cherab.imas.ggd.UnstructGrid2D¶

class cherab.imas.ggd.UnstructGrid2D(vertices: ArrayLike, cells: NDArray[integer[Any]] | Sequence[Sequence[SupportsIndex] | NDArray[integer[Any]]], valid_data_mask: NDArray[bool] | Sequence[bool] | None = None, name: str = 'Cells', coordinate_system: 'cylindrical' | 'cartesian' = 'cylindrical')Source ¶

Bases: GGDGrid

Unstructured 2D grid object.

The grid cells are polygons. Vertices may be shared with neighbouring cells.

To use Raysect’s KDtree accelerator, each polygonal cell is triangulated.

Parameters:

vertices: ArrayLike¶: Array-like of shape (N, 2) containing coordinates of the polygon vertices.
cells: NDArray[integer[Any]] | Sequence[Sequence[SupportsIndex] | NDArray[integer[Any]]]¶: An (N, 4) integer array or a list/tuple of 1-D integer index arrays containing the vertex indices in clockwise or counterclockwise order for each polygonal cell (the starting vertex must not be included twice).
valid_data_mask: NDArray[bool] | Sequence[bool] | None = None¶: Boolean mask over the source face/data entries. Its number of True values must equal the number of cells retained by this grid. Data passed to plotting/interpolation may therefore be either source-sized or already compacted to the valid cells.
name: str = 'Cells'¶: Name of the grid, by default 'Cells'.
coordinate_system: 'cylindrical' | 'cartesian' = 'cylindrical'¶: Coordinate system of the grid, by default 'cylindrical'.

Methods

`interpolator`(grid_data[, fill_value, ...])	Return an `UnstructGridFunction2D` interpolator instance for the data defined on this grid.
`plot_mesh`([data, ax])	Plot the polygonal mesh grid geometry to a matplotlib figure.
`plot_triangle_mesh`([data, ax])	Plot the triangle mesh grid geometry to a matplotlib figure.
`subset`(indices[, name, valid_data_mask])	Create a subset UnstructGrid2D from this instance.
`vector_interpolator`(grid_vectors[, ...])	Return an `UnstructGridVectorFunction2D` interpolator instance for the vector data defined on this grid.

Attributes

`cell_area`	Cell areas as `(num_cell,)` array.
`cell_centre`	Coordinate of cell centres as `(num_cell, dimension)` array.
`cell_to_triangle_map`	Array of shape `(K, 2)` mapping every grid cell index to triangle IDs.
`cell_volume`	Cell volume as `(num_cell,)` array.
`cells`	List of `K` polygonal cells as 1-D integer index arrays.
`coordinate_system`	Coordinate system.
`dimension`	Grid dimension.
`mesh_extent`	Extent of the mesh.
`name`	Grid name.
`num_cell`	Number of grid cells.
`triangle_to_cell_map`	Array of shape `(M,)` mapping every triangle index to a grid cell ID.
`triangles`	Mesh triangles as `(M, 3)` array.
`valid_data_mask`	Boolean mask over source data entries retained by this grid.
`vertices`	Mesh vertex coordinates as `(N, 2)` array.

property vertices : NDArray[float64]Source ¶: Mesh vertex coordinates as (N, 2) array.

property cells : tuple[NDArray[int64], ...]Source ¶: List of K polygonal cells as 1-D integer index arrays.

property triangles : NDArray[int32]Source ¶: Mesh triangles as (M, 3) array.

property triangle_to_cell_map : NDArray[int32]Source ¶: Array of shape (M,) mapping every triangle index to a grid cell ID.

property cell_to_triangle_map : NDArray[int32]Source ¶

Array of shape (K, 2) mapping every grid cell index to triangle IDs.

The first column is the index of the first triangle forming the cell. The second column is the number of triangles forming the cell.

>>> itri, ntri = mesh.cell_to_triangle_map[icell]
>>> tri_cell = mesh.triangles[itri : itri + ntri]

property valid_data_mask : NDArray[bool]Source ¶: Boolean mask over source data entries retained by this grid.

subset(indices: Sequence[SupportsIndex] | NDArray[integer[Any]], name: str | None = None, *, valid_data_mask: NDArray[bool] | Sequence[bool] | None = None) → UnstructGrid2DSource ¶

Create a subset UnstructGrid2D from this instance.

Parameters:

indices: Sequence[SupportsIndex] | NDArray[integer[Any]]¶: Indices of the cells of the original grid in the subset.
valid_data_mask: NDArray[bool] | Sequence[bool] | None = None¶: Boolean array indicating which cells in the subset have valid data.
name: str | None = None¶: Name of the grid subset. Default is instance.name + " subset".

Returns:

UnstructGrid2D – Subset instance.

