatter_format = scatter_format
+
     @legendre_order.setter
     def legendre_order(self, legendre_order):
         cv.check_type('legendre_order', legendre_order, Integral)
-        cv.check_greater_than('legendre_order', legendre_order, 0, equality=True)
+        cv.check_greater_than('legendre_order', legendre_order, 0,
+                              equality=True)
         cv.check_less_than('legendre_order', legendre_order, 10, equality=True)
 
-        if self.correction == 'P0' and legendre_order > 0:
-            msg = 'The P0 correction will be ignored since the scattering ' \
-                  'order {} is greater than zero'.format(self.legendre_order)
-            warn(msg, RuntimeWarning)
-            self.correction = None
+        if self.scatter_format == 'legendre':
+            if self.correction == 'P0' and legendre_order > 0:
+                msg = 'The P0 correction will be ignored since the ' \
+                      'scattering order {} is greater than '\
+                      'zero'.format(self.legendre_order)
+                warn(msg, RuntimeWarning)
+                self.correction = None
+        elif self.scatter_format == 'histogram':
+            msg = 'The legendre order will be ignored since the ' \
+                  'scatter format is set to histogram'
+            warn(msg)
 
         self._legendre_order = legendre_order
 
+    @histogram_bins.setter
+    def histogram_bins(self, histogram_bins):
+        cv.check_type('histogram_bins', histogram_bins, Integral)
+        cv.check_greater_than('histogram_bins', histogram_bins, 0)
+
+        if self.scatter_format == 'legendre':
+            msg = 'The histogram bins will be ignored since the ' \
+                  'scatter format is set to legendre'
+            warn(msg)
+
+        self._histogram_bins = histogram_bins
+
     @tally_trigger.setter
     def tally_trigger(self, tally_trigger):
         cv.check_type('tally trigger', tally_trigger, openmc.Trigger)
@@ -443,7 +494,9 @@ class Library(object):
                 # Specify whether to use a transport ('P0') correction
                 if isinstance(mgxs, openmc.mgxs.ScatterMatrixXS):
                     mgxs.correction = self.correction
+                    mgxs.scatter_format = self.scatter_format
                     mgxs.legendre_order = self.legendre_order
+                    mgxs.histogram_bins = self.histogram_bins
 
                 self.all_mgxs[domain.id][mgxs_type] = mgxs
 
@@ -901,15 +954,14 @@ class Library(object):
         xsdata = openmc.XSdata(name, self.energy_groups)
 
         if order is None:
-            # Set the order to the Library's order (the defualt behavior)
+            # Set the order to the Library's order (the default behavior)
             xsdata.order = self.legendre_order
         else:
             # Set the order of the xsdata object to the minimum of
             # the provided order or the Library's order.
             xsdata.order = min(order, self.legendre_order)
 
-        # Right now only 'legendre' data and isotropic weighting is supported
-        self.scatter_format = 'legendre'
+        # Right now only isotropic weighting is supported
         self.representation = 'isotropic'
 
         if nuclide != 'total':
diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 65802f2ef..cafda1ecf 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -60,6 +60,9 @@ _DOMAINS = (openmc.Cell,
             openmc.Material,
             openmc.Mesh)
 
+# Supported ScatterMatrixXS and NuScatterMatrixXS angular distribution types
+MU_TREATMENTS = ('legendre', 'histogram')
+
 
 class MGXS(object):
     """An abstract multi-group cross section for some energy group structure
@@ -3212,8 +3215,8 @@ class NuScatterXS(MGXS):
 
 
 class ScatterMatrixXS(MatrixMGXS):
-    r"""A scattering matrix multi-group cross section for one or more Legendre
-    moments.
+    r"""A scattering matrix multi-group cross section with the cosine of the
+    change-in-angle represented as one or more Legendre moments or a histogram.
 
     This class can be used for both OpenMC input generation and tally data
     post-processing to compute spatially-homogenized and energy-integrated
@@ -3231,7 +3234,7 @@ class ScatterMatrixXS(MatrixMGXS):
 
     For a spatial domain :math:`V`, incoming energy group
     :math:`[E_{g'},E_{g'-1}]`, and outgoing energy group :math:`[E_g,E_{g-1}]`,
-    the scattering moments are calculated as:
+    the Legendre scattering moments are calculated as:
 
     .. math::
 
@@ -3271,9 +3274,18 @@ class ScatterMatrixXS(MatrixMGXS):
     Attributes
     ----------
     correction : 'P0' or None
-        Apply the P0 correction to scattering matrices if set to 'P0'
+        Apply the P0 correction to scattering matrices if set to 'P0'; this is
+        used only if :attr:`ScatterMatrixXS.scatter_format` is 'legendre'
+    scatter_format : {'legendre', or 'histogram'}
+        Representation of the angular scattering distribution (default is
+        'legendre')
     legendre_order : int
-        The highest Legendre moment in the scattering matrix (default is 0)
+        The highest Legendre moment in the scattering matrix; this is used if
+        :attr:`ScatterMatrixXS.scatter_format` is 'legendre'. (default is 0)
+    histogram_bins : int
+        The number of equally-spaced bins for the histogram representation of
+        the angular scattering distribution; this is used if
+        :attr:`ScatterMatrixXS.scatter_format` is 'histogram'. (default is 16)
     name : str, optional
         Name of the multi-group cross section
     rxn_type : str
@@ -3340,7 +3352,9 @@ class ScatterMatrixXS(MatrixMGXS):
                                               groups, by_nuclide, name)
         self._rxn_type = 'scatter'
         self._correction = 'P0'
+        self._scatter_format = 'legendre'
         self._legendre_order = 0
+        self._histogram_bins = 16
         self._hdf5_key = 'scatter matrix'
         self._estimator = 'analog'
         self._valid_estimators = ['analog']
@@ -3348,26 +3362,39 @@ class ScatterMatrixXS(MatrixMGXS):
     def __deepcopy__(self, memo):
         clone = super(ScatterMatrixXS, self).__deepcopy__(memo)
         clone._correction = self.correction
+        clone._scatter_format = self.scatter_format
         clone._legendre_order = self.legendre_order
+        clone._histogram_bins = self.histogram_bins
         return clone
 
     @property
     def correction(self):
         return self._correction
 
+    @property
+    def scatter_format(self):
+        return self._scatter_format
+
     @property
     def legendre_order(self):
         return self._legendre_order
 
+    @property
+    def histogram_bins(self):
+        return self._histogram_bins
+
     @property
     def scores(self):
         scores = ['flux']
 
-        if self.correction == 'P0' and self.legendre_order == 0:
-            scores += ['{}-0'.format(self.rxn_type),
-                       '{}-1'.format(self.rxn_type)]
-        else:
-            scores += ['{}-P{}'.format(self.rxn_type, self.legendre_order)]
+        if self.scatter_format == 'legendre':
+            if self.correction == 'P0' and self.legendre_order == 0:
+                scores += ['{}-0'.format(self.rxn_type),
+                           '{}-1'.format(self.rxn_type)]
+            else:
+                scores += ['{}-P{}'.format(self.rxn_type, self.legendre_order)]
+        elif self.scatter_format == 'histogram':
+            scores += [self.rxn_type]
 
         return scores
 
@@ -3377,10 +3404,14 @@ class ScatterMatrixXS(MatrixMGXS):
         energy = openmc.EnergyFilter(group_edges)
         energyout = openmc.EnergyoutFilter(group_edges)
 
-        if self.correction == 'P0' and self.legendre_order == 0:
-            filters = [[energy], [energy, energyout], [energyout]]
-        else:
-            filters = [[energy], [energy, energyout]]
+        if self.scatter_format == 'legendre':
+            if self.correction == 'P0' and self.legendre_order == 0:
+                filters = [[energy], [energy, energyout], [energyout]]
+            else:
+                filters = [[energy], [energy, energyout]]
+        elif self.scatter_format == 'histogram':
+            bins = np.linspace(-1., 1., num=self.histogram_bins, endpoint=True)
+            filters = [[energy], [energy, energyout, openmc.MuFilter(bins)]]
 
         return filters
 
@@ -3388,20 +3419,24 @@ class ScatterMatrixXS(MatrixMGXS):
     def rxn_rate_tally(self):
 
         if self._rxn_rate_tally is None:
+            if self.scatter_format == 'legendre':
+                # If using P0 correction subtract scatter-1 from the diagonal
+                if self.correction == 'P0' and self.legendre_order == 0:
+                    scatter_p0 = self.tallies['{}-0'.format(self.rxn_type)]
+                    scatter_p1 = self.tallies['{}-1'.format(self.rxn_type)]
+                    energy_filter = scatter_p0.find_filter(openmc.EnergyFilter)
+                    energy_filter = copy.deepcopy(energy_filter)
+                    scatter_p1 = scatter_p1.diagonalize_filter(energy_filter)
+                    self._rxn_rate_tally = scatter_p0 - scatter_p1
 
-            # If using P0 correction subtract scatter-1 from the diagonal
-            if self.correction == 'P0' and self.legendre_order == 0:
-                scatter_p0 = self.tallies['{}-0'.format(self.rxn_type)]
-                scatter_p1 = self.tallies['{}-1'.format(self.rxn_type)]
-                energy_filter = scatter_p0.find_filter(openmc.EnergyFilter)
-                energy_filter = copy.deepcopy(energy_filter)
-                scatter_p1 = scatter_p1.diagonalize_filter(energy_filter)
-                self._rxn_rate_tally = scatter_p0 - scatter_p1
-
-            # Extract scattering moment reaction rate Tally
-            else:
-                tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order)
-                self._rxn_rate_tally = self.tallies[tally_key]
+                # Extract scattering moment reaction rate Tally
+                else:
+                    tally_key = '{}-P{}'.format(self.rxn_type,
+                                                self.legendre_order)
+                    self._rxn_rate_tally = self.tallies[tally_key]
+            elif self.scatter_format == 'histogram':
+                # Extract scattering rate distribution tally
+                self._rxn_rate_tally = self.tallies[self.rxn_type]
 
             self._rxn_rate_tally.sparse = self.sparse
 
@@ -3411,27 +3446,52 @@ class ScatterMatrixXS(MatrixMGXS):
     def correction(self, correction):
         cv.check_value('correction', correction, ('P0', None))
 
-        if correction == 'P0' and self.legendre_order > 0:
-            msg = 'The P0 correction will be ignored since the scattering ' \
-                  'order {} is greater than zero'.format(self.legendre_order)
+        if self.scatter_format == 'legendre':
+            if correction == 'P0' and self.legendre_order > 0:
+                msg = 'The P0 correction will be ignored since the ' \
+                      'scattering order {} is greater than '\
+                      'zero'.format(self.legendre_order)
+                warnings.warn(msg)
+        elif self.scatter_format == 'histogram':
+            msg = 'The P0 correction will be ignored since the ' \
+                  'scatter format is set to histogram'
             warnings.warn(msg)
 
         self._correction = correction
 
+    @scatter_format.setter
+    def scatter_format(self, scatter_format):
+        cv.check_value('scatter_format', scatter_format, MU_TREATMENTS)
+        self._scatter_format = scatter_format
+
     @legendre_order.setter
     def legendre_order(self, legendre_order):
         cv.check_type('legendre_order', legendre_order, Integral)
-        cv.check_greater_than('legendre_order', legendre_order, 0, equality=True)
+        cv.check_greater_than('legendre_order', legendre_order, 0,
+                              equality=True)
         cv.check_less_than('legendre_order', legendre_order, 10, equality=True)
 
-        if self.correction == 'P0' and legendre_order > 0:
-            msg = 'The P0 correction will be ignored since the scattering ' \
-                  'order {} is greater than zero'.format(self.legendre_order)
-            warnings.warn(msg, RuntimeWarning)
-            self.correction = None
+        if self.scatter_format == 'legendre':
+            if self.correction == 'P0' and legendre_order > 0:
+                msg = 'The P0 correction will be ignored since the ' \
+                      'scattering order {} is greater than '\
+                      'zero'.format(self.legendre_order)
+                warnings.warn(msg, RuntimeWarning)
+                self.correction = None
+        elif self.scatter_format == 'histogram':
+            msg = 'The legendre order will be ignored since the ' \
+                  'scatter format is set to histogram'
+            warnings.warn(msg)
 
         self._legendre_order = legendre_order
 
+    @histogram_bins.setter
+    def histogram_bins(self, histogram_bins):
+        cv.check_type('histogram_bins', histogram_bins, Integral)
+        cv.check_greater_than('histogram_bins', histogram_bins, 0)
+
+        self._histogram_bins = histogram_bins
+
     def load_from_statepoint(self, statepoint):
         """Extracts tallies in an OpenMC StatePoint with the data needed to
         compute multi-group cross sections.
@@ -3461,12 +3521,16 @@ class ScatterMatrixXS(MatrixMGXS):
             self._rxn_rate_tally = None
             self._loaded_sp = False
 
-        # Expand scores to match the format in the statepoint
-        # e.g., "scatter-P2" -> "scatter-0", "scatter-1", "scatter-2"
-        if self.correction != 'P0' or self.legendre_order != 0:
-            tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order)
-            self.tallies[tally_key].scores = \
-                [self.rxn_type + '-{}'.format(i) for i in range(self.legendre_order+1)]
+        if self.scatter_format == 'legendre':
+            # Expand scores to match the format in the statepoint
+            # e.g., "scatter-P2" -> "scatter-0", "scatter-1", "scatter-2"
+            if self.correction != 'P0' or self.legendre_order != 0:
+                tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order)
+                self.tallies[tally_key].scores = \
+                    [self.rxn_type + '-{}'.format(i)
+                     for i in range(self.legendre_order + 1)]
+        elif self.scatter_format == 'histogram':
+            self.tallies[self.rxn_type].scores = [self.rxn_type]
 
         super(ScatterMatrixXS, self).load_from_statepoint(statepoint)
 
@@ -3513,7 +3577,7 @@ class ScatterMatrixXS(MatrixMGXS):
         slice_xs._xs_tally = None
 
         # Slice the Legendre order if needed
-        if legendre_order != 'same':
+        if legendre_order != 'same' and self.scatter_format == 'legendre':
             cv.check_type('legendre_order', legendre_order, Integral)
             cv.check_less_than('legendre_order', legendre_order,
                                self.legendre_order, equality=True)
@@ -3522,7 +3586,8 @@ class ScatterMatrixXS(MatrixMGXS):
             # Slice the scattering tally
             tally_key = '{}-P{}'.format(self.rxn_type, self.legendre_order)
             expand_scores = \
-                [self.rxn_type + '-{}'.format(i) for i in range(self.legendre_order+1)]
+                [self.rxn_type + '-{}'.format(i)
+                 for i in range(self.legendre_order + 1)]
             slice_xs.tallies[tally_key] = \
                 slice_xs.tallies[tally_key].get_slice(scores=expand_scores)
 
@@ -3553,7 +3618,8 @@ class ScatterMatrixXS(MatrixMGXS):
         This method constructs a 5D NumPy array for the requested
         multi-group cross section data for one or more subdomains
         (1st dimension), energy groups in (2nd dimension), energy groups out
-        (3rd dimension), nuclides (4th dimension), and moments (5th dimension).
+        (3rd dimension), nuclides (4th dimension), and moments/histograms
+        (5th dimension).
 
         NOTE: The scattering moments are not multiplied by the :math:`(2l+1)/2`
         prefactor in the expansion of the scattering source into Legendre
@@ -3642,7 +3708,7 @@ class ScatterMatrixXS(MatrixMGXS):
                 filter_bins.append((self.energy_groups.get_group_bounds(group),))
 
         # Construct CrossScore for requested scattering moment
-        if moment != 'all':
+        if moment != 'all' and self.scatter_format == 'legendre':
             cv.check_type('moment', moment, Integral)
             cv.check_greater_than('moment', moment, 0, equality=True)
             cv.check_less_than(
@@ -3760,28 +3826,38 @@ class ScatterMatrixXS(MatrixMGXS):
         df = super(ScatterMatrixXS, self).get_pandas_dataframe(
             groups, nuclides, xs_type, distribcell_paths)
 
-        # Add a moment column to dataframe
-        if self.legendre_order > 0:
-            # Insert a column corresponding to the Legendre moments
-            moments = ['P{}'.format(i) for i in range(self.legendre_order+1)]
-            moments = np.tile(moments, int(df.shape[0] / len(moments)))
-            df['moment'] = moments
+        if self.scatter_format == 'legendre':
+            # Add a moment column to dataframe
+            if self.legendre_order > 0:
+                # Insert a column corresponding to the Legendre moments
+                moments = ['P{}'.format(i)
+                           for i in range(self.legendre_order + 1)]
+                moments = np.tile(moments, int(df.shape[0] / len(moments)))
+                df['moment'] = moments
 
-            # Place the moment column before the mean column
-            columns = df.columns.tolist()
-            mean_index = [i for i, s in enumerate(columns) if 'mean' in s][0]
-            if self.domain_type == 'mesh':
-                df = df[columns[:mean_index] + [('moment', '')] + columns[mean_index:-1]]
-            else:
-                df = df[columns[:mean_index] + ['moment'] + columns[mean_index:-1]]
+                # Place the moment column before the mean column
+                columns = df.columns.tolist()
+                mean_index \
+                    = [i for i, s in enumerate(columns) if 'mean' in s][0]
+                if self.domain_type == 'mesh':
+                    df = df[columns[:mean_index] + [('moment', '')] +
+                            columns[mean_index:-1]]
+                else:
+                    df = df[columns[:mean_index] + ['moment'] +
+                            columns[mean_index:-1]]
 
-        # Select rows corresponding to requested scattering moment
-        if moment != 'all':
-            cv.check_type('moment', moment, Integral)
-            cv.check_greater_than('moment', moment, 0, equality=True)
-            cv.check_less_than(
-                'moment', moment, self.legendre_order, equality=True)
-            df = df[df['moment'] == 'P{}'.format(moment)]
+            # Select rows corresponding to requested scattering moment
+            if moment != 'all':
+                cv.check_type('moment', moment, Integral)
+                cv.check_greater_than('moment', moment, 0, equality=True)
+                cv.check_less_than(
+                    'moment', moment, self.legendre_order, equality=True)
+                df = df[df['moment'] == 'P{}'.format(moment)]
+
+        elif self.scatter_format == 'histogram':
+            # Add a change-in-angle (mu) column to dataframe
+            ###TODO NOT SURE I NEED TO DO THIS
+            pass
 
         return df
 
@@ -3832,7 +3908,7 @@ class ScatterMatrixXS(MatrixMGXS):
 
         cv.check_value('xs_type', xs_type, ['macro', 'micro'])
 
-        if self.correction != 'P0':
+        if self.correction != 'P0' and self.scatter_format == 'legendre':
             rxn_type = '{0} (P{1})'.format(self.rxn_type, moment)
         else:
             rxn_type = self.rxn_type
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 35dff1223..5504b6e7c 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1008,21 +1008,26 @@ class XSdata(object):
         check_type('temperature', temperature, Real)
         check_value('temperature', temperature, self.temperatures)
 
-        if self.scatter_format != 'legendre':
-            msg = 'Anisotropic scattering representations other than ' \
-                  'Legendre expansions have not yet been implemented in ' \
-                  'openmc.mgxs.'
-            raise ValueError(msg)
+        # Set the value of scatter_format based on the same value within
+        # scatter
+        self.scatter_format = scatter.scatter_format
 
         # If the user has not defined XSdata.order, then we will set
         # the order based on the data within scatter.
-        # Otherwise, we will check to see that XSdata.order to match
+        # Otherwise, we will check to see that XSdata.order matches
         # the order of scatter
-        if self.order is None:
-            self.order = scatter.legendre_order
-        else:
-            check_value('legendre_order', scatter.legendre_order,
-                        [self.order])
+        if self.scatter_format == 'legendre':
+            if self.order is None:
+                self.order = scatter.legendre_order
+            else:
+                check_value('legendre_order', scatter.legendre_order,
+                            [self.order])
+        elif self.scatter_format == 'histogram':
+            if self.order is None:
+                self.order = scatter.histogram_bins
+            else:
+                check_value('histogram_bins', scatter.histogram_bins,
+                            [self.order])
 
         i = np.where(self.temperatures == temperature)[0][0]
         if self.representation == 'isotropic':
@@ -1030,10 +1035,16 @@ class XSdata(object):
             self._scatter_matrix[i] = np.zeros((self.num_orders,
                                                 self.energy_groups.num_groups,
                                                 self.energy_groups.num_groups))
-            for moment in range(self.num_orders):
-                self._scatter_matrix[i][moment, :, :] = \
+            if self.scatter_format == 'legendre':
+                for moment in range(self.num_orders):
+                    self._scatter_matrix[i][moment, :, :] = \
+                        scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
+                                       moment=moment, subdomains=subdomain)
+            else:
+                self._scatter_matrix[i][:, :, :] = \
                     scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
-                                   moment=moment, subdomains=subdomain)
+                                   subdomains=subdomain)
+                import pdb; pdb.set_trace()
 
         elif self.representation == 'angle':
             msg = 'Angular-Dependent MGXS have not yet been implemented'
diff --git a/openmc/tallies.py b/openmc/tallies.py
index f9daa7a22..6922e77ac 100644
--- a/openmc/tallies.py
+++ b/openmc/tallies.py
@@ -1301,7 +1301,8 @@ class Tally(object):
 
                     # Create list of 2-tuples for energy boundary bins
                     elif isinstance(self_filter, (openmc.EnergyFilter,
-                        openmc.EnergyoutFilter)):
+                        openmc.EnergyoutFilter, openmc.MuFilter,
+                        openmc.PolarFilter, openmc.AzimuthalFilter)):
                         bins = []
                         for k in range(self_filter.num_bins):
                             bins.append((self_filter.bins[k], self_filter.bins[k+1]))

From f126d4387ada157e88126a3e013ec95e7dbde5d8 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Tue, 18 Oct 2016 05:15:51 -0400
Subject: [PATCH 02/27] working on the writing of the MGXS lib

---
 openmc/filter.py       | 21 +++++++++++++++------
 openmc/mgxs/library.py | 36 ++++++++++++++----------------------
 openmc/mgxs/mgxs.py    | 19 +++++++++++++++----
 openmc/mgxs_library.py | 18 +++++++++++-------
 4 files changed, 55 insertions(+), 39 deletions(-)

diff --git a/openmc/filter.py b/openmc/filter.py
index 91ceb2931..fef7a25b0 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -868,15 +868,13 @@ class RealFilter(Filter):
             return np.allclose(self.bins, other.bins)
 
     def get_bin_index(self, filter_bin):
-        # Use lower energy bound to find index for RealFilters
-        deltas = np.abs(self.bins - filter_bin[1]) / filter_bin[1]
-        min_delta = np.min(deltas)
-        if min_delta < 1E-3:
-            return deltas.argmin() - 1
-        else:
+        i = np.where(self.bins == filter_bin[1])[0]
+        if len(i) == 0:
             msg = 'Unable to get the bin index for Filter since "{0}" ' \
                   'is not one of the bins'.format(filter_bin)
             raise ValueError(msg)
+        else:
+            return i[0] - 1
 
     def get_bin(self, bin_index):
         cv.check_type('bin_index', bin_index, Integral)
@@ -907,6 +905,17 @@ class EnergyFilter(RealFilter):
 
     """
 
+    def get_bin_index(self, filter_bin):
+        # Use lower energy bound to find index for RealFilters
+        deltas = np.abs(self.bins - filter_bin[1]) / filter_bin[1]
+        min_delta = np.min(deltas)
+        if min_delta < 1E-3:
+            return deltas.argmin() - 1
+        else:
+            msg = 'Unable to get the bin index for Filter since "{0}" ' \
+                  'is not one of the bins'.format(filter_bin)
+            raise ValueError(msg)
+
     def check_bins(self, bins):
         for edge in bins:
             if not isinstance(edge, Real):
diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py
index 96bfa6fab..46d404e4f 100644
--- a/openmc/mgxs/library.py
+++ b/openmc/mgxs/library.py
@@ -875,13 +875,13 @@ class Library(object):
         return pickle.load(open(full_filename, 'rb'))
 
     def get_xsdata(self, domain, xsdata_name, nuclide='total', xs_type='macro',
-                   order=None, subdomain=None):
+                   subdomain=None):
         """Generates an openmc.XSdata object describing a multi-group cross section
         dataset for writing to an openmc.MGXSLibrary object.
 
         Note that this method does not build an XSdata
         object with nested temperature tables.  The temperature of each
-        XSdata object will be left at the default value of 300K.
+        XSdata object will be left at the default value of 294K.
 
         Parameters
         ----------
@@ -896,10 +896,6 @@ class Library(object):
             Provide the macro or micro cross section in units of cm^-1 or
             barns. Defaults to 'macro'. If the Library object is not tallied by
             nuclide this will be set to 'macro' regardless.
-        order : int
-            Scattering order for this data entry.  Default is None,
-            which will set the XSdata object to use the order of the
-            Library.
         subdomain : iterable of int
             This parameter is not used unless using a mesh domain. In that
             case, the subdomain is an [i,j,k] index (1-based indexing) of the
@@ -929,10 +925,6 @@ class Library(object):
         cv.check_type('xsdata_name', xsdata_name, basestring)
         cv.check_type('nuclide', nuclide, basestring)
         cv.check_value('xs_type', xs_type, ['macro', 'micro'])
-        cv.check_type('order', order, (type(None), Integral))
-        if order is not None:
-            cv.check_greater_than('order', order, 0, equality=True)
-            cv.check_less_than('order', order, 10, equality=True)
         if subdomain is not None:
             cv.check_iterable_type('subdomain', subdomain, Integral,
                                    max_depth=3)
@@ -953,14 +945,6 @@ class Library(object):
             name += '_' + nuclide
         xsdata = openmc.XSdata(name, self.energy_groups)
 
-        if order is None:
-            # Set the order to the Library's order (the default behavior)
-            xsdata.order = self.legendre_order
-        else:
-            # Set the order of the xsdata object to the minimum of
-            # the provided order or the Library's order.
-            xsdata.order = min(order, self.legendre_order)
-
         # Right now only isotropic weighting is supported
         self.representation = 'isotropic'
 
@@ -1033,6 +1017,7 @@ class Library(object):
             using_multiplicity = False
 
         if using_multiplicity:
+            # import pdb; pdb.set_trace()
             nuscatt_mgxs = self.get_mgxs(domain, 'nu-scatter matrix')
             xsdata.set_scatter_matrix_mgxs(nuscatt_mgxs, xs_type=xs_type,
                                            nuclide=[nuclide],
@@ -1049,10 +1034,17 @@ class Library(object):
                 # accounted for approximately by using an adjusted
                 # absorption cross section.
                 if 'total' in self.mgxs_types or 'transport' in self.mgxs_types:
-                    for i in range(len(xsdata.temperatures)):
-                        xsdata._absorption[i] = \
-                            np.subtract(xsdata._total[i], np.sum(
-                                xsdata._scatter_matrix[i][0, :, :], axis=1))
+                    if xsdata.scatter_format == 'legendre':
+                        for i in range(len(xsdata.temperatures)):
+                            xsdata._absorption[i] = \
+                                np.subtract(xsdata._total[i], np.sum(
+                                    xsdata._scatter_matrix[i][0, :, :], axis=1))
+                    elif xsdata.scatter_format == 'histogram':
+                        for i in range(len(xsdata.temperatures)):
+                            xsdata._absorption[i] = \
+                                np.subtract(xsdata._total[i], np.sum(np.sum(
+                                    xsdata._scatter_matrix[i][:, :, :], axis=0),
+                                    axis=1))
 
         return xsdata
 
diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index cafda1ecf..c30cc87ac 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3410,7 +3410,8 @@ class ScatterMatrixXS(MatrixMGXS):
             else:
                 filters = [[energy], [energy, energyout]]
         elif self.scatter_format == 'histogram':
-            bins = np.linspace(-1., 1., num=self.histogram_bins, endpoint=True)
+            bins = np.linspace(-1., 1., num=self.histogram_bins + 1,
+                               endpoint=True)
             filters = [[energy], [energy, energyout, openmc.MuFilter(bins)]]
 
         return filters
@@ -3758,9 +3759,19 @@ class ScatterMatrixXS(MatrixMGXS):
         else:
             num_out_groups = len(out_groups)
 
+        if self.scatter_format == 'histogram':
+            num_mu_bins = self.histogram_bins
+        else:
+            num_mu_bins = 1
+
         # Reshape tally data array with separate axes for domain and energy
-        num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
-        new_shape = (num_subdomains, num_in_groups, num_out_groups)
+        num_subdomains = int(xs.shape[0] /
+                             (num_mu_bins * num_in_groups * num_out_groups))
+        if self.scatter_format == 'histogram':
+            new_shape = (num_subdomains, num_in_groups, num_out_groups,
+                         num_mu_bins)
+        else:
+            new_shape = (num_subdomains, num_in_groups, num_out_groups)
         new_shape += xs.shape[1:]
         xs = np.reshape(xs, new_shape)
 
@@ -3771,7 +3782,7 @@ class ScatterMatrixXS(MatrixMGXS):
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            xs = xs[:, ::-1, ::-1, :]
+            xs = xs[:, ::-1, ::-1, ...]
 
         if squeeze:
             xs = np.squeeze(xs)
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 5504b6e7c..c78b9ff0c 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1031,21 +1031,21 @@ class XSdata(object):
 
         i = np.where(self.temperatures == temperature)[0][0]
         if self.representation == 'isotropic':
-            # Get the scattering orders in the outermost dimension
-            self._scatter_matrix[i] = np.zeros((self.num_orders,
-                                                self.energy_groups.num_groups,
-                                                self.energy_groups.num_groups))
             if self.scatter_format == 'legendre':
+                # Get the scattering orders in the outermost dimension
+                self._scatter_matrix[i] = np.zeros((self.num_orders,
+                                                    self.energy_groups.num_groups,
+                                                    self.energy_groups.num_groups))
                 for moment in range(self.num_orders):
                     self._scatter_matrix[i][moment, :, :] = \
                         scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
                                        moment=moment, subdomains=subdomain)
             else:
-                self._scatter_matrix[i][:, :, :] = \
+                self._scatter_matrix[i] = \
                     scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
                                    subdomains=subdomain)
-                import pdb; pdb.set_trace()
-
+                # self._scatter_matrix[i] = \
+                #     np.swapaxes(self._scatter_matrix[i], 0, 2)
         elif self.representation == 'angle':
             msg = 'Angular-Dependent MGXS have not yet been implemented'
             raise ValueError(msg)
@@ -1124,6 +1124,10 @@ class XSdata(object):
                 scatt = scatter.get_xs(nuclides=nuclide,
                                        xs_type=xs_type, moment=0,
                                        subdomains=subdomain)
+                if scatter.scatter_format == 'histogram':
+                    scatt = np.sum(scatt, axis=4)
+                if nuscatter.scatter_format == 'histogram':
+                    nuscatt = np.sum(nuscatt, axis=4)
                 self._multiplicity_matrix[i] = np.divide(nuscatt, scatt)
         elif self.representation == 'angle':
             msg = 'Angular-Dependent MGXS have not yet been implemented'

From 45fb4201f643cb49045e3af36c8a771953d5e995 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 23 Oct 2016 13:14:46 -0400
Subject: [PATCH 03/27] Fixed angular indexing

---
 openmc/mgxs/mgxs.py    | 5 +++++
 openmc/mgxs_library.py | 6 ++----
 2 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index fb81e4c31..470fd01d0 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3776,6 +3776,11 @@ class ScatterMatrixXS(MatrixMGXS):
         if order_groups == 'increasing':
             xs = xs[:, ::-1, ::-1, ...]
 
