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Implement MeshSurfaceFilter.get_pandas_dataframe. Fix surface/mesh filters
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Paul Romano
parent
206166cc41
commit
22429dd389
2 changed files with 136 additions and 30 deletions
164
openmc/filter.py
164
openmc/filter.py
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@ -22,12 +22,14 @@ _FILTER_TYPES = ['universe', 'material', 'cell', 'cellborn', 'surface',
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'mesh', 'energy', 'energyout', 'mu', 'polar', 'azimuthal',
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'distribcell', 'delayedgroup', 'energyfunction', 'cellfrom']
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_CURRENT_NAMES = {1: 'x-min out', 2: 'x-min in',
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3: 'x-max out', 4: 'x-max in',
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5: 'y-min out', 6: 'y-min in',
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7: 'y-max out', 8: 'y-max in',
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9: 'z-min out', 10: 'z-min in',
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11: 'z-max out', 12: 'z-max in'}
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_CURRENT_NAMES = OrderedDict([
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(1, 'x-min out'), (2, 'x-min in'),
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(3, 'x-max out'), (4, 'x-max in'),
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(5, 'y-min out'), (6, 'y-min in'),
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(7, 'y-max out'), (8, 'y-max in'),
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(9, 'z-min out'), (10, 'z-min in'),
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(11, 'z-max out'), (12, 'z-max in')
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])
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class FilterMeta(ABCMeta):
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@ -497,9 +499,9 @@ class CellFilter(WithIDFilter):
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Parameters
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----------
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bins : openmc.Cell, Integral, or iterable thereof
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The Cells to tally. Either openmc.Cell objects or their
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Integral ID numbers can be used.
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bins : openmc.Cell, int, or iterable thereof
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The cells to tally. Either openmc.Cell objects or their ID numbers can
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be used.
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filter_id : int
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Unique identifier for the filter
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@ -565,21 +567,21 @@ class CellbornFilter(WithIDFilter):
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class SurfaceFilter(Filter):
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"""Bins particle currents on Mesh surfaces.
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"""Filters particles by surface crossing
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Parameters
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----------
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bins : Iterable of Integral
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Indices corresponding to which face of a mesh cell the current is
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crossing.
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bins : openmc.Surface, int, or iterable of Integral
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The surfaces to tally over. Either openmc.Surface objects of their ID
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numbers can be used.
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filter_id : int
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Unique identifier for the filter
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Attributes
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----------
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bins : Iterable of Integral
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Indices corresponding to which face of a mesh cell the current is
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crossing.
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The surfaces to tally over. Either openmc.Surface objects of their ID
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numbers can be used.
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id : int
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Unique identifier for the filter
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num_bins : Integral
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@ -598,13 +600,6 @@ class SurfaceFilter(Filter):
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self._bins = bins
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@property
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def num_bins(self):
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# Need to handle number of bins carefully -- for surface current
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# tallies, the number of bins depends on the mesh, which we don't have a
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# reference to in this filter
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return self._num_bins
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def get_pandas_dataframe(self, data_size, stride, **kwargs):
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"""Builds a Pandas DataFrame for the Filter's bins.
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@ -689,7 +684,6 @@ class MeshFilter(Filter):
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filter_id = int(group.name.split('/')[-1].lstrip('filter '))
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out = cls(mesh_obj, filter_id=filter_id)
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out._num_bins = group['n_bins'].value
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return out
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@ -705,10 +699,7 @@ class MeshFilter(Filter):
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@property
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def num_bins(self):
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try:
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return self._num_bins
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except AttributeError:
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return reduce(operator.mul, self.mesh.dimension)
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return reduce(operator.mul, self.mesh.dimension)
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def check_bins(self, bins):
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if not len(bins) == 1:
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@ -802,7 +793,7 @@ class MeshFilter(Filter):
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filter_dict = {}
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# Append Mesh ID as outermost index of multi-index
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mesh_key = 'mesh {0}'.format(self.mesh.id)
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mesh_key = 'mesh {}'.format(self.mesh.id)
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# Find mesh dimensions - use 3D indices for simplicity
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n_dim = len(self.mesh.dimension)
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@ -846,7 +837,122 @@ class MeshFilter(Filter):
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class MeshSurfaceFilter(MeshFilter):
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pass
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"""Filter events by surface crossings on a regular, rectangular mesh.
