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Merged
pshriwise merged 2 commits into from
Apr 28, 2022
Merged

Support for CellInstanceFilter #88

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54c4b73
Implement support for CellInstanceFilter tally plotting
paulromano Apr 27, 2022
258a503
Combine separate functions for distribcell / cell instance plotting
paulromano Apr 27, 2022
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Implement support for CellInstanceFilter tally plotting
  • Loading branch information
@paulromano
paulromano committed Apr 27, 2022
commit 54c4b737d67bd7f0d9894828d2b58860063e99a6
7 changes: 5 additions & 2 deletions openmc_plotter/docks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -406,8 +406,11 @@ def _createFilterTree(self, spatial_filters):
continue

def _bin_sort_val(bin):
if isinstance(bin, Iterable) and all([isinstance(val, float) for val in bin]):
return np.sum(bin)
if isinstance(bin, Iterable):
if all([isinstance(val, float) for val in bin]):
return np.sum(bin)
else:
return tuple(bin)
else:
return bin

Expand Down
56 changes: 39 additions & 17 deletions openmc_plotter/plotmodel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@
openmc.MaterialFilter,
openmc.CellFilter,
openmc.DistribcellFilter,
openmc.CellInstanceFilter,
openmc.MeshFilter)

_PRODUCTIONS = ('delayed-nu-fission', 'prompt-nu-fission', 'nu-fission',
Expand Down Expand Up @@ -330,6 +331,9 @@ def create_tally_image(self, view=None):

units_out = list(units)[0]

contains_distribcell = tally.contains_filter(openmc.DistribcellFilter)
contains_cellinstance = tally.contains_filter(openmc.CellInstanceFilter)

if tally.contains_filter(openmc.MeshFilter):
if tally_value == 'rel_err':
# get both the std. dev. data and mean data
Expand Down Expand Up @@ -360,28 +364,26 @@ def create_tally_image(self, view=None):
nuclides,
view)
return image + (units_out,)
elif tally.contains_filter(openmc.DistribcellFilter):
elif contains_distribcell or contains_cellinstance:
# Select appropriate function
if contains_distribcell:
create_image = self._create_distribcell_image
else:
create_image = self._create_cellinstance_image

if tally_value == 'rel_err':
mean_data = self._create_distribcell_image(tally,
'mean',
scores,
nuclides)
std_dev_data = self._create_distribcell_image(tally,
'std_dev',
scores,
nuclides)
image_data = 100 * np.divide(std_dev_data[0],
mean_data[0],
out=np.zeros_like(mean_data[0]),
where=mean_data != 0)
mean_data = create_image(tally, 'mean', scores, nuclides)
std_dev_data = create_image(tally, 'std_dev', scores, nuclides)
image_data = 100 * np.divide(
std_dev_data[0], mean_data[0],
out=np.zeros_like(mean_data[0]),
where=mean_data != 0
)
data_min = np.min(image_data)
data_max = np.max(image_data)
return image_data, None, data_min, data_max, '% error'
else:
image = self._create_distribcell_image(tally,
tally_value,
scores,
nuclides)
image = create_image(tally, tally_value, scores, nuclides)
return image + (units_out,)
else:
# same as above, get the std. dev. data
Expand Down Expand Up @@ -522,6 +524,26 @@ def _create_distribcell_image(self, tally, tally_value, scores, nuclides):

return image_data, None, data_min, data_max

def _create_cellinstance_image(self, tally, tally_value, scores, nuclides):
cellinst_filter = tally.find_filter(openmc.CellInstanceFilter)

data = tally.get_values(scores=scores, nuclides=nuclides, value=tally_value)
data = data.flatten()

# create a mask for ids that match the cell
image_data = np.full_like(self.ids, np.nan, dtype=float)

for v, (cell_id, instance) in zip(data, cellinst_filter.bins):
cell_id_mask = self.cell_ids == cell_id
instance_mask = self.instances == instance
image_data[cell_id_mask & instance_mask] = v

data_min = np.min(data)
data_max = np.max(data)
image_data = np.ma.masked_where(image_data < 0.0, image_data)

return image_data, None, data_min, data_max

def _create_tally_mesh_image(self, tally, tally_value, scores, nuclides, view=None):
# some variables used throughout
if view is None:
Expand Down