+        # Place the histogram bins before the outgoing group index
+        if self.scatter_format == 'histogram':
+            xs = np.swapaxes(xs, 3, 1)
+            xs = np.swapaxes(xs, 3, 2)
+
         if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_2d(xs)
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 8a7d771ac..6256da352 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1043,8 +1043,6 @@ class XSdata(object):
                 self._scatter_matrix[i] = \
                     scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
                                    subdomains=subdomain)
-                # self._scatter_matrix[i] = \
-                #     np.swapaxes(self._scatter_matrix[i], 0, 2)
         elif self.representation == 'angle':
             msg = 'Angular-Dependent MGXS have not yet been implemented'
             raise ValueError(msg)
@@ -1124,9 +1122,9 @@ class XSdata(object):
                                        xs_type=xs_type, moment=0,
                                        subdomains=subdomain)
                 if scatter.scatter_format == 'histogram':
-                    scatt = np.sum(scatt, axis=4)
+                    scatt = np.sum(scatt, axis=0)
                 if nuscatter.scatter_format == 'histogram':
-                    nuscatt = np.sum(nuscatt, axis=4)
+                    nuscatt = np.sum(nuscatt, axis=0)
                 self._multiplicity_matrix[i] = np.divide(nuscatt, scatt)
         elif self.representation == 'angle':
             msg = 'Angular-Dependent MGXS have not yet been implemented'

From 50a40795976ea5db3a7e34110b9a105115800b5c Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sat, 12 Nov 2016 09:40:07 -0500
Subject: [PATCH 04/27] minor changes

---
 openmc/mgxs/mgxs.py    |  4 ++--
 openmc/mgxs_library.py | 15 +++++++++++----
 2 files changed, 13 insertions(+), 6 deletions(-)

diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 2fb7459b0..324cbe56c 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3776,10 +3776,10 @@ class ScatterMatrixXS(MatrixMGXS):
         if order_groups == 'increasing':
             xs = xs[:, ::-1, ::-1, ...]
 
-        # Place the histogram bins before the outgoing group index
+        # Place the histogram bins before the incoming groups
         if self.scatter_format == 'histogram':
-            xs = np.swapaxes(xs, 3, 1)
             xs = np.swapaxes(xs, 3, 2)
+            xs = np.swapaxes(xs, 2, 1)
 
         if squeeze:
             xs = np.squeeze(xs)
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 290b25424..e3af59632 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1738,11 +1738,18 @@ class XSdata(object):
             if self.representation == 'isotropic':
 
                 g_out_bounds = np.zeros((G, 2), dtype=np.int)
-
                 for g_in in range(G):
-                    nz = np.nonzero(self._scatter_matrix[i][0, g_in, :])
-                    g_out_bounds[g_in, 0] = nz[0][0]
-                    g_out_bounds[g_in, 1] = nz[0][-1]
+                    if self.scatter_format == 'legendre':
+                        nz = np.nonzero(self._scatter_matrix[i][0, g_in, :])
+                    elif self.scatter_format == 'histogram':
+                        nz = np.nonzero(np.sum(
+                            self._scatter_matrix[i][:, g_in, :], axis=0))
+                    if len(nz[0]) == 0:
+                        g_out_bounds[g_in, 0] = 0
+                        g_out_bounds[g_in, 1] = 0
+                    else:
+                        g_out_bounds[g_in, 0] = nz[0][0]
+                        g_out_bounds[g_in, 1] = nz[0][-1]
 
                 # Now create the flattened scatter matrix array
                 matrix = self._scatter_matrix[i]

From 2455388315919dca1080fd060d8e2765eea5fd92 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 13 Nov 2016 13:29:45 -0500
Subject: [PATCH 05/27] Fixed array ordering of scattering matrix

---
 openmc/mgxs/library.py     | 25 +++++++++++++++++-----
 openmc/mgxs/mgxs.py        | 17 ++++++++-------
 openmc/mgxs_library.py     | 43 ++++++++++++++++++++------------------
 scripts/openmc-update-mgxs | 40 +++++++++++++++++++++++------------
 src/mgxs_header.F90        |  6 +++---
 src/scattdata_header.F90   |  4 ++--
 6 files changed, 84 insertions(+), 51 deletions(-)

diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py
index 05cabf496..97bb6d96b 100644
--- a/openmc/mgxs/library.py
+++ b/openmc/mgxs/library.py
@@ -287,7 +287,7 @@ class Library(object):
     def by_nuclide(self, by_nuclide):
         cv.check_type('by_nuclide', by_nuclide, bool)
 
-        if by_nuclide == True and self.domain_type == 'mesh':
+        if by_nuclide and self.domain_type == 'mesh':
             raise ValueError('Unable to create MGXS library by nuclide with '
                              'mesh domain')
 
@@ -297,7 +297,7 @@ class Library(object):
     def domain_type(self, domain_type):
         cv.check_value('domain type', domain_type, openmc.mgxs.DOMAIN_TYPES)
 
-        if self.by_nuclide == True and domain_type == 'mesh':
+        if self.by_nuclide and domain_type == 'mesh':
             raise ValueError('Unable to create MGXS library by nuclide with '
                              'mesh domain')
 
@@ -372,7 +372,15 @@ class Library(object):
 
     @scatter_format.setter
     def scatter_format(self, scatter_format):
-        cv.check_value('scatter_format', scatter_format, openmc.mgxs.MU_TREATMENTS)
+        cv.check_value('scatter_format', scatter_format,
+                       openmc.mgxs.MU_TREATMENTS)
+
+        if scatter_format == 'histogram' and self.correction == 'P0':
+            msg = 'The P0 correction will be ignored since the ' \
+                  'scatter format is set to histogram'
+            warn(msg)
+            self.correction = None
+
         self._scatter_format = scatter_format
 
     @legendre_order.setter
@@ -405,6 +413,13 @@ class Library(object):
             msg = 'The histogram bins will be ignored since the ' \
                   'scatter format is set to legendre'
             warn(msg)
+        elif self.scatter_format == 'histogram':
+            if self.correction == 'P0':
+                msg = 'The P0 correction will be ignored since ' \
+                      'a histogram representation of the scattering '\
+                      'kernel is requested'
+                warn(msg, RuntimeWarning)
+                self.correction = None
 
         self._histogram_bins = histogram_bins
 
@@ -471,7 +486,7 @@ class Library(object):
                         mgxs.delayed_groups = None
                     else:
                         delayed_groups \
-                            = list(range(1,self.num_delayed_groups+1))
+                            = list(range(1, self.num_delayed_groups + 1))
                         mgxs.delayed_groups = delayed_groups
 
                 # If a tally trigger was specified, add it to the MGXS
@@ -1351,7 +1366,7 @@ class Library(object):
                          'scattering matrix is not provided.')
         # Total or transport can be present, but if using
         # self.correction=="P0", then we should use transport.
-        if (((self.correction is "P0") and
+        if (((self.correction == "P0") and
              ('nu-transport' not in self.mgxs_types))):
             error_flag = True
             warn('A "nu-transport" MGXS type is required since a "P0" '
diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 324cbe56c..036feac74 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3775,15 +3775,16 @@ class ScatterMatrixXS(MatrixMGXS):
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
             xs = xs[:, ::-1, ::-1, ...]
-
-        # Place the histogram bins before the incoming groups
-        if self.scatter_format == 'histogram':
-            xs = np.swapaxes(xs, 3, 2)
-            xs = np.swapaxes(xs, 2, 1)
-
+        # import pdb; pdb.set_trace()
         if squeeze:
-            xs = np.squeeze(xs)
-            xs = np.atleast_2d(xs)
+            # We want to squeeze out everything but the in_groups, out_groups,
+            # and, if needed, num_mu_bins dimension. These must not be squeezed
+            # so 1-group problems have the correct shape.
+            if self.scatter_format == 'histogram':
+                axes = (5, 4, 0)
+            else:
+                axes = (4, 3, 0)
+            xs = np.squeeze(xs, axis=axes)
 
         return xs
 
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index e3af59632..5256dd102 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -15,7 +15,7 @@ from openmc.checkvalue import check_type, check_value, check_greater_than, \
 # Supported incoming particle MGXS angular treatment representations
 _REPRESENTATIONS = ['isotropic', 'angle']
 _SCATTER_TYPES = ['tabular', 'legendre', 'histogram']
-_XS_SHAPES = ["[Order][G][G']", "[G]", "[G']", "[G][G']", "[DG]", "[G][DG]",
+_XS_SHAPES = ["[G][G'][Order]", "[G]", "[G']", "[G][G']", "[DG]", "[G][DG]",
               "[G'][DG]"]
 
 
@@ -134,7 +134,7 @@ class XSdata(object):
     Note that some cross sections can be input in more than one shape so they
     are listed multiple times:
 
-    [Order][G][G']: scatter_matrix
+    [G][G'][Order]: scatter_matrix
 
     [G]: total, absorption, fission, kappa_fission, nu_fission,
          prompt_nu_fission, inverse_velocity
@@ -298,9 +298,9 @@ class XSdata(object):
                                           self.num_delayed_groups)
             self._xs_shapes["[G'][DG]"] = (self.energy_groups.num_groups,
                                            self.num_delayed_groups)
-            self._xs_shapes["[Order][G][G']"] \
-                = (self.num_orders, self.energy_groups.num_groups,
-                   self.energy_groups.num_groups)
+            self._xs_shapes["[G][G'][Order]"] \
+                = (self.energy_groups.num_groups,
+                   self.energy_groups.num_groups, self.num_orders)
 
             # If representation is by angle prepend num polar and num azim
             if self.representation == 'angle':
@@ -718,7 +718,7 @@ class XSdata(object):
         """
 
         # Get the accepted shapes for this xs
-        shapes = [self.xs_shapes["[Order][G][G']"]]
+        shapes = [self.xs_shapes["[G][G'][Order]"]]
 
         # Convert to a numpy array so we can easily get the shape for checking
         scatter = np.asarray(scatter)
@@ -1534,11 +1534,10 @@ class XSdata(object):
         if self.representation == 'isotropic':
             if self.scatter_format == 'legendre':
                 # Get the scattering orders in the outermost dimension
-                self._scatter_matrix[i] = np.zeros((self.num_orders,
-                                                    self.energy_groups.num_groups,
-                                                    self.energy_groups.num_groups))
+                self._scatter_matrix[i] = \
+                    np.zeros(self.xs_shapes["[G][G'][Order]"])
                 for moment in range(self.num_orders):
-                    self._scatter_matrix[i][moment, :, :] = \
+                    self._scatter_matrix[i][:, :, moment] = \
                         scatter.get_xs(nuclides=nuclide, xs_type=xs_type,
                                        moment=moment, subdomains=subdomain)
             else:
@@ -1657,7 +1656,7 @@ class XSdata(object):
                 if self.num_polar is not None:
                     grp.attrs['num_polar'] = self.num_polar
 
-        grp.attrs['scatter_shape'] = np.string_("[Order][G][G']")
+        grp.attrs['scatter_shape'] = np.string_("[G][G'][Order]")
         if self.scatter_format is not None:
             grp.attrs['scatter_format'] = np.string_(self.scatter_format)
         if self.order is not None:
@@ -1736,14 +1735,13 @@ class XSdata(object):
             # Get the sparse scattering data to print to the library
             G = self.energy_groups.num_groups
             if self.representation == 'isotropic':
-
                 g_out_bounds = np.zeros((G, 2), dtype=np.int)
                 for g_in in range(G):
                     if self.scatter_format == 'legendre':
-                        nz = np.nonzero(self._scatter_matrix[i][0, g_in, :])
+                        nz = np.nonzero(self._scatter_matrix[i][g_in, :, 0])
                     elif self.scatter_format == 'histogram':
                         nz = np.nonzero(np.sum(
-                            self._scatter_matrix[i][:, g_in, :], axis=0))
+                            self._scatter_matrix[i][g_in, :, :], axis=1))
                     if len(nz[0]) == 0:
                         g_out_bounds[g_in, 0] = 0
                         g_out_bounds[g_in, 1] = 0
@@ -1757,8 +1755,8 @@ class XSdata(object):
                 for g_in in range(G):
                     for g_out in range(g_out_bounds[g_in, 0],
                                        g_out_bounds[g_in, 1] + 1):
-                        for l in range(len(matrix[:, g_in, g_out])):
-                            flat_scatt.append(matrix[l, g_in, g_out])
+                        for l in range(len(matrix[g_in, g_out, :])):
+                            flat_scatt.append(matrix[g_in, g_out, l])
 
                 # And write it.
                 scatt_grp = xs_grp.create_group('scatter_data')
@@ -1767,7 +1765,6 @@ class XSdata(object):
 
                 # Repeat for multiplicity
                 if self._multiplicity_matrix[i] is not None:
-
                     # Now create the flattened scatter matrix array
                     matrix = self._multiplicity_matrix[i][:, :]
                     flat_mult = []
@@ -1793,7 +1790,13 @@ class XSdata(object):
                 for p in range(Np):
                     for a in range(Na):
                         for g_in in range(G):
-                            matrix = self._scatter_matrix[i][p, a, 0, g_in, :]
+                            if self.scatter_format == 'legendre':
+                                matrix = \
+                                    self._scatter_matrix[i][p, a, g_in, :, 0]
+                            elif self.scatter_format == 'histogram':
+                                matrix = \
+                                    np.sum(self._scatter_matrix[i][p, a, g_in, :, :],
+                                           axis=1)
                             nz = np.nonzero(matrix)
                             g_out_bounds[p, a, g_in, 0] = nz[0][0]
                             g_out_bounds[p, a, g_in, 1] = nz[0][-1]
@@ -1806,8 +1809,8 @@ class XSdata(object):
                         for g_in in range(G):
                             for g_out in range(g_out_bounds[p, a, g_in, 0],
                                                g_out_bounds[p, a, g_in, 1] + 1):
-                                for l in range(len(matrix[:, g_in, g_out])):
-                                    flat_scatt.append(matrix[l, g_in, g_out])
+                                for l in range(len(matrix[g_in, g_out, :])):
+                                    flat_scatt.append(matrix[g_in, g_out, l])
 
                 # And write it.
                 scatt_grp = xs_grp.create_group('scatter_data')
diff --git a/scripts/openmc-update-mgxs b/scripts/openmc-update-mgxs
index cad48d0e3..54a553f77 100755
--- a/scripts/openmc-update-mgxs
+++ b/scripts/openmc-update-mgxs
@@ -23,12 +23,10 @@ optional arguments:
 
 from __future__ import print_function
 import os
-from shutil import move
 import warnings
 import xml.etree.ElementTree as ET
 
 import argparse
-import h5py
 import numpy as np
 
 import openmc.mgxs_library
@@ -51,7 +49,7 @@ def parse_args():
 
     if args['output'] == '':
         filename = args['input'].name
-        extension = filenameos.path.splitext()
+        extension = os.path.splitext(filename)
         if extension == '.xml':
             filename = filename[:filename.rfind('.')] + '.h5'
         args['output'] = filename
@@ -84,6 +82,8 @@ if __name__ == '__main__':
     temp = tree.find('group_structure').text.strip()
     temp = np.array(temp.split())
     group_structure = temp.astype(np.float)
+    # Convert from MeV to eV
+    group_structure *= 1.e6
     energy_groups = openmc.mgxs.EnergyGroups(group_structure)
     temp = tree.find('inverse-velocity')
     if temp is not None:
@@ -103,7 +103,7 @@ if __name__ == '__main__':
         temperature = get_data(xsdata_elem, 'kT')
         if temperature is not None:
             temperature = \
-                float(temperature) / openmc.data.K_BOLTZMANN
+                float(temperature) / openmc.data.K_BOLTZMANN * 1.E6
         else:
             temperature = 294.
         temperatures = [temperature]
@@ -163,7 +163,7 @@ if __name__ == '__main__':
         if temp is not None:
             temp = np.array(temp.split(), dtype=float)
             total = temp.astype(np.float)
-            total.shape = xsd[i].vector_shape
+            total.shape = xsd[i].xs_shapes['[G]']
             xsd[i].set_total(total, temperature)
 
         if inverse_velocity is not None:
@@ -172,41 +172,55 @@ if __name__ == '__main__':
         temp = get_data(xsdata_elem, 'absorption')
         temp = np.array(temp.split())
         absorption = temp.astype(np.float)
-        absorption.shape = xsd[i].vector_shape
+        absorption.shape = xsd[i].xs_shapes['[G]']
         xsd[i].set_absorption(absorption, temperature)
 
         temp = get_data(xsdata_elem, 'scatter')
         temp = np.array(temp.split())
         scatter = temp.astype(np.float)
-        scatter.shape = xsd[i].pn_matrix_shape
+        # This is now a flattened-array of something that started with a
+        # shape of [Order][G][G']; we need to unflatten and then switch the
+        # ordering
+        in_shape = (order_dim, energy_groups.num_groups,
+                    energy_groups.num_groups)
+        if representation == 'angle':
+            in_shape = (n_pol, n_azi) + in_shape
+            scatter.shape = in_shape
+            scatter = np.swapaxes(scatter, 2, 3)
+            scatter = np.swapaxes(scatter, 3, 4)
+        else:
+            scatter.shape = in_shape
+            scatter = np.swapaxes(scatter, 0, 1)
+            scatter = np.swapaxes(scatter, 1, 2)
+
         xsd[i].set_scatter_matrix(scatter, temperature)
 
         temp = get_data(xsdata_elem, 'multiplicity')
         if temp is not None:
             temp = np.array(temp.split())
             multiplicity = temp.astype(np.float)
-            multiplicity.shape = xsd[i].matrix_shape
+            multiplicity.shape = xsd[i].xs_shapes["[G][G']"]
             xsd[i].set_multiplicity_matrix(multiplicity, temperature)
 
         temp = get_data(xsdata_elem, 'fission')
         if temp is not None:
             temp = np.array(temp.split())
             fission = temp.astype(np.float)
-            fission.shape = xsd[i].vector_shape
+            fission.shape = xsd[i].xs_shapes['[G]']
             xsd[i].set_fission(fission, temperature)
 
         temp = get_data(xsdata_elem, 'kappa_fission')
         if temp is not None:
             temp = np.array(temp.split())
             kappa_fission = temp.astype(np.float)
-            kappa_fission.shape = xsd[i].vector_shape
+            kappa_fission.shape = xsd[i].xs_shapes['[G]']
             xsd[i].set_kappa_fission(kappa_fission, temperature)
 
         temp = get_data(xsdata_elem, 'chi')
         if temp is not None:
             temp = np.array(temp.split())
             chi = temp.astype(np.float)
-            chi.shape = xsd[i].vector_shape
+            chi.shape = xsd[i].xs_shapes['[G]']
             xsd[i].set_chi(chi, temperature)
         else:
             chi = None
@@ -216,9 +230,9 @@ if __name__ == '__main__':
             temp = np.array(temp.split())
             nu_fission = temp.astype(np.float)
             if chi is not None:
-                nu_fission.shape = xsd[i].vector_shape
+                nu_fission.shape = xsd[i].xs_shapes['[G]']
             else:
-                nu_fission.shape = xsd[i].matrix_shape
+                nu_fission.shape = xsd[i].xs_shapes["[G][G']"]
             xsd[i].set_nu_fission(nu_fission, temperature)
 
     # Build library as we go, but first we have enough to initialize it
diff --git a/src/mgxs_header.F90 b/src/mgxs_header.F90
index 17104d508..4fb1f7272 100644
--- a/src/mgxs_header.F90
+++ b/src/mgxs_header.F90
@@ -355,7 +355,7 @@ module mgxs_header
       if (attribute_exists(xs_id, "scatter_shape")) then
         call read_attribute(temp_str, xs_id, "scatter_shape")
         temp_str = trim(temp_str)
-        if (to_lower(temp_str) /= "[order][g][g']") then
+        if (to_lower(temp_str) /= "[g][g'][order]") then
           call fatal_error("Invalid scatter_shape option!")
         end if
       end if
@@ -1794,8 +1794,8 @@ module mgxs_header
             order_dim = order + 1
           end if
 
-          ! Convert temp_1d to a jagged array ((gin) % data(l, gout)) for passing
-          ! to ScattData
+          ! Convert temp_1d to a jagged array ((gin) % data(l, gout)) for
+          ! passing to ScattData
           allocate(input_scatt(energy_groups, this % n_azi, this % n_pol))
 
           index = 1
diff --git a/src/scattdata_header.F90 b/src/scattdata_header.F90
index 6004cbd19..684be88b8 100644
--- a/src/scattdata_header.F90
+++ b/src/scattdata_header.F90
@@ -274,7 +274,7 @@ contains
       ! Get this by summing the un-normalized P0 coefficient in matrix
       ! over all outgoing groups
       do gin = 1, groups
-        this % scattxs(gin) = sum(matrix(gin) % data(1, :), dim=1)
+        this % scattxs(gin) = sum(matrix(gin) % data(:, :))
       end do
 
       allocate(energy(groups))
@@ -282,7 +282,7 @@ contains
       ! while also normalizing matrix itself (making CDF of f(mu=1)=1)
       do gin = 1, groups
         allocate(energy(gin) % data(gmin(gin):gmax(gin)))
-        do gout = 1, groups
+        do gout = gmin(gin), gmax(gin)
           norm = sum(matrix(gin) % data(:, gout))
           energy(gin) % data(gout) = norm
           if (norm /= ZERO) then

From 7c4ed737afe8b9ece0b35523bd7c7030962548a6 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 13 Nov 2016 14:38:57 -0500
Subject: [PATCH 06/27] Fixing failing tests

---
 openmc/mgxs/mgxs.py                 |   9 ++++-
 tests/1d_mgxs.h5                    | Bin 128136 -> 134280 bytes
 tests/test_tallies/inputs_true.dat  |   2 +-
 tests/test_tallies/results_true.dat |   2 +-
 tests/test_tallies/test_tallies.py  |  51 ++++++++++------------------
 5 files changed, 28 insertions(+), 36 deletions(-)

diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 036feac74..1337b1fa7 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3784,7 +3784,14 @@ class ScatterMatrixXS(MatrixMGXS):
                 axes = (5, 4, 0)
             else:
                 axes = (4, 3, 0)
-            xs = np.squeeze(xs, axis=axes)
+            # Squeeze will return a ValueError if the axis has a size greater
+            # than 1, so try each axis in axes one at a time, catching the
+            # ValueError as needed.
+            for axis in axes:
+                try:
+                    xs = np.squeeze(xs, axis=axis)
+                except ValueError:
+                    pass
 
         return xs
 
diff --git a/tests/1d_mgxs.h5 b/tests/1d_mgxs.h5
index e3b85c24163fe4020435db5c5d674575f2b65be0..8f28e02cbcfb2d51e94d81bafdd97ba1220313d3 100644
GIT binary patch
delta 1872
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za2V9(cRwlOP_TL5e;Z947H`kfWc=fbOA;6+XDo0@%B^I~@($)<@L*tJU|?Wm;A0SB
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z1h$as#xm2!SWsXBgNxdMz)Blq*=S=dJ8g`GBt5E!EhlYU%S9VwxoKl855(Aw2cI);
zyx_-J@9ymH1J2N(oDT%Z86L!sMk$&Z7$CV6QXpWHhh#V0@{oK3m#@dL0FndX3NYj$
zNg201Bu(O$ha@hTd_ATQA;|=$08<_k-?-%=5r<nI5(7|qSu8;e3RVy(;Df}{4PZ=R
H!}*K=*xXlq

delta 457
zcmeB}$<gtWeS#*_7sid+>p3P1aq9E?7p0^Y#YVdWk$Nlx!{i0J7L%_jOHI7Mwz+`Q
zNQHo!$qHHun<Mm$BnYV6tl-`xG5MCRJ}-)Wljp@-L2a8{z$vjgAmNe>epMj*Zq&XK
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IWc2U`08!MZ3jhEB

diff --git a/tests/test_tallies/inputs_true.dat b/tests/test_tallies/inputs_true.dat
index 69472c8d6..a8b40554b 100644
--- a/tests/test_tallies/inputs_true.dat
+++ b/tests/test_tallies/inputs_true.dat
@@ -1 +1 @@
-b1f616bc0e342e3886b4b27eca22c4d1e55e445979254d5ba5f9ea01048f53d0e9a01c575745ae130eb34108080d2256ab9e4cb926ea0050891a44ae37ecdd88
\ No newline at end of file
+ac118c5796593df0f53491920875bbe77921882253e7f24942e365e5812d726fb3d3bab86da02b3aad93f6f8f20a090125ffa51f9fdf9aef84009702f9cc363d
\ No newline at end of file
diff --git a/tests/test_tallies/results_true.dat b/tests/test_tallies/results_true.dat
index 639e8baf3..1d6f6bfaf 100644
--- a/tests/test_tallies/results_true.dat
+++ b/tests/test_tallies/results_true.dat
@@ -1 +1 @@
-ceb1420d48e097185dd0798a495676c8e968c37c6e75fd6232137a4df8f6fae33d8232b95c68f6479815a014d20ccfc7611f96b22fcb7da159b42346e00cdf4e
\ No newline at end of file
+a8172f7492fcc69d21f53c20523ffd0ad2882a753a3e1d263d135153cc6b3ee8d8e38f8823a4a2eb3288d730579892875d2d19f85f083dd659f91414988115ea
\ No newline at end of file
diff --git a/tests/test_tallies/test_tallies.py b/tests/test_tallies/test_tallies.py
index 9b48729ef..9e525d2cf 100644
--- a/tests/test_tallies/test_tallies.py
+++ b/tests/test_tallies/test_tallies.py
@@ -3,6 +3,7 @@
 import os
 import sys
 sys.path.insert(0, os.pardir)
+import numpy as np
 from testing_harness import PyAPITestHarness
 from openmc.filter import *
 from openmc import Mesh, Tally, Tallies
@@ -21,33 +22,27 @@ class TalliesTestHarness(PyAPITestHarness):
         self._input_set.settings.source = Source(space=Box(
             [-160, -160, -183], [160, 160, 183]))
 
-        azimuthal_bins = (-3.1416, -1.8850, -0.6283, 0.6283, 1.8850, 3.1416)
-        azimuthal_filter1 = AzimuthalFilter(azimuthal_bins)
+        azimuthal_bins = (-3.14159, -1.8850, -0.6283, 0.6283, 1.8850, 3.14159)
+        azimuthal_filter = AzimuthalFilter(azimuthal_bins)
         azimuthal_tally1 = Tally()
-        azimuthal_tally1.filters = [azimuthal_filter1]
+        azimuthal_tally1.filters = [azimuthal_filter]
         azimuthal_tally1.scores = ['flux']
         azimuthal_tally1.estimator = 'tracklength'
 
         azimuthal_tally2 = Tally()
-        azimuthal_tally2.filters = [azimuthal_filter1]
+        azimuthal_tally2.filters = [azimuthal_filter]
         azimuthal_tally2.scores = ['flux']
         azimuthal_tally2.estimator = 'analog'
 
-        azimuthal_filter2 = AzimuthalFilter(5)
-        azimuthal_tally3 = Tally()
-        azimuthal_tally3.filters = [azimuthal_filter2]
-        azimuthal_tally3.scores = ['flux']
-        azimuthal_tally3.estimator = 'tracklength'
-
         mesh_2x2 = Mesh(mesh_id=1)
         mesh_2x2.lower_left  = [-182.07, -182.07]
         mesh_2x2.upper_right = [182.07,  182.07]
         mesh_2x2.dimension = [2, 2]
         mesh_filter = MeshFilter(mesh_2x2)
-        azimuthal_tally4 = Tally()
-        azimuthal_tally4.filters = [azimuthal_filter2, mesh_filter]
-        azimuthal_tally4.scores = ['flux']
-        azimuthal_tally4.estimator = 'tracklength'
+        azimuthal_tally3 = Tally()
+        azimuthal_tally3.filters = [azimuthal_filter, mesh_filter]
+        azimuthal_tally3.scores = ['flux']
+        azimuthal_tally3.estimator = 'tracklength'
 
         cellborn_tally = Tally()
         cellborn_tally.filters = [CellbornFilter((10, 21, 22, 23))]
@@ -76,20 +71,17 @@ class TalliesTestHarness(PyAPITestHarness):
         material_tally.filters = [MaterialFilter((1, 2, 3, 4))]
         material_tally.scores = ['total']
 
