Source code for openmc.universe

from collections import OrderedDict
from collections.abc import Iterable
from copy import copy, deepcopy
from numbers import Real
import random

import numpy as np

import openmc
import openmc.checkvalue as cv
from .mixin import IDManagerMixin
from .plots import _SVG_COLORS


[docs]class Universe(IDManagerMixin): """A collection of cells that can be repeated. Parameters ---------- universe_id : int, optional Unique identifier of the universe. If not specified, an identifier will automatically be assigned name : str, optional Name of the universe. If not specified, the name is the empty string. cells : Iterable of openmc.Cell, optional Cells to add to the universe. By default no cells are added. Attributes ---------- id : int Unique identifier of the universe name : str Name of the universe cells : collections.OrderedDict Dictionary whose keys are cell IDs and values are :class:`Cell` instances volume : float Volume of the universe in cm^3. This can either be set manually or calculated in a stochastic volume calculation and added via the :meth:`Universe.add_volume_information` method. bounding_box : 2-tuple of numpy.array Lower-left and upper-right coordinates of an axis-aligned bounding box of the universe. """ next_id = 1 used_ids = set() def __init__(self, universe_id=None, name='', cells=None): # Initialize Cell class attributes self.id = universe_id self.name = name self._volume = None self._atoms = {} # Keys - Cell IDs # Values - Cells self._cells = OrderedDict() if cells is not None: self.add_cells(cells) def __repr__(self): string = 'Universe\n' string += '{: <16}=\t{}\n'.format('\tID', self._id) string += '{: <16}=\t{}\n'.format('\tName', self._name) string += '{: <16}=\t{}\n'.format('\tCells', list(self._cells.keys())) return string @property def name(self): return self._name @property def cells(self): return self._cells @property def volume(self): return self._volume @property def bounding_box(self): regions = [c.region for c in self.cells.values() if c.region is not None] if regions: return openmc.Union(regions).bounding_box else: # Infinite bounding box return openmc.Intersection([]).bounding_box @name.setter def name(self, name): if name is not None: cv.check_type('universe name', name, str) self._name = name else: self._name = '' @volume.setter def volume(self, volume): if volume is not None: cv.check_type('universe volume', volume, Real) self._volume = volume
[docs] @classmethod def from_hdf5(cls, group, cells): """Create universe from HDF5 group Parameters ---------- group : h5py.Group Group in HDF5 file cells : dict Dictionary mapping cell IDs to instances of :class:`openmc.Cell`. Returns ------- openmc.Universe Universe instance """ universe_id = int(group.name.split('/')[-1].lstrip('universe ')) cell_ids = group['cells'][()] # Create this Universe universe = cls(universe_id) # Add each Cell to the Universe for cell_id in cell_ids: universe.add_cell(cells[cell_id]) return universe
[docs] def add_volume_information(self, volume_calc): """Add volume information to a universe. Parameters ---------- volume_calc : openmc.VolumeCalculation Results from a stochastic volume calculation """ if volume_calc.domain_type == 'universe': if self.id in volume_calc.volumes: self._volume = volume_calc.volumes[self.id].n self._atoms = volume_calc.atoms[self.id] else: raise ValueError('No volume information found for this universe.') else: raise ValueError('No volume information found for this universe.')
[docs] def find(self, point): """Find cells/universes/lattices which contain a given point Parameters ---------- point : 3-tuple of float Cartesian coordinates of the point Returns ------- list Sequence of universes, cells, and lattices which are traversed to find the given point """ p = np.asarray(point) for cell in self._cells.values(): if p in cell: if cell.fill_type in ('material', 'distribmat', 'void'): return [self, cell] elif cell.fill_type == 'universe': if cell.translation is not None: p -= cell.translation if cell.rotation is not None: p[:] = cell.rotation_matrix.dot(p) return [self, cell] + cell.fill.find(p) else: return [self, cell] + cell.fill.find(p) return []
