diff --git a/openmc/filter.py b/openmc/filter.py index 8fa2e7e62..87aeb70c3 100644 --- a/openmc/filter.py +++ b/openmc/filter.py @@ -972,53 +972,36 @@ class MeshFilter(Filter): Returns ------- pandas.DataFrame - A Pandas DataFrame with three columns describing the x,y,z mesh - cell indices corresponding to 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. + A Pandas DataFrame with columns describing the mesh cell indices + corresponding to each filter bin. Column names depend on the mesh + type (e.g., x/y/z for RegularMesh, r/phi/z for CylindricalMesh, + r/theta/phi for SphericalMesh, or element index for + UnstructuredMesh). 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. See also -------- Tally.get_pandas_dataframe(), CrossFilter.get_pandas_dataframe() """ - # Initialize Pandas DataFrame - df = pd.DataFrame() - # Initialize dictionary to build Pandas Multi-index column filter_dict = {} # Append mesh ID as outermost index of multi-index mesh_key = f'mesh {self.mesh.id}' - # Find mesh dimensions - use 3D indices for simplicity - n_dim = len(self.mesh.dimension) - if n_dim == 3: - nx, ny, nz = self.mesh.dimension - elif n_dim == 2: - nx, ny = self.mesh.dimension - nz = 1 - else: - nx = self.mesh.dimension - ny = nz = 1 + # Determine index base (0-based for unstructured, 1-based otherwise) + idx_start = 0 if isinstance(self.mesh, openmc.UnstructuredMesh) else 1 - # Generate multi-index sub-column for x-axis - filter_dict[mesh_key, 'x'] = _repeat_and_tile( - np.arange(1, nx + 1), stride, data_size) + # Generate a multi-index sub-column for each axis + for label, dim_size in zip(self.mesh._axis_labels, self.mesh.dimension): + filter_dict[mesh_key, label] = _repeat_and_tile( + np.arange(idx_start, idx_start + dim_size), stride, data_size) + stride *= dim_size - # Generate multi-index sub-column for y-axis - filter_dict[mesh_key, 'y'] = _repeat_and_tile( - np.arange(1, ny + 1), nx * stride, data_size) - - # Generate multi-index sub-column for z-axis - filter_dict[mesh_key, 'z'] = _repeat_and_tile( - np.arange(1, nz + 1), nx * ny * stride, data_size) - - # Initialize a Pandas DataFrame from the mesh dictionary - df = pd.concat([df, pd.DataFrame(filter_dict)]) - - return df + return pd.DataFrame(filter_dict) def to_xml_element(self): """Return XML Element representing the Filter. diff --git a/openmc/mesh.py b/openmc/mesh.py index efe1c20a1..946b90fbf 100644 --- a/openmc/mesh.py +++ b/openmc/mesh.py @@ -236,12 +236,12 @@ class MeshBase(IDManagerMixin, ABC): self._name = name else: self._name = '' - + @property @abstractmethod def lower_left(self): pass - + @property @abstractmethod def upper_right(self): @@ -255,7 +255,7 @@ class MeshBase(IDManagerMixin, ABC): @abstractmethod def indices(self): pass - + @property @abstractmethod def n_elements(self): @@ -537,6 +537,11 @@ class StructuredMesh(MeshBase): def n_dimension(self): pass + @property + @abstractmethod + def _axis_labels(self): + pass + @property @abstractmethod def _grids(self): @@ -636,7 +641,7 @@ class StructuredMesh(MeshBase): s0 = (slice(0, -1),)*ndim + (slice(None),) s1 = (slice(1, None),)*ndim + (slice(None),) return (vertices[s0] + vertices[s1]) / 2 - + @property def n_elements(self): return np.prod(self.dimension) @@ -995,6 +1000,10 @@ class RegularMesh(StructuredMesh): else: return None + @property + def _axis_labels(self): + return ('x', 'y', 'z')[:self.n_dimension] + @property def lower_left(self): return self._lower_left @@ -1475,6 +1484,10 @@ class RectilinearMesh(StructuredMesh): def n_dimension(self): return 3 + @property + def _axis_labels(self): + return ('x', 'y', 'z') + @property def x_grid(self): return self._x_grid @@ -1709,6 +1722,10 @@ class CylindricalMesh(StructuredMesh): def n_dimension(self): return 3 + @property + def _axis_labels(self): + return ('r', 'phi', 'z') + @property def origin(self): return self._origin @@ -2156,6 +2173,10 @@ class SphericalMesh(StructuredMesh): def n_dimension(self): return 3 + @property + def _axis_labels(self): + return ('r', 'theta', 'phi') + @property def origin(self): return self._origin @@ -2671,6 +2692,10 @@ class UnstructuredMesh(MeshBase): def n_dimension(self): return 3 + @property + def _axis_labels(self): + return ('element_index',) + @property @require_statepoint_data def indices(self): diff --git a/openmc/mgxs/mdgxs.py b/openmc/mgxs/mdgxs.py index c12c1a9ab..57cc955ba 100644 --- a/openmc/mgxs/mdgxs.py +++ b/openmc/mgxs/mdgxs.py @@ -877,8 +877,8 @@ class MDGXS(MGXS): # energy groups such that data is from fast to thermal if self.domain_type == 'mesh': mesh_str = f'mesh {self.domain.id}' - df.sort_values(by=[(mesh_str, 'x'), (mesh_str, 'y'), - (mesh_str, 'z')] + columns, inplace=True) + mesh_cols = [(mesh_str, label) for label in self.domain._axis_labels] + df.sort_values(by=mesh_cols + columns, inplace=True) else: df.sort_values(by=[self.domain_type] + columns, inplace=True) diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py index 12b8f6a75..4c13c7508 100644 --- a/openmc/mgxs/mgxs.py +++ b/openmc/mgxs/mgxs.py @@ -2134,8 +2134,8 @@ class MGXS: # energy groups such that data is from fast to thermal if self.domain_type == 'mesh': mesh_str = f'mesh {self.domain.id}' - df.sort_values(by=[(mesh_str, 'x'), (mesh_str, 'y'), - (mesh_str, 'z')] + columns, inplace=True) + mesh_cols = [(mesh_str, label) for label in self.domain._axis_labels] + df.sort_values(by=mesh_cols + columns, inplace=True) else: df.sort_values(by=[self.domain_type] + columns, inplace=True) diff --git a/tests/regression_tests/mgxs_library_condense/results_true.dat b/tests/regression_tests/mgxs_library_condense/results_true.dat index 98b30932c..023d5afa2 100644 --- a/tests/regression_tests/mgxs_library_condense/results_true.dat +++ b/tests/regression_tests/mgxs_library_condense/results_true.dat @@ -1,189 +1,189 @@ - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.702881 0.026175 -2 1 2 1 1 total 0.706921 0.029169 -1 2 1 1 1 total 0.707809 0.024766 -3 2 2 1 1 total 0.717967 0.024008 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.431023 0.028803 -2 1 2 1 1 total 0.451864 0.030748 -1 2 1 1 1 total 0.456990 0.026359 -3 2 2 1 1 total 0.450621 0.026744 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.431023 0.028803 -2 1 2 1 1 total 0.451864 0.030748 -1 2 1 1 1 total 0.456990 0.026359 -3 2 2 1 1 total 0.450621 0.026744 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.022398 0.001401 -2 1 2 1 1 total 0.022325 0.001371 -1 2 1 1 1 total 0.022942 