+        mu_bins = (-1.0, -0.5, 0.0, 0.5, 1.0)
+        mu_filter = MuFilter(mu_bins)
         mu_tally1 = Tally()
-        mu_tally1.filters = [MuFilter((-1.0, -0.5, 0.0, 0.5, 1.0))]
+        mu_tally1.filters = [mu_filter]
         mu_tally1.scores = ['scatter', 'nu-scatter']
 
-        mu_filter = MuFilter(5)
         mu_tally2 = Tally()
-        mu_tally2.filters = [mu_filter]
+        mu_tally2.filters = [mu_filter, mesh_filter]
         mu_tally2.scores = ['scatter', 'nu-scatter']
 
-        mu_tally3 = Tally()
-        mu_tally3.filters = [mu_filter, mesh_filter]
-        mu_tally3.scores = ['scatter', 'nu-scatter']
-
-        polar_bins = (0.0, 0.6283, 1.2566, 1.8850, 2.5132, 3.1416)
+        polar_bins = (0.0, 0.6283, 1.2566, 1.8850, 2.5132, 3.14159)
         polar_filter = PolarFilter(polar_bins)
         polar_tally1 = Tally()
         polar_tally1.filters = [polar_filter]
@@ -101,17 +93,11 @@ class TalliesTestHarness(PyAPITestHarness):
         polar_tally2.scores = ['flux']
         polar_tally2.estimator = 'analog'
 
-        polar_filter2 = PolarFilter((5,))
         polar_tally3 = Tally()
-        polar_tally3.filters = [polar_filter2]
+        polar_tally3.filters = [polar_filter, mesh_filter]
         polar_tally3.scores = ['flux']
         polar_tally3.estimator = 'tracklength'
 
-        polar_tally4 = Tally()
-        polar_tally4.filters = [polar_filter2, mesh_filter]
-        polar_tally4.scores = ['flux']
-        polar_tally4.estimator = 'tracklength'
-
         universe_tally = Tally()
         universe_tally.filters = [UniverseFilter((1, 2, 3, 4, 6, 8))]
         universe_tally.scores = ['total']
@@ -173,10 +159,9 @@ class TalliesTestHarness(PyAPITestHarness):
         self._input_set.tallies = Tallies()
         self._input_set.tallies += (
             [azimuthal_tally1, azimuthal_tally2, azimuthal_tally3,
-             azimuthal_tally4, cellborn_tally, dg_tally, energy_tally,
-             energyout_tally, transfer_tally, material_tally, mu_tally1,
-             mu_tally2, mu_tally3, polar_tally1, polar_tally2, polar_tally3,
-             polar_tally4, universe_tally])
+             cellborn_tally, dg_tally, energy_tally, energyout_tally,
+             transfer_tally, material_tally, mu_tally1, mu_tally2,
+             polar_tally1, polar_tally2, polar_tally3, universe_tally])
         self._input_set.tallies += score_tallies
         self._input_set.tallies += flux_tallies
         self._input_set.tallies += (scatter_tally1, scatter_tally2)

From 1a921e7d08fc41b72bf1dd65cd17e922222b78b1 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 13 Nov 2016 14:56:57 -0500
Subject: [PATCH 07/27] Fixed final failing test

---
 tests/test_mg_tallies/results_true.dat | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_mg_tallies/results_true.dat b/tests/test_mg_tallies/results_true.dat
index a765c0ba0..8ab726bbb 100644
--- a/tests/test_mg_tallies/results_true.dat
+++ b/tests/test_mg_tallies/results_true.dat
@@ -1 +1 @@
-3d2ce1b8bdd558fe9f8560e8bb91455e1fedd80a47349344399e22f5b0fac1391f1721e7f12a42bb0c458fd6c87ebf9fa38fe9539fcf69292b21cebf8e5f8989
\ No newline at end of file
+864328b2c4f3c4bfa9c80c756acbedac6fbdf3d502c03c2f2a3e7461b774729c47a55341c9515eff246e1bd445485f0d0a05a5712663ee499046afdbe0c77aef
\ No newline at end of file

From df7ae534138080dedfa3e351cfe068b64f54dd2a Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 13 Nov 2016 15:27:06 -0500
Subject: [PATCH 08/27] Cleaned up mgxs_library and made sure the mgxs-part-iv
 notebook was up to date

---
 .../pythonapi/examples/mgxs-part-iv.ipynb     | 217 ++++++++++--------
 openmc/mgxs_library.py                        | 140 +++++------
 2 files changed, 172 insertions(+), 185 deletions(-)

diff --git a/docs/source/pythonapi/examples/mgxs-part-iv.ipynb b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb
index cd011d862..312bb8ee6 100644
--- a/docs/source/pythonapi/examples/mgxs-part-iv.ipynb
+++ b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb
@@ -429,7 +429,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN\nAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAADFBMVEX////pgJFyEhJNv8RV\nUZDeAAAAAWJLR0QAiAUdSAAAAAd0SU1FB+AKHxEkM8uGp70AAAWFSURBVGje7Zs7cttADIZ9CSvX\ncrP0iCxUqbBc8Ag6xR6BhV2EvYvwFD4CCx1ABT1jMdgndpegRQnOrCbjpPlGESISC4A/gd27e8H5\n83CX3b4+iKJrRHkS4vkghMPBonRYWGwtfgD2YN+dRDUOoh6lACw0Noi9w2fESuEoAR/uVuMolX03\n9oXGT7F3eFL2iEfhUX1f4cPdL/ishs+68ai+udE4xPhexbjX2FfjGNoPj/DPNX4Tsd+EODr8FvsV\ndf1Hd9P2VvCi4+s/aXvrf+upAD+1/9GV1mkOH5X9vV6THtfvACslcaUCbESL61drBPtdI8SrFMWr\nELsXCkuFDYW75gbiP7d9Cf7bAYI/aCwUShrBvh30+lWQkzVgZ/HD4OixNCgcQpJ3BxU/Ln91elKo\nM5VEE38QtJ+Yv6cQ9xjKNYayyl8TypP8DfJnQ2H/b/N3ye9P83cT33SQv/sQh9gV7zZ/0dNj5HQa\nC5vVzv9+/WFN2w8KVaZ2BwL1+pv4g0x1QRfjq0dB4Q3kT277oP6VNL6gKxNU9a8zK+WLbi/Wwpdi\nhbboKqyxFOulHMj6v4W/AXbmUeAxrv9J/CqEBXaRKsXaodD4nsYvkT/G6H1D4SR/iPy1Roj9JsQ5\ne18/7EUHv1+Fvx/Xj5V9Ugb5K8TW4TZEEdcvoz/up0VTe9qsVIppKVX6a7D6y9ZvwEKjrtQxPtv6\nfXII9vCxKOGaIeAIfEF8IvAG8ie3vRK9rRQl+PPpSctbhfpTUCpviH+kxsZgpT91+snoX1l49KK3\niUQvICRy5aUw6l8leoVwoo3Uv1rKreF/UFLY6d9QP4L9Wf2r7EP9GOSfcsjZ56f60kz+XmVPXv+R\nuP49ff0T/53Rv6n/7m2lvXT9Wqd/VUz8hvh5M/ED6ILmt4mfHYZSaePnTWpsf/SvqV9O6dLYYClL\nEetnoH/LBLFoBvrX189uTv8++kot5vTvQD4/9jP690g9P/4z/bvo/XVG/xYoZZx+8fr3MxAtsf7t\nUOkG2JqsTtCIpgCt/qX1226KqZS7gfzJbe+c9jLrtIZ8lXD+s4umlW6AKIVrlML2/cXjgPFjlJqI\nRC+Fj0bVJe+vSh56pSdR6YkQ1ygF10Wqf0FeLta/iKn9Mv1L24ti2e+7W4n1b3T/W+L+t9H9T/Sv\nVboUmqJJon1/hZq8LnzRDlDrX1u0xRT1+6vEpomMmyYkqi95vIH8yW1PN+122KkLcNLKi/WTF01z\n/cNASrWE/l3ev6T17zX909z9X27/euK/Rf3zWP+Waf9eEv37KkWJ+rfDl6ZglNDa+cEBhwYDvkoN\nP/rX69814NaI3imq0l7OYDy/qSdDGwr7r+Y3VbzoKZr6XX2lfxfOb87qXzr+b1j/Xlp/nP6dn98M\ncdH7cn7zjPObKsYWS3Eb9w8n85smHtqQuPuZ30T2dlIT6F9xFl+n8xslegL9a4c2KRr9W4rp/GYq\numiM9Nec/j2v/yj9u1h//hv9e93vc++f63/u+rPjL3f+5Lbn1j9m/eXWf+7zh/v8+2b9e/Hzn6s/\nuPqHrb8g71n6L3f+5Lbnvn8w33+4718/+5d47//c/gO7/5E7/nPbc/tv3P4fs//I7X9y+6/fqH+v\n6j9z+9/c/ju3/8+eP+TOn9z23PkXc/7Gnf9x5483q38Xzn+582fu/Js9fy8kb/6fO39y23P3n3S8\n/S/c/Tfc/T83uX/pgv1XE/9duP+Lu/+Mvf8td/znti8kb/8ld/9nx9t/Sjw/Ltr/yt1/+337f6/b\nf0zoB3nJ/ucVc/81d/83e/957vzJbc89/8A8f8E9/5HE78XnT/4H/cs5f8Q9/8Q9f8U+/5U7f3Lb\nc88fdrzzjyvm+cuf/Uu887/c88fs88954/8vO4SjPC+2QRIAAAAldEVYdGRhdGU6Y3JlYXRlADIw\nMTYtMTAtMzFUMTI6MzY6NTEtMDU6MDD2oqCYAAAAJXRFWHRkYXRlOm1vZGlmeQAyMDE2LTEwLTMx\nVDEyOjM2OjUxLTA1OjAwh/8YJAAAAABJRU5ErkJggg==\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAACBjSFJN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\nVDE1OjI0OjU3LTA1OjAw2FkRRwAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
@@ -575,7 +575,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/romano/openmc/openmc/mgxs/library.py:370: RuntimeWarning: The P0 correction will be ignored since the scattering order 0 is greater than zero\n",
+      "/home/nelsonag/git/openmc/openmc/mgxs/library.py:398: RuntimeWarning: The P0 correction will be ignored since the scattering order 0 is greater than zero\n",
       "  warn(msg, RuntimeWarning)\n"
      ]
     }
@@ -731,9 +731,9 @@
       "         Copyright | 2011-2016 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | da5563eddb5f2c2d6b2c9839d518de40962b78f2\n",
-      "         Date/Time | 2016-10-31 12:36:52\n",
-      "    OpenMP Threads | 4\n",
+      "          Git SHA1 | 1a921e7d08fc41b72bf1dd65cd17e922222b78b1\n",
+      "         Date/Time | 2016-11-13 15:24:57\n",
+      "    OpenMP Threads | 8\n",
       "\n",
       " ===========================================================================\n",
       " ========================>     INITIALIZATION     <=========================\n",
@@ -743,12 +743,12 @@
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
-      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
-      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
-      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
-      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
-      " Reading B10 from /home/romano/openmc/scripts/nndc_hdf5/B10.h5\n",
+      " Reading U235 from /opt/xsdata/nndc/U235.h5\n",
+      " Reading U238 from /opt/xsdata/nndc/U238.h5\n",
+      " Reading O16 from /opt/xsdata/nndc/O16.h5\n",
+      " Reading Zr90 from /opt/xsdata/nndc/Zr90.h5\n",
+      " Reading H1 from /opt/xsdata/nndc/H1.h5\n",
+      " Reading B10 from /opt/xsdata/nndc/B10.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
@@ -819,20 +819,20 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  5.3479E-01 seconds\n",
-      "   Reading cross sections          =  3.8403E-01 seconds\n",
-      " Total time in simulation          =  3.9455E+01 seconds\n",
-      "   Time in transport only          =  3.9331E+01 seconds\n",
-      "   Time in inactive batches        =  4.6776E+00 seconds\n",
-      "   Time in active batches          =  3.4778E+01 seconds\n",
-      "   Time synchronizing fission bank =  1.0514E-02 seconds\n",
-      "     Sampling source sites         =  7.2826E-03 seconds\n",
-      "     SEND/RECV source sites        =  3.1267E-03 seconds\n",
-      "   Time accumulating tallies       =  3.7644E-04 seconds\n",
-      " Total time for finalization       =  7.7600E-06 seconds\n",
-      " Total time elapsed                =  4.0029E+01 seconds\n",
-      " Calculation Rate (inactive)       =  10689.2 neutrons/second\n",
-      " Calculation Rate (active)         =  5750.82 neutrons/second\n",
+      " Total time for initialization     =  2.4361E-01 seconds\n",
+      "   Reading cross sections          =  1.6584E-01 seconds\n",
+      " Total time in simulation          =  7.3766E+00 seconds\n",
+      "   Time in transport only          =  7.3482E+00 seconds\n",
+      "   Time in inactive batches        =  8.5442E-01 seconds\n",
+      "   Time in active batches          =  6.5222E+00 seconds\n",
+      "   Time synchronizing fission bank =  4.9435E-03 seconds\n",
+      "     Sampling source sites         =  3.3815E-03 seconds\n",
+      "     SEND/RECV source sites        =  1.5249E-03 seconds\n",
+      "   Time accumulating tallies       =  9.5694E-05 seconds\n",
+      " Total time for finalization       =  2.9260E-06 seconds\n",
+      " Total time elapsed                =  7.6377E+00 seconds\n",
+      " Calculation Rate (inactive)       =  58519.0 neutrons/second\n",
+      " Calculation Rate (active)         =  30664.7 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
@@ -970,7 +970,20 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/nelsonag/git/openmc/openmc/tallies.py:1944: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  self_rel_err = data['self']['std. dev.'] / data['self']['mean']\n",
+      "/home/nelsonag/git/openmc/openmc/tallies.py:1945: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  other_rel_err = data['other']['std. dev.'] / data['other']['mean']\n",
+      "/home/nelsonag/git/openmc/openmc/tallies.py:1946: RuntimeWarning: invalid value encountered in true_divide\n",
+      "  new_tally._mean = data['self']['mean'] / data['other']['mean']\n"
+     ]
+    }
+   ],
    "source": [
     "# Create a MGXS File which can then be written to disk\n",
     "mgxs_file = mgxs_lib.create_mg_library(xs_type='macro', xsdata_names=['fuel', 'zircaloy', 'water'])\n",
@@ -1107,9 +1120,9 @@
       "         Copyright | 2011-2016 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | da5563eddb5f2c2d6b2c9839d518de40962b78f2\n",
-      "         Date/Time | 2016-10-31 12:37:32\n",
-      "    OpenMP Threads | 4\n",
+      "          Git SHA1 | 1a921e7d08fc41b72bf1dd65cd17e922222b78b1\n",
+      "         Date/Time | 2016-11-13 15:25:05\n",
+      "    OpenMP Threads | 8\n",
       "\n",
       " ===========================================================================\n",
       " ========================>     INITIALIZATION     <=========================\n",
@@ -1133,56 +1146,56 @@
       "\n",
       "  Bat./Gen.      k            Average k         \n",
       "  =========   ========   ====================   \n",
-      "        1/1    1.00711                       \n",
-      "        2/1    1.01538                       \n",
-      "        3/1    1.01664                       \n",
-      "        4/1    1.03592                       \n",
-      "        5/1    1.00771                       \n",
-      "        6/1    1.00555                       \n",
-      "        7/1    1.02573                       \n",
-      "        8/1    1.04322                       \n",
-      "        9/1    1.02270                       \n",
-      "       10/1    1.02354                       \n",
-      "       11/1    1.02023                       \n",
-      "       12/1    1.03047    1.02535 +/- 0.00512\n",
-      "       13/1    1.04476    1.03182 +/- 0.00711\n",
-      "       14/1    1.02223    1.02942 +/- 0.00557\n",
-      "       15/1    1.02082    1.02770 +/- 0.00465\n",
-      "       16/1    1.01472    1.02554 +/- 0.00437\n",
-      "       17/1    1.02104    1.02489 +/- 0.00375\n",
-      "       18/1    1.04471    1.02737 +/- 0.00408\n",
-      "       19/1    1.02806    1.02745 +/- 0.00360\n",
-      "       20/1    1.02044    1.02675 +/- 0.00330\n",
-      "       21/1    1.02592    1.02667 +/- 0.00298\n",
-      "       22/1    1.02242    1.02632 +/- 0.00275\n",
-      "       23/1    0.99969    1.02427 +/- 0.00325\n",
-      "       24/1    1.02213    1.02412 +/- 0.00301\n",
-      "       25/1    1.02080    1.02390 +/- 0.00281\n",
-      "       26/1    1.01033    1.02305 +/- 0.00277\n",
-      "       27/1    1.02881    1.02339 +/- 0.00262\n",
-      "       28/1    1.01649    1.02300 +/- 0.00250\n",
-      "       29/1    1.03817    1.02380 +/- 0.00250\n",
-      "       30/1    1.00958    1.02309 +/- 0.00247\n",
-      "       31/1    1.01811    1.02285 +/- 0.00236\n",
-      "       32/1    1.02709    1.02305 +/- 0.00226\n",
-      "       33/1    1.01823    1.02284 +/- 0.00217\n",
-      "       34/1    1.01208    1.02239 +/- 0.00213\n",
-      "       35/1    1.01380    1.02204 +/- 0.00207\n",
-      "       36/1    1.02358    1.02210 +/- 0.00199\n",
-      "       37/1    1.03653    1.02264 +/- 0.00199\n",
-      "       38/1    1.03117    1.02294 +/- 0.00194\n",
-      "       39/1    1.00915    1.02247 +/- 0.00193\n",
-      "       40/1    1.03107    1.02275 +/- 0.00189\n",
-      "       41/1    1.02316    1.02277 +/- 0.00182\n",
-      "       42/1    1.02677    1.02289 +/- 0.00177\n",
-      "       43/1    0.99361    1.02200 +/- 0.00193\n",
-      "       44/1    1.04841    1.02278 +/- 0.00203\n",
-      "       45/1    0.99768    1.02206 +/- 0.00210\n",
-      "       46/1    1.02694    1.02220 +/- 0.00204\n",
-      "       47/1    1.03540    1.02256 +/- 0.00202\n",
-      "       48/1    1.03539    1.02289 +/- 0.00199\n",
-      "       49/1    1.02498    1.02295 +/- 0.00194\n",
-      "       50/1    1.00692    1.02255 +/- 0.00193\n",
+      "        1/1    0.98369                       \n",
+      "        2/1    1.01520                       \n",
+      "        3/1    1.03642                       \n",
+      "        4/1    1.02658                       \n",
+      "        5/1    1.03102                       \n",
+      "        6/1    1.05382                       \n",
+      "        7/1    1.01978                       \n",
+      "        8/1    1.01753                       \n",
+      "        9/1    1.02420                       \n",
+      "       10/1    0.99889                       \n",
+      "       11/1    1.04874                       \n",
+      "       12/1    1.01382    1.03128 +/- 0.01746\n",
+      "       13/1    1.03987    1.03414 +/- 0.01048\n",
+      "       14/1    1.02282    1.03131 +/- 0.00793\n",
+      "       15/1    1.03282    1.03162 +/- 0.00615\n",
+      "       16/1    0.99669    1.02579 +/- 0.00769\n",
+      "       17/1    1.00052    1.02218 +/- 0.00743\n",
+      "       18/1    1.01124    1.02082 +/- 0.00658\n",
+      "       19/1    1.00629    1.01920 +/- 0.00602\n",
+      "       20/1    1.05322    1.02260 +/- 0.00637\n",
+      "       21/1    1.00763    1.02124 +/- 0.00592\n",
+      "       22/1    1.01841    1.02101 +/- 0.00541\n",
+      "       23/1    1.03430    1.02203 +/- 0.00508\n",
+      "       24/1    1.03064    1.02264 +/- 0.00474\n",
+      "       25/1    1.03272    1.02331 +/- 0.00447\n",
+      "       26/1    1.01226    1.02262 +/- 0.00424\n",
+      "       27/1    1.00883    1.02181 +/- 0.00406\n",
+      "       28/1    1.02712    1.02211 +/- 0.00384\n",
+      "       29/1    1.03146    1.02260 +/- 0.00367\n",
+      "       30/1    1.02964    1.02295 +/- 0.00350\n",
+      "       31/1    0.99832    1.02178 +/- 0.00353\n",
+      "       32/1    1.03420    1.02234 +/- 0.00341\n",
+      "       33/1    1.01860    1.02218 +/- 0.00326\n",
+      "       34/1    1.03328    1.02264 +/- 0.00316\n",
+      "       35/1    1.01865    1.02248 +/- 0.00303\n",
+      "       36/1    1.02643    1.02264 +/- 0.00292\n",
+      "       37/1    1.01070    1.02219 +/- 0.00284\n",
+      "       38/1    1.01871    1.02207 +/- 0.00274\n",
+      "       39/1    0.98827    1.02090 +/- 0.00289\n",
+      "       40/1    1.01740    1.02079 +/- 0.00279\n",
+      "       41/1    1.02920    1.02106 +/- 0.00272\n",
+      "       42/1    1.02496    1.02118 +/- 0.00263\n",
+      "       43/1    1.04288    1.02184 +/- 0.00264\n",
+      "       44/1    1.03749    1.02230 +/- 0.00260\n",
+      "       45/1    1.04338    1.02290 +/- 0.00259\n",
+      "       46/1    1.03146    1.02314 +/- 0.00253\n",
+      "       47/1    1.04668    1.02377 +/- 0.00254\n",
+      "       48/1    1.02707    1.02386 +/- 0.00248\n",
+      "       49/1    1.02589    1.02391 +/- 0.00241\n",
+      "       50/1    1.02100    1.02384 +/- 0.00235\n",
       " Creating state point statepoint.50.h5...\n",
       "\n",
       " ===========================================================================\n",
@@ -1192,27 +1205,27 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  3.6445E-02 seconds\n",
-      "   Reading cross sections          =  4.9377E-03 seconds\n",
-      " Total time in simulation          =  3.0983E+01 seconds\n",
-      "   Time in transport only          =  3.0902E+01 seconds\n",
-      "   Time in inactive batches        =  3.2106E+00 seconds\n",
-      "   Time in active batches          =  2.7772E+01 seconds\n",
-      "   Time synchronizing fission bank =  9.7451E-03 seconds\n",
-      "     Sampling source sites         =  6.9236E-03 seconds\n",
-      "     SEND/RECV source sites        =  2.6796E-03 seconds\n",
-      "   Time accumulating tallies       =  3.2976E-04 seconds\n",
-      " Total time for finalization       =  7.4870E-06 seconds\n",
-      " Total time elapsed                =  3.1057E+01 seconds\n",
-      " Calculation Rate (inactive)       =  15573.4 neutrons/second\n",
-      " Calculation Rate (active)         =  7201.41 neutrons/second\n",
+      " Total time for initialization     =  2.5229E-02 seconds\n",
+      "   Reading cross sections          =  1.1001E-02 seconds\n",
+      " Total time in simulation          =  7.3074E+00 seconds\n",
+      "   Time in transport only          =  7.2846E+00 seconds\n",
+      "   Time in inactive batches        =  6.2995E-01 seconds\n",
+      "   Time in active batches          =  6.6774E+00 seconds\n",
+      "   Time synchronizing fission bank =  4.8069E-03 seconds\n",
+      "     Sampling source sites         =  3.3693E-03 seconds\n",
+      "     SEND/RECV source sites        =  1.3618E-03 seconds\n",
+      "   Time accumulating tallies       =  8.0542E-05 seconds\n",
+      " Total time for finalization       =  2.9260E-06 seconds\n",
+      " Total time elapsed                =  7.3508E+00 seconds\n",
+      " Calculation Rate (inactive)       =  79370.9 neutrons/second\n",
+      " Calculation Rate (active)         =  29951.7 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
-      " k-effective (Collision)     =  1.02346 +/-  0.00203\n",
-      " k-effective (Track-length)  =  1.02255 +/-  0.00193\n",
-      " k-effective (Absorption)    =  1.02775 +/-  0.00139\n",
-      " Combined k-effective        =  1.02594 +/-  0.00120\n",
+      " k-effective (Collision)     =  1.02315 +/-  0.00205\n",
+      " k-effective (Track-length)  =  1.02384 +/-  0.00235\n",
+      " k-effective (Absorption)    =  1.02372 +/-  0.00194\n",
+      " Combined k-effective        =  1.02369 +/-  0.00173\n",
       " Leakage Fraction            =  0.00000 +/-  0.00000\n",
       "\n"
      ]
@@ -1294,8 +1307,8 @@
      "output_type": "stream",
      "text": [
       "Continuous-Energy keff = 1.024739\n",
-      "Multi-Group keff = 1.025941\n",
-      "bias [pcm]: -120.2\n"
+      "Multi-Group keff = 1.023689\n",
+      "bias [pcm]: 105.0\n"
      ]
     }
    ],
@@ -1392,7 +1405,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.text.Text at 0x7f4c89d6c4a8>"
+       "<matplotlib.text.Text at 0x7f4ad8f44eb8>"
       ]
      },
      "execution_count": 40,
@@ -1401,9 +1414,9 @@
     },
     {
      "data": {
-      "image/png": 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lADkgd47r/kO15KlT98WYgvWCQPgrl8DK2aKdHwMNRJ1rlm0QdTbKs5Cid+Bk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\nz6tq0gAAAABJRU5ErkJggg==\n",
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mtjpx7/MDZ9nQfDea+IJYp7T1WHLyEMRlKpUMbZz8W1imL1hyDWqx9UsVHkKYRDycUrjk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\nIiI5p2RAREQk55QMiIiI5Nz/A+/fWb9QS6P+AAAAAElFTkSuQmCC\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f4c8c1169b0>"
+       "<matplotlib.figure.Figure at 0x7f4ad8fc5940>"
       ]
      },
      "metadata": {},
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 5256dd102..1f13e18ee 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1735,108 +1735,82 @@ class XSdata(object):
             # Get the sparse scattering data to print to the library
             G = self.energy_groups.num_groups
             if self.representation == 'isotropic':
-                g_out_bounds = np.zeros((G, 2), dtype=np.int)
-                for g_in in range(G):
-                    if self.scatter_format == 'legendre':
-                        nz = np.nonzero(self._scatter_matrix[i][g_in, :, 0])
-                    elif self.scatter_format == 'histogram':
-                        nz = np.nonzero(np.sum(
-                            self._scatter_matrix[i][g_in, :, :], axis=1))
-                    if len(nz[0]) == 0:
-                        g_out_bounds[g_in, 0] = 0
-                        g_out_bounds[g_in, 1] = 0
-                    else:
-                        g_out_bounds[g_in, 0] = nz[0][0]
-                        g_out_bounds[g_in, 1] = nz[0][-1]
-
-                # Now create the flattened scatter matrix array
-                matrix = self._scatter_matrix[i]
-                flat_scatt = []
-                for g_in in range(G):
-                    for g_out in range(g_out_bounds[g_in, 0],
-                                       g_out_bounds[g_in, 1] + 1):
-                        for l in range(len(matrix[g_in, g_out, :])):
-                            flat_scatt.append(matrix[g_in, g_out, l])
-
-                # And write it.
-                scatt_grp = xs_grp.create_group('scatter_data')
-                scatt_grp.create_dataset("scatter_matrix",
-                                         data=np.array(flat_scatt))
-
-                # Repeat for multiplicity
-                if self._multiplicity_matrix[i] is not None:
-                    # Now create the flattened scatter matrix array
-                    matrix = self._multiplicity_matrix[i][:, :]
-                    flat_mult = []
-                    for g_in in range(G):
-                        for g_out in range(g_out_bounds[g_in, 0],
-                                           g_out_bounds[g_in, 1] + 1):
-                            flat_mult.append(matrix[g_in, g_out])
-
-                    scatt_grp.create_dataset("multiplicity matrix",
-                                             data=np.array(flat_mult))
-
-                # And finally, adjust g_out_bounds for 1-based group counting
-                # and write it.
-                g_out_bounds[:, :] += 1
-                scatt_grp.create_dataset("g_min", data=g_out_bounds[:, 0])
-                scatt_grp.create_dataset("g_max", data=g_out_bounds[:, 1])
-
+                Np = 1
+                Na = 1
             elif self.representation == 'angle':
                 Np = self.num_polar
                 Na = self.num_azimuthal
-                g_out_bounds = np.zeros((Np, Na, G, 2), dtype=np.int)
 
-                for p in range(Np):
-                    for a in range(Na):
-                        for g_in in range(G):
-                            if self.scatter_format == 'legendre':
+            g_out_bounds = np.zeros((Np, Na, G, 2), dtype=np.int)
+            for p in range(Np):
+                for a in range(Na):
+                    for g_in in range(G):
+                        if self.scatter_format == 'legendre':
+                            if self.representation == 'isotropic':
+                                matrix = \
+                                    self._scatter_matrix[i][g_in, :, 0]
+                            elif self.representation == 'angle':
                                 matrix = \
                                     self._scatter_matrix[i][p, a, g_in, :, 0]
-                            elif self.scatter_format == 'histogram':
+                        elif self.scatter_format == 'histogram':
+                            if self.representation == 'isotropic':
+                                matrix = \
+                                    np.sum(self._scatter_matrix[i][g_in, :, :],
+                                           axis=1)
+                            elif self.representation == 'angle':
                                 matrix = \
                                     np.sum(self._scatter_matrix[i][p, a, g_in, :, :],
                                            axis=1)
-                            nz = np.nonzero(matrix)
-                            g_out_bounds[p, a, g_in, 0] = nz[0][0]
-                            g_out_bounds[p, a, g_in, 1] = nz[0][-1]
+                        nz = np.nonzero(matrix)
+                        g_out_bounds[p, a, g_in, 0] = nz[0][0]
+                        g_out_bounds[p, a, g_in, 1] = nz[0][-1]
+
+            # Now create the flattened scatter matrix array
+            flat_scatt = []
+            for p in range(Np):
+                for a in range(Na):
+                    if self.representation == 'isotropic':
+                        matrix = self._scatter_matrix[i][:, :, :]
+                    elif self.representation == 'angle':
+                        matrix = self._scatter_matrix[i][p, a, :, :, :]
+                    for g_in in range(G):
+                        for g_out in range(g_out_bounds[p, a, g_in, 0],
+                                           g_out_bounds[p, a, g_in, 1] + 1):
+                            for l in range(len(matrix[g_in, g_out, :])):
+                                flat_scatt.append(matrix[g_in, g_out, l])
+
+            # And write it.
+            scatt_grp = xs_grp.create_group('scatter_data')
+            scatt_grp.create_dataset("scatter_matrix",
+                                     data=np.array(flat_scatt))
+
+            # Repeat for multiplicity
+            if self._multiplicity_matrix[i] is not None:
 