Raises:

ValueError – If the validity mask is not one-dimensional or does not select exactly one valid entry per subset cell.

interpolator(grid_data: NDArray[floating[Any]] | Sequence[float], fill_value: float = 0, *, interpolator_cache: 'none' | 'memory' | 'disk' = 'memory', interpolator_cache_dir: str | Path | None = None, interpolator_cache_namespace: str = 'ggd') → UnstructGridFunction2DSource ¶

Return an UnstructGridFunction2D interpolator instance for the data defined on this grid.

On the second and subsequent calls, the interpolator is created as an instance of the previously created interpolator sharing the same KDtree structure.

Parameters:

grid_data: NDArray[floating[Any]] | Sequence[float]¶: Array containing data in the grid cells.
fill_value: float = 0¶: Value returned outside the grid, by default 0.0.
interpolator_cache: 'none' | 'memory' | 'disk' = 'memory'¶: Cache mode for the interpolator, by default "memory". The cache mode is described in the InterpolatorCacheMode type alias.
interpolator_cache_dir: str | Path | None = None¶: Directory used when interpolator_cache="disk", by default None (uses the system cache directory, e.g., ~/.cache/cherab/imas/interpolators).
interpolator_cache_namespace: str = 'ggd'¶: Namespace prefix to avoid cache-key collisions, by default "ggd".

Returns:

UnstructGridFunction2D – Interpolator instance.

vector_interpolator(grid_vectors: NDArray[float64], fill_vector: Vector3D = Vector3D(0.0, 0.0, 0.0), *, interpolator_cache: 'none' | 'memory' | 'disk' = 'memory', interpolator_cache_dir: str | Path | None = None, interpolator_cache_namespace: str = 'ggd') → UnstructGridVectorFunction2DSource ¶

Return an UnstructGridVectorFunction2D interpolator instance for the vector data defined on this grid.

On the second and subsequent calls, the interpolator is created as an instance of the previously created interpolator sharing the same KDtree structure.

Parameters:

grid_vectors: NDArray[float64]¶: (3, K) Array containing 3D vectors in the grid cells.
fill_vector: Vector3D = Vector3D(0.0, 0.0, 0.0)¶: 3D vector returned outside the grid, by default Vector3D(0, 0, 0).
interpolator_cache: 'none' | 'memory' | 'disk' = 'memory'¶: Cache mode for the interpolator, by default "memory". The cache mode is described in the InterpolatorCacheMode type alias.
interpolator_cache_dir: str | Path | None = None¶: Directory used when interpolator_cache="disk", by default None (uses the system cache directory, e.g., ~/.cache/cherab/imas/interpolators).
interpolator_cache_namespace: str = 'ggd'¶: Namespace prefix to avoid cache-key collisions, by default "ggd".

Returns:

UnstructGridVectorFunction2D – Interpolator instance.

plot_triangle_mesh(data: NDArray[floating[Any]] | Sequence[float] | None = None, ax: Axes | None = None, **grid_styles) → AxesSource ¶

Plot the triangle mesh grid geometry to a matplotlib figure.

Parameters:

data: NDArray[floating[Any]] | Sequence[float] | None = None¶: Data array defined on the polygonal mesh.
ax: Axes | None = None¶: Matplotlib axes to plot on. If None, a new figure and axes are created.
**grid_styles¶: Styles for the grid lines and faces, by default {"facecolor": "none", "edgecolor": "b", "linewidth": 0.25}.

Returns:

Axes – The matplotlib axes with the plotted mesh.

property cell_area : NDArray[float64]Source ¶: Cell areas as (num_cell,) array.

property cell_centre : NDArray[float64]Source ¶: Coordinate of cell centres as (num_cell, dimension) array.

property cell_volume : NDArray[float64]Source ¶: Cell volume as (num_cell,) array.

property coordinate_system : strSource ¶: Coordinate system.

property dimension : intSource ¶: Grid dimension.

property mesh_extent : dict[str, float]Source ¶

Extent of the mesh.

A dictionary with xmin, xmax, ymin and ymax, … keys.

property name : strSource ¶: Grid name.

property num_cell : intSource ¶: Number of grid cells.

plot_mesh(data: NDArray[floating[Any]] | Sequence[float] | None = None, ax: Axes | None = None, **grid_styles) → AxesSource ¶

Plot the polygonal mesh grid geometry to a matplotlib figure.

Parameters:

data: NDArray[floating[Any]] | Sequence[float] | None = None¶: Data array defined on the polygonal mesh.
ax: Axes | None = None¶: Matplotlib axes to plot on. If None, a new figure and axes are created.
**grid_styles¶: Styles for the grid lines and faces, by default {"facecolor": "none", "edgecolor": "b", "linewidth": 0.25}. If data is provided, the styles are not applied to the grid lines and faces to allow the data colormap to be visible.

Returns:

Axes – The matplotlib axes with the plotted mesh.