0.000990 -3 2 2 1 1 total 0.022705 0.001322 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.022394 0.001401 -2 1 2 1 1 total 0.022321 0.001371 -1 2 1 1 1 total 0.022935 0.000990 -3 2 2 1 1 total 0.022699 0.001322 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.011562 0.001544 -2 1 2 1 1 total 0.011852 0.001418 -1 2 1 1 1 total 0.012168 0.000958 -3 2 2 1 1 total 0.011986 0.001418 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.010836 0.000803 -2 1 2 1 1 total 0.010473 0.000591 -1 2 1 1 1 total 0.010774 0.000415 -3 2 2 1 1 total 0.010719 0.000688 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.026602 0.001957 -2 1 2 1 1 total 0.025695 0.001442 -1 2 1 1 1 total 0.026454 0.001015 -3 2 2 1 1 total 0.026310 0.001678 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 2.098256e+06 155243.612264 -2 1 2 1 1 total 2.027699e+06 114334.400924 -1 2 1 1 1 total 2.086255e+06 80325.567787 -3 2 2 1 1 total 2.075596e+06 133128.805680 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.680483 0.025407 -2 1 2 1 1 total 0.684597 0.028126 -1 2 1 1 1 total 0.684867 0.024133 -3 2 2 1 1 total 0.695262 0.023087 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.678017 0.026288 -2 1 2 1 1 total 0.674888 0.033989 -1 2 1 1 1 total 0.681736 0.025618 -3 2 2 1 1 total 0.683701 0.023788 - mesh 1 group in group out legendre nuclide mean std. dev. - x y z -0 1 1 1 1 1 P0 total 0.678017 0.026290 -1 1 1 1 1 1 P1 total 0.271858 0.011693 -2 1 1 1 1 1 P2 total 0.095219 0.002950 -3 1 1 1 1 1 P3 total 0.012808 0.004686 -8 1 2 1 1 1 P0 total 0.674888 0.033578 -9 1 2 1 1 1 P1 total 0.255058 0.009912 -10 1 2 1 1 1 P2 total 0.098001 0.005459 -11 1 2 1 1 1 P3 total 0.012058 0.005439 -4 2 1 1 1 1 P0 total 0.681736 0.025439 -5 2 1 1 1 1 P1 total 0.250820 0.009035 -6 2 1 1 1 1 P2 total 0.092563 0.006549 -7 2 1 1 1 1 P3 total 0.008511 0.003905 -12 2 2 1 1 1 P0 total 0.683701 0.024254 -13 2 2 1 1 1 P1 total 0.267345 0.011695 -14 2 2 1 1 1 P2 total 0.096222 0.005551 -15 2 2 1 1 1 P3 total 0.011515 0.003236 - mesh 1 group in group out legendre nuclide mean std. dev. - x y z -0 1 1 1 1 1 P0 total 0.678017 0.026290 -1 1 1 1 1 1 P1 total 0.271858 0.011693 -2 1 1 1 1 1 P2 total 0.095219 0.002950 -3 1 1 1 1 1 P3 total 0.012808 0.004686 -8 1 2 1 1 1 P0 total 0.674888 0.033578 -9 1 2 1 1 1 P1 total 0.255058 0.009912 -10 1 2 1 1 1 P2 total 0.098001 0.005459 -11 1 2 1 1 1 P3 total 0.012058 0.005439 -4 2 1 1 1 1 P0 total 0.681736 0.025439 -5 2 1 1 1 1 P1 total 0.250820 0.009035 -6 2 1 1 1 1 P2 total 0.092563 0.006549 -7 2 1 1 1 1 P3 total 0.008511 0.003905 -12 2 2 1 1 1 P0 total 0.683701 0.024254 -13 2 2 1 1 1 P1 total 0.267345 0.011695 -14 2 2 1 1 1 P2 total 0.096222 0.005551 -15 2 2 1 1 1 P3 total 0.011515 0.003236 - mesh 1 group in group out nuclide mean std. dev. - x y z -0 1 1 1 1 1 total 1.0 0.041785 -2 1 2 1 1 1 total 1.0 0.057717 -1 2 1 1 1 1 total 1.0 0.040074 -3 2 2 1 1 1 total 1.0 0.042758 - mesh 1 group in group out nuclide mean std. dev. - x y z -0 1 1 1 1 1 total 0.028438 0.003513 -2 1 2 1 1 1 total 0.022222 0.001560 -1 2 1 1 1 1 total 0.025698 0.002756 -3 2 2 1 1 1 total 0.026501 0.002315 - mesh 1 group in group out nuclide mean std. dev. - x y z -0 1 1 1 1 1 total 1.0 0.041785 -2 1 2 1 1 1 