                 # Now create the flattened scatter matrix array
-                flat_scatt = []
+                flat_mult = []
                 for p in range(Np):
                     for a in range(Na):
-                        matrix = self._scatter_matrix[i][p, a, :, :, :]
+                        if self.representation == 'isotropic':
+                            matrix = self._multiplicity_matrix[i][:, :]
+                        elif self.representation == 'angle':
+                            matrix = self._multiplicity_matrix[i][p, a, :, :]
                         for g_in in range(G):
                             for g_out in range(g_out_bounds[p, a, g_in, 0],
                                                g_out_bounds[p, a, g_in, 1] + 1):
-                                for l in range(len(matrix[g_in, g_out, :])):
-                                    flat_scatt.append(matrix[g_in, g_out, l])
+                                flat_mult.append(matrix[g_in, g_out])
 
                 # And write it.
-                scatt_grp = xs_grp.create_group('scatter_data')
-                scatt_grp.create_dataset("scatter_matrix",
-                                         data=np.array(flat_scatt))
+                scatt_grp.create_dataset("multiplicity_matrix",
+                                         data=np.array(flat_mult))
 
-                # Repeat for multiplicity
-                if self._multiplicity_matrix[i] is not None:
-
-                    # Now create the flattened scatter matrix array
-                    flat_mult = []
-                    for p in range(Np):
-                        for a in range(Na):
-                            matrix = self._multiplicity_matrix[i][p, a, :, :]
-                            for g_in in range(G):
-                                for g_out in range(g_out_bounds[p, a, g_in, 0],
-                                                   g_out_bounds[p, a, g_in, 1] + 1):
-                                    flat_mult.append(matrix[g_in, g_out])
-
-                    # And write it.
-                    scatt_grp.create_dataset("multiplicity_matrix",
-                                             data=np.array(flat_mult))
-
-                # And finally, adjust g_out_bounds for 1-based group counting
-                # and write it.
-                g_out_bounds[:, :, :, :] += 1
+            # And finally, adjust g_out_bounds for 1-based group counting
+            # and write it.
+            g_out_bounds[:, :, :, :] += 1
+            if self.representation == 'isotropic':
+                scatt_grp.create_dataset("g_min", data=g_out_bounds[0, 0, :, 0])
+                scatt_grp.create_dataset("g_max", data=g_out_bounds[0, 0, :, 1])
+            elif self.representation == 'angle':
                 scatt_grp.create_dataset("g_min", data=g_out_bounds[:, :, :, 0])
                 scatt_grp.create_dataset("g_max", data=g_out_bounds[:, :, :, 1])
 

From 5af55a74d49520665da4e852522249ab93e00bfe Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 13 Nov 2016 15:38:19 -0500
Subject: [PATCH 09/27] Removed errant pdb import

---
 openmc/mgxs/mgxs.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 1337b1fa7..06527d5c2 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -3775,7 +3775,7 @@ class ScatterMatrixXS(MatrixMGXS):
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
             xs = xs[:, ::-1, ::-1, ...]
-        # import pdb; pdb.set_trace()
+
         if squeeze:
             # We want to squeeze out everything but the in_groups, out_groups,
             # and, if needed, num_mu_bins dimension. These must not be squeezed

From a29e719c501afd198c42de22d4b15a862518defc Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Mon, 14 Nov 2016 19:07:16 -0500
Subject: [PATCH 10/27] Removed mistake from a poor merge

---
 openmc/mgxs/library.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py
index 97bb6d96b..513884d96 100644
--- a/openmc/mgxs/library.py
+++ b/openmc/mgxs/library.py
@@ -946,6 +946,7 @@ class Library(object):
         if nuclide != 'total':
             name += '_' + nuclide
         xsdata = openmc.XSdata(name, self.energy_groups)
+        xsdata.num_delayed_groups = self.num_delayed_groups
 
         # Right now only isotropic weighting is supported
         self.representation = 'isotropic'

From ecd3112e21d0cb6908e116e7e224f9cab166a133 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Mon, 14 Nov 2016 20:47:38 -0500
Subject: [PATCH 11/27] Updating example problems for the new format

---
 .../python/pincell_multigroup/build-xml.py    |  10 ++++++++--
 examples/xml/pincell_multigroup/mgxs.h5       | Bin 16696 -> 16696 bytes
 2 files changed, 8 insertions(+), 2 deletions(-)

diff --git a/examples/python/pincell_multigroup/build-xml.py b/examples/python/pincell_multigroup/build-xml.py
index ee74233c1..cc57b61e2 100644
--- a/examples/python/pincell_multigroup/build-xml.py
+++ b/examples/python/pincell_multigroup/build-xml.py
@@ -1,3 +1,5 @@
+import numpy as np
+
 import openmc
 import openmc.mgxs
 
@@ -26,7 +28,7 @@ uo2_xsdata.set_total(
      0.5644058])
 uo2_xsdata.set_absorption([8.0248E-03, 3.7174E-03, 2.6769E-02, 9.6236E-02,
                            3.0020E-02, 1.1126E-01, 2.8278E-01])
-uo2_xsdata.set_scatter_matrix(
+scatter_matrix = np.array(
     [[[0.1275370, 0.0423780, 0.0000094, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
       [0.0000000, 0.3244560, 0.0016314, 0.0000000, 0.0000000, 0.0000000, 0.0000000],
       [0.0000000, 0.0000000, 0.4509400, 0.0026792, 0.0000000, 0.0000000, 0.0000000],
@@ -34,6 +36,8 @@ uo2_xsdata.set_scatter_matrix(
       [0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]])
+scatter_matrix = np.swapaxes(np.swapaxes(scatter_matrix, 0, 1), 1, 2)
+uo2_xsdata.set_scatter_matrix(scatter_matrix)
 uo2_xsdata.set_fission([7.21206E-03, 8.19301E-04, 6.45320E-03,
                         1.85648E-02, 1.78084E-02, 8.30348E-02,
                         2.16004E-01])
@@ -50,7 +54,7 @@ h2o_xsdata.set_total([0.15920605, 0.412969593, 0.59030986, 0.58435,
 h2o_xsdata.set_absorption([6.0105E-04, 1.5793E-05, 3.3716E-04,
                            1.9406E-03, 5.7416E-03, 1.5001E-02,
                            3.7239E-02])
-h2o_xsdata.set_scatter_matrix(
+scatter_matrix = np.array(
     [[[0.0444777, 0.1134000, 0.0007235, 0.0000037, 0.0000001, 0.0000000, 0.0000000],
       [0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010],
       [0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034],
@@ -58,6 +62,8 @@ h2o_xsdata.set_scatter_matrix(
       [0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]])
+scatter_matrix = np.swapaxes(np.swapaxes(scatter_matrix, 0, 1), 1, 2)
+h2o_xsdata.set_scatter_matrix(scatter_matrix)
 
 mg_cross_sections_file = openmc.MGXSLibrary(groups)
 mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata])
diff --git a/examples/xml/pincell_multigroup/mgxs.h5 b/examples/xml/pincell_multigroup/mgxs.h5
index 1d5561b0006a8afb89663ca33573eedaabad7a91..ae3b17e90f2dafb1a350d9bd1392d61254f2a37c 100644
GIT binary patch
delta 194
zcmdnd#JHo0af2r(k9%yiyLxQ2e^E+m(PUoT$&(i-N^IiFVPW2wp|v@mPn8$Mm^@##
zeY2d*IYzMPds$ux<G&n~!LI;i$Sc-Dbk0}xWr8SHhbh)zVnMNOGq3J@h~oc-s;p3J
fIyY}HKLatn-tsIn*a&}Hs9E#vA!bc}uigm&6H`Mw

delta 194
zcmdnd#JHo0af2r(kAG20YEf*oI}oW)=GC1%d4ZzDCaxS7=GeK?oAdcpc|nZH^Htk7
z%gLN$1dG0x<%KZ*%Rw3Z3Q&f;Vl71Hd{tj2h+=h^Vhtu16x%lQ>b{34{%@$t3bm$l
d^9J)X5Yy`|&oYCJ@VAAUHQyd$*5vo<od7nSK#2eV


From 2395f9a96c1ecf8cbc3705ea7ebc88baf9dcf4c7 Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Mon, 7 Nov 2016 11:34:09 -0600
Subject: [PATCH 12/27] Add FissionProductYields class and Decay class

---
 docs/source/conf.py             |   2 +-
 docs/source/pythonapi/index.rst |   2 +
 openmc/data/__init__.py         |   1 +
 openmc/data/decay.py            | 458 ++++++++++++++++++++++++++++++++
 openmc/data/endf.py             |  21 +-
 setup.py                        |   1 +
 6 files changed, 474 insertions(+), 11 deletions(-)
 create mode 100644 openmc/data/decay.py

diff --git a/docs/source/conf.py b/docs/source/conf.py
index 672217c84..4e21ec20b 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -25,7 +25,7 @@ except ImportError:
 
 
 MOCK_MODULES = ['numpy', 'numpy.polynomial', 'numpy.polynomial.polynomial',
-                'h5py', 'pandas', 'opencg']
+                'h5py', 'pandas', 'uncertainties', 'opencg']
 sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES)
 
 import numpy as np
diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst
index e364452b1..b86107f37 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/pythonapi/index.rst
@@ -373,6 +373,8 @@ Core Classes
     openmc.data.CoherentElastic
     openmc.data.FissionEnergyRelease
     openmc.data.DataLibrary
+    openmc.data.Decay
+    openmc.data.FissionProductYields
 
 Core Functions
 --------------
diff --git a/openmc/data/__init__.py b/openmc/data/__init__.py
index 373136538..c361a204d 100644
--- a/openmc/data/__init__.py
+++ b/openmc/data/__init__.py
@@ -6,6 +6,7 @@ HDF5_VERSION = (HDF5_VERSION_MAJOR, HDF5_VERSION_MINOR)
 
 from .data import *
 from .neutron import *
+from .decay import *
 from .reaction import *
 from .ace import *
 from .angle_distribution import *
diff --git a/openmc/data/decay.py b/openmc/data/decay.py
new file mode 100644
index 000000000..35bc11345
--- /dev/null
+++ b/openmc/data/decay.py
@@ -0,0 +1,458 @@
+from collections import Iterable, namedtuple
+from io import StringIO
+from math import log
+from numbers import Real
+import re
+from warnings import warn
+
+from six import string_types
+import numpy as np
+try:
+    from uncertainties import ufloat, unumpy, UFloat
+except ImportError:
+    ufloat = UFloat = namedtuple('UFloat', ['nominal_value', 'std_dev'])
+
+import openmc.checkvalue as cv
+from openmc.mixin import EqualityMixin
+from .data import ATOMIC_SYMBOL, ATOMIC_NUMBER
+from .endf import Evaluation, get_head_record, get_list_record, get_tab1_record
+
+
+# Gives name and (change in A, change in Z) resulting from decay
+_DECAY_MODES = {
+    0: ('gamma', (0, 0)),
+    1: ('beta-', (0, 1)),
+    2: ('ec/beta+', (0, -1)),
+    3: ('IT', (0, 0)),
+    4: ('alpha', (-4, -2)),
+    5: ('n', (-1, 0)),
+    6: ('sf', None),
+    7: ('p', (-1, -1)),
+    8: ('e-', (0, 0)),
+    9: ('xray', (0, 0)),
+    10: ('unknown', None)
+}
+
+_RADIATION_TYPES = {
+    0: 'gamma',
+    1: 'beta-',
+    2: 'ec/beta+',
+    4: 'alpha',
+    5: 'n',
+    6: 'sf',
+    7: 'p',
+    8: 'e-',
+    9: 'xray',
+    10: 'anti-neutrino',
+    11: 'neutrino'
+}
+
+
+def get_decay_modes(value):
+    """Return sequence of decay modes given an ENDF RTYP value.
+
+    Parameters
+    ----------
+    value : float
+        ENDF definition of sequence of decay modes
+
+    Returns
+    -------
+    list of str
+        List of successive decays, e.g. ('beta-', 'neutron')
+
+    """
+    return [_DECAY_MODES[int(x)][0] for x in
+            str(value).strip('0').replace('.', '')]
+
+
+class FissionProductYields(EqualityMixin):
+    """Independent and cumulative fission product yields.
+
+    Parameters
+    ----------
+    ev_or_filename : str of openmc.data.endf.Evaluation
+        ENDF fission product yield evaluation to read from. If given as a
+        string, it is assumed to be the filename for the ENDF file.
+
+    Attributes
+    ----------
+    cumulative : list of dict
+        Cumulative yields for each tabulated energy. Each item in the list is a
+        dictionary whose keys are nuclide names and values are cumulative
+        yields. The i-th dictionary corresponds to the i-th energy.
+    energies : Iterable of float or None
+        Energies at which fission product yields are tabulated.
+    independent : list of dict
+        Independent yields for each tabulated energy. Each item in the list is a
+        dictionary whose keys are nuclide names and values are independent
+        yields. The i-th dictionary corresponds to the i-th energy.
+    nuclide : dict
+        Properties of the fissioning nuclide.
+
+    """
+    def __init__(self, ev_or_filename):
+        # Define function that can be used to read both independent and
+        # cumulative yields
+        def get_yields(file_obj):
+            # Determine number of energies
+            n_energy = get_head_record(file_obj)[2]
+            if n_energy > 1:
+                energies = np.zeros(n_energy)
+            else:
+                energies = None
+
+            data = []
+            for i in range(n_energy):
+                # Determine i-th energy and number of products
+                items, values = get_list_record(file_obj)
+                if n_energy > 1:
+                    energies[i] = items[0]
+                n_products = items[5]
+
+                # Get yields for i-th energy
+                yields = {}
+                for j in range(n_products):
+                    Z, A = divmod(int(values[4*j]), 1000)
+                    excited_state = int(values[4*j + 1])
+                    name = ATOMIC_SYMBOL[Z] + str(A)
+                    if excited_state > 0:
+                        name += '_e{}'.format(excited_state)
+                    yield_j = ufloat(values[4*j + 2], values[4*j + 3])
+                    yields[name] = yield_j
+
+                data.append(yields)
+
+            return energies, data
+
+        # Get evaluation if str is passed
+        if isinstance(ev_or_filename, Evaluation):
+            ev = ev_or_filename
+        else:
+            ev = Evaluation(ev_or_filename)
+
+        # Assign basic nuclide properties
+        self.nuclide = {
+            'name': ev.gnd_name,
+            'atomic_number': ev.target['atomic_number'],
+            'mass_number': ev.target['mass_number'],
+            'isomeric_state': ev.target['isomeric_state']
+        }
+
+        # Read independent yields
+        if (8, 454) in ev.section:
+            file_obj = StringIO(ev.section[8, 454])
+            self.energies, self.independent = get_yields(file_obj)
+
+        # Read cumulative yields
+        if (8, 459) in ev.section:
+            file_obj = StringIO(ev.section[8, 459])
+            energies, self.cumulative = get_yields(file_obj)
+            assert np.all(energies == self.energies)
+
+    @classmethod
+    def from_endf(cls, filename):
+        """Generate fission product yield data from an ENDF evaluation
+
+        Parameters
+        ----------
+        ev_or_filename : str or openmc.data.endf.Evaluation
+            ENDF fission product yield evaluation to read from. If given as a
+            string, it is assumed to be the filename for the ENDF file.
+
+        Returns
+        -------
+        openmc.data.FissionProductYields
+            Fission product yield data
+
+        """
+        return cls(filename)
+
+
+class DecayMode(EqualityMixin):
+    """Radioactive decay mode.
+
+    Parameters
+    ----------
+    parent : str
+        Parent decaying nuclide
+    modes : list of str
+        Successive decay modes
+    daughter_state : int
+        Metastable state of the daughter nuclide
+    energy : uncertainties.UFloat
+        Total decay energy in eV available in the decay process.
+    branching_ratio : uncertainties.UFloat
+        Fraction of the decay of the parent nuclide which proceeds by this mode.
+
+    Attributes
+    ----------
+    branching_ratio : uncertainties.UFloat
+        Fraction of the decay of the parent nuclide which proceeds by this mode.
+    daughter : str
+        Name of daughter nuclide produced from decay
+    energy : uncertainties.UFloat
+        Total decay energy in eV available in the decay process.
+    modes : list of str
+        Successive decay modes
+    parent : str
+        Parent decaying nuclide
+
+    """
+
+    def __init__(self, parent, modes, daughter_state, energy,
+                 branching_ratio):
+        self._daughter_state = daughter_state
+        self.parent = parent
+        self.modes = modes
+        self.energy = energy
+        self.branching_ratio = branching_ratio
+
+    def __repr__(self):
+        return ('<DecayMode: ({}), {} -> {}, {}>'.format(
+            ','.join(self.modes), self.parent, self.daughter,
+            self.branching_ratio))
+
+    @property
+    def branching_ratio(self):
+        return self._branching_ratio
+
+    @property
+    def daughter(self):
+        # Determine atomic number and mass number of parent
+        symbol, A = re.match(r'([A-Zn][a-z]*)(\d+)', self.parent).groups()
+        A = int(A)
+        Z = ATOMIC_NUMBER[symbol]
+
+        # Process changes
+        for mode in self.modes:
+            for name, changes in _DECAY_MODES.values():
+                if name == mode:
+                    if changes is not None:
+                        delta_A, delta_Z = changes
+                        A += delta_A
+                        Z += delta_Z
+
+        if self._daughter_state > 0:
+            return '{}{}_m{}'.format(ATOMIC_SYMBOL[Z], A, self._daughter_state)
+        else:
+            return '{}{}'.format(ATOMIC_SYMBOL[Z], A)
+
+    @property
+    def energy(self):
+        return self._energy
+
+    @property
+    def modes(self):
+        return self._modes
+
+    @property
+    def parent(self):
+        return self._parent
+
+    @branching_ratio.setter
+    def branching_ratio(self, branching_ratio):
+        cv.check_type('branching ratio', branching_ratio, UFloat)
+        cv.check_greater_than('branching ratio',
+                              branching_ratio.nominal_value, 0.0, True)
+        if branching_ratio.nominal_value == 0.0:
+            warn('Decay mode {} of parent {} has a zero branching ratio.'
+                 .format(self.modes, self.parent))
+        cv.check_greater_than('branching ratio uncertainty',
+                              branching_ratio.std_dev, 0.0, True)
+        self._branching_ratio = branching_ratio
+
+    @energy.setter
+    def energy(self, energy):
+        cv.check_type('decay energy', energy, UFloat)
+        cv.check_greater_than('decay energy', energy.nominal_value, 0.0, True)
+        cv.check_greater_than('decay energy uncertainty',
+                              energy.std_dev, 0.0, True)
+        self._energy = energy
+
+    @modes.setter
+    def modes(self, modes):
+        cv.check_type('decay modes', modes, Iterable, string_types)
+        self._modes = modes
+
+    @parent.setter
+    def parent(self, parent):
+        cv.check_type('parent nuclide', parent, string_types)
+        self._parent = parent
+
+
+class Decay(EqualityMixin):
+    """Radioactive decay data.
+
+    Parameters
+    ----------
+    ev_or_filename : str of openmc.data.endf.Evaluation
+        ENDF radioactive decay data evaluation to read from. If given as a
+        string, it is assumed to be the filename for the ENDF file.
+
+    Attributes
+    ----------
+    average_energies : dict
+        Average decay energies in eV of each type of radiation for decay heat
+        applications.
+    decay_constant : uncertainties.UFloat
+        Decay constant in inverse seconds.
+    half_life : uncertainties.UFloat
+        Half-life of the decay in seconds.
+    modes : list
+        Decay mode information for each mode of decay.
+    nuclide : dict
+        Dictionary describing decaying nuclide with keys 'name',
+        'excited_state', 'mass', 'stable', 'spin', and 'parity'.
+    spectra : dict
+        Resulting radiation spectra for each radiation type.
+
+    """
+    def __init__(self, ev_or_filename):
+        # Get evaluation if str is passed
+        if isinstance(ev_or_filename, Evaluation):
+            ev = ev_or_filename
+        else:
+            ev = Evaluation(ev_or_filename)
+        #assert ev.info['sublibrary'] == 'Radioactive decay data'
+
+        file_obj = StringIO(ev.section[8, 457])
+
+        self.nuclide = {}
+        self.modes = []
+        self.spectra = {}
+        self.average_energies = {}
+
+        # Get head record
+        items = get_head_record(file_obj)
+        Z, A = divmod(items[0], 1000)
+        metastable = items[3]
+        self.nuclide['atomic_number'] = Z
+        self.nuclide['mass_number'] = A
+        self.nuclide['isomeric_state'] = metastable
+        if metastable > 0:
+            self.nuclide['name'] = '{}{}_m{}'.format(ATOMIC_SYMBOL[Z], A,
+                                                    metastable)
+        else:
+            self.nuclide['name'] = '{}{}'.format(ATOMIC_SYMBOL[Z], A)
+        self.nuclide['mass'] = items[1]  # AWR
+        self.nuclide['excited_state'] = items[2]  # State of the original nuclide
+        self.nuclide['stable'] = (items[4] == 1)  # Nucleus stability flag
+
+        # Determine if radioactive/stable
+        if not self.nuclide['stable']:
+            NSP = items[5]  # Number of radiation types
+
+            # Half-life and decay energies
+            items, values = get_list_record(file_obj)
+            self.half_life = ufloat(items[0], items[1])
+            NC = items[4]//2
+            pairs = [x for x in zip(values[::2], values[1::2])]
+            ex = self.average_energies
+            ex['light'] = ufloat(*pairs[0])
+            ex['electromagnetic'] = ufloat(*pairs[1])
+            ex['heavy'] = ufloat(*pairs[2])
+            if NC == 17:
+                ex['beta-'] = ufloat(*pairs[3])
+                ex['beta+'] = ufloat(*pairs[4])
+                ex['auger'] = ufloat(*pairs[5])
+                ex['conversion'] = ufloat(*pairs[6])
+                ex['gamma'] = ufloat(*pairs[7])
+                ex['xray'] = ufloat(*pairs[8])
+                ex['Bremsstrahlung'] = ufloat(*pairs[9])
+                ex['annihilation'] = ufloat(*pairs[10])
+                ex['alpha'] = ufloat(*pairs[11])
+                ex['recoil'] = ufloat(*pairs[12])
+                ex['SF'] = ufloat(*pairs[13])
+                ex['neutron'] = ufloat(*pairs[14])
+                ex['proton'] = ufloat(*pairs[15])
+                ex['neutrino'] = ufloat(*pairs[16])
+
+            items, values = get_list_record(file_obj)
+            spin = items[0]
+            if spin == -77.777:
+                self.nuclide['spin'] = None
+            else:
+                self.nuclide['spin'] = spin
+            self.nuclide['parity'] = items[1]  # Parity of the nuclide
+
+            # Decay mode information
+            n_modes = items[5]  # Number of decay modes
+            for i in range(n_modes):
+                decay_type = get_decay_modes(values[6*i])
+                isomeric_state = int(values[6*i + 1])
+                energy = ufloat(*values[6*i + 2:6*i + 4])
+                branching_ratio = ufloat(*values[6*i + 4:6*(i + 1)])
+
+                mode = DecayMode(self.nuclide['name'], decay_type, isomeric_state,
+                                 energy, branching_ratio)
+                self.modes.append(mode)
+
+            discrete_type = {0.0: None, 1.0: 'allowed', 2.0: 'first-forbidden',
+                             3.0: 'second-forbidden', 4.0: 'third-forbidden',
+                             5.0: 'fourth-forbidden', 6.0: 'fifth-forbidden'}
+
+            # Read spectra
+            for i in range(NSP):
+                spectrum = {}
+
+                items, values = get_list_record(file_obj)
+                # Decay radiation type
+                spectrum['type'] = _RADIATION_TYPES[items[1]]
+                # Continuous spectrum flag
+                spectrum['continuous_flag'] = {0: 'discrete', 1: 'continuous',
+                                               2: 'both'}[items[2]]
+                spectrum['discrete_normalization'] = ufloat(*values[0:2])
+                spectrum['energy_average'] = ufloat(*values[2:4])
+                spectrum['continuous_normalization'] = ufloat(*values[4:6])
+
+                NER = items[5]  # Number of tabulated discrete energies
+
+                if not spectrum['continuous_flag'] == 'continuous':
+                    # Information about discrete spectrum
+                    spectrum['discrete'] = []
+                    for j in range(NER):
+                        items, values = get_list_record(file_obj)
+                        di = {}
+                        di['energy'] = ufloat(*items[0:2])
+                        di['from_mode'] = get_decay_modes(values[0])
+                        di['type'] = discrete_type[values[1]]
+                        di['intensity'] = ufloat(*values[2:4])
+                        if spectrum['type'] == 'ec/beta+':
+                            di['positron_intensity'] = ufloat(*values[4:6])
+                        elif spectrum['type'] == 'gamma':
+                            di['internal_pair'] = ufloat(*values[4:6])
+                            if len(values) >= 8:
+                                di['total_internal_conversion'] = ufloat(*values[6:8])
+                            if len(values) == 12:
+                                di['k_shell_conversion'] = ufloat(*values[8:10])
+                                di['l_shell_conversion'] = ufloat(*values[10:12])
+                        spectrum['discrete'].append(di)
+
+                if not spectrum['continuous_flag'] == 'discrete':
+                    # Read continuous spectrum
+                    ci = {}
+                    params, ci['probability'] = get_tab1_record(file_obj)
+                    ci['type'] = get_decay_modes(params[0])
+
+                    # Read covariance (Ek, Fk) table
+                    LCOV = params[3]
+                    if LCOV != 0:
+                        items, values = get_list_record(file_obj)
+                        ci['covariance_lb'] = items[3]
+                        ci['covariance'] = zip(values[0::2], values[1::2])
+
+                    spectrum['continuous'] = ci
+
+                # Add spectrum to dictionary
+                self.spectra[spectrum['type']] = spectrum
+
+        else:
+            items, values = get_list_record(file_obj)
+            items, values = get_list_record(file_obj)
+            self.nuclide['spin'] = items[0]
+            self.nuclide['parity'] = items[1]
+
+    @property
+    def decay_constant(self):
+        return log(2.)/self.half_life
diff --git a/openmc/data/endf.py b/openmc/data/endf.py
index c0049f977..0197b65e4 100644
--- a/openmc/data/endf.py
+++ b/openmc/data/endf.py
@@ -17,6 +17,7 @@ from collections import OrderedDict, Iterable
 import numpy as np
 from numpy.polynomial.polynomial import Polynomial
 
+from .data import ATOMIC_SYMBOL
 from .function import Tabulated1D, INTERPOLATION_SCHEME
 from openmc.stats.univariate import Uniform, Tabular, Legendre
 
@@ -47,16 +48,6 @@ SUM_RULES = {1: [2, 3],
 _ENDF_FLOAT_RE = re.compile(r'([\s\-\+]?\d*\.\d+)([\+\-]\d+)')
 
 
-def radiation_type(value):
-    p = {0: 'gamma', 1: 'beta-', 2: 'ec/beta+', 3: 'IT',
-         4: 'alpha', 5: 'neutron', 6: 'sf', 7: 'proton',
-         8: 'e-', 9: 'xray', 10: 'unknown'}
-    if value % 1.0 == 0:
-        return p[int(value)]
-    else:
-        return (p[int(value)], p[int(10*value % 10)])
-
-
 def float_endf(s):
     """Convert string of floating point number in ENDF to float.
 
