finam.data.StructuredGrid#

class finam.data.StructuredGrid[source]#

Bases: Grid

Abstract structured grid specification.

Attributes:

axes: list of np.ndarray: Axes of the structured grid (xyz order, all increase).
axes_attributes: list of dict: Axes attributes following the CF convention (xyz order).
axes_increase: list of bool: False to indicate a bottom up axis (xyz order).
axes_names: list of str: Axes names (xyz order).
axes_reversed: bool: Indicate reversed axes order for the associated data (zyx order).
cell_axes: list of np.ndarray: Axes of the cell centers (xyz order, all increase).
cell_centers: np.ndarray: Grid cell centers in given order starting top left corner.
cell_count: int: Number of grid cells.
cell_node_counts: np.ndarray: Node count for each cell.
cell_types: np.ndarray: Cell types.
cells: np.ndarray: Cell nodes in ESMF format.
cells_connectivity: np.ndarray: Cells connectivity in ESMF format (list of node IDs).
cells_definition: np.ndarray: Cell definition in VTK format (list of number of nodes with node IDs).
cells_offset: np.ndarray: The location of the start of each cell in cells_connectivity.
crs: The coordinate reference system.
data_axes: list of np.ndarray: Axes as used for the data matrix.
data_axes_names: list of str: Axes names of the data matrix.
data_location: Location of the associated data (either CELLS or POINTS).
data_points: Points of the associated data (either cell_centers or points).
data_shape: tuple: Shape of the associated data matrix.
data_size: int: Size of the associated data.
dim: int: Dimension of the grid or data.
dims: tuple: Axes lengths (xyz order).
mesh_dim: int: Maximal cell dimension.
name: Grid name.
order: str: Point, cell and data order (C- or Fortran-like).
point_count: int: Number of grid points.
points: np.ndarray: Grid points in given order starting top left corner.

Methods

`compatible_with`(other[, check_location])	Check for compatibility with other Grid.
`copy`([deep])	Copy of this grid.
`export_vtk`(path[, data, cell_data, ...])	Export grid and data to a VTK file.
`from_canonical`(data)	Convert canonical data to grid specific form.
`get_transform_to`(other)	Get transformation for compatible grids.
`to_canonical`(data)	Convert grid specific data to canonical form.

abstract property dims#

Axes lengths (xyz order).

Type:: tuple

abstract property axes#

Axes of the structured grid (xyz order, all increase).

Type:: list of np.ndarray

abstract property axes_reversed#

Indicate reversed axes order for the associated data (zyx order).

Type:: bool

abstract property axes_increase#

False to indicate a bottom up axis (xyz order).

Type:: list of bool

abstract property order#

Point, cell and data order (C- or Fortran-like).

Type:: str

property point_count#

Number of grid points.

Type:: int

property cell_count#

Number of grid cells.

Type:: int

property cell_axes#

Axes of the cell centers (xyz order, all increase).

Type:: list of np.ndarray

property points#

Grid points in given order starting top left corner.

Type:: np.ndarray

property cells#

Cell nodes in ESMF format.

Type:: np.ndarray

property cell_centers#

Grid cell centers in given order starting top left corner.

Type:: np.ndarray

property mesh_dim#

Maximal cell dimension.

Type:: int

property cell_types#

Cell types.

Type:: np.ndarray

property data_axes#

Axes as used for the data matrix.

Type:: list of np.ndarray

property data_axes_names#

Axes names of the data matrix.

Type:: list of str

property data_shape#

Shape of the associated data matrix.

Type:: tuple

compatible_with(other, check_location=True)[source]#

Check for compatibility with other Grid.

Parameters:

other (instance of Grid) – Other grid to compatibility with.
check_location (bool, optional) – Whether to check location for equality, by default True

Returns:

compatibility

Return type:

bool

export_vtk(path, data=None, cell_data=None, point_data=None, field_data=None, mesh_type='structured')[source]#

Export grid and data to a VTK file.

Parameters:

path (pathlike) – File path. Suffix will be replaced according to mesh type (.vtr, .vtu)
data (dict or None, optional) – Data in the corresponding shape given by name, by default None
cell_data (dict or None, optional) – Additional cell data, by default None
point_data (dict or None, optional) – Additional point data, by default None
field_data (dict or None, optional) – Additional field data, by default None
mesh_type (str, optional) – Mesh type (“structured”/”unstructured”), by default “structured”

Raises:

ValueError – If mesh type is not supported.

to_canonical(data)[source]#

Convert grid specific data to canonical form.

Canonical means, that data axis are in xyz order and following increasing axis values.

Parameters:: data (arraylike) – Data to convert.
Returns:: Canonical Data.
Return type:: arraylike
Raises:: ValueError – When data has wrong shape.

abstract property axes_attributes#

Axes attributes following the CF convention (xyz order).

Type:: list of dict

abstract property axes_names#

Axes names (xyz order).

Type:: list of str

property cell_node_counts#

Node count for each cell.

Type:: np.ndarray

property cells_connectivity#

Cells connectivity in ESMF format (list of node IDs).

Type:: np.ndarray

property cells_definition#

Cell definition in VTK format (list of number of nodes with node IDs).

Type:: np.ndarray

property cells_offset#

The location of the start of each cell in cells_connectivity.

Type:: np.ndarray

copy(deep=False)#

Copy of this grid.

Parameters:: deep (bool, optional) – If false, only a shallow copy is returned to save memory, by default False
Returns:: The grid copy.
Return type:: Grid

abstract property crs#: The coordinate reference system.

abstract property data_location#: Location of the associated data (either CELLS or POINTS).

property data_points#: Points of the associated data (either cell_centers or points).

property data_size#

Size of the associated data.

Type:: int

abstract property dim#

Dimension of the grid or data.

Type:: int

from_canonical(data)[source]#

Convert canonical data to grid specific form.

Canonical means, that data axis are in xyz order and following increasing axis values.

Parameters:: data (arraylike) – Data to convert.
Returns:: Grid specific Data.
Return type:: arraylike
Raises:: ValueError – When data has wrong shape.

property name#: Grid name.

valid_locations = (Location.CELLS, Location.POINTS)#

Valid locations for the grid.

Type:: tuple

get_transform_to(other)[source]#

Get transformation for compatible grids.

Parameters:: other (instance of Grid) – Other grid to compatibility with.
Returns:: data transformation
Return type:: callable