total 1.0 0.057717 -1 2 1 1 1 1 total 1.0 0.040074 -3 2 2 1 1 1 total 1.0 0.042758 - mesh 1 group in group out legendre nuclide mean std. dev. - x y z -0 1 1 1 1 1 P0 total 0.680483 0.038131 -1 1 1 1 1 1 P1 total 0.272847 0.016111 -2 1 1 1 1 1 P2 total 0.095565 0.004869 -3 1 1 1 1 1 P3 total 0.012854 0.004731 -8 1 2 1 1 1 P0 total 0.684597 0.048501 -9 1 2 1 1 1 P1 total 0.258727 0.016473 -10 1 2 1 1 1 P2 total 0.099411 0.007470 -11 1 2 1 1 1 P3 total 0.012231 0.005552 -4 2 1 1 1 1 P0 total 0.684867 0.036546 -5 2 1 1 1 1 P1 total 0.251972 0.013220 -6 2 1 1 1 1 P2 total 0.092988 0.007474 -7 2 1 1 1 1 P3 total 0.008550 0.003936 -12 2 2 1 1 1 P0 total 0.695262 0.037640 -13 2 2 1 1 1 P1 total 0.271866 0.016280 -14 2 2 1 1 1 P2 total 0.097849 0.006919 -15 2 2 1 1 1 P3 total 0.011710 0.003325 - mesh 1 group in group out legendre nuclide mean std. dev. - x y z -0 1 1 1 1 1 P0 total 0.680483 0.047566 -1 1 1 1 1 1 P1 total 0.272847 0.019737 -2 1 1 1 1 1 P2 total 0.095565 0.006297 -3 1 1 1 1 1 P3 total 0.012854 0.004762 -8 1 2 1 1 1 P0 total 0.684597 0.062559 -9 1 2 1 1 1 P1 total 0.258727 0.022234 -10 1 2 1 1 1 P2 total 0.099411 0.009420 -11 1 2 1 1 1 P3 total 0.012231 0.005597 -4 2 1 1 1 1 P0 total 0.684867 0.045704 -5 2 1 1 1 1 P1 total 0.251972 0.016635 -6 2 1 1 1 1 P2 total 0.092988 0.008352 -7 2 1 1 1 1 P3 total 0.008550 0.003951 -12 2 2 1 1 1 P0 total 0.695262 0.047964 -13 2 2 1 1 1 P1 total 0.271866 0.020004 -14 2 2 1 1 1 P2 total 0.097849 0.008086 -15 2 2 1 1 1 P3 total 0.011710 0.003363 - mesh 1 group out nuclide mean std. dev. - x y z -0 1 1 1 1 total 1.0 0.142430 -2 1 2 1 1 total 1.0 0.112715 -1 2 1 1 1 total 1.0 0.192385 -3 2 2 1 1 total 1.0 0.109836 - mesh 1 group out nuclide mean std. dev. - x y z -0 1 1 1 1 total 1.0 0.143959 -2 1 2 1 1 total 1.0 0.102504 -1 2 1 1 1 total 1.0 0.188381 -3 2 2 1 1 total 1.0 0.116230 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 5.060544e-07 3.651604e-08 -2 1 2 1 1 total 5.101988e-07 4.947639e-08 -1 2 1 1 1 total 5.206450e-07 2.814648e-08 -3 2 2 1 1 total 5.278759e-07 3.171554e-08 - mesh 1 group in nuclide mean std. dev. - x y z -0 1 1 1 1 total 0.026414 0.001944 -2 1 2 1 1 total 0.025515 0.001432 -1 2 1 1 1 total 0.026267 0.001008 -3 2 2 1 1 total 0.026125 0.001667 - mesh 1 group in group out nuclide mean std. dev. - x y z -0 1 1 1 1 1 total 0.028220 0.003510 -2 1 2 1 1 1 total 0.021754 0.001519 -1 2 1 1 1 1 total 0.025487 0.002676 -3 2 2 1 1 1 total 0.026281 0.002263 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.702881 0.026175 +2 1 2 1 total 0.706921 0.029169 +1 2 1 1 total 0.707809 0.024766 +3 2 2 1 total 0.717967 0.024008 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.431023 0.028803 +2 1 2 1 total 0.451864 0.030748 +1 2 1 1 total 0.456990 0.026359 +3 2 2 1 total 0.450621 0.026744 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.431023 0.028803 +2 1 2 1 total 0.451864 0.030748 +1 2 1 1 total 0.456990 0.026359 +3 2 2 1 total 0.450621 0.026744 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.022398 0.001401 +2 1 2 1 total 0.022325 0.001371 +1 2 1 1 total 0.022942 0.000990 +3 2 2 1 total 0.022705 0.001322 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.022394 0.001401 +2 1 2 1 total 0.022321 0.001371 +1 2 1 1 total 0.022935 0.000990 +3 2 2 1 total 0.022699 0.001322 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.011562 0.001544 +2 1 2 1 total 0.011852 0.001418 +1 2 1 1 total 0.012168 0.000958 +3 2 2 1 total 0.011986 0.001418 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.010836 0.000803 +2 1 2 1 total 0.010473 0.000591 +1 2 1 1 total 0.010774 0.000415 +3 2 2 1 total 0.010719 0.000688 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.026602 0.001957 +2 1 2 1 total 0.025695 0.001442 +1 2 1 1 total 0.026454 0.001015 +3 2 2 1 total 0.026310 0.001678 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 2.098256e+06 155243.612264 +2 1 2 1 total 2.027699e+06 114334.400924 +1 2 1 1 total 2.086255e+06 80325.567787 +3 2 2 1 total 2.075596e+06 133128.805680 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.680483 0.025407 +2 1 2 1 total 0.684597 0.028126 +1 2 1 1 total 0.684867 0.024133 +3 2 2 1 total 0.695262 0.023087 + mesh 1 group in nuclide mean std. dev. + x y +0 1 1 1 total 0.678017 0.026288 +2 1 2 1 total 0.674888 0.033989 +1 2 1 1 total 0.681736 0.025618 +3 2 2 1 total 0.683701 0.023788 + mesh 1 group in group out legendre nuclide mean std. dev. + x y +0 1 1 1 1 P0 total 0.678017 0.026290 +1 1 1 1 1 P1 total 0.271858 0.011693 +2 1 1 1 1 P2 total 0.095219 0.002950 +3 1 1 1 1 P3 total 0.012808 0.004686 +8 1 2 1 1 P0 total 0.674888 0.033578 +9 1 2 1 1 P1 total 0.255058 0.009912 +10 1 2 1 1 P2 total 0.098001 0.005459 +11 1 2 1 1 P3 total 0.012058 0.005439 +4 2 1 1 1 P0 total 0.681736 0.025439 +5 2 1 1 1 P1 total 0.250820 0.009035 +6 2 1 1 1 P2 total 0.092563 0.006549 +7 2 1 1 1 P3 total 0.008511 0.003905 +12 2 2 1 1 P0 total 0.683701 0.024254 +13 2 2 1 1 P1 total 0.267345 0.011695 +14 2 2 1 1 P2 total 0.096222 0.005551 +15 2 2 1 1 P3 total 0.011515 0.003236 + mesh 1 group in group out legendre nuclide mean std. dev. + x y +0 1 1 1 1 P0 total 0.678017 0.026290 +1 1 1 1 1 P1 total 0.271858 0.011693 +2 1 1 1 1 P2 total 0.095219 0.002950 +3 1 1 1 1 P3 total 0.012808 0.004686 +8 1 2 1 1 P0 total 0.674888 0.033578 +9 1 2 1 1 P1 total 0.255058 0.009912 +10 1 2 1 1 P2 total 0.098001 0.005459 +11 1 2 1 1 P3 total 0.012058 0.005439 +4 2 1 1 1 P0 total 0.681736 0.025439 +5 2 1 1 1 P1 total 0.250820 0.009035 +6 2 1 1 1 P2 total 0.092563 0.006549 +7 2 1 1 1 P3 total 0.008511 0.003905 +12 2 2 1 1 P0 total 0.683701 0.024254 +13 2 2 1 1 P1 total 0.267345 0.011695 +14 2 2 1 1 P2 total 0.096222 0.005551 +15 2 2 1 1 P3 total 0.011515 0.003236 + mesh 1 group in group out nuclide mean std. dev. + x y +0 1 1 1 1 total 1.0 0.041785 +2 1 2 1 1 total 1.0 0.057717 +1 2 1 1 1 total 1.0 0.040074 +3 2 2 1 1 total 1.0 0.042758 + mesh 1 group in group out nuclide mean std. dev. + x y +0 1 1 1 1 total 0.028438 0.003513 +2 1 2 1 1 total 0.022222 0.001560 +1 2 1 1 1 total 0.025698 0.002756 +3 2 2 1 1 total 0.026501 0.002315 + mesh 1 group in group out nuclide mean std. dev. + x y +0 1 1 1 1 total 1.0 0.041785 +2 1 2 1 1 total 1.0 0.057717 +1 2 1 1 1 total 1.0 0.040074 +3 2 2 1 1 total 1.0 0.042758 + mesh 1 group in group out legendre nuclide mean std. dev. + x y +0 1 1 1 1 P0 total 0.680483 0.038131 +1 1 1 1 1 P1 total 0.272847 0.016111 +2 1 1 1 1 P2 total 0.095565 0.004869 +3 1 1 1 1 P3 total 