@@ -396,6 +387,16 @@ class Evaluation(object):
                 mod = 0
             self.reaction_list.append((mf, mt, nc, mod))
 
+    @property
+    def gnd_name(self):
+        symbol = ATOMIC_SYMBOL[self.target['atomic_number']]
+        A = self.target['mass_number']
+        m = self.target['isomeric_state']
+        if m > 0:
+            return '{}{}_m{}'.format(symbol, A, m)
+        else:
+            return '{}{}'.format(symbol, A)
+
 
 class Tabulated2D(object):
     """Metadata for a two-dimensional function.
diff --git a/setup.py b/setup.py
index 0885c28a8..befb9c0d2 100755
--- a/setup.py
+++ b/setup.py
@@ -43,6 +43,7 @@ if have_setuptools:
 
         # Optional dependencies
         'extras_require': {
+            'decay': ['uncertainties'],
             'pandas': ['pandas>=0.17.0'],
             'sparse' : ['scipy'],
             'vtk': ['vtk', 'silomesh'],

From c34460d647adc52a39e3f44ee98db6e2ac11ed22 Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Fri, 18 Nov 2016 06:52:21 -0600
Subject: [PATCH 13/27] Make spaces per indent configurable for
 clean_xml_indentation

---
 openmc/clean_xml.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/openmc/clean_xml.py b/openmc/clean_xml.py
index 564281a5c..6aaf64c66 100644
--- a/openmc/clean_xml.py
+++ b/openmc/clean_xml.py
@@ -65,25 +65,25 @@ def sort_xml_elements(tree):
     tree.extend(sorted_elements)
 
 
-def clean_xml_indentation(element, level=0):
+def clean_xml_indentation(element, level=0, spaces_per_level=4):
     """
     copy and paste from http://effbot.org/zone/elementent-lib.htm#prettyprint
     it basically walks your tree and adds spaces and newlines so the tree is
     printed in a nice way
     """
 
-    i = "\n" + level*"    "
+    i = "\n" + level*spaces_per_level*" "
 
     if len(element):
 
         if not element.text or not element.text.strip():
-            element.text = i + "    "
+            element.text = i + spaces_per_level*" "
 
         if not element.tail or not element.tail.strip():
             element.tail = i
 
         for sub_element in element:
-            clean_xml_indentation(sub_element, level+1)
+            clean_xml_indentation(sub_element, level+1, spaces_per_level)
 
         if not sub_element.tail or not sub_element.tail.strip():
             sub_element.tail = i

From e5ecfb18b982e9d9992a5dde918efedb93a706af Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Fri, 18 Nov 2016 06:52:47 -0600
Subject: [PATCH 14/27] Add (n,2n) level reactions to REACTION_NAME

---
 openmc/data/reaction.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/openmc/data/reaction.py b/openmc/data/reaction.py
index 23b864bf3..08930fa65 100644
--- a/openmc/data/reaction.py
+++ b/openmc/data/reaction.py
@@ -55,13 +55,14 @@ REACTION_NAME = {1: '(n,total)', 2: '(n,elastic)', 4: '(n,level)',
                  195: '(n,4n2a)', 196: '(n,4npa)', 197: '(n,3p)',
                  198: '(n,n3p)', 199: '(n,3n2pa)', 200: '(n,5n2p)', 444: '(n,damage)',
                  649: '(n,pc)', 699: '(n,dc)', 749: '(n,tc)', 799: '(n,3Hec)',
-                 849: '(n,ac)'}
-REACTION_NAME.update({i: '(n,n{})'.format(i-50) for i in range(50, 91)})
-REACTION_NAME.update({i: '(n,p{})'.format(i-600) for i in range(600, 649)})
-REACTION_NAME.update({i: '(n,d{})'.format(i-650) for i in range(650, 699)})
-REACTION_NAME.update({i: '(n,t{})'.format(i-700) for i in range(700, 749)})
-REACTION_NAME.update({i: '(n,3He{})'.format(i-750) for i in range(750, 799)})
-REACTION_NAME.update({i: '(n,a{})'.format(i-800) for i in range(800, 849)})
+                 849: '(n,ac)', 891: '(n,2nc)'}
+REACTION_NAME.update({i: '(n,n{})'.format(i - 50) for i in range(50, 91)})
+REACTION_NAME.update({i: '(n,p{})'.format(i - 600) for i in range(600, 649)})
+REACTION_NAME.update({i: '(n,d{})'.format(i - 650) for i in range(650, 699)})
+REACTION_NAME.update({i: '(n,t{})'.format(i - 700) for i in range(700, 749)})
+REACTION_NAME.update({i: '(n,3He{})'.format(i - 750) for i in range(750, 799)})
+REACTION_NAME.update({i: '(n,a{})'.format(i - 800) for i in range(800, 849)})
+REACTION_NAME.update({i: '(n,2n{})'.format(i - 875) for i in range(875, 891)})
 
 
 def _get_products(ev, mt):

From fb4d9df41b86b8c68f9b185d0fc85f0fad157155 Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Fri, 18 Nov 2016 06:54:15 -0600
Subject: [PATCH 15/27] Make sure LaboratoryAngleEnergy has a to_hdf5() method

---
 openmc/data/laboratory.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/openmc/data/laboratory.py b/openmc/data/laboratory.py
index be449b79a..0a8908362 100644
--- a/openmc/data/laboratory.py
+++ b/openmc/data/laboratory.py
@@ -137,3 +137,6 @@ class LaboratoryAngleEnergy(AngleEnergy):
             energy_out.append(energy_out_i)
 
         return cls(tab2.breakpoints, tab2.interpolation, energy, mu, energy_out)
+
+    def to_hdf5(self, group):
+        raise NotImplementedError

From 643eaf53cbbfe133df54f38c5bb0d0c23cb93442 Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Fri, 18 Nov 2016 11:04:34 -0600
Subject: [PATCH 16/27] Add function to read all ENDF evaluations from a single
 file

---
 docs/source/pythonapi/index.rst |  1 +
 openmc/data/endf.py             | 39 +++++++++++++++++++++++++++++----
 2 files changed, 36 insertions(+), 4 deletions(-)

diff --git a/docs/source/pythonapi/index.rst b/docs/source/pythonapi/index.rst
index b86107f37..fc01b99e7 100644
--- a/docs/source/pythonapi/index.rst
+++ b/docs/source/pythonapi/index.rst
@@ -478,6 +478,7 @@ Functions
 
     openmc.data.endf.float_endf
     openmc.data.endf.get_cont_record
+    openmc.data.endf.get_evaluations
     openmc.data.endf.get_head_record
     openmc.data.endf.get_tab1_record
     openmc.data.endf.get_tab2_record
diff --git a/openmc/data/endf.py b/openmc/data/endf.py
index 0197b65e4..34553ad2d 100644
--- a/openmc/data/endf.py
+++ b/openmc/data/endf.py
@@ -14,6 +14,7 @@ import os
 from math import pi
 from collections import OrderedDict, Iterable
 
+from six import string_types
 import numpy as np
 from numpy.polynomial.polynomial import Polynomial
 
@@ -249,14 +250,40 @@ def get_tab2_record(file_obj):
 
     return params, Tabulated2D(breakpoints, interpolation)
 
+def get_evaluations(filename):
+    """Return a list of all evaluations within an ENDF file.
+
+    Parameters
+    ----------
+    filename : str
+        Path to ENDF-6 formatted file
+
+    Returns
+    -------
+    list
+        A list of :class:`openmc.data.endf.Evaluation` instances.
+
+    """
+    evaluations = []
+    with open(filename, 'r') as fh:
+        while True:
+            pos = fh.tell()
+            line = fh.readline()
+            if line[66:70] == '  -1':
+                break
+            fh.seek(pos)
+            evaluations.append(Evaluation(fh))
+    return evaluations
+
 
 class Evaluation(object):
     """ENDF material evaluation with multiple files/sections
 
     Parameters
     ----------
-    filename : str
-        Path to ENDF file to read
+    filename_or_obj : str or file-like
+        Path to ENDF file to read or an open file positioned at the start of an
+        ENDF material
 
     Attributes
     ----------
@@ -273,8 +300,11 @@ class Evaluation(object):
         indicator (MOD).
 
     """
-    def __init__(self, filename):
-        fh = open(filename, 'r')
+    def __init__(self, filename_or_obj):
+        if isinstance(filename_or_obj, string_types):
+            fh = open(filename_or_obj, 'r')
+        else:
+            fh = filename_or_obj
         self.section = {}
         self.info = {}
         self.target = {}
@@ -304,6 +334,7 @@ class Evaluation(object):
 
             # If end of material reached, exit loop
             if MAT == 0:
+                fh.readline()
                 break
 
             section_data = ''

From 91567fd9f4cf6590fae350bd74d761bc56949cff Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Mon, 21 Nov 2016 10:49:39 -0600
Subject: [PATCH 17/27] Fix broken links, update publications, list
 @samuelshaner as dev

---
 docs/source/developers.rst        |  3 ++-
 docs/source/devguide/workflow.rst |  2 +-
 docs/source/methods/geometry.rst  |  6 +++---
 docs/source/publications.rst      | 23 ++++++++++++++++++++++-
 4 files changed, 28 insertions(+), 6 deletions(-)

diff --git a/docs/source/developers.rst b/docs/source/developers.rst
index d82d89744..0bdae2416 100644
--- a/docs/source/developers.rst
+++ b/docs/source/developers.rst
@@ -13,6 +13,7 @@ Active development of the OpenMC Monte Carlo code is currently led by:
 * `Jon Walsh <https://github.com/walshjon>`_
 * `Sterling Harper <https://github.com/smharper>`_
 * `Will Boyd <https://github.com/wbinventor>`_
+* `Samuel Shaner <https://github.com/samuelshaner>`_
 * `Benoit Forget <http://web.mit.edu/nse/people/faculty/forget.html>`_
 * `Kord Smith <http://web.mit.edu/nse/people/faculty/smith.html>`_
-* `Andrew Siegel <http://www.mcs.anl.gov/about/people_detail.php?id=404>`_
+* `Andrew Siegel <http://www.mcs.anl.gov/person/andrew-siegel>`_
diff --git a/docs/source/devguide/workflow.rst b/docs/source/devguide/workflow.rst
index 2f36436ca..a53bd114b 100644
--- a/docs/source/devguide/workflow.rst
+++ b/docs/source/devguide/workflow.rst
@@ -238,4 +238,4 @@ from your private repository into a public fork.
 .. _paid plan: https://github.com/plans
 .. _Bitbucket: https://bitbucket.org
 .. _ctest: http://www.cmake.org/cmake/help/v2.8.12/ctest.html
-.. _NNDC:  http://http://www.nndc.bnl.gov/endf/b7.1/acefiles.html
+.. _NNDC:  http://www.nndc.bnl.gov/endf/b7.1/acefiles.html
diff --git a/docs/source/methods/geometry.rst b/docs/source/methods/geometry.rst
index c2e7270b6..36c252bb1 100644
--- a/docs/source/methods/geometry.rst
+++ b/docs/source/methods/geometry.rst
@@ -384,7 +384,7 @@ x - x_0`, :math:`\bar{y} = y - y_0`, and :math:`\bar{z} = z - z_0`. We then have
 Expanding equation :eq:`dist-xcone-1` and rearranging terms, we obtain
 
 .. math::
-    :label: dist-xcylinder-2
+    :label: dist-xcone-2
 
     (v^2 + w^2 - R^2u^2) d^2 + 2 (\bar{y}v + \bar{z}w - R^2\bar{x}u) d +
     (\bar{y}^2 + \bar{z}^2 - R^2\bar{x}^2) = 0
@@ -392,7 +392,7 @@ Expanding equation :eq:`dist-xcone-1` and rearranging terms, we obtain
 Defining the terms
 
 .. math::
-    :label: dist-quadric-terms
+    :label: dist-xcone-terms
 
     a = v^2 + w^2 - R^2u^2
 
@@ -896,4 +896,4 @@ Dxy + Eyz + Fxz + Gx + Hy + Jz + K = 0`. Thus, the gradient to the surface is
 .. _surfaces: http://en.wikipedia.org/wiki/Surface
 .. _MCNP: http://mcnp.lanl.gov
 .. _Serpent: http://montecarlo.vtt.fi
-.. _Monte Carlo Performance benchmark: https://github.com/paulromano/benchmarks/tree/master/mc-performance/openmc
+.. _Monte Carlo Performance benchmark: https://github.com/mit-crpg/benchmarks/tree/master/mc-performance/openmc
diff --git a/docs/source/publications.rst b/docs/source/publications.rst
index c5b29b194..7e79cf33f 100644
--- a/docs/source/publications.rst
+++ b/docs/source/publications.rst
@@ -82,6 +82,10 @@ Coupling and Multi-physics
 Geometry
 --------
 
+- Derek M. Lax, "Memory efficient indexing algorithm for physical properties in
+  OpenMC," S. M. Thesis, Massachusetts Institute of Technology
+  (2015). `<http://hdl.handle.net/1721.1/97862>`_
+
 - Derek Lax, William Boyd, Nicholas Horelik, Benoit Forget, and Kord Smith, "A
   memory efficient algorithm for classifying unique regions in constructive
   solid geometries," *Proc. PHYSOR*, Kyoto, Japan, Sep. 28--Oct. 3 (2014).
@@ -106,6 +110,10 @@ Miscellaneous
   triggers for the OpenMC Monte Carlo code," *Trans. Am. Nucl. Soc.*, **112**,
   637-640 (2015).
 
+- Kyungkwan Noh and Deokjung Lee, "Whole Core Analysis using OpenMC Monte Carlo
+  Code," *Trans. Kor. Nucl. Soc. Autumn Meeting*, Gyeongju, Korea,
+  Oct. 24-25, 2013.
+
 - Timothy P. Burke, Brian C. Kiedrowski, and William R. Martin, "Flux and
   Reaction Rate Kernel Density Estimators in OpenMC," *Trans. Am. Nucl. Soc.*,
   **109**, 683-686 (2013).
@@ -139,7 +147,7 @@ Doppler Broadening
 
 - Colin Josey, Pablo Ducru, Benoit Forget, and Kord Smith, "Windowed multipole
   for cross section Doppler broadening," *J. Comput. Phys.*, **307**, 715-727
-  (2016). `<http://dx.doi.org/10.1016/jcp.2015.08.013>`_
+  (2016). `<http://dx.doi.org/10.1016/j.jcp.2015.08.013>`_
 
 - Jonathan A. Walsh, Benoit Forget, Kord S. Smith, and Forrest B. Brown,
   "On-the-fly Doppler Broadening of Unresolved Resonance Region Cross Sections
@@ -213,10 +221,19 @@ Parallelism
   memory subsystem on Monte Carlo code performance," *Proc. Joint
   Int. Conf. M&C+SNA+MC*, Nashville, Tennessee, Apr. 19--23 (2015).
 
+- Hajime Fujita, Nan Dun, Aiman Fang, Zachary A. Rubinstein, Ziming Zheng, Kamil
+  Iskra, Jeff Hammonds, Anshu Dubey, Pavan Balaji, and Andrew A. Chien, "Using
+  Global View Resilience (GVR) to add Resilience to Exascale Applications,"
+  *Proc. Supercomputing*, New Orleans, Louisiana, Nov. 16--21, 2014.
+
 - Nicholas Horelik, Benoit Forget, Kord Smith, and Andrew Siegel, "Domain
   decomposition and terabyte tallies with the OpenMC Monte Carlo neutron
   transport code," *Proc. PHYSOR*, Kyoto Japan, Sep. 28--Oct. 3 (2014).
 
+- John R. Tramm, Andrew R. Siegel, Tanzima Islam, and Martin Schulz, "XSBench --
+  the development and verification of a performance abstraction for Monte Carlo
+  reactor analysis," *Proc. PHYSOR*, Kyoto, Japan, Sep 28--Oct. 3, 2014.
+
 - Nicholas Horelik, Andrew Siegel, Benoit Forget, and Kord Smith, "Monte Carlo
   domain decomposition for robust nuclear reactor analysis," *Parallel Comput.*,
   **40**, 646--660 (2014). `<http://dx.doi.org/10.1016/j.parco.2014.10.001>`_
@@ -270,6 +287,10 @@ Parallelism
 Depletion
 ---------
 
+- Anas Gul, K. S. Chaudri, R. Khan, and M. Azeen, "Development and verification
+  of LOOP: A Linkage of ORIGEN2.2 and OpenMC," *Ann. Nucl. Energy*, **99**,
+  321--327 (2017). `<http://dx.doi.org/10.1016/j.anucene.2016.09.016>`_
+
 - Kai Huang, Hongchun Wu, Yunzhao Li, and Liangzhi Cao, "Generalized depletion
   chain simplification based of significance analysis," *Proc. PHYSOR*, Sun
   Valley, Idaho, May 1-5, 2016.

From 4e059a4d2b435fae41902a8cef1834b69cc5727c Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Mon, 21 Nov 2016 14:10:40 -0600
Subject: [PATCH 18/27] Use isomeric state, not excited state, for fission
 products.

After a discussion with Dave Brown from BNL, it was confirmed that FPS in the
ENDF-6 format for fission product yields refers to the isomeric state, not the
excited state.
---
 openmc/data/decay.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/openmc/data/decay.py b/openmc/data/decay.py
index 35bc11345..41929c034 100644
--- a/openmc/data/decay.py
+++ b/openmc/data/decay.py
@@ -114,10 +114,10 @@ class FissionProductYields(EqualityMixin):
                 yields = {}
                 for j in range(n_products):
                     Z, A = divmod(int(values[4*j]), 1000)
-                    excited_state = int(values[4*j + 1])
+                    isomeric_state = int(values[4*j + 1])
                     name = ATOMIC_SYMBOL[Z] + str(A)
-                    if excited_state > 0:
-                        name += '_e{}'.format(excited_state)
+                    if isomeric_state > 0:
+                        name += '_m{}'.format(isomeric_state)
                     yield_j = ufloat(values[4*j + 2], values[4*j + 3])
                     yields[name] = yield_j
 

From 6434886820d1225dfe57dcb4954fd7675148e19f Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Wed, 23 Nov 2016 18:51:05 -0600
Subject: [PATCH 19/27] Address @smharper comments on #761. Also add one
 publication in docs.

---
 docs/source/publications.rst |  5 +++++
 openmc/data/decay.py         | 25 +++++++++++++++----------
 2 files changed, 20 insertions(+), 10 deletions(-)

diff --git a/docs/source/publications.rst b/docs/source/publications.rst
index 7e79cf33f..097cd43d0 100644
--- a/docs/source/publications.rst
+++ b/docs/source/publications.rst
@@ -177,6 +177,11 @@ Nuclear Data
 - Paul K. Romano and Sterling M. Harper, "Nuclear data processing capabilities
   in OpenMC", *Proc. Nuclear Data*, Sep. 11-16, 2016.
 
+- Jonathan A. Walsh, Benoit Froget, Kord S. Smith, and Forrest B. Brown,
+  "Neutron Cross Section Processing Methods for Improved Integral Benchmarking
+  of Unresolved Resonance Region Evaluations," *Eur. Phys. J. Web Conf.*
+  **111**, 06001 (2016). `<http://dx.doi.org/10.1051/epjconf/201611106001>`_
+
 - Jonathan A. Walsh, Paul K. Romano, Benoit Forget, and Kord S. Smith,
   "Optimizations of the energy grid search algorithm in continuous-energy Monte
   Carlo particle transport codes", *Comput. Phys. Commun.*, **196**, 134-142
diff --git a/openmc/data/decay.py b/openmc/data/decay.py
index 41929c034..33d447973 100644
--- a/openmc/data/decay.py
+++ b/openmc/data/decay.py
@@ -80,16 +80,26 @@ class FissionProductYields(EqualityMixin):
     cumulative : list of dict
         Cumulative yields for each tabulated energy. Each item in the list is a
         dictionary whose keys are nuclide names and values are cumulative
-        yields. The i-th dictionary corresponds to the i-th energy.
+        yields. The i-th dictionary corresponds to the i-th incident neutron
+        energy.
     energies : Iterable of float or None
         Energies at which fission product yields are tabulated.
     independent : list of dict
         Independent yields for each tabulated energy. Each item in the list is a
         dictionary whose keys are nuclide names and values are independent
-        yields. The i-th dictionary corresponds to the i-th energy.
+        yields. The i-th dictionary corresponds to the i-th incident neutron
+        energy.
     nuclide : dict
         Properties of the fissioning nuclide.
 
+    Notes
+    -----
+    Neutron fission yields are typically not measured with a monoenergetic
+    source of neutrons. As such, if the fission yields are given at, e.g.,
+    0.0253 eV, one should interpret this as meaning that they are derived from a
+    typical thermal reactor flux spectrum as opposed to a monoenergetic source
+    at 0.0253 eV.
+
     """
     def __init__(self, ev_or_filename):
         # Define function that can be used to read both independent and
@@ -97,17 +107,13 @@ class FissionProductYields(EqualityMixin):
         def get_yields(file_obj):
             # Determine number of energies
             n_energy = get_head_record(file_obj)[2]
-            if n_energy > 1:
-                energies = np.zeros(n_energy)
-            else:
-                energies = None
+            energies = np.zeros(n_energy)
 
             data = []
             for i in range(n_energy):
                 # Determine i-th energy and number of products
                 items, values = get_list_record(file_obj)
-                if n_energy > 1:
-                    energies[i] = items[0]
+                energies[i] = items[0]
                 n_products = items[5]
 
                 # Get yields for i-th energy
@@ -314,7 +320,6 @@ class Decay(EqualityMixin):
             ev = ev_or_filename
         else:
             ev = Evaluation(ev_or_filename)
-        #assert ev.info['sublibrary'] == 'Radioactive decay data'
 
         file_obj = StringIO(ev.section[8, 457])
 
@@ -332,7 +337,7 @@ class Decay(EqualityMixin):
         self.nuclide['isomeric_state'] = metastable
         if metastable > 0:
             self.nuclide['name'] = '{}{}_m{}'.format(ATOMIC_SYMBOL[Z], A,
-                                                    metastable)
+                                                     metastable)
         else:
             self.nuclide['name'] = '{}{}'.format(ATOMIC_SYMBOL[Z], A)
         self.nuclide['mass'] = items[1]  # AWR

From 6ba1f046311aef9ef9b67985b494fbd00fe0caff Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Sun, 27 Nov 2016 06:34:47 -0500
Subject: [PATCH 20/27] Resolving @paulromano comments

---
 .../python/pincell_multigroup/build-xml.py    |  4 +--
 openmc/filter.py                              | 11 +++++---
 openmc/mgxs/library.py                        |  2 +-
 openmc/mgxs/mgxs.py                           | 25 +++++++++++++------
 openmc/mgxs_library.py                        | 10 ++++++--
 tests/test_tallies/test_tallies.py            |  3 ++-
 6 files changed, 38 insertions(+), 17 deletions(-)

diff --git a/examples/python/pincell_multigroup/build-xml.py b/examples/python/pincell_multigroup/build-xml.py
index cc57b61e2..9cc23300d 100644
--- a/examples/python/pincell_multigroup/build-xml.py
+++ b/examples/python/pincell_multigroup/build-xml.py
@@ -36,7 +36,7 @@ scatter_matrix = np.array(
       [0.0000000, 0.0000000, 0.0000000, 0.0001253, 0.2714010, 0.0102550, 0.0000000],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0012968, 0.2658020, 0.0168090],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0085458, 0.2730800]]])
-scatter_matrix = np.swapaxes(np.swapaxes(scatter_matrix, 0, 1), 1, 2)
+scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
 uo2_xsdata.set_scatter_matrix(scatter_matrix)
 uo2_xsdata.set_fission([7.21206E-03, 8.19301E-04, 6.45320E-03,
                         1.85648E-02, 1.78084E-02, 8.30348E-02,
@@ -62,7 +62,7 @@ scatter_matrix = np.array(
       [0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200],
       [0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000]]])
-scatter_matrix = np.swapaxes(np.swapaxes(scatter_matrix, 0, 1), 1, 2)
+scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
 h2o_xsdata.set_scatter_matrix(scatter_matrix)
 
 mg_cross_sections_file = openmc.MGXSLibrary(groups)
diff --git a/openmc/filter.py b/openmc/filter.py
index 61818f89f..a7a8b934a 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -100,10 +100,13 @@ class Filter(object):
     @classmethod
     def _recursive_subclasses(cls):
         """Return all subclasses and their subclasses, etc."""
-        subs = cls.__subclasses__()
-        subsubs = [grand for s in subs for grand in s.__subclasses__()]
-        subsubsubs = [grand for s in subsubs for grand in s.__subclasses__()]
-        return subs + subsubs + subsubsubs
+        all_subclasses = []
+
+        for subclass in cls.__subclasses__():
+            all_subclasses.append(subclass)
+            all_subclasses.extend(subclass._recursive_subclasses())
+
+        return all_subclasses
 
     @classmethod
     def from_hdf5(cls, group, **kwargs):
diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py
index 2e2b7f908..7e0289064 100644
--- a/openmc/mgxs/library.py
+++ b/openmc/mgxs/library.py
@@ -59,7 +59,7 @@ class Library(object):
         The spatial domain(s) for which MGXS in the Library are computed
     correction : {'P0', None}
         Apply the P0 correction to scattering matrices if set to 'P0'
-    scatter_format : {'legendre', or 'histogram'}
+    scatter_format : {'legendre', 'histogram'}
         Representation of the angular scattering distribution (default is
         'legendre')
     legendre_order : int
diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index db31e2f32..58b8a32c2 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -1529,9 +1529,19 @@ class MGXS(object):
         else:
             df = df.drop('score', axis=1)
 
+        # Determine if change-in-angle bins are included in the MGXS to
+        # properly tile the group boundaries
+        if 'mu low' in df:
+            # Find the length of the mu filters indirectly from the number
+            # of times the mu bins repeats.
+            num_mu = int(df.shape[0] /
+                         df[df['mu low'] == df['mu low'][0]].shape[0])
+        else:
+            num_mu = 1
+
         # Override energy groups bounds with indices
         all_groups = np.arange(self.num_groups, 0, -1, dtype=np.int)
-        all_groups = np.repeat(all_groups, len(query_nuclides))
+        all_groups = np.repeat(all_groups, len(query_nuclides) * num_mu)
         if 'energy low [eV]' in df and 'energyout low [eV]' in df:
             df.rename(columns={'energy low [eV]': 'group in'},
                       inplace=True)
@@ -3791,10 +3801,8 @@ class ScatterMatrixXS(MatrixMGXS):
             # than 1, so try each axis in axes one at a time, catching the
             # ValueError as needed.
             for axis in axes:
-                try:
+                if xs.shape[axis] == 1:
                     xs = np.squeeze(xs, axis=axis)
-                except ValueError:
-                    pass
 
         return xs
 
@@ -3874,9 +3882,12 @@ class ScatterMatrixXS(MatrixMGXS):
                 df = df[df['moment'] == 'P{}'.format(moment)]
 
         elif self.scatter_format == 'histogram':
-            # Add a change-in-angle (mu) column to dataframe
-            ###TODO NOT SURE I NEED TO DO THIS
-            pass
+            # Replace the mu low and mu high columns with a single mu bin
+            del df['mu high']
+            df.rename(columns={'mu low': 'mu bins'}, inplace=True)
+            bins = [i + 1 for i in range(self.histogram_bins)]
+            bins = np.tile(bins, int(df.shape[0] / len(bins)))
+            df['mu bins'] = bins
 
         return df
 
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 25452bdb4..347c015e7 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1773,8 +1773,14 @@ class XSdata(object):
                                     np.sum(self._scatter_matrix[i][p, a, g_in, :, :],
                                            axis=1)
                         nz = np.nonzero(matrix)
-                        g_out_bounds[p, a, g_in, 0] = nz[0][0]
-                        g_out_bounds[p, a, g_in, 1] = nz[0][-1]
+                        # It is possible that there only zeros in matrix
+                        # and therefore nz will be empty, in that case set
+                        # g_out_bounds to 0s
+                        if len(nz[0]) == 0:
+                            g_out_bounds[p, a, g_in, :] = 0
+                        else:
+                            g_out_bounds[p, a, g_in, 0] = nz[0][0]
+                            g_out_bounds[p, a, g_in, 1] = nz[0][-1]
 
             # Now create the flattened scatter matrix array
             flat_scatt = []
diff --git a/tests/test_tallies/test_tallies.py b/tests/test_tallies/test_tallies.py
index 9e525d2cf..033c7b812 100644
--- a/tests/test_tallies/test_tallies.py
+++ b/tests/test_tallies/test_tallies.py
@@ -3,13 +3,14 @@
 import os
 import sys
 sys.path.insert(0, os.pardir)
-import numpy as np
+
 from testing_harness import PyAPITestHarness
 from openmc.filter import *
 from openmc import Mesh, Tally, Tallies
 from openmc.source import Source
 from openmc.stats import Box
 
+
 class TalliesTestHarness(PyAPITestHarness):
     def _build_inputs(self):
         # Build default materials/geometry

From 0e029771e70cdf8ebdbf3fcd5b220c65f836ad26 Mon Sep 17 00:00:00 2001
From: Paul Romano <paul.k.romano@gmail.com>
Date: Sun, 27 Nov 2016 16:04:40 -0600
Subject: [PATCH 21/27] Fix decay_constant attribute, add Decay.from_endf
 classmethod

---
 openmc/data/decay.py | 28 +++++++++++++++++++++++++---
 1 file changed, 25 insertions(+), 3 deletions(-)

diff --git a/openmc/data/decay.py b/openmc/data/decay.py
index 33d447973..4327b2fc3 100644
--- a/openmc/data/decay.py
+++ b/openmc/data/decay.py
@@ -157,7 +157,7 @@ class FissionProductYields(EqualityMixin):
             assert np.all(energies == self.energies)
 
     @classmethod
-    def from_endf(cls, filename):
+    def from_endf(cls, ev_or_filename):
         """Generate fission product yield data from an ENDF evaluation
 
         Parameters
@@ -172,7 +172,7 @@ class FissionProductYields(EqualityMixin):
             Fission product yield data
 
         """
-        return cls(filename)
+        return cls(ev_or_filename)
 
 
 class DecayMode(EqualityMixin):
@@ -460,4 +460,26 @@ class Decay(EqualityMixin):
 
     @property
     def decay_constant(self):
-        return log(2.)/self.half_life
+        if hasattr(self.half_life, 'n'):
+            return log(2.)/self.half_life
+        else:
+            mu, sigma = self.half_life
+            return ufloat(log(2.)/mu, log(2.)/mu**2*sigma)
+
+    @classmethod
+    def from_endf(cls, ev_or_filename):
+        """Generate radioactive decay data from an ENDF evaluation
+
+        Parameters
+        ----------
+        ev_or_filename : str or openmc.data.endf.Evaluation
+            ENDF radioactive decay data evaluation to read from. If given as a
+            string, it is assumed to be the filename for the ENDF file.
+
+        Returns
+        -------
+        openmc.data.Decay
+            Radioactive decay data
+
+        """
+        return cls(ev_or_filename)

From 0a0b50de2f630c35264ac007da18d929ede8d7fe Mon Sep 17 00:00:00 2001
From: Will Boyd <wbinventor@gmail.com>
Date: Mon, 28 Nov 2016 10:22:47 -0500
Subject: [PATCH 22/27] Removed use of Filter.type property