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Parameters
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----------
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mesh : openmc.Mesh
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The Mesh object that events will be tallied onto
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filter_id : int
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Unique identifier for the filter
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Attributes
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----------
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bins : Integral
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The Mesh ID
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mesh : openmc.Mesh
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The Mesh object that events will be tallied onto
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id : int
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Unique identifier for the filter
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num_bins : Integral
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The number of filter bins
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"""
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@property
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def num_bins(self):
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n_dim = len(self.mesh.dimension)
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return 4*n_dim*reduce(operator.mul, self.mesh.dimension)
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def get_bin_index(self, filter_bin):
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raise NotImplementedError
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def get_bin(self, bin_index):
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raise NotImplementedError
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def get_pandas_dataframe(self, data_size, stride, **kwargs):
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"""Builds a Pandas DataFrame for the Filter's bins.
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This method constructs a Pandas DataFrame object for the filter with
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columns annotated by filter bin information. This is a helper method for
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:meth:`Tally.get_pandas_dataframe`.
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Parameters
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----------
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data_size : int
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The total number of bins in the tally corresponding to this filter
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stride : int
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Stride in memory for the filter
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Returns
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-------
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pandas.DataFrame
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A Pandas DataFrame with three columns describing the x,y,z mesh
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cell indices corresponding to each filter bin. The number of rows
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in the DataFrame is the same as the total number of bins in the
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corresponding tally, with the filter bin appropriately tiled to map
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to the corresponding tally bins.
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See also
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--------
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Tally.get_pandas_dataframe(), CrossFilter.get_pandas_dataframe()
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"""
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# Initialize Pandas DataFrame
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df = pd.DataFrame()
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# Initialize dictionary to build Pandas Multi-index column
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filter_dict = {}
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# Append Mesh ID as outermost index of multi-index
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mesh_key = 'mesh {}'.format(self.mesh.id)
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# Find mesh dimensions - use 3D indices for simplicity
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if len(self.mesh.dimension) == 3:
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nx, ny, nz = self.mesh.dimension
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elif len(self.mesh.dimension) == 2:
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nx, ny = self.mesh.dimension
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nz = 1
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else:
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nx = self.mesh.dimension
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ny = nz = 1
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# Generate multi-index sub-column for x-axis
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filter_bins = np.arange(1, nx + 1)
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repeat_factor = 12 * stride
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filter_bins = np.repeat(filter_bins, repeat_factor)
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tile_factor = data_size // len(filter_bins)
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filter_bins = np.tile(filter_bins, tile_factor)
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filter_dict[(mesh_key, 'x')] = filter_bins
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# Generate multi-index sub-column for y-axis
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filter_bins = np.arange(1, ny + 1)
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repeat_factor = 12 * nx * stride
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filter_bins = np.repeat(filter_bins, repeat_factor)
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tile_factor = data_size // len(filter_bins)
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filter_bins = np.tile(filter_bins, tile_factor)
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filter_dict[(mesh_key, 'y')] = filter_bins
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# Generate multi-index sub-column for z-axis
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filter_bins = np.arange(1, nz + 1)
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repeat_factor = 12 * nx * ny * stride
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filter_bins = np.repeat(filter_bins, repeat_factor)
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tile_factor = data_size // len(filter_bins)
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filter_bins = np.tile(filter_bins, tile_factor)
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filter_dict[(mesh_key, 'z')] = filter_bins
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# Generate multi-index sub-column for surface
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filter_bins = list(_CURRENT_NAMES.values())
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repeat_factor = stride
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filter_bins = np.repeat(filter_bins, repeat_factor)
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tile_factor = data_size // len(filter_bins)
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filter_bins = np.tile(filter_bins, tile_factor)
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filter_dict[(mesh_key, 'surf')] = filter_bins
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# Initialize a Pandas DataFrame from the mesh dictionary
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df = pd.concat([df, pd.DataFrame(filter_dict)])
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return df
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class RealFilter(Filter):
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@ -2738,7 +2738,7 @@ class Tally(IDManagerMixin):
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new_filter = filter_type(bins)
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# Set number of bins manually for mesh/distribcell filters
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if filter_type in (openmc.DistribcellFilter, openmc.MeshFilter):
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if filter_type is openmc.DistribcellFilter:
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new_filter._num_bins = find_filter._num_bins
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# Replace existing filter with new one
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