0.012854 0.004731 +8 1 2 1 1 P0 total 0.684597 0.048501 +9 1 2 1 1 P1 total 0.258727 0.016473 +10 1 2 1 1 P2 total 0.099411 0.007470 +11 1 2 1 1 P3 total 0.012231 0.005552 +4 2 1 1 1 P0 total 0.684867 0.036546 +5 2 1 1 1 P1 total 0.251972 0.013220 +6 2 1 1 1 P2 total 0.092988 0.007474 +7 2 1 1 1 P3 total 0.008550 0.003936 +12 2 2 1 1 P0 total 0.695262 0.037640 +13 2 2 1 1 P1 total 0.271866 0.016280 +14 2 2 1 1 P2 total 0.097849 0.006919 +15 2 2 1 1 P3 total 0.011710 0.003325 + mesh 1 group in group out legendre nuclide mean std. dev. + x y +0 1 1 1 1 P0 total 0.680483 0.047566 +1 1 1 1 1 P1 total 0.272847 0.019737 +2 1 1 1 1 P2 total 0.095565 0.006297 +3 1 1 1 1 P3 total 0.012854 0.004762 +8 1 2 1 1 P0 total 0.684597 0.062559 +9 1 2 1 1 P1 total 0.258727 0.022234 +10 1 2 1 1 P2 total 0.099411 0.009420 +11 1 2 1 1 P3 total 0.012231 0.005597 +4 2 1 1 1 P0 total 0.684867 0.045704 +5 2 1 1 1 P1 total 0.251972 0.016635 +6 2 1 1 1 P2 total 0.092988 0.008352 +7 2 1 1 1 P3 total 0.008550 0.003951 +12 2 2 1 1 P0 total 0.695262 0.047964 +13 2 2 1 1 P1 total 0.271866 0.020004 +14 2 2 1 1 P2 total 0.097849 0.008086 +15 2 2 1 1 P3 total 0.011710 0.003363 + mesh 1 group out nuclide mean std. dev. + x y +0 1 1 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0.000026 +15 1 2 4 1 1 total 0.000026 0.000026 +16 1 2 5 1 1 total 0.000059 0.000036 +17 1 2 6 1 1 total 0.000033 0.000033 +6 2 1 1 1 1 total 0.000000 0.000000 +7 2 1 2 1 1 total 0.000000 0.000000 +8 2 1 3 1 1 total 0.000032 0.000032 +9 2 1 4 1 1 total 0.000080 0.000033 +10 2 1 5 1 1 total 0.000028 0.000028 +11 2 1 6 1 1 total 0.000000 0.000000 +18 2 2 1 1 1 total 0.000054 0.000033 +19 2 2 2 1 1 total 0.000029 0.000029 +20 2 2 3 1 1 total 0.000000 0.000000 +21 2 2 4 1 1 total 0.000054 0.000033 +22 2 2 5 1 1 total 0.000032 0.000032 +23 2 2 6 1 1 total 0.000000 0.000000 diff --git a/tests/unit_tests/dagmc/test_lost_particles.py b/tests/unit_tests/dagmc/test_lost_particles.py index 3a4166009..931a37f64 100644 --- a/tests/unit_tests/dagmc/test_lost_particles.py +++ b/tests/unit_tests/dagmc/test_lost_particles.py @@ -57,6 +57,10 @@ def broken_dagmc_model(request): model.settings.inactive = 2 model.settings.output = {'summary': False} + # Limit max particle events to prevent particles from getting stuck in the + # implicit complement of the non-root DAGMC universe. + model.settings.max_particle_events = 100 + model.export_to_xml() return model diff --git a/tests/unit_tests/test_filter_mesh.py b/tests/unit_tests/test_filter_mesh.py index faa43af47..e26bea337 100644 --- a/tests/unit_tests/test_filter_mesh.py +++ b/tests/unit_tests/test_filter_mesh.py @@ -285,3 +285,128 @@ def test_mesh_filter_rotation_roundtrip(run_in_tmpdir): elem = mesh_filter.to_xml_element() mesh_filter_xml = openmc.MeshFilter.from_xml_element(elem, meshes={mesh.id: mesh}) assert np.allclose(mesh_filter_xml.rotation, mesh_filter.rotation) + + +def test_mesh_filter_dataframe_regular_3d(): + """Test MeshFilter.get_pandas_dataframe with a 3D RegularMesh.""" + mesh = openmc.RegularMesh() + mesh.lower_left = [0, 0, 0] + mesh.upper_right = [3, 4, 5] + mesh.dimension = [3, 4, 5] + + f = openmc.MeshFilter(mesh) + data_size = 3 * 4 * 5 + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'x') in