---
 .../pythonapi/examples/mgxs-part-ii.ipynb     | 1049 ++++++++++-------
 openmc/filter.py                              |   15 +-
 2 files changed, 627 insertions(+), 437 deletions(-)

diff --git a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
index c43fab6ff..e35c205c3 100644
--- a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
+++ b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
@@ -34,7 +34,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/romano/miniconda3/envs/default/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning:  This call to matplotlib.use() has no effect\n",
+      "/home/wbinventor/miniconda3/lib/python3.5/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
+      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n",
+      "/home/wbinventor/miniconda3/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning:  This call to matplotlib.use() has no effect\n",
       "because the backend has already been chosen;\n",
       "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n",
       "or matplotlib.backends is imported for the first time.\n",
@@ -453,8 +455,8 @@
       "         Copyright | 2011-2016 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | da5563eddb5f2c2d6b2c9839d518de40962b78f2\n",
-      "         Date/Time | 2016-10-31 12:29:16\n",
+      "          Git SHA1 | 2c25ec97653482825b529215b8a61b54d468d34e\n",
+      "         Date/Time | 2016-11-28 09:10:24\n",
       "    OpenMP Threads | 4\n",
       "\n",
       " ===========================================================================\n",
@@ -465,11 +467,16 @@
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
-      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
-      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
-      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
-      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
+      " Reading U235 from\n",
+      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/U235.h5\n",
+      " Reading U238 from\n",
+      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/U238.h5\n",
+      " Reading O16 from\n",
+      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/O16.h5\n",
+      " Reading H1 from\n",
+      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/H1.h5\n",
+      " Reading Zr90 from\n",
+      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/Zr90.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
@@ -531,7 +538,7 @@
       "       48/1    1.21610    1.22612 +/- 0.00251\n",
       "       49/1    1.22199    1.22602 +/- 0.00245\n",
       "       50/1    1.20860    1.22558 +/- 0.00243\n",
-      " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10050\n",
+      " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10057\n",
       " The estimated number of batches is 73\n",
       " Creating state point statepoint.050.h5...\n",
       "       51/1    1.21850    1.22541 +/- 0.00237\n",
@@ -557,7 +564,7 @@
       "       71/1    1.19720    1.22444 +/- 0.00195\n",
       "       72/1    1.23770    1.22465 +/- 0.00193\n",
       "       73/1    1.23894    1.22488 +/- 0.00191\n",
-      " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10050\n",
+      " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10057\n",
       " The estimated number of batches is 74\n",
       "       74/1    1.22437    1.22487 +/- 0.00188\n",
       " Triggers satisfied for batch 74\n",
@@ -570,20 +577,20 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  5.0262E-01 seconds\n",
-      "   Reading cross sections          =  3.4207E-01 seconds\n",
-      " Total time in simulation          =  1.2843E+02 seconds\n",
-      "   Time in transport only          =  1.2831E+02 seconds\n",
-      "   Time in inactive batches        =  8.1328E+00 seconds\n",
-      "   Time in active batches          =  1.2030E+02 seconds\n",
-      "   Time synchronizing fission bank =  2.9797E-02 seconds\n",
-      "     Sampling source sites         =  2.1385E-02 seconds\n",
-      "     SEND/RECV source sites        =  8.2632E-03 seconds\n",
-      "   Time accumulating tallies       =  1.4577E-03 seconds\n",
-      " Total time for finalization       =  1.3462E-02 seconds\n",
-      " Total time elapsed                =  1.2901E+02 seconds\n",
-      " Calculation Rate (inactive)       =  12295.9 neutrons/second\n",
-      " Calculation Rate (active)         =  3325.12 neutrons/second\n",
+      " Total time for initialization     =  3.1270E-01 seconds\n",
+      "   Reading cross sections          =  1.8695E-01 seconds\n",
+      " Total time in simulation          =  1.1922E+02 seconds\n",
+      "   Time in transport only          =  1.1903E+02 seconds\n",
+      "   Time in inactive batches        =  8.5633E+00 seconds\n",
+      "   Time in active batches          =  1.1066E+02 seconds\n",
+      "   Time synchronizing fission bank =  2.4702E-02 seconds\n",
+      "     Sampling source sites         =  1.8297E-02 seconds\n",
+      "     SEND/RECV source sites        =  6.2794E-03 seconds\n",
+      "   Time accumulating tallies       =  2.6114E-03 seconds\n",
+      " Total time for finalization       =  1.6967E-02 seconds\n",
+      " Total time elapsed                =  1.1961E+02 seconds\n",
+      " Calculation Rate (inactive)       =  11677.8 neutrons/second\n",
+      " Calculation Rate (active)         =  3614.65 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
@@ -1172,169 +1179,239 @@
      "text": [
       "[  NORMAL ]  Importing ray tracing data from file...\n",
       "[  NORMAL ]  Computing the eigenvalue...\n",
-      "[  NORMAL ]  Iteration 0:\tk_eff = 0.574672\tres = 0.000E+00\n",
-      "[  NORMAL ]  Iteration 1:\tk_eff = 0.679815\tres = 4.253E-01\n",
-      "[  NORMAL ]  Iteration 2:\tk_eff = 0.660826\tres = 1.830E-01\n",
-      "[  NORMAL ]  Iteration 3:\tk_eff = 0.658941\tres = 2.793E-02\n",
-      "[  NORMAL ]  Iteration 4:\tk_eff = 0.643012\tres = 2.852E-03\n",
-      "[  NORMAL ]  Iteration 5:\tk_eff = 0.625810\tres = 2.417E-02\n",
-      "[  NORMAL ]  Iteration 6:\tk_eff = 0.606678\tres = 2.675E-02\n",
-      "[  NORMAL ]  Iteration 7:\tk_eff = 0.587485\tres = 3.057E-02\n",
-      "[  NORMAL ]  Iteration 8:\tk_eff = 0.569029\tres = 3.164E-02\n",
-      "[  NORMAL ]  Iteration 9:\tk_eff = 0.551707\tres = 3.142E-02\n",
-      "[  NORMAL ]  Iteration 10:\tk_eff = 0.536035\tres = 3.044E-02\n",
-      "[  NORMAL ]  Iteration 11:\tk_eff = 0.522274\tres = 2.841E-02\n",
-      "[  NORMAL ]  Iteration 12:\tk_eff = 0.510609\tres = 2.567E-02\n",
-      "[  NORMAL ]  Iteration 13:\tk_eff = 0.501106\tres = 2.234E-02\n",
-      "[  NORMAL ]  Iteration 14:\tk_eff = 0.493831\tres = 1.861E-02\n",
-      "[  NORMAL ]  Iteration 15:\tk_eff = 0.488780\tres = 1.452E-02\n",
-      "[  NORMAL ]  Iteration 16:\tk_eff = 0.485923\tres = 1.023E-02\n",
-      "[  NORMAL ]  Iteration 17:\tk_eff = 0.485210\tres = 5.846E-03\n",
-      "[  NORMAL ]  Iteration 18:\tk_eff = 0.486569\tres = 1.467E-03\n",
-      "[  NORMAL ]  Iteration 19:\tk_eff = 0.489903\tres = 2.801E-03\n",
-      "[  NORMAL ]  Iteration 20:\tk_eff = 0.495103\tres = 6.852E-03\n",
-      "[  NORMAL ]  Iteration 21:\tk_eff = 0.502053\tres = 1.061E-02\n",
-      "[  NORMAL ]  Iteration 22:\tk_eff = 0.510627\tres = 1.404E-02\n",
-      "[  NORMAL ]  Iteration 23:\tk_eff = 0.520693\tres = 1.708E-02\n",
-      "[  NORMAL ]  Iteration 24:\tk_eff = 0.532117\tres = 1.971E-02\n",
-      "[  NORMAL ]  Iteration 25:\tk_eff = 0.544764\tres = 2.194E-02\n",
-      "[  NORMAL ]  Iteration 26:\tk_eff = 0.558501\tres = 2.377E-02\n",
-      "[  NORMAL ]  Iteration 27:\tk_eff = 0.573195\tres = 2.522E-02\n",
-      "[  NORMAL ]  Iteration 28:\tk_eff = 0.588718\tres = 2.631E-02\n",
-      "[  NORMAL ]  Iteration 29:\tk_eff = 0.604946\tres = 2.708E-02\n",
-      "[  NORMAL ]  Iteration 30:\tk_eff = 0.621759\tres = 2.756E-02\n",
-      "[  NORMAL ]  Iteration 31:\tk_eff = 0.639047\tres = 2.779E-02\n",
-      "[  NORMAL ]  Iteration 32:\tk_eff = 0.656702\tres = 2.780E-02\n",
-      "[  NORMAL ]  Iteration 33:\tk_eff = 0.674624\tres = 2.763E-02\n",
-      "[  NORMAL ]  Iteration 34:\tk_eff = 0.692722\tres = 2.729E-02\n",
-      "[  NORMAL ]  Iteration 35:\tk_eff = 0.710910\tres = 2.683E-02\n",
-      "[  NORMAL ]  Iteration 36:\tk_eff = 0.729109\tres = 2.625E-02\n",
-      "[  NORMAL ]  Iteration 37:\tk_eff = 0.747248\tres = 2.560E-02\n",
-      "[  NORMAL ]  Iteration 38:\tk_eff = 0.765263\tres = 2.488E-02\n",
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      ]
     }
    ],
@@ -1367,8 +1444,8 @@
      "output_type": "stream",
      "text": [
       "openmc keff = 1.223474\n",
-      "openmoc keff = 1.220892\n",
-      "bias [pcm]: -258.1\n"
+      "openmoc keff = 1.220814\n",
+      "bias [pcm]: -266.0\n"
      ]
     }
    ],
@@ -1443,237 +1520,346 @@
      "text": [
       "[  NORMAL ]  Importing ray tracing data from file...\n",
       "[  NORMAL ]  Computing the eigenvalue...\n",
-      "[  NORMAL ]  Iteration 0:\tk_eff = 0.495816\tres = 0.000E+00\n",
-      "[  NORMAL ]  Iteration 1:\tk_eff = 0.557477\tres = 5.042E-01\n",
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+      "[  NORMAL ]  Iteration 313:\tk_eff = 1.222599\tres = 1.946E-05\n",
+      "[  NORMAL ]  Iteration 314:\tk_eff = 1.222622\tres = 1.899E-05\n",
+      "[  NORMAL ]  Iteration 315:\tk_eff = 1.222644\tres = 1.852E-05\n",
+      "[  NORMAL ]  Iteration 316:\tk_eff = 1.222665\tres = 1.807E-05\n",
+      "[  NORMAL ]  Iteration 317:\tk_eff = 1.222686\tres = 1.763E-05\n",
+      "[  NORMAL ]  Iteration 318:\tk_eff = 1.222707\tres = 1.720E-05\n",
+      "[  NORMAL ]  Iteration 319:\tk_eff = 1.222727\tres = 1.678E-05\n",
+      "[  NORMAL ]  Iteration 320:\tk_eff = 1.222746\tres = 1.637E-05\n",
+      "[  NORMAL ]  Iteration 321:\tk_eff = 1.222766\tres = 1.597E-05\n",
+      "[  NORMAL ]  Iteration 322:\tk_eff = 1.222784\tres = 1.558E-05\n",
+      "[  NORMAL ]  Iteration 323:\tk_eff = 1.222802\tres = 1.520E-05\n",
+      "[  NORMAL ]  Iteration 324:\tk_eff = 1.222820\tres = 1.483E-05\n",
+      "[  NORMAL ]  Iteration 325:\tk_eff = 1.222837\tres = 1.446E-05\n",
+      "[  NORMAL ]  Iteration 326:\tk_eff = 1.222854\tres = 1.411E-05\n",
+      "[  NORMAL ]  Iteration 327:\tk_eff = 1.222870\tres = 1.377E-05\n",
+      "[  NORMAL ]  Iteration 328:\tk_eff = 1.222886\tres = 1.343E-05\n",
+      "[  NORMAL ]  Iteration 329:\tk_eff = 1.222902\tres = 1.310E-05\n",
+      "[  NORMAL ]  Iteration 330:\tk_eff = 1.222917\tres = 1.278E-05\n",
+      "[  NORMAL ]  Iteration 331:\tk_eff = 1.222932\tres = 1.247E-05\n",
+      "[  NORMAL ]  Iteration 332:\tk_eff = 1.222947\tres = 1.216E-05\n",
+      "[  NORMAL ]  Iteration 333:\tk_eff = 1.222961\tres = 1.187E-05\n",
+      "[  NORMAL ]  Iteration 334:\tk_eff = 1.222975\tres = 1.158E-05\n",
+      "[  NORMAL ]  Iteration 335:\tk_eff = 1.222988\tres = 1.129E-05\n",
+      "[  NORMAL ]  Iteration 336:\tk_eff = 1.223001\tres = 1.102E-05\n",
+      "[  NORMAL ]  Iteration 337:\tk_eff = 1.223014\tres = 1.075E-05\n",
+      "[  NORMAL ]  Iteration 338:\tk_eff = 1.223027\tres = 1.049E-05\n",
+      "[  NORMAL ]  Iteration 339:\tk_eff = 1.223039\tres = 1.023E-05\n"
      ]
     }
    ],
@@ -1699,8 +1885,8 @@
      "output_type": "stream",
      "text": [
       "openmc keff = 1.223474\n",
-      "openmoc keff = 1.223227\n",
-      "bias [pcm]: -24.7\n"
+      "openmoc keff = 1.223039\n",
+      "bias [pcm]: -43.5\n"
      ]
     }
    ],
@@ -1753,7 +1939,7 @@
    "outputs": [],
    "source": [
     "# Parse ACE data into memory\n",
-    "u235 = openmc.data.IncidentNeutron.from_ace('../../../../scripts/nndc/293.6K/U_235_293.6K.ace')\n",
+    "u235 = openmc.data.IncidentNeutron.from_hdf5('../../../../data/nndc_hdf5/U235.h5')\n",
     "\n",
     "# Extract the continuous-energy U-235 fission cross section data\n",
     "fission = u235[18]"
@@ -1785,9 +1971,9 @@
     },
     {
      "data": {
-      "image/png": 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9XXjr7b+y8zNjUla2RCW78zkTk6HJfXETg4g8qKpnisg8nOsWwtsBUNVONCOO\nSZZgaZdWRySVBteyxxvX8/OvYzNuMZt4iaGjvulbjcGkQ0s1hinu76tTUA7TSVVNmEjJbTe1mhzK\nWMtTT+UzblxmLQUSb66keNZl3QZjUqWlFdw+dP9cAKxS1beAjYCDgK9SUDbTCbQ0tLXpcNbHH8/P\nuMnp2tqU1NaTvsdjWcKkXiItmE8CR4rILsA1QAXOxW7GpFTXriHeeiv9Y/1DoebrMCSzjyEYhNra\n5BzfmFgSSQz9VPVK4EjgYVW9jsa1GYxJmRNOqOfJJ/PTXQx69Srj4YedcrRlSgyA1as9PP1024bp\n3ndfPhtvXJbQvjNn+rjsssKobbYet2mrRBKDT0Q2AA4DXhKRDYGkXYkjInuLyIMi8oSIbJesOCb7\njBhRz9tv+zJi6cxFi5yaS/gCt0RmVwUnMYwf37ZV7hYvjv8xveaaQlaubHw9Hnwwn4cfjr5wsG/f\nMl57Lf01LZM9EkkMtwHvAy+56zK8DVybxDIVq2p40r79khjHZJnNNi/n99Vett6mjB49y6N+uvfr\nQ/F9qZuppWlNYfny5CSr1kYl3XtvAW++2XjSj9eH8fPPNu7VJC6R2VWfUtXNVPV8ESkHDlfVf7Yn\nmIgMdoe/IiIeEblfRN4VkTdEpL8b7yURKQHGYX0ZnV6ik/G1NEPr7793ZIkcTRPD5MmF8XfuIN98\nk/6akukcEpld9TQR+buI9AC+AJ4TkevbGkhEJgAPAeFP0GFAoaoOBSYCk9z9NsCZpO9KVV3Z1jgm\nt7RlptZYQ17ffx+23LKsw4eAhi88a2+nc0UFfPxx7I9fXcSI3DlzGvsj9tuvlB12KG22/9KlXlav\ndv4OhZzkcf/9+UnrEDe5L5H65RjgIuBYYAawHfDndsRaDBwecXt34FUAd5K+ndztdwAbAjeJyBHt\niGNySKzhrNdfV82RI+piDmltatEi50QZ2Q7fEcKJob0J56abCtl//+Yn+SVLPAwZ0pgIb7utsSay\nZo2HpUubf2Svv76QU08tjirPVVcVdfhzNp1HQsMjVPU3ETkQ+Juq+kWkbb1nzjGmi8gmEZvKgdUR\ntwMi4lXVUW05rs/npby8zcVpF4uVGfFOOw223TaPVauK2WST6PuaHvfzz50TaU1NEeXRM260aO5c\nDz/+CKecEvvM/+KLPgYNKmHXXRvvj3xexcUFlJc7I5fq65s/3uOJ/dGrq2s+cXF+fvS+5eXFzV7D\nioq8hu1uBJXJAAAgAElEQVRhXbo0PudLLili/Pj2T1qYq+9HixXn8Qns87mIzAL6A3NF5Fngv+2O\n2KgCiByD51XVNl++5PcHqaio7oDitK68vNhiZUA8nw9OPLGA66/3cMcdtVHLhDY97sKFzrfvn3+u\nY+ONE29bOf/8Er7+Oo8RI2JNDVZGTY2Hiy7K49VXKwl/jBrfi2UsWOAnGAyw334Bxo5tfrKvq/MD\nzacdr6ysJfJjGQqB3x+9b0VFdcRr6HyEAgEntt9fAjid0WvX1lBREWrYZ11e81x9P3bmWD16xB8C\nnUhT0qnArcAQVa0DnnC3rav5wIEAIjIEWNQBxzSdxNln1zFrVj5LlsRvLgkG4bPPYOedA23ugM5L\ncHRnvOsXJk8u5IQTSrjvvnymTWt+7cXUqbHXorjxxuhO7MiZVhMR2bR18MElLF1qzUmm7eImBhE5\n0/3zMmAYcI6IXAkMBC7vgNjTgVoRmY/Tr3B+BxzTdBLdusHYsXX89a/x14z64QcP5eWw6aZBfv+9\nbSfIRDtum86R1PTK7KuvbtuaVu+803olftq05vt89lkeM2dGb//uOy9nnx0df8yYIubPt2saTMta\nehd6mvxeZ6r6PTDU/TsEnN1Rxzadz1ln1fHss/GvtVy0KI8BA0J07Rpi9eq2vY3DF661pmnn88iR\nyV+FbezYYsaOhXnzor/Xffhh8xP+ggXRH/HnnsunqCjEbrvZkCUTX0uJ4SMAVb0mRWUxpk0KCuD2\n22vhkNj3f/hhHrvsEmL16hBr17Y1MSS+3xZbBPjtt9Q32Xz2WXRiuO++7F8q1WSGlvoYwtNuIyJ3\npKAsxrTZkCHxv/m+914egwdDWVmINWuSlxgKCqC+PvWJYdy41I0kM51LS4kh8p2+V7ILYkxHCJ/Q\nv/vOw3ffedh99xBlZc46ym2R6PUJ4cSQ6FxJmejOOwuorEx3KUwmSXQCFRvaYLLCiScW8957eVxy\nSREnn1xPfn5yawyBABQWhpKaGDrqqu0XXnBajsPzLwUCcNJJRdx0U2HM/gnTebWUGEJx/jYmYw0a\nFOCvfy2kX78gF17ozC3RlsRQXQ09e5YlnBhCoXBTUntLnDoPPhjdB1FZCa++mv5pzE3maanzeQcR\nCTfgeiL/BkKqal8xTMY5//w6zj8/evnPtjQlhUcvJbqGgd/vJAZI3mI94fmP1v040bfD02gATJhQ\nxLffelm+vI1tbiYnxU0Mqmrz9Jqc0KVL4jWG8AVl8S4sa9pkFAh48PlC5Ocnr9bQUU1Jkcf54AMv\nb7/d+PH/9tvGj7uql27dQvToYQ0FnZWd/E3OKytLfLhqhTsnn98fe/+mNQm/35lQz+fL/MSwcKFT\nyX/iiQL+8pfmE/iF7bFHKWee2bYL80xuscRgcl55eeI1hqqqlverqYm+Pxh0kkJVlYddd01O62pH\nTxmeiPnzfaxtPou56SQsMZic16WL08eQyAm2qqrl+2tro2/7/Y3zKi1enFuD9777zk4PnVWrE7OI\niAc4C9jH3X8eMLk9M6Eak2w9ejafW7sP4Afo1frjT3R/woL9ulA1YSLVY8YBzZuSAoHEJ9xrr1TW\nGHr2bJxx8/77CzjvvDq6dg3Rs6eP5ctTVw6TXol8JbgV2B+YCjyKc7GbXQltMkaiK7y1R9MlQ6ur\no2sFqUgM6TJtWj4PP5zf0O9iOo9EEsN+wBGq+i9VnQEcSftWcDMmKdqy/Gd7RC4Z2rQpKTwqKZnS\n0cdgOrdEFurxuT91EbdtakaTMarHjGto6mkqvGDJ8OEl3HprDQMHttwCOnlyAddd56yJEIpxwX/T\nzufwqKRkypTE8M03HjbbLEMKY5Iqkbf0P4A3RWSciIwD3gCeSm6xjOlYiV79XN3KAlux+hh8Puda\niWR5/vn0XZ383HP5DVNo7Lpr8mplJrMkkhhuAa4D+gKbAjeo6o3JLJQxHS1WYli2zMOFF0avmNba\n9Q5NawzhPobS0tz8Jr1mjYfKytwabWVal0hT0gequiPwSrILY0yyxJoW480383jiiQLuuKOx42DF\nCg/rrx9i1arYJ8PmfQxOYijK4evBFixo7F1futRDnz4hpk/3seWWQbbZxgYn5qJEEsP/RGQP4D+q\nWtvq3sZkoK5dQ80W0/HEOPcvX+6hb98gq1bFHmrU/DoGD3l5kJ+fmzUGgCuuaMx6Bx9cwg47BJg5\nM5899vDz/POpWdzepFYiiWEQ8BaAiISwSfRMFtpuuwBvvOEDGuetiJUYVqzw0Ldv85N8+PqIc92f\nBtd1aDEz34/uD8A7QM/2HSZYGn19iMksrfYxqGoPVfW6k+r53L8tKZissssuAd5/Py9qhE94au3I\nWVFXrPBQXu7stBbrbE2WpteHmMzSamIQkWEiMt+9uaWILBGRoUkulzEdql+/EPX18NNPjdWEcKdq\neBqM+npn2u2SEicx3Fx0VVKvj+jsIq8PMZklkaakScBJAKqqInIg8ASwczILZkxH8nicWsN//pPH\nxhs7c2c3JgYPZWVOH8T664fYZpsgvXoFuWvthYz/djTgTBXx7rtree65fCZPLmhY4/n882spLIQ5\nc3ydehW0hQvX0qdPYv0ssaYtMZklkeGqRar6WfiGqv4fYMs+mawTTgxh4ZpCeL3jNWuc0Usnn1zP\nu+9WNlvF7YcfvDz7bD5duzaeAMOT6LXW+bz77lm8KLTpdBJJDP8nIreIyLbuz/XAV8kumDEdbY89\nArz2mq9hZFG4xhD+vXathy5dQng8kJ/ffEW2WbN8/PSTl+7dG5NAIOAhLy+Er5W695575vZkAd9/\nbzOx5pJE/punAV2Ap3Em0usCnJHMQhmTDNttF2TbbYPcfLNzUVt4vYGmiQGcWkA4MYQ7rMOjmDba\nKDIxOPv26tVyjSFyor2rr05w3dAscuihJRkzdYdZd632MajqKmBsCspiTNLdfXc1f/lLKT5fiJ9+\ncr4XhZuU1q511m6AcGJwMkE4Qfz2m4fzz6+lvDzkDn1tnBLjjjtqmDfP1+xaibDIifa65Gh/dm1t\nbl/o15nErTGIyEfu76CIBCJ+giKS2/Vik7O6dYOZM6v44IM83nknj8GD/TFrDOGJ8YLBxsSwapUz\nlDWy2Sg8iV5JCVFJ4auvoi+zjqwx5Oo03TNnJjKWxWSDuP9JdxoM3OsXUk5E9gKOU1VrtjIdaoMN\nQkyfXk1dHdx4YyHffOO8xdeu9UTNeZSXFyIQiE4MXbtGT6QXrjFEuuuuatZbL3pbdGLIzTaX8eOL\nGDnShqDmgriJQUROaumBqjq144vTEHszYCBQ2Nq+xrSHxwOFhTBkSIB7783nvPOim5KgsZ8hPDrp\n11+dGkNdXWPNIHKhni++8LP11j6OOqr5CKRkT82dCfx+m2wvV7RU93sMWA7MxVmLIfK/HsLpiG4z\nERkM3Kyqe7nLht4HDABqgNNVdYmqfgNMEpGkJR9jAIYP9/PXvxby3/96o5qSoDEx+N3z/KpVzvUO\nkRPs1dV5KChwHtO/PyxduibmCKXI6TdiTcVhTCZp6XvMjjhLeW6FkwieBk5T1VNU9dT2BBORCcBD\nNNYEDgMKVXUoMBHnYrpI9hEySeXzwdixddx5ZyGVlc6JPywvL9zH4LwN6+s9dO0a3cdQVwcFBdHH\ni8Xjgdtvd9qgOkPtwWS3uG9RVV2oqhNVdRBwPzAc+I+IPCAiw9oZbzFweMTt3YFX3Xjv40zYFyk3\nG2NNRjnuuHoWLvSyaJG3WVOS3x99PUN5eSiqj6BpYojH66VhDqby8hAbbGDTVZvMldAwAlX9L/Bf\nd/rtm4EToO0zjKnqdBHZJGJTObA64rZfRLyqGnT3b7GfA8Dn81JeXtzWorSLxcq+eInEKi+HAw6A\nqVN9jBnjobzc5z4WSkqKqatr3LdPnyJKSxsrsqFQHuut56W8PL/FWMXF+ZSUOH+vt14hP/0UpKgo\n96oObf2/xto/094fnTFWi4nB7QPYExgJHAAsBCYDM9sdMVoFUBZxuyEpJMrvD1JRkZo54cPrB1us\n7ImXaKzBg31MnVqMz1dLRYVTRfB4Svn99xrq6yH8Pcjrraauzgc4H7qqqiD19XVUVARixGp8a9fW\n1lNTEwKKqakJx4h86+eGRF7rHq3sn4nvj1yM1aNH/PdfS6OS7gf+DHwMPAtcoqqV7StmXPOBg4Dn\nRGQIsKiDj29MQnbayUkGsfsYGvcrKoruR6ivj9+U5Ax39TT8He50ts5nk+laqsuOxvmaNBC4CVjk\nTrm9RESWdFD86UCtO633HcD5HXRcY9qkX78Qu+7qZ/PNGyus4VFJTedMiuw8rq/3xJ1Ab+HCxu9R\ngYCnISG0pfN55Mj61ncypoO11JTULxkBVfV7YKj7dwg4OxlxjGkLjwdmzIiuejcmBk+z7WG1tfFr\nDOFhrOB0UreWGCZPrmbcOKeJasqUamprnXmcpk2zyYxNarV05fP3qSyIMZnG641dY4gclVRf78zE\nGktkk1F9PS02JS1f7kyh8ckndTz8cAGHH+5cPPHII5YUTOrl3rAIYzpIuI8hclRSeHtYXZ2HwsLY\nTUmRNYPIGkNLfQxN77MZS006WGIwJo5w53FLiSHRGoPf78HrDU/Ql/jZPtsSQ3imWpPdLDEYE4fP\n51zgFp4baeutnTalyERQUxO/jyEyMRxySH3D7UQuiMtWgwaVusN7TTazxGBMHF6v05RUWwt/+EOQ\nqVOdzunwkFaPJ0RtbfxRSY0L+wTp379xuGq8GkaueP/9xipVKATLltn43GxjicGYOMKjkqqrPWy7\nbYC+fZ0E0K9fkMGD/fh8idUYwtc9JFJj2G676J7ubLvm4cwz67nsskKefdbHvvuW8Nhj+Wy/fRde\nfrlxSVWT+SwxGBNHODH89puHbt0aawXl5TBzZjX5+eHrGGI/Pjxd9wsvOA3vjTWG+B0Hxxzjbxih\nFPmYbDF2bB2XX17LFVcUsXixl0sucZZ0O/nkYmbPtoV8soUlBmPiCA9X/flnDz17Nj+Zd+/ubItX\nAygpgQsuqGXjjcNNT7S4fy7Iz4f99w/wxBNV3Htv9NrWK1dmWZbrxCwxGBNHXl6IYNDDggV5DB7c\nfDXb8Gyp8b7Ve71w6aWNQ5rCk+gVFSU+1Cjbagxhu+wS5C9/8TNrVuPV33fdVdDsmhCTmSwxGBNH\nXh6sWQMLF8ZODLFqES0JJ5KuXRN/TLYmhrBddgmycOFaNtssSPfuIcaPL0p3kUwCLDEYE4fPB//+\nt48BAwJR6zRE3t8WPXo4iSHyOojOoE+fEAsWVDJyZD3PPhvdIfP991me+XKUJQZj4igshDffzGPo\n0NjtH239Nt+jRyiqYzkR2V5jiHT22fV8/33089955y4sXZpDTzJHWGIwJo6SkhBffpnHoEHpaxjP\npcTg8UBxjLVjrriikLVr4eabC/jppxx6wlnMxo8ZE0f4JNa/f+y1o4IpWJ0zlxJDPDNn5vPNN16+\n+CKPuXN9vP56iIoK5/Wvq4PS0nSXsPOxGoMxcRQXO30CvXrF7mRORWJo6qabalrfKYssXryGI46o\n54svnI6XTz/No0cPH5tvXsbFFxcycGCbVxA2HcASgzFxhCfPCw8zbSodNYbTTsutiYjKy+Gkkxqf\n0yabBBsmGfzHPwr4/XcPvXpZckg1SwzGxLF6dcvtOOmoMeSiAQMCHHFEPW+9VckHH1RSVRVgzz2d\n9ShEAoRCHn77DVS9PPWUjxUrPHzyiZ26ksn6GIyJo6Ii/YmhZ8/czz6lpfDAA9FNZHfcUcMVVxQy\ndWoNm27aha22KiM/P0R9vYejj65n2TIP06a1vNi9aT9Lu8bEccghfo4+On7TzVVX1XLPPe0/OUUu\n/RnPfvu1bUTU+++vbW9xMsomm4SYOtVJFjNnVjFyZD077OAkyX/+M5+33vLxwAM5Pk1tGlmNwZg4\nRo2qZ9So+IlhwIAgAwa0/xt9v35BVPN48cX4q9u0Nipp9Og6fvzRw8sv57vHzLKVfRKw3XZB7rmn\nhspKePfdPE44wen0ufLKIn7+2cu++/rZeedA3L6gzi4UgmnTfEybls/664e44II6ttqq5fet1RiM\nSZNwU1TXru0/mffuHWzzFdjZyOOBLl1g330DTJ9exRZbBBg1qo7S0hC33lrINtt0YfToIubNy7P5\nmJp48UUfd91VwIkn1rPttkFGjChmzz1bzqKWGIxJk3DTSKLXKmy7beMZ76uv/A1/t7b855NPNtZI\nbrut9eGup55a1+o+6eL1wm67BZg/v4rbbqvl0kvreOmlKj76aC277BLghhsKGTSolJtvLuCjj7zU\n5Nbo3jarqoIbbijk9ttrOeQQP+eeW8enn1byz3+23ARqicGYNJk82TlrJZIYTj21jjfeaN+Cym3t\np9h99+z7yr3++s5Q3rlzq3jyyWoqKz1ceGERIl3Yd98SLrywkLlz83J2JFldHVx2WSHbbVfKYYcV\nc845Xp57zsc11xQycGAgalqXvDzo3bvlbxOdoBJqTGbyul/LEkkMfftGn9FaqyWMHl3HkCEBTjml\n+RwUO+wQYOHC+DP5desW4umnqzj22OQ32vfoWR57+zocc5j70+BT9+eJOGVYh1iJCJZ2oWrCRLj0\n4qTFuPbaQr75xsuLL1bx889evv++kBdeyOeXXzyt1g5iscRgTJq1lhjuvLOGAw6I3wkeK0mMHFnP\nZpvF/no8eHDzxJCXFyIQcAoyZEiAN99M3hSwwdIueCtzY/RUIryVaym57Sbqk5QYfv7Zw7Rp+fz7\n35X06BFis80ClJeHOPHE9o+Ys6YkY9KstcRw/PH1dOsWvW399Rsf21rtoS2xEt1nXVRNmEiwtHNd\nzZzMRDhtWj6HHVbfMK17R7AagzFp1tYT8fLlaygvjzFNaTuddFIdG2wQYtKkwlbL88c/Bvjyy3Wr\nTVSPGUf1mHFx7y8vL6aiIjUXr5WXF7N6dTVffOFl3rw85s3z8eGHeQwYEGC33QIccICfrbcOtnsN\njXhNZR1p1iwf11xT26HHzLjEICK7AqOBEDBeVSvSXCRjksrjWbdveldcUUtFhYd33mn8OMerRcQ6\n6d9+u3NSCSeGePsB7LhjgIoKDz//nDuNDR4PbLNNkG22CXLOOfVUVcH8+Xm8/baPM84opqIChg8P\ncPzxdey8c7BDa1QVFfD553l8+aWXpUs99OoVYqONQmy6aZCttgo29EPF8913HpYu9TBkSMcOGMi4\nxACc6f7sAhwDPJje4hiTXOt6HUL//iEefbSal15q+UBdu4b405/8fPVVQbtjeTyw9dbBZonhj38M\ncMgh/jiPyi4lJU4iGD48wHXX1fLxx17mzvVx7rnFVFbC+uuH8Hqd12G77QIMGRJg4MDWhzsVFuU3\n6+juAWwGHNLOsvYAVgD0jn1fi1pog0xpYhCRwcDNqrqXiHiA+4ABQA1wuqouAbyqWiciy4C9U1k+\nY1Lt9dcr2XTTdW8bLi+HY49t+cT84IPV9O0bYr31Wo/X0rfisjLn8Xvt5ef33z18/HEe8+ZVtfrt\nNlsNHBhk4MA6Lrqojh9+8FBV5aGuDj7/3MuiRXk88kgBvXsH2XPPAJtuGmTDDUOUloaoq/Pw56Iu\n5NdkX0d7yhKDiEwATgTCr9JhQKGqDnUTxiR3W5WIFODkwGWpKp8x6bDddus2sD7WyXiDDYL84Q/N\nT/7hk/2BB/q55ZZCSkpCVFXFzgAtJYbbbqvhhRfyWW+9UMMMtLmaFCJ5PM4cTk4rN+50KH6uu66W\nV17x8dlnXubM8bF8uZM8CgpCfNfrSk7/6VqKA9mVHFJZY1gMHE7jaOLdgVcBVPV9EdnJ3f4QMMUt\n2+gUls+YrPLcc1Uxlx394otKwLnqNZaWTvp5ec5Jr7Aw/j5lZbDzzgH239/Pgw+2v1kqV/h8cPDB\nfg4+ONa9Z7GWs1hLx3WqL1/uYfLkAp5/3sf48XWMHt18KHMisVpqakpZYlDV6SKyScSmcmB1xO2A\niHhV9SPglESP6/N5O3SEhsXKrXi5HOugg1o+KYf7LsJlKi0tpLw8RJcmI0UjyxwKObeHD4f33vMz\nZIhzkP33DzF7tof8fB/l5V7eeScE5PPII95mx1hXufw/64hY5eVw991w991BnFN489P4usZKZ+dz\nBVAWcdurqm2uV/v9wZQObbNY2RWvM8dyagxl7n5lVFXVUlERYO1aL5Ef/cbjlEXd7t+/cduMGQFe\nftmZlbOiorGZqn//Ij780NehzzvTXsdcjdWjR1nc+9LZMjgfOBBARIYAi9JYFmNy3gYbOCf0eINR\n5syp5LXXotufwk1L4MyhFD5G2KRJNXzzTXa1n5vWpbPGMB0YLiLz3dsJNx8ZY9rmxx/XtNhvAMRc\nW2Lp0rX06hX/m2V+vvNjcktKE4Oqfg8Mdf8OAWenMr4xnUlkJ3OspJDo9BhLlqwBUtcHZdIvEy9w\nM8akwN1318QduRSpaWe1yX2WGIzJUUVFMHVq/DN/rlypbDpeJ7gsxZjOyeOBP/85+xbdMelnicGY\nTqYt03SbzskSgzHGmCiWGIwxxkSxxGBMJ9OnT5ANNli3yftMbrPEYEwns956jRPtGROLJQZjjDFR\nLDEYY4yJYonBGGNMFEsMxhhjolhiMMYYE8USgzHGmCiWGIwxxkSxxGCMMSaKJQZjjDFRLDEYY4yJ\nYonBGGNMFEsMxhhjolhiMMYYE8USgzHGmCiWGIwxxkSxxGCMMSaKJQZjjDFRLDEYY4yJYonBGGNM\nlIxMDCKyl4g8lO5yGGNMZ5RxiUFENgMGAoXpLosxxnRGvlQEEZHBwM2qupeIeID7gAFADXC6qi4J\n76uq3wCTRGRqKspmjDEmWtJrDCIyAXiIxhrAYUChqg4FJgKT3P2uFZGnRGQ9dz9PsstmjDGmuVTU\nGBYDhwNPuLd3B14FUNX3RWSQ+/eVTR4XSkHZjDHGNOEJhZJ//hWRTYCnVXWo26n8nKrOdu/7Duiv\nqsGkF8QYY0yr0tH5XAGURZbBkoIxxmSOdCSG+cCBACIyBFiUhjIYY4yJIyWjkpqYDgwXkfnu7VPS\nUAZjjDFxpKSPwRhjTPbIuAvcjDHGpJclBmOMMVEsMRhjjIliicEYY0yUdIxKSioR2R6YDCwBHlPV\nt5IcrxcwS1V3TnKcHYFx7s2LVXVFkuPtDRwDFAO3qmpShxWLyF7Acap6RhJj7AqMxrmqfryqViQr\nVkTMpD8vN07K/l9peC+m6jOW6nPHH4HxONMF3aaqXyQx1nhgB2AL4ElVfaCl/XOxxjAY+AXwA5+n\nIN4E4LsUxCnEeRO9DOyagnjFqnomcAewXzIDpXBG3TPdn0dwTqJJleKZglP2/yL178VUfcZSfe44\nHfgJZzLR75IZSFXvxnnvf9ZaUoAsqTG0ZXZW4B3gGaAXzhvqkmTFEpGzgCeBC5P9vFR1gXtB4IXA\nUSmI95KIlOB8M2zTa9iOWOs8o26C8byqWiciy4C92xsr0XgdNVNwgrHW6f/Vxljr/F5MNNa6fsba\nEgv4N+tw7mhHvM2BUcBO7u/7kxgL4FjghUSOmfE1hrbOzopTXcoDfnd/JyvW08CROE0Tu4jIiGQ+\nLxHZGfgQ56rxNn9I2hGvB061+kpVXZnkWOs0o26i8YAqESkAegPL2hOrjfHC2j1TcBteyw1o5/+r\nHbEGsQ7vxbbEAobTzs9YO2K1+9zRznj/A6qA30j+ex9gT1V9LZHjZnxioHF21rCo2VmBhtlZVfU4\n4HucD8gt7u9kxTpWVfdV1bOB91X1+SQ/rzLg78CtwD/aGKs98W4HNgRuEpEjkhlLVX9392vv1Zat\nxdvJ3f4QMAWnSv1kO2MlEm9Qk/3X5SrSRJ/bHbT//9XWWOWs23sxkVjh98iIdfiMJRor/Ly+o/3n\njvbEm4LznjwfeDpJsSLfi8WJHjTjm5JUdbo7O2tYObA64rZfRBom4lPVBcCCVMSKeNxJyY6lqm8A\nb7Q1zjrEG5WqWBGPa/PrmGC8gBvvIzpgCpZ2vJbtel4Jxgo/t3b/v9oRa53eiwnGSsdr2O5zRzvj\nfYjThJTMWA2vo6oen+hxs6HG0FQqZ2fN1VipjpfLzy3V8SxWdsVKdbwOiZWNiSGVs7PmaqxUx8vl\n55bqeBYru2KlOl6HxMr4pqQYUjk7a67GSnW8XH5uqY5nsbIrVqrjdUgsm13VGGNMlGxsSjLGGJNE\nlhiMMcZEscRgjDEmiiUGY4wxUSwxGGOMiWKJwRhjTBRLDMYYY6Jk4wVuxrSZO5/MVzjz7IdnsgwB\nD6lqu6Y77qByjcKZAXOmqp4cZ5+pwBeqenOT7YtxLmB6AGc9hv5JLq7pJCwxmM7kZ1XdMd2FiGGG\nqp7awv2PAncDDYlBRHYHflPVd0TkQGBekstoOhFLDMYAIrIUeA5n2uJ64ChV/d5de+BOnCmLVwKj\n3e3zcObR3xo4GtgKuAaoBD7G+Ww9AVynqru5MU4CBqvq2BbKcQnO4jdeYLaqXqqq80SkVES2UdXw\nymIn4qxEZ0yHsz4G05lsJCIfuT8fu7+3ce/bEJjj1ijeAc4RkXzgYeBYVR2E0+TzcMTxPlHVPwJL\ncZLHXu5+3YCQOz11LxHp5+4/CngsXuFEZH+cufoHATsCfxCR49y7HweOd/crBA6i/XP4G9MiqzGY\nzqSlpqQQMNv9+zNgD2BLYDPgX+6SiQBdIh7zvvt7D+BdVQ2vCvc4zkpaAFOBE0TkMaCnqn7QQvn2\nBXbBWR3NAxThLDwFTkJ5HbgMOBh4XVUrWjiWMe1micEYl6rWuX+GcE7MecA34WTiJodeEQ+pdn8H\niL8U5GM4K2rV4iSJluQBd6nqXW68cpyF6VHVH0TkWxEZitOMdGfiz8yYtrGmJNOZtLSubqz7/g/o\n5nb0ApwOPBVjv3eBQSLSy00ex+Au56mqPwA/AWfh9Dm05A3gRLc/wQfMwFlXPOzvbhk2V9U3WzmW\nMdWuvloAAADqSURBVO1mNQbTmfQWkY+abHtbVc8jxrrMqlonIkcBd7vt+hVAeInJUMR+K0VkPDAX\npxbxHY21CYB/AodHNDXFpKqzRGR7nCYqL/CKqkbWMl4E7iF6gXdjOpytx2DMOhKRbsC5qnq1e/tu\n4CtVvdf95j8VeFZVX4zx2FHAMFVt9+ItIrIpME9V+7W2rzGJsKYkY9aRqv4GrCcin4vIJzhr7j7k\n3v0z4I+VFCIc7HZOt5nbzPUSkMw1i00nYzUGY4wxUazGYIwxJoolBmOMMVEsMRhjjIliicEYY0wU\nSwzGGGOiWGIwxhgT5f8B4ykN0fh7FfYAAAAASUVORK5CYII=\n",
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Lz0uD3U1J7t+RuIJ5zpwMNmzQPgbVPIJJDGOAfwJnY3U+f2xvUyqi/K3hcA6w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\nSikvmhiUUkp50cSglFLKy/8DFQOc8G/UVmwAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2ae5a247f0>"
+       "<matplotlib.figure.Figure at 0x7fbd166e3a90>"
       ]
      },
      "metadata": {},
@@ -1869,9 +2055,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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14iDr9sA3gO0lzSl7fWad4Ly2Kih7Rqd3ACcB4yTNKnNdZp3ivLaqKLsHvyvwTuDCfBCq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\nNzOrKRd4M7OacoE3M6up/w91pX7x6KMxWwAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f2ae5b62128>"
+       "<matplotlib.figure.Figure at 0x7fbd1678fa58>"
       ]
      },
      "metadata": {},
@@ -1898,6 +2084,15 @@
     "# Show the plot on screen\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/openmc/filter.py b/openmc/filter.py
index 88a88f99d..0320cdeca 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -1,8 +1,7 @@
-from abc import ABCMeta, abstractproperty
+from abc import ABCMeta
 from collections import Iterable, OrderedDict
 import copy
 from numbers import Real, Integral
-import sys
 from xml.etree import ElementTree as ET
 
