hyperion.grid.VoronoiGrid¶

class
hyperion.grid.
VoronoiGrid
(*args, **kwargs)¶ A voronoi mesh.
The mesh can be initialized by passing the x, y, and z coordinates of the points used to compute the mesh:
>>> grid = Voronoi(x, y, z)
where
x
,y
, andz
are 1d sequences of point positions.VoronoiGrid
objects may contain multiple quantities (e.g. density, specific energy). To access these, you can specify the name of the quantity as an item:>>> grid['density']
which is no longer a
VoronoiGrid
object, but aVoronoiGridView
object. When setting this for the first time, this can be set either to anotherVoronoiGridView
object, an external h5py link, or an empty list. For example, the following should work:>>> grid['density_new'] = grid['density']
VoronoiGridView
objects allow the specific dust population to be selected as an index:>>> grid['density'][0]
Which is also a
VoronoiGridView
object. The data can then be accessed with thearray
attribute:>>> grid['density'][0].array
which is a 1d array of the requested quantity.
Methods
read
(group[, quantities])Read the geometry and physical quantities from an voronoi grid read_geometry
(group)Read in geometry information from a cartesian grid read_quantities
(group[, quantities])Read in physical quantities from a cartesian grid write
(group[, quantities, copy, …])Write out the voronoi grid write_single_array
(group, name, array[, …])Write out a single quantity, checking for consistency with geometry add_derived_quantity
(name, function)evaluate_function_average
(func[, n_samples, …])Evaluate the average of a function inside each cell using randomly sampled points inside each cell. Methods (detail)

read
(group, quantities='all')¶ Read the geometry and physical quantities from an voronoi grid
Parameters: group : h5py.Group
The HDF5 group to read the grid from. This group should contain groups named ‘Geometry’ and ‘Quantities’.
quantities : ‘all’ or list
Which physical quantities to read in. Use ‘all’ to read in all quantities or a list of strings to read only specific quantities.

read_geometry
(group)¶ Read in geometry information from a cartesian grid
Parameters: group : h5py.Group
The HDF5 group to read the grid geometry from.

read_quantities
(group, quantities='all')¶ Read in physical quantities from a cartesian grid
Parameters: group : h5py.Group
The HDF5 group to read the grid quantities from
quantities : ‘all’ or list
Which physical quantities to read in. Use ‘all’ to read in all quantities or a list of strings to read only specific quantities.

write
(group, quantities='all', copy=True, absolute_paths=False, compression=True, wall_dtype=<type 'float'>, physics_dtype=<type 'float'>)¶ Write out the voronoi grid
Parameters: group : h5py.Group
The HDF5 group to write the grid to
quantities : ‘all’ or list
Which physical quantities to write out. Use ‘all’ to write out all quantities or a list of strings to write only specific quantities.
copy : bool
Whether to copy external links, or leave them as links.
absolute_paths : bool
If copy is False, then this indicates whether to use absolute or relative paths for links.
compression : bool
Whether to compress the arrays in the HDF5 file
wall_dtype : type
The datatype to use to write the wall positions (ignored for this kind of grid)
physics_dtype : type
The datatype to use to write the physical quantities

write_single_array
(group, name, array, copy=True, absolute_paths=False, compression=True, physics_dtype=<type 'float'>)¶ Write out a single quantity, checking for consistency with geometry
Parameters: group : h5py.Group
The HDF5 group to write the grid to
name : str
The name of the array in the group
array : np.ndarray
The array to write out
copy : bool
Whether to copy external links, or leave them as links.
absolute_paths : bool
If copy is False, then this indicates whether to use absolute or relative paths for links.
compression : bool
Whether to compress the arrays in the HDF5 file
wall_dtype : type
The datatype to use to write the wall positions
physics_dtype : type
The datatype to use to write the physical quantities

add_derived_quantity
(name, function)¶

evaluate_function_average
(func, n_samples=None, min_cell_samples=None)¶ Evaluate the average of a function inside each cell using randomly sampled points inside each cell.
Note
This feature is still experimental, use with caution
Parameters: func : function
The function to evaluate in each cell. This should take three 1d arrays of
x
,y
, andz
and return a 1d array of values.n_samples : int
The total number of points to sample within the domain. Points will be uniformly sampled in each Voronoi cell so that at least
n_samples
total points will be produced. Each cell will contain a number of samples proportional to its volume (but at leastmin_cell_samples
points will always be sampled in each cell).min_cell_samples : int
The minimum number of samples per cell.


class
hyperion.grid.
VoronoiGridView
(grid, quantity)¶ Methods
append
(grid)Used to append quantities from another grid add
(grid)Used to add quantities from another grid Methods (detail)

append
(grid)¶ Used to append quantities from another grid
Parameters: grid : 1D Numpy array or VoronoiGridView instance
The grid to copy the quantity from

add
(grid)¶ Used to add quantities from another grid
Parameters: grid : 1D Numpy array or VoronoiGridView instance
The grid to copy the quantity from