df.columns + assert (mesh_key, 'y') in df.columns + assert (mesh_key, 'z') in df.columns + assert len(df) == data_size + # x varies fastest (stride=1), then y (stride=3), then z (stride=12) + assert list(df[(mesh_key, 'x')][:3]) == [1, 2, 3] + assert df[(mesh_key, 'y')].iloc[0] == 1 + assert df[(mesh_key, 'y')].iloc[3] == 2 + + +def test_mesh_filter_dataframe_regular_2d(): + """Test MeshFilter.get_pandas_dataframe with a 2D RegularMesh.""" + mesh = openmc.RegularMesh() + mesh.lower_left = [0, 0] + mesh.upper_right = [2, 3] + mesh.dimension = [2, 3] + + f = openmc.MeshFilter(mesh) + data_size = 2 * 3 + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'x') in df.columns + assert (mesh_key, 'y') in df.columns + # Should NOT have a z column for a 2D mesh + assert (mesh_key, 'z') not in df.columns + assert len(df) == data_size + + +def test_mesh_filter_dataframe_regular_1d(): + """Test MeshFilter.get_pandas_dataframe with a 1D RegularMesh.""" + mesh = openmc.RegularMesh() + mesh.lower_left = [0] + mesh.upper_right = [5] + mesh.dimension = [5] + + f = openmc.MeshFilter(mesh) + data_size = 5 + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'x') in df.columns + assert (mesh_key, 'y') not in df.columns + assert (mesh_key, 'z') not in df.columns + assert len(df) == data_size + assert list(df[(mesh_key, 'x')]) == [1, 2, 3, 4, 5] + + +def test_mesh_filter_dataframe_cylindrical(): + """Test MeshFilter.get_pandas_dataframe with a CylindricalMesh.""" + mesh = openmc.CylindricalMesh( + r_grid=[0.0, 1.0, 2.0], + phi_grid=[0.0, math.pi], + z_grid=[0.0, 5.0, 10.0] + ) + + f = openmc.MeshFilter(mesh) + nr, nphi, nz = mesh.dimension # 2, 1, 2 + data_size = nr * nphi * nz + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'r') in df.columns + assert (mesh_key, 'phi') in df.columns + assert (mesh_key, 'z') in df.columns + # Should NOT have x, y columns + assert (mesh_key, 'x') not in df.columns + assert (mesh_key, 'y') not in df.columns + assert len(df) == data_size + # r varies fastest + assert list(df[(mesh_key, 'r')][:nr]) == [1, 2] + + +def test_mesh_filter_dataframe_spherical(): + """Test MeshFilter.get_pandas_dataframe with a SphericalMesh.""" + mesh = openmc.SphericalMesh( + r_grid=[0.0, 1.0, 2.0, 3.0], + theta_grid=[0, math.pi], + phi_grid=[0, 2 * math.pi] + ) + + f = openmc.MeshFilter(mesh) + nr, ntheta, nphi = mesh.dimension # 3, 1, 1 + data_size = nr * ntheta * nphi + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'r') in df.columns + assert (mesh_key, 'theta') in df.columns + assert (mesh_key, 'phi') in df.columns + assert (mesh_key, 'x') not in df.columns + assert len(df) == data_size + + +def test_mesh_filter_dataframe_rectilinear(): + """Test MeshFilter.get_pandas_dataframe with a RectilinearMesh.""" + mesh = openmc.RectilinearMesh() + mesh.x_grid = [0.0, 1.0, 2.0] + mesh.y_grid = [0.0, 1.0, 2.0, 3.0] + mesh.z_grid = [0.0, 5.0] + + f = openmc.MeshFilter(mesh) + nx, ny, nz = mesh.dimension # 2, 3, 1 + data_size = nx * ny * nz + df = f.get_pandas_dataframe(data_size, stride=1) + + mesh_key = f'mesh {mesh.id}' + assert (mesh_key, 'x') in df.columns + assert (mesh_key, 'y') in df.columns + assert (mesh_key, 'z') in df.columns + assert len(df) == data_size