[docs] def plot(self, origin=(0., 0., 0.), width=(1., 1.), pixels=(200, 200), basis='xy', color_by='cell', colors=None, seed=None, **kwargs): """Display a slice plot of the universe. To display or save the plot, call :func:`matplotlib.pyplot.show` or :func:`matplotlib.pyplot.savefig`. In a Jupyter notebook, enabling the matplotlib inline backend will show the plot inline. Parameters ---------- origin : Iterable of float Coordinates at the origin of the plot width : Iterable of float Width of the plot in each basis direction pixels : Iterable of int Number of pixels to use in each basis direction basis : {'xy', 'xz', 'yz'} The basis directions for the plot color_by : {'cell', 'material'} Indicate whether the plot should be colored by cell or by material colors : dict Assigns colors to specific materials or cells. Keys are instances of :class:`Cell` or :class:`Material` and values are RGB 3-tuples, RGBA 4-tuples, or strings indicating SVG color names. Red, green, blue, and alpha should all be floats in the range [0.0, 1.0], for example: .. code-block:: python # Make water blue water = openmc.Cell(fill=h2o) universe.plot(..., colors={water: (0., 0., 1.)) seed : hashable object or None Hashable object which is used to seed the random number generator used to select colors. If None, the generator is seeded from the current time. **kwargs All keyword arguments are passed to :func:`matplotlib.pyplot.imshow`. Returns ------- matplotlib.image.AxesImage Resulting image """ import matplotlib.pyplot as plt # Seed the random number generator if seed is not None: random.seed(seed) if colors is None: # Create default dictionary if none supplied colors = {} else: # Convert to RGBA if necessary colors = copy(colors) for obj, color in colors.items(): if isinstance(color, str): if color.lower() not in _SVG_COLORS: raise ValueError("'{}' is not a valid color." .format(color)) colors[obj] = [x/255 for x in _SVG_COLORS[color.lower()]] + [1.0] elif len(color) == 3: colors[obj] = list(color) + [1.0] if basis == 'xy': x_min = origin[0] - 0.5*width[0] x_max = origin[0] + 0.5*width[0] y_min = origin[1] - 0.5*width[1] y_max = origin[1] + 0.5*width[1] elif basis == 'yz': # The x-axis will correspond to physical y and the y-axis will # correspond to physical z x_min = origin[1] - 0.5*width[0] x_max = origin[1] + 0.5*width[0] y_min = origin[2] - 0.5*width[1] y_max = origin[2] + 0.5*width[1] elif basis == 'xz': # The y-axis will correspond to physical z x_min = origin[0] - 0.5*width[0] x_max = origin[0] + 0.5*width[0] y_min = origin[2] - 0.5*width[1] y_max = origin[2] + 0.5*width[1] # Determine locations to determine cells at x_coords = np.linspace(x_min, x_max, pixels[0], endpoint=False) + \ 0.5*(x_max - x_min)/pixels[0] y_coords = np.linspace(y_max, y_min, pixels[1], endpoint=False) - \ 0.5*(y_max - y_min)/pixels[1] # Initialize output image in RGBA format. Flip the pixels from # traditional (x, y) to (y, x) used in graphics. img = np.zeros((pixels[1], pixels[0], 4)) for i, x in enumerate(x_coords): for j, y in enumerate(y_coords): if basis == 'xy': path = self.find((x, y, origin[2])) elif basis == 'yz': path = self.find((origin[0], x, y)) elif basis == 'xz': path = self.find((x, origin[1], y)) if len(path) > 0: try: if color_by == 'cell': obj = path[-1] elif color_by == 'material': if path[-1].fill_type == 'material': obj = path[-1].fill else: continue except AttributeError: continue if obj not in colors: colors[obj] = (random.random(), random.random(), random.random(), 1.0) img[j, i, :] = colors[obj] # Display image return plt.imshow(img, extent=(x_min, x_max, y_min, y_max), interpolation='nearest', **kwargs)
[docs] def add_cell(self, cell): """Add a cell to the universe. Parameters ---------- cell : openmc.Cell Cell to add """ if not isinstance(cell, openmc.Cell): msg = 'Unable to add a Cell to Universe ID="{0}" since "{1}" is not ' \ 'a Cell'.format(self._id, cell) raise TypeError(msg) cell_id = cell.id if cell_id not in self._cells: self._cells[cell_id] = cell
[docs] def add_cells(self, cells): """Add multiple cells to the universe. Parameters ---------- cells : Iterable of openmc.Cell Cells to add """ if not isinstance(cells, Iterable): msg = 'Unable to add Cells to Universe ID="{0}" since "{1}" is not ' \ 'iterable'.format(self._id, cells) raise TypeError(msg) for cell in cells: self.add_cell(cell)
[docs] def remove_cell(self, cell): """Remove a cell from the universe. Parameters ---------- cell : openmc.Cell Cell to remove """ if not isinstance(cell, openmc.Cell): msg = 'Unable to remove a Cell from Universe ID="{0}" since "{1}" is ' \ 'not a Cell'.format(self._id, cell) raise TypeError(msg) # If the Cell is in the Universe's list of Cells, delete it self._cells.pop(cell.id, None)
[docs] def clear_cells(self): """Remove all cells from the universe.""" self._cells.clear()
[docs] def get_nuclides(self): """Returns all nuclides in the universe Returns ------- nuclides : list of str List of nuclide names """ nuclides = [] # Append all Nuclides in each Cell in the Universe to the dictionary for cell in self.cells.values(): for nuclide in cell.get_nuclides(): if nuclide not in nuclides: nuclides.append(nuclide) return nuclides