 from six import add_metaclass
@@ -829,7 +828,7 @@ class EnergyFilter(Filter):
             if bins[index] < bins[index-1]:
                 msg = 'Unable to add bin edges "{0}" to a "{1}" Filter ' \
                       'since they are not monotonically ' \
-                      'increasing'.format(bins, self.type)
+                      'increasing'.format(bins, type(self))
                 raise ValueError(msg)
 
     def can_merge(self, other):
@@ -848,7 +847,7 @@ class EnergyFilter(Filter):
     def merge(self, other):
         if not self.can_merge(other):
             msg = 'Unable to merge "{0}" with "{1}" ' \
-                  'filters'.format(self.type, other.type)
+                  'filters'.format(type(self), other.type)
             raise ValueError(msg)
 
         # Merge unique filter bins
@@ -1324,13 +1323,11 @@ class PolarFilter(Filter):
         # Extract the lower and upper angle bounds, then repeat and tile
         # them as necessary to account for other filters.
         lo_bins = np.repeat(self.bins[:-1], self.stride)
-        hi_bins = np.repeat(self.bins[1:], self.stride)
         tile_factor = data_size / len(lo_bins)
         lo_bins = np.tile(lo_bins, tile_factor)
-        hi_bins = np.tile(hi_bins, tile_factor)
 
         # Add the new angle columns to the DataFrame.
-        df.loc[:, self.type + ' low'] = lo_bins
+        df.loc[:, 'polar low'] = lo_bins
 
         return df
 
@@ -1402,13 +1399,11 @@ class AzimuthalFilter(Filter):
         # Extract the lower and upper angle bounds, then repeat and tile
         # them as necessary to account for other filters.
         lo_bins = np.repeat(self.bins[:-1], self.stride)
-        hi_bins = np.repeat(self.bins[1:], self.stride)
         tile_factor = data_size / len(lo_bins)
         lo_bins = np.tile(lo_bins, tile_factor)
-        hi_bins = np.tile(hi_bins, tile_factor)
 
         # Add the new angle columns to the DataFrame.
-        df.loc[:, self.type + ' low'] = lo_bins
+        df.loc[:, 'azimuthal low'] = lo_bins
 
         return df
 

From cdbcdd52348bee444211c50fbfcd969db52d8cd2 Mon Sep 17 00:00:00 2001
From: Will Boyd <wbinventor@gmail.com>
Date: Mon, 28 Nov 2016 18:18:03 -0500
Subject: [PATCH 23/27] Reverted changes to MGXS Part II notebook per
 suggestion by @nelsonag

---
 .../pythonapi/examples/mgxs-part-ii.ipynb     | 1049 +++++++----------
 1 file changed, 427 insertions(+), 622 deletions(-)

diff --git a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
index e35c205c3..c43fab6ff 100644
--- a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
+++ b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb
@@ -34,9 +34,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/wbinventor/miniconda3/lib/python3.5/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
-      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n",
-      "/home/wbinventor/miniconda3/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning:  This call to matplotlib.use() has no effect\n",
+      "/home/romano/miniconda3/envs/default/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning:  This call to matplotlib.use() has no effect\n",
       "because the backend has already been chosen;\n",
       "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n",
       "or matplotlib.backends is imported for the first time.\n",
@@ -455,8 +453,8 @@
       "         Copyright | 2011-2016 Massachusetts Institute of Technology\n",
       "           License | http://openmc.readthedocs.io/en/latest/license.html\n",
       "           Version | 0.8.0\n",
-      "          Git SHA1 | 2c25ec97653482825b529215b8a61b54d468d34e\n",
-      "         Date/Time | 2016-11-28 09:10:24\n",
+      "          Git SHA1 | da5563eddb5f2c2d6b2c9839d518de40962b78f2\n",
+      "         Date/Time | 2016-10-31 12:29:16\n",
       "    OpenMP Threads | 4\n",
       "\n",
       " ===========================================================================\n",
@@ -467,16 +465,11 @@
       " Reading geometry XML file...\n",
       " Reading materials XML file...\n",
       " Reading cross sections XML file...\n",
-      " Reading U235 from\n",
-      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/U235.h5\n",
-      " Reading U238 from\n",
-      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/U238.h5\n",
-      " Reading O16 from\n",
-      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/O16.h5\n",
-      " Reading H1 from\n",
-      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/H1.h5\n",
-      " Reading Zr90 from\n",
-      " /home/wbinventor/Documents/NSE-CRPG-Codes/openmc/data/nndc_hdf5/Zr90.h5\n",
+      " Reading U235 from /home/romano/openmc/scripts/nndc_hdf5/U235.h5\n",
+      " Reading U238 from /home/romano/openmc/scripts/nndc_hdf5/U238.h5\n",
+      " Reading O16 from /home/romano/openmc/scripts/nndc_hdf5/O16.h5\n",
+      " Reading H1 from /home/romano/openmc/scripts/nndc_hdf5/H1.h5\n",
+      " Reading Zr90 from /home/romano/openmc/scripts/nndc_hdf5/Zr90.h5\n",
       " Maximum neutron transport energy: 2.00000E+07 eV for U235\n",
       " Reading tallies XML file...\n",
       " Building neighboring cells lists for each surface...\n",
@@ -538,7 +531,7 @@
       "       48/1    1.21610    1.22612 +/- 0.00251\n",
       "       49/1    1.22199    1.22602 +/- 0.00245\n",
       "       50/1    1.20860    1.22558 +/- 0.00243\n",
-      " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10057\n",
+      " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10050\n",
       " The estimated number of batches is 73\n",
       " Creating state point statepoint.050.h5...\n",
       "       51/1    1.21850    1.22541 +/- 0.00237\n",
@@ -564,7 +557,7 @@
       "       71/1    1.19720    1.22444 +/- 0.00195\n",
       "       72/1    1.23770    1.22465 +/- 0.00193\n",
       "       73/1    1.23894    1.22488 +/- 0.00191\n",
-      " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10057\n",
+      " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10050\n",
       " The estimated number of batches is 74\n",
       "       74/1    1.22437    1.22487 +/- 0.00188\n",
       " Triggers satisfied for batch 74\n",
@@ -577,20 +570,20 @@
       "\n",
       " =======================>     TIMING STATISTICS     <=======================\n",
       "\n",
-      " Total time for initialization     =  3.1270E-01 seconds\n",
-      "   Reading cross sections          =  1.8695E-01 seconds\n",
-      " Total time in simulation          =  1.1922E+02 seconds\n",
-      "   Time in transport only          =  1.1903E+02 seconds\n",
-      "   Time in inactive batches        =  8.5633E+00 seconds\n",
-      "   Time in active batches          =  1.1066E+02 seconds\n",
-      "   Time synchronizing fission bank =  2.4702E-02 seconds\n",
-      "     Sampling source sites         =  1.8297E-02 seconds\n",
-      "     SEND/RECV source sites        =  6.2794E-03 seconds\n",
-      "   Time accumulating tallies       =  2.6114E-03 seconds\n",
-      " Total time for finalization       =  1.6967E-02 seconds\n",
-      " Total time elapsed                =  1.1961E+02 seconds\n",
-      " Calculation Rate (inactive)       =  11677.8 neutrons/second\n",
-      " Calculation Rate (active)         =  3614.65 neutrons/second\n",
+      " Total time for initialization     =  5.0262E-01 seconds\n",
+      "   Reading cross sections          =  3.4207E-01 seconds\n",
+      " Total time in simulation          =  1.2843E+02 seconds\n",
+      "   Time in transport only          =  1.2831E+02 seconds\n",
+      "   Time in inactive batches        =  8.1328E+00 seconds\n",
+      "   Time in active batches          =  1.2030E+02 seconds\n",
+      "   Time synchronizing fission bank =  2.9797E-02 seconds\n",
+      "     Sampling source sites         =  2.1385E-02 seconds\n",
+      "     SEND/RECV source sites        =  8.2632E-03 seconds\n",
+      "   Time accumulating tallies       =  1.4577E-03 seconds\n",
+      " Total time for finalization       =  1.3462E-02 seconds\n",
+      " Total time elapsed                =  1.2901E+02 seconds\n",
+      " Calculation Rate (inactive)       =  12295.9 neutrons/second\n",
+      " Calculation Rate (active)         =  3325.12 neutrons/second\n",
       "\n",
       " ============================>     RESULTS     <============================\n",
       "\n",
@@ -1179,239 +1172,169 @@
      "text": [
       "[  NORMAL ]  Importing ray tracing data from file...\n",
       "[  NORMAL ]  Computing the eigenvalue...\n",
-      "[  NORMAL ]  Iteration 0:\tk_eff = 0.423123\tres = 0.000E+00\n",
-      "[  NORMAL ]  Iteration 1:\tk_eff = 0.475921\tres = 5.769E-01\n",
-      "[  NORMAL ]  Iteration 2:\tk_eff = 0.491443\tres = 1.248E-01\n",
-      "[  NORMAL ]  Iteration 3:\tk_eff = 0.487441\tres = 3.261E-02\n",
-      "[  NORMAL ]  Iteration 4:\tk_eff = 0.483949\tres = 8.144E-03\n",
-      "[  NORMAL ]  Iteration 5:\tk_eff = 0.477326\tres = 7.164E-03\n",
-      "[  NORMAL ]  Iteration 6:\tk_eff = 0.469012\tres = 1.369E-02\n",
-      "[  NORMAL ]  Iteration 7:\tk_eff = 0.460422\tres = 1.742E-02\n",
-      "[  NORMAL ]  Iteration 8:\tk_eff = 0.450721\tres = 1.832E-02\n",
-      "[  NORMAL ]  Iteration 9:\tk_eff = 0.441532\tres = 2.107E-02\n",
-      "[  NORMAL ]  Iteration 10:\tk_eff = 0.432168\tres = 2.039E-02\n",
-      "[  NORMAL ]  Iteration 11:\tk_eff = 0.423131\tres = 2.121E-02\n",
-      "[  NORMAL ]  Iteration 12:\tk_eff = 0.414705\tres = 2.091E-02\n",
-      "[  NORMAL ]  Iteration 13:\tk_eff = 0.406942\tres = 1.991E-02\n",
-      "[  NORMAL ]  Iteration 14:\tk_eff = 0.399627\tres = 1.872E-02\n",
-      "[  NORMAL ]  Iteration 15:\tk_eff = 0.393329\tres = 1.798E-02\n",
-      "[  NORMAL ]  Iteration 16:\tk_eff = 0.387699\tres = 1.576E-02\n",
-      "[  NORMAL ]  Iteration 17:\tk_eff = 0.382948\tres = 1.431E-02\n",
-      "[  NORMAL ]  Iteration 18:\tk_eff = 0.379028\tres = 1.225E-02\n",
-      "[  NORMAL ]  Iteration 19:\tk_eff = 0.375934\tres = 1.024E-02\n",
-      "[  NORMAL ]  Iteration 20:\tk_eff = 0.373784\tres = 8.161E-03\n",
-      "[  NORMAL ]  Iteration 21:\tk_eff = 0.372654\tres = 5.719E-03\n",
-      "[  NORMAL ]  Iteration 22:\tk_eff = 0.372273\tres = 3.023E-03\n",
-      "[  NORMAL ]  Iteration 23:\tk_eff = 0.372879\tres = 1.024E-03\n",
-      "[  NORMAL ]  Iteration 24:\tk_eff = 0.374353\tres = 1.629E-03\n",
-      "[  NORMAL ]  Iteration 25:\tk_eff = 0.376678\tres = 3.951E-03\n",
-      "[  NORMAL ]  Iteration 26:\tk_eff = 0.379854\tres = 6.212E-03\n",
-      "[  NORMAL ]  Iteration 27:\tk_eff = 0.383870\tres = 8.432E-03\n",
-      "[  NORMAL ]  Iteration 28:\tk_eff = 0.388663\tres = 1.057E-02\n",
-      "[  NORMAL ]  Iteration 29:\tk_eff = 0.394216\tres = 1.249E-02\n",
-      "[  NORMAL ]  Iteration 30:\tk_eff = 0.400506\tres = 1.429E-02\n",
-      "[  NORMAL ]  Iteration 31:\tk_eff = 0.407501\tres = 1.596E-02\n",
-      "[  NORMAL ]  Iteration 32:\tk_eff = 0.415145\tres = 1.747E-02\n",
-      "[  NORMAL ]  Iteration 33:\tk_eff = 0.423426\tres = 1.876E-02\n",
-      "[  NORMAL ]  Iteration 34:\tk_eff = 0.432299\tres = 1.995E-02\n",
-      "[  NORMAL ]  Iteration 35:\tk_eff = 0.441713\tres = 2.095E-02\n",
-      "[  NORMAL ]  Iteration 36:\tk_eff = 0.451665\tres = 2.178E-02\n",
-      "[  NORMAL ]  Iteration 37:\tk_eff = 0.462081\tres = 2.253E-02\n",
-      "[  NORMAL ]  Iteration 38:\tk_eff = 0.472951\tres = 2.306E-02\n",
-      "[  NORMAL ]  Iteration 39:\tk_eff = 0.484220\tres = 2.352E-02\n",
-      "[  NORMAL ]  Iteration 40:\tk_eff = 0.495861\tres = 2.383E-02\n",
-      "[  NORMAL ]  Iteration 41:\tk_eff = 0.507836\tres = 2.404E-02\n",
-      "[  NORMAL ]  Iteration 42:\tk_eff = 0.520110\tres = 2.415E-02\n",
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-      "[  NORMAL ]  Iteration 44:\tk_eff = 0.545418\tres = 2.411E-02\n",
-      "[  NORMAL ]  Iteration 45:\tk_eff = 0.558388\tres = 2.398E-02\n",
-      "[  NORMAL ]  Iteration 46:\tk_eff = 0.571526\tres = 2.378E-02\n",
-      "[  NORMAL ]  Iteration 47:\tk_eff = 0.584802\tres = 2.353E-02\n",
-      "[  NORMAL ]  Iteration 48:\tk_eff = 0.598189\tres = 2.323E-02\n",
-      "[  NORMAL ]  Iteration 49:\tk_eff = 0.611657\tres = 2.289E-02\n",
-      "[  NORMAL ]  Iteration 50:\tk_eff = 0.625182\tres = 2.252E-02\n",
-      "[  NORMAL ]  Iteration 51:\tk_eff = 0.638738\tres = 2.211E-02\n",
-      "[  NORMAL ]  Iteration 52:\tk_eff = 0.652302\tres = 2.168E-02\n",
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-      "[  NORMAL ]  Iteration 73:\tk_eff = 0.909807\tres = 1.189E-02\n",
-      "[  NORMAL ]  Iteration 74:\tk_eff = 0.919919\tres = 1.150E-02\n",
-      "[  NORMAL ]  Iteration 75:\tk_eff = 0.929798\tres = 1.111E-02\n",
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-      "[  NORMAL ]  Iteration 78:\tk_eff = 0.958036\tres = 1.002E-02\n",
-      "[  NORMAL ]  Iteration 79:\tk_eff = 0.966983\tres = 9.674E-03\n",
-      "[  NORMAL ]  Iteration 80:\tk_eff = 0.975698\tres = 9.339E-03\n",
-      "[  NORMAL ]  Iteration 81:\tk_eff = 0.984184\tres = 9.013E-03\n",
-      "[  NORMAL ]  Iteration 82:\tk_eff = 0.992441\tres = 8.697E-03\n",
-      "[  NORMAL ]  Iteration 83:\tk_eff = 1.000472\tres = 8.390E-03\n",
-      "[  NORMAL ]  Iteration 84:\tk_eff = 1.008280\tres = 8.092E-03\n",
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-      "[  NORMAL ]  Iteration 88:\tk_eff = 1.037327\tres = 6.990E-03\n",
-      "[  NORMAL ]  Iteration 89:\tk_eff = 1.044059\tres = 6.736E-03\n",
-      "[  NORMAL ]  Iteration 90:\tk_eff = 1.050585\tres = 6.490E-03\n",
-      "[  NORMAL ]  Iteration 91:\tk_eff = 1.056911\tres = 6.251E-03\n",
-      "[  NORMAL ]  Iteration 92:\tk_eff = 1.063038\tres = 6.021E-03\n",
-      "[  NORMAL ]  Iteration 93:\tk_eff = 1.068972\tres = 5.798E-03\n",
-      "[  NORMAL ]  Iteration 94:\tk_eff = 1.074716\tres = 5.582E-03\n",
-      "[  NORMAL ]  Iteration 95:\tk_eff = 1.080275\tres = 5.373E-03\n",
-      "[  NORMAL ]  Iteration 96:\tk_eff = 1.085651\tres = 5.172E-03\n",
-      "[  NORMAL ]  Iteration 97:\tk_eff = 1.090850\tres = 4.977E-03\n",
-      "[  NORMAL ]  Iteration 98:\tk_eff = 1.095876\tres = 4.789E-03\n",
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-      "[  NORMAL ]  Iteration 100:\tk_eff = 1.105424\tres = 4.432E-03\n",
-      "[  NORMAL ]  Iteration 101:\tk_eff = 1.109955\tres = 4.262E-03\n",
-      "[  NORMAL ]  Iteration 102:\tk_eff = 1.114328\tres = 4.099E-03\n",
-      "[  NORMAL ]  Iteration 103:\tk_eff = 1.118550\tres = 3.941E-03\n",
-      "[  NORMAL ]  Iteration 104:\tk_eff = 1.122623\tres = 3.788E-03\n",
-      "[  NORMAL ]  Iteration 105:\tk_eff = 1.126551\tres = 3.641E-03\n",
-      "[  NORMAL ]  Iteration 106:\tk_eff = 1.130339\tres = 3.499E-03\n",
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-      "[  NORMAL ]  Iteration 112:\tk_eff = 1.150342\tres = 2.749E-03\n",
-      "[  NORMAL ]  Iteration 113:\tk_eff = 1.153257\tres = 2.640E-03\n",
-      "[  NORMAL ]  Iteration 114:\tk_eff = 1.156062\tres = 2.534E-03\n",
-      "[  NORMAL ]  Iteration 115:\tk_eff = 1.158761\tres = 2.432E-03\n",
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-      "[  NORMAL ]  Iteration 121:\tk_eff = 1.172906\tres = 1.897E-03\n",
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-      "[  NORMAL ]  Iteration 136:\tk_eff = 1.196287\tres = 9.997E-04\n",
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-      "[  NORMAL ]  Iteration 139:\tk_eff = 1.199439\tres = 8.768E-04\n",
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      ]
     }
    ],
@@ -1444,8 +1367,8 @@
      "output_type": "stream",
      "text": [
       "openmc keff = 1.223474\n",
-      "openmoc keff = 1.220814\n",
-      "bias [pcm]: -266.0\n"
+      "openmoc keff = 1.220892\n",
+      "bias [pcm]: -258.1\n"
      ]
     }
    ],
@@ -1520,346 +1443,237 @@
      "text": [
       "[  NORMAL ]  Importing ray tracing data from file...\n",
       "[  NORMAL ]  Computing the eigenvalue...\n",
-      "[  NORMAL ]  Iteration 0:\tk_eff = 0.366907\tres = 0.000E+00\n",
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+      "[  NORMAL ]  Iteration 230:\tk_eff = 1.223227\tres = 1.000E-05\n"
      ]
     }
    ],
@@ -1885,8 +1699,8 @@
      "output_type": "stream",
      "text": [
       "openmc keff = 1.223474\n",
-      "openmoc keff = 1.223039\n",
-      "bias [pcm]: -43.5\n"
+      "openmoc keff = 1.223227\n",
+      "bias [pcm]: -24.7\n"
      ]
     }
    ],
@@ -1939,7 +1753,7 @@
    "outputs": [],
    "source": [
     "# Parse ACE data into memory\n",
-    "u235 = openmc.data.IncidentNeutron.from_hdf5('../../../../data/nndc_hdf5/U235.h5')\n",
+    "u235 = openmc.data.IncidentNeutron.from_ace('../../../../scripts/nndc/293.6K/U_235_293.6K.ace')\n",
     "\n",
     "# Extract the continuous-energy U-235 fission cross section data\n",
     "fission = u235[18]"
@@ -1971,9 +1785,9 @@
     },
     {
      "data": {
-      "image/png": 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Lz0uD3U1J7t+RuIJ5zpwMNmzQPgbVPIJJDGOAfwJnY3U+f2xvUyqi/K3hcA6w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\nVVBc7G7OymfnznKKi6vYbz/Ybz9rG8B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9XXjr7b+y8zNjUla2RCW78zkTk6HJfXETg4g8qKpnisg8nOsWwtsBUNVONCOO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\nSwzGGGOiWGIwxhgT5f8B4ykN0fh7FfYAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbd166e3a90>"
+       "<matplotlib.figure.Figure at 0x7f2ae5a247f0>"
       ]
      },
      "metadata": {},
@@ -2055,9 +1869,9 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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RMQY4DdhrkVtpVqACctt5bZXQVw9+YqvBJV0XEV03I14H+EOrMc0KMLGVNzuvrSp6LfCS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\nfn35+EIOpHUAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fbd1678fa58>"
+       "<matplotlib.figure.Figure at 0x7f2ae5b62128>"
       ]
      },
      "metadata": {},
@@ -2084,15 +1898,6 @@
     "# Show the plot on screen\n",
     "plt.show()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

From b9ad56a038005aaf56f2a18d92fc40fcae50af48 Mon Sep 17 00:00:00 2001
From: Will Boyd <wbinventor@gmail.com>
Date: Mon, 28 Nov 2016 18:32:46 -0500
Subject: [PATCH 24/27] Added low and high filter bounds to Pandas DataFrames
 for Azimuthal and Polar filters

---
 openmc/filter.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/openmc/filter.py b/openmc/filter.py
index 0320cdeca..9da77c18e 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -1323,11 +1323,14 @@ class PolarFilter(Filter):
         # Extract the lower and upper angle bounds, then repeat and tile
         # them as necessary to account for other filters.
         lo_bins = np.repeat(self.bins[:-1], self.stride)
+        hi_bins = np.repeast(self.bins[1:], self.stride)
         tile_factor = data_size / len(lo_bins)
         lo_bins = np.tile(lo_bins, tile_factor)
+        hi_bins = np.tile(hi_bins, tile_factor)
 
         # Add the new angle columns to the DataFrame.
         df.loc[:, 'polar low'] = lo_bins
+        df.loc[:, 'polar high'] = hi_bins
 
         return df
 
@@ -1399,11 +1402,14 @@ class AzimuthalFilter(Filter):
         # Extract the lower and upper angle bounds, then repeat and tile
         # them as necessary to account for other filters.
         lo_bins = np.repeat(self.bins[:-1], self.stride)
+        hi_bins = np.repeat(self.bins[1:], self.stride)
         tile_factor = data_size / len(lo_bins)
         lo_bins = np.tile(lo_bins, tile_factor)
+        hi_bins = np.tile(hi_bins, tile_factor)
 
         # Add the new angle columns to the DataFrame.
         df.loc[:, 'azimuthal low'] = lo_bins
+        df.loc[:, 'azimuthal high'] = hi_bins
 
         return df
 

From 81e3230adde9acc211615ae03337fe095eab1dde Mon Sep 17 00:00:00 2001
From: Will Boyd <wbinventor@gmail.com>
Date: Mon, 28 Nov 2016 19:25:02 -0500
Subject: [PATCH 25/27] Fixed typo in filter.py

---
 openmc/filter.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/openmc/filter.py b/openmc/filter.py
index 9da77c18e..bf59e8238 100644
--- a/openmc/filter.py
+++ b/openmc/filter.py
@@ -1323,7 +1323,7 @@ class PolarFilter(Filter):
         # Extract the lower and upper angle bounds, then repeat and tile
         # them as necessary to account for other filters.
         lo_bins = np.repeat(self.bins[:-1], self.stride)
-        hi_bins = np.repeast(self.bins[1:], self.stride)
+        hi_bins = np.repeat(self.bins[1:], self.stride)
         tile_factor = data_size / len(lo_bins)
         lo_bins = np.tile(lo_bins, tile_factor)
         hi_bins = np.tile(hi_bins, tile_factor)

From 2a594cc7041c89ed9dc45858816b22d329faae86 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Tue, 29 Nov 2016 18:46:09 -0500
Subject: [PATCH 26/27] Added from_hdf5 for MGXSLibrary class and some
 miscellaneous fixes'

---
 openmc/data/reaction.py |   2 +-
 openmc/macroscopic.py   |   4 +-
 openmc/mgxs/mgxs.py     |   6 +-
 openmc/mgxs_library.py  | 239 +++++++++++++++++++++++++++++++++++++---
 4 files changed, 231 insertions(+), 20 deletions(-)

diff --git a/openmc/data/reaction.py b/openmc/data/reaction.py
index 08930fa65..bb976f9fa 100644
--- a/openmc/data/reaction.py
+++ b/openmc/data/reaction.py
@@ -818,7 +818,7 @@ class Reaction(EqualityMixin):
         Parameters
         ----------
         group : h5py.Group
-            HDF5 group to write to
+            HDF5 group to read from
         energy : dict
             Dictionary whose keys are temperatures (e.g., '300K') and values are
             arrays of energies at which cross sections are tabulated at.
diff --git a/openmc/macroscopic.py b/openmc/macroscopic.py
index 4d3589141..f2521c4ac 100644
--- a/openmc/macroscopic.py
+++ b/openmc/macroscopic.py
@@ -1,5 +1,3 @@
-import sys
-
 from six import string_types
 
 from openmc.checkvalue import check_type
@@ -45,7 +43,7 @@ class Macroscopic(object):
         return hash((self._name))
 
     def __repr__(self):
-        string = 'Nuclide    -    {0}\n'.format(self._name)
+        string = 'Macroscopic    -    {0}\n'.format(self._name)
         return string
 
     @property
diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 58b8a32c2..6f8abefd1 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -62,6 +62,9 @@ _DOMAINS = (openmc.Cell,
 # Supported ScatterMatrixXS and NuScatterMatrixXS angular distribution types
 MU_TREATMENTS = ('legendre', 'histogram')
 
+# Maximum Legendre order supported by OpenMC
+MAX_LEGENDRE = 10
+
 
 @add_metaclass(ABCMeta)
 class MGXS(object):
@@ -3475,7 +3478,8 @@ class ScatterMatrixXS(MatrixMGXS):
         cv.check_type('legendre_order', legendre_order, Integral)
         cv.check_greater_than('legendre_order', legendre_order, 0,
                               equality=True)
-        cv.check_less_than('legendre_order', legendre_order, 10, equality=True)
+        cv.check_less_than('legendre_order', legendre_order, MAX_LEGENDRE,
+                           equality=True)
 
         if self.scatter_format == 'legendre':
             if self.correction == 'P0' and legendre_order > 0:
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 347c015e7..70ff7a91b 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -1,6 +1,6 @@
 from collections import Iterable
 from numbers import Real, Integral
-import sys
+import os
 
 from six import string_types
 import numpy as np
@@ -16,7 +16,7 @@ from openmc.checkvalue import check_type, check_value, check_greater_than, \
 _REPRESENTATIONS = ['isotropic', 'angle']
 _SCATTER_TYPES = ['tabular', 'legendre', 'histogram']
 _XS_SHAPES = ["[G][G'][Order]", "[G]", "[G']", "[G][G']", "[DG]", "[G][DG]",
-              "[G'][DG]"]
+              "[G'][DG]", "[G][G'][DG]"]
 
 
 class XSdata(object):
@@ -42,7 +42,7 @@ class XSdata(object):
     ----------
     name : str
         Unique identifier for the xsdata object
-    aromic_weight_ratio : float
+    atomic_weight_ratio : float
         Atomic weight ratio of an isotope.  That is, the ratio of the mass
         of the isotope to the mass of a single neutron.
     temperatures : numpy.ndarray
@@ -303,13 +303,14 @@ class XSdata(object):
             self._xs_shapes["[G][G'][DG]"] = (self.energy_groups.num_groups,
                                               self.energy_groups.num_groups,
                                               self.num_delayed_groups)
+
             self._xs_shapes["[G][G'][Order]"] \
                 = (self.energy_groups.num_groups,
                    self.energy_groups.num_groups, self.num_orders)
 
             # If representation is by angle prepend num polar and num azim
             if self.representation == 'angle':
-                for key,shapes in self._xs_shapes.items():
+                for key, shapes in self._xs_shapes.items():
                     self._xs_shapes[key] \
                         = (self.num_polar, self.num_azimuthal) + shapes
 
@@ -337,7 +338,7 @@ class XSdata(object):
     def num_delayed_groups(self, num_delayed_groups):
 
         # Check validity of num_delayed_groups
-        check_type('num_delayed_groups', num_delayed_groups, int)
+        check_type('num_delayed_groups', num_delayed_groups, Integral)
         check_less_than('num_delayed_groups', num_delayed_groups,
                         openmc.mgxs.MAX_DELAYED_GROUPS, equality=True)
         check_greater_than('num_delayed_groups', num_delayed_groups, 0,
@@ -359,6 +360,13 @@ class XSdata(object):
         check_greater_than('atomic_weight_ratio', atomic_weight_ratio, 0.0)
         self._atomic_weight_ratio = atomic_weight_ratio
 
+    @fissionable.setter
+    def fissionable(self, fissionable):
+
+        # Check validity of type
+        check_type('fissionable', fissionable, bool)
+        self._fissionable = fissionable
+
     @temperatures.setter
     def temperatures(self, temperatures):
 
@@ -1652,6 +1660,7 @@ class XSdata(object):
             HDF5 File (a root Group) to write to
 
         """
+
         grp = file.create_group(self.name)
         if self.atomic_weight_ratio is not None:
             grp.attrs['atomic_weight_ratio'] = self.atomic_weight_ratio
@@ -1719,11 +1728,12 @@ class XSdata(object):
                    (self._delayed_nu_fission[i] is None or \
                     self._prompt_nu_fission[i] is None):
                     raise ValueError('nu-fission or prompt-nu-fission and '
-                                     'delayed-nu-fission data must be provided '
-                                     'when writing the HDF5 library')
+                                     'delayed-nu-fission data must be '
+                                     'provided when writing the HDF5 library')
 
                 if self._nu_fission[i] is not None:
-                    xs_grp.create_dataset("nu-fission", data=self._nu_fission[i])
+                    xs_grp.create_dataset("nu-fission",
+                                          data=self._nu_fission[i])
 
                 if self._prompt_nu_fission[i] is not None:
                     xs_grp.create_dataset("prompt-nu-fission",
@@ -1737,7 +1747,8 @@ class XSdata(object):
                     xs_grp.create_dataset("beta", data=self._beta[i])
 
                 if self._decay_rate[i] is not None:
-                    xs_grp.create_dataset("decay rate", data=self._decay_rate[i])
+                    xs_grp.create_dataset("decay rate",
+                                          data=self._decay_rate[i])
 
             if self._scatter_matrix[i] is None:
                 raise ValueError('Scatter matrix must be provided when '
@@ -1836,6 +1847,143 @@ class XSdata(object):
                 xs_grp.create_dataset("inverse-velocity",
                                       data=self._inverse_velocity[i])
 
+    @classmethod
+    def from_hdf5(cls, group, name, energy_groups, num_delayed_groups):
+        """Generate XSdata object from an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to read from
+        name : str
+            Name of the mgxs data set.
+        energy_groups : openmc.mgxs.EnergyGroups
+            Energy group structure
+        num_delayed_groups : int
+            Number of delayed groups
+
+        Returns
+        -------
+        openmc.XSdata
+            Multi-group cross section data
+
+        """
+
+        # Get a list of all the subgroups which will contain our temperature
+        # strings
+        subgroups = group.keys()
+        temperatures = []
+        for subgroup in subgroups:
+            if subgroup != 'kTs':
+                temperatures.append(subgroup)
+
+        # To ensure the actual floating point temperature used when creating
+        # the new library is consistent with that used when originally creating
+        # the file, get the floating point temperatures straight from the kTs
+        # group.
+        kTs_group = group['kTs']
+        float_temperatures = []
+        for temperature in temperatures:
+            kT = kTs_group[temperature].value
+            float_temperatures.append(kT / openmc.data.K_BOLTZMANN)
+
+        attrs = group.attrs.keys()
+        if 'representation' in attrs:
+            representation = group.attrs['representation'].decode()
+        else:
+            representation = 'isotropic'
+
+        data = cls(name, energy_groups, float_temperatures, representation,
+                   num_delayed_groups)
+
+        if 'scatter_format' in attrs:
+            data.scatter_format = group.attrs['scatter_format'].decode()
+
+        # Get the remaining optional attributes
+        if 'atomic_weight_ratio' in attrs:
+            data.atomic_weight_ratio = group.attrs['atomic_weight_ratio']
+        if 'order' in attrs:
+            data.order = group.attrs['order']
+        if data.representation == 'angle':
+            data.num_azimuthal = group.attrs['num_azimuthal']
+            data.num_polar = group.attrs['num_polar']
+
+        # Read the temperature-dependent datasets
+        for temp, float_temp in zip(temperatures, float_temperatures):
+            xs_types = ['total', 'absorption', 'fission', 'kappa-fission',
+                        'chi', 'chi-prompt', 'chi-delayed', 'nu-fission',
+                        'prompt-nu-fission', 'delayed-nu-fission', 'beta',
+                        'decay rate', 'inverse-velocity']
+
+            temperature_group = group[temp]
+
+            for xs_type in xs_types:
+                set_func = 'set_' + xs_type.replace(' ', '_').replace('-', '_')
+                if xs_type in temperature_group:
+                    getattr(data, set_func)(temperature_group[xs_type].value,
+                                            float_temp)
+
+            scatt_group = temperature_group['scatter_data']
+
+            # Get scatter matrix and 'un-flatten' it
+            g_max = scatt_group['g_max']
+            g_min = scatt_group['g_min']
+            flat_scatter = scatt_group['scatter_matrix'].value
+            scatter_matrix = np.zeros(data.xs_shapes["[G][G'][Order]"])
+            G = data.energy_groups.num_groups
+            if data.representation == 'isotropic':
+                Np = 1
+                Na = 1
+            elif data.representation == 'angle':
+                Np = data.num_polar
+                Na = data.num_azimuthal
+            flat_index = 0
+            for p in range(Np):
+                for a in range(Na):
+                    for g_in in range(G):
+                        if data.representation == 'isotropic':
+                            g_mins = g_min[g_in]
+                            g_maxs = g_max[g_in]
+                        elif data.representation == 'angle':
+                            g_mins = g_min[p, a, g_in]
+                            g_maxs = g_max[p, a, g_in]
+                        for g_out in range(g_mins - 1, g_maxs):
+                            for ang in range(data.num_orders):
+                                if data.representation == 'isotropic':
+                                    scatter_matrix[g_in, g_out, ang] = \
+                                        flat_scatter[flat_index]
+                                elif data.representation == 'angle':
+                                    scatter_matrix[p, a, g_in, g_out, ang] = \
+                                        flat_scatter[flat_index]
+                                flat_index += 1
+            data.set_scatter_matrix(scatter_matrix, float_temp)
+
+            # Repeat for multiplicity
+            if 'multiplicity_matrix' in scatt_group:
+                flat_mult = scatt_group['multiplicity_matrix'].value
+                mult_matrix = np.zeros(data.xs_shapes["[G][G']"])
+                flat_index = 0
+                for p in range(Np):
+                    for a in range(Na):
+                        for g_in in range(G):
+                            if data.representation == 'isotropic':
+                                g_mins = g_min[g_in]
+                                g_maxs = g_max[g_in]
+                            elif data.representation == 'angle':
+                                g_mins = g_min[p, a, g_in]
+                                g_maxs = g_max[p, a, g_in]
+                            for g_out in range(g_mins - 1, g_maxs):
+                                if data.representation == 'isotropic':
+                                    mult_matrix[g_in, g_out] = \
+                                        flat_mult[flat_index]
+                                elif data.representation == 'angle':
+                                    mult_matrix[p, a, g_in, g_out] = \
+                                        flat_mult[flat_index]
+                                flat_index += 1
+                data.set_multiplicity_matrix(mult_matrix, float_temp)
+
+        return data
+
 
 class MGXSLibrary(object):
     """Multi-Group Cross Sections file used for an OpenMC simulation.
@@ -1872,14 +2020,14 @@ class MGXSLibrary(object):
     def num_delayed_groups(self):
         return self._num_delayed_groups
 
-    @property
-    def temperatures(self):
-        return self._temperatures
-
     @property
     def xsdatas(self):
         return self._xsdatas
 
+    @property
+    def names(self):
+        return [xsdata.name for xsdata in self.xsdatas]
+
     @energy_groups.setter
     def energy_groups(self, energy_groups):
         check_type('energy groups', energy_groups, openmc.mgxs.EnergyGroups)
@@ -1887,7 +2035,7 @@ class MGXSLibrary(object):
 
     @num_delayed_groups.setter
     def num_delayed_groups(self, num_delayed_groups):
-        check_type('num_delayed_groups', num_delayed_groups, int)
+        check_type('num_delayed_groups', num_delayed_groups, Integral)
         check_greater_than('num_delayed_groups', num_delayed_groups, 0,
                            equality=True)
         check_less_than('num_delayed_groups', num_delayed_groups,
@@ -1916,7 +2064,7 @@ class MGXSLibrary(object):
         self._xsdatas.append(xsdata)
 
     def add_xsdatas(self, xsdatas):
-        """Add multiple xsdatas to the file.
+        """Add multiple XSdatas to the file.
 
         Parameters
         ----------
@@ -1947,6 +2095,27 @@ class MGXSLibrary(object):
 
         self._xsdatas.remove(xsdata)
 
+    def get_by_name(self, name):
+        """Access the XSdata objects by name
+
+        Parameters
+        ----------
+        name : str
+            Name of openmc.XSdata object to obtain
+
+        Returns
+        -------
+        result : openmc.XSdata or None
+            Provides the matching XSdata object or None, if not found
+
+        """
+        check_type("name", name, str)
+        result = None
+        for xsdata in self.xsdatas:
+            if name == xsdata.name:
+                result = xsdata
+        return result
+
     def export_to_hdf5(self, filename='mgxs.h5'):
         """Create an hdf5 file that can be used for a simulation.
 
@@ -1969,3 +2138,43 @@ class MGXSLibrary(object):
             xsdata.to_hdf5(file)
 
         file.close()
+
+    @classmethod
+    def from_hdf5(cls, filename=None):
+        """Generate an MGXS Library from an HDF5 group or file
+        Parameters
+        ----------
+        filename : str, optional
+            Name of HDF5 file containing MGXS data. Default is None.
+            If not provided, the value of the OPENMC_MG_CROSS_SECTIONS
+            environmental variable will be used
+        Returns
+        -------
+        openmc.MGXSLibrary
+            Multi-group cross section data object.
+        """
+
+        # If filename is None, get the cross sections from the
+        # OPENMC_CROSS_SECTIONS environment variable
+        if filename is None:
+            filename = os.environ.get('OPENMC_MG_CROSS_SECTIONS')
+
+        # Check to make sure there was an environmental variable.
+        if filename is None:
+            raise ValueError("Either path or OPENMC_MG_CROSS_SECTIONS "
+                             "environmental variable must be set")
+
+        check_type('filename', filename, str)
+        file = h5py.File(filename, 'r')
+
+        group_structure = file.attrs['group structure']
+        num_delayed_groups = file.attrs['delayed_groups']
+        energy_groups = openmc.mgxs.EnergyGroups(group_structure)
+        data = cls(energy_groups, num_delayed_groups)
+
+        for group_name, group in file.items():
+            data.add_xsdata(openmc.XSdata.from_hdf5(group, group_name,
+                                                    energy_groups,
+                                                    num_delayed_groups))
+
+        return data

From c423975189d897925f7e316b822649b49812a9f0 Mon Sep 17 00:00:00 2001
From: Adam Nelson <nelsonag@umich.edu>
Date: Wed, 30 Nov 2016 19:48:30 -0500
Subject: [PATCH 27/27] Modified XSData docstring, removed XSData.fissionable
 setter and made openmc.mgxs.MAX_LEGENDRE private.

---
 openmc/mgxs/mgxs.py    |  4 ++--
 openmc/mgxs_library.py | 37 +++++++++++++++----------------------
 2 files changed, 17 insertions(+), 24 deletions(-)

diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py
index 6f8abefd1..ce7511193 100644
--- a/openmc/mgxs/mgxs.py
+++ b/openmc/mgxs/mgxs.py
@@ -63,7 +63,7 @@ _DOMAINS = (openmc.Cell,
 MU_TREATMENTS = ('legendre', 'histogram')
 
 # Maximum Legendre order supported by OpenMC
-MAX_LEGENDRE = 10
+_MAX_LEGENDRE = 10
 
 
 @add_metaclass(ABCMeta)
@@ -3478,7 +3478,7 @@ class ScatterMatrixXS(MatrixMGXS):
         cv.check_type('legendre_order', legendre_order, Integral)
         cv.check_greater_than('legendre_order', legendre_order, 0,
                               equality=True)
-        cv.check_less_than('legendre_order', legendre_order, MAX_LEGENDRE,
+        cv.check_less_than('legendre_order', legendre_order, _MAX_LEGENDRE,
                            equality=True)
 
         if self.scatter_format == 'legendre':
diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py
index 70ff7a91b..10fda4593 100644
--- a/openmc/mgxs_library.py
+++ b/openmc/mgxs_library.py
@@ -71,50 +71,50 @@ class XSdata(object):
         Number of equal width angular bins that the polar angular domain is
         subdivided into. This only applies when :attr:`XSdata.representation`
         is "angle".
-    total : dict of numpy.ndarray
+    total : list of numpy.ndarray
         Group-wise total cross section.
-    absorption : dict of numpy.ndarray
+    absorption : list of numpy.ndarray
         Group-wise absorption cross section.
-    scatter_matrix : dict of numpy.ndarray
+    scatter_matrix : list of numpy.ndarray
         Scattering moment matrices presented with the columns representing
         incoming group and rows representing the outgoing group.  That is,
         down-scatter will be above the diagonal of the resultant matrix.
-    multiplicity_matrix : dict of numpy.ndarray
+    multiplicity_matrix : list of numpy.ndarray
         Ratio of neutrons produced in scattering collisions to the neutrons
         which undergo scattering collisions; that is, the multiplicity provides
         the code with a scaling factor to account for neutrons produced in
         (n,xn) reactions.
-    fission : dict of numpy.ndarray
+    fission : list of numpy.ndarray
         Group-wise fission cross section.
-    kappa_fission : dict of numpy.ndarray
+    kappa_fission : list of numpy.ndarray
         Group-wise kappa_fission cross section.
-    chi : dict of numpy.ndarray
+    chi : list of numpy.ndarray
         Group-wise fission spectra ordered by increasing group index (i.e.,
         fast to thermal). This attribute should be used if making the common
         approximation that the fission spectra does not depend on incoming
         energy. If the user does not wish to make this approximation, then
         this should not be provided and this information included in the
         :attr:`XSdata.nu_fission` attribute instead.
-    chi_prompt : dict of numpy.ndarray
+    chi_prompt : list of numpy.ndarray
         Group-wise prompt fission spectra ordered by increasing group index
         (i.e., fast to thermal). This attribute should be used if chi from
         prompt and delayed neutrons is being set separately.
-    chi_delayed : dict of numpy.ndarray
+    chi_delayed : list of numpy.ndarray
         Group-wise delayed fission spectra ordered by increasing group index
         (i.e., fast to thermal). This attribute should be used if chi from
         prompt and delayed neutrons is being set separately.
-    nu_fission : dict of numpy.ndarray
+    nu_fission : list of numpy.ndarray
         Group-wise fission production cross section vector (i.e., if ``chi`` is
         provided), or is the group-wise fission production matrix.
-    prompt_nu_fission : dict of numpy.ndarray
+    prompt_nu_fission : list of numpy.ndarray
         Group-wise prompt fission production cross section vector.
-    delayed_nu_fission : dict of numpy.ndarray
+    delayed_nu_fission : list of numpy.ndarray
         Group-wise delayed fission production cross section vector.
-    beta : dict of numpy.ndarray
+    beta : list of numpy.ndarray
         Delayed-group-wise delayed neutron fraction cross section vector.
-    decay_rate : dict of numpy.ndarray
+    decay_rate : list of numpy.ndarray
         Delayed-group-wise decay rate vector.
-    inverse_velocity : dict of numpy.ndarray
+    inverse_velocity : list of numpy.ndarray
         Inverse of velocity, in units of sec/cm.
     xs_shapes : dict of iterable of int
         Dictionary with keys of _XS_SHAPES and iterable of int values with the
@@ -360,13 +360,6 @@ class XSdata(object):
         check_greater_than('atomic_weight_ratio', atomic_weight_ratio, 0.0)
         self._atomic_weight_ratio = atomic_weight_ratio
 
-    @fissionable.setter
-    def fissionable(self, fissionable):
-
-        # Check validity of type
-        check_type('fissionable', fissionable, bool)
-        self._fissionable = fissionable
-
     @temperatures.setter
     def temperatures(self, temperatures):