[docs] def get_nuclide_densities(self): """Return all nuclides contained in the universe Returns ------- nuclides : collections.OrderedDict Dictionary whose keys are nuclide names and values are 2-tuples of (nuclide, density) """ nuclides = OrderedDict() if self._atoms is not None: volume = self.volume for name, atoms in self._atoms.items(): nuclide = openmc.Nuclide(name) density = 1.0e-24 * atoms.n/volume # density in atoms/b-cm nuclides[name] = (nuclide, density) else: raise RuntimeError( 'Volume information is needed to calculate microscopic cross ' 'sections for universe {}. This can be done by running a ' 'stochastic volume calculation via the ' 'openmc.VolumeCalculation object'.format(self.id)) return nuclides
[docs] def get_all_cells(self, memo=None): """Return all cells that are contained within the universe Returns ------- cells : collections.OrderedDict Dictionary whose keys are cell IDs and values are :class:`Cell` instances """ cells = OrderedDict() if memo and self in memo: return cells if memo is not None: memo.add(self) # Add this Universe's cells to the dictionary cells.update(self._cells) # Append all Cells in each Cell in the Universe to the dictionary for cell in self._cells.values(): cells.update(cell.get_all_cells(memo)) return cells
[docs] def get_all_materials(self, memo=None): """Return all materials that are contained within the universe Returns ------- materials : collections.OrderedDict Dictionary whose keys are material IDs and values are :class:`Material` instances """ materials = OrderedDict() # Append all Cells in each Cell in the Universe to the dictionary cells = self.get_all_cells(memo) for cell in cells.values(): materials.update(cell.get_all_materials(memo)) return materials
[docs] def get_all_universes(self): """Return all universes that are contained within this one. Returns ------- universes : collections.OrderedDict Dictionary whose keys are universe IDs and values are :class:`Universe` instances """ # Append all Universes within each Cell to the dictionary universes = OrderedDict() for cell in self.get_all_cells().values(): universes.update(cell.get_all_universes()) return universes
[docs] def clone(self, clone_materials=True, clone_regions=True, memo=None): """Create a copy of this universe with a new unique ID, and clones all cells within this universe. Parameters ---------- clone_materials : bool Whether to create separates copies of the materials filling cells contained in this universe. clone_regions : bool Whether to create separates copies of the regions bounding cells contained in this universe. memo : dict or None A nested dictionary of previously cloned objects. This parameter is used internally and should not be specified by the user. Returns ------- clone : openmc.Universe The clone of this universe """ if memo is None: memo = {} # If no nemoize'd clone exists, instantiate one if self not in memo: clone = deepcopy(self) clone.id = None # Clone all cells for the universe clone clone._cells = OrderedDict() for cell in self._cells.values(): clone.add_cell(cell.clone(clone_materials, clone_regions, memo)) # Memoize the clone memo[self] = clone return memo[self]
[docs] def create_xml_subelement(self, xml_element, memo=None): """Add the universe xml representation to an incoming xml element Parameters ---------- xml_element : xml.etree.ElementTree.Element XML element to be added to memo : set or None A set of object id's representing geometry entities already written to the xml_element. This parameter is used internally and should not be specified by users. Returns ------- None """ # Iterate over all Cells for cell in self._cells.values(): # If the cell was already written, move on if memo and cell in memo: continue if memo is not None: memo.add(cell) # Create XML subelement for this Cell cell_element = cell.create_xml_subelement(xml_element, memo) # Append the Universe ID to the subelement and add to Element cell_element.set("universe", str(self._id)) xml_element.append(cell_element)
def _determine_paths(self, path='', instances_only=False): """Count the number of instances for each cell in the universe, and record the count in the :attr:`Cell.num_instances` properties.""" univ_path = path + 'u{}'.format(self.id) for cell in self.cells.values(): cell_path = '{}->c{}'.format(univ_path, cell.id) fill = cell._fill fill_type = cell.fill_type # If universe-filled, recursively count cells in filling universe if fill_type == 'universe': fill._determine_paths(cell_path + '->', instances_only) # If lattice-filled, recursively call for all universes in lattice elif fill_type == 'lattice': latt = fill # Count instances in each universe in the lattice for index in latt._natural_indices: latt_path = '{}->l{}({})->'.format( cell_path, latt.id, ",".join(str(x) for x in index)) univ = latt.get_universe(index) univ._determine_paths(latt_path, instances_only) else: if fill_type == 'material': mat = fill elif fill_type == 'distribmat': mat = fill[cell._num_instances] else: mat = None if mat is not None: mat._num_instances += 1 if not instances_only: mat._paths.append('{}->m{}'.format(cell_path, mat.id)) # Append current path cell._num_instances += 1 if not instances_only: cell._paths.append(cell_path)