UnstructuredData

class subsurface.structs.base_structures.unstructured_data.UnstructuredData(data: xarray.core.dataset.Dataset, cells_attr_name: str = 'cell_attrs', vertex_attr_name: str = 'vertex_attrs')

Bases: object

Attributes Summary

attributes
attributes_to_dict
cells
cells_attr_name
extent
n_elements
n_points
n_vertex_per_element
points_attributes
points_attributes_to_dict
vertex
vertex_attr_name	Primary structure definition for unstructured data

Methods Summary

create_default_cells_arg(cells, n_vertex)
data_array_attributes_from_raw_data(…)
from_array(vertex, cells[, cells_attr, …])	Constructor of UnstructuredData from arrays or pandas DataFrames.
from_data_arrays_dict(xarray_dict[, coords, …])
from_raw_data(raw_data[, coords, …])
raw_attributes_to_dict_data_arrays(…)
to_binary([order])
to_xarray()
vertex_and_cells_arrays_to_data_array(cells, …)

Attributes Documentation

attributes

attributes_to_dict

cells

cells_attr_name: str = 'cell_attrs'

extent

n_elements

n_points

n_vertex_per_element

points_attributes

points_attributes_to_dict

vertex

vertex_attr_name: str = 'vertex_attrs'

Primary structure definition for unstructured data

data

Data structure where we store

Type

xarray.Dataset

Parameters

ds (xarray.Dataset) – Directly a dataset with the expected structured. This arg is specially thought for loading data from disk

Notes

Depending on the shape of edge the following unstructured elements can be created:

• cells NDArray[(Any, 0), IntX] or NDArray[(Any, 1), IntX] -> Point cloud. E.g. Outcrop scan with lidar

• cells NDArray[(Any, 2), IntX] -> Lines. E.g. Borehole

• cells NDArray[(Any, 3), IntX] -> Mesh. E.g surface-DEM Topography

• cells NDArray[(Any, 4), IntX]

  • -> tetrahedron

  • -> quadrilateral (or tetragon) UNSUPPORTED?

• cells NDArray[(Any, 8), IntX] -> Hexahedron: Unstructured grid/Prisms

Methods Documentation

classmethod create_default_cells_arg(cells: Literal[points, lines], n_vertex: int) → numpy.ndarray

classmethod data_array_attributes_from_raw_data(raw_data: Union[None, pandas.core.frame.DataFrame], dims: List[str], n_rows: int) → xarray.core.dataarray.DataArray

classmethod from_array(vertex: numpy.ndarray, cells: Union[numpy.ndarray, Literal[lines, points]], cells_attr: Union[None, pandas.core.frame.DataFrame, Dict[str, xarray.core.dataarray.DataArray]] = None, vertex_attr: Union[None, pandas.core.frame.DataFrame, Dict[str, xarray.core.dataarray.DataArray]] = None, coords: Optional[Mapping[Hashable, Any]] = None, xarray_attributes: Optional[Mapping[Hashable, Any]] = None, default_cells_attr_name: str = 'cell_attrs', default_points_attr_name: str = 'vertex_attrs', attributes: Union[None, pandas.core.frame.DataFrame, Dict[str, xarray.core.dataarray.DataArray]] = None)

Constructor of UnstructuredData from arrays or pandas DataFrames.

Parameters

• vertex (np.ndarray) – NDArray[(Any, 3), FloatX]: XYZ point data

• cells (Union[np.ndarray, Literal["lines", "points"]]) – NDArray[(Any, …), IntX]: Combination of vertex that create different geometric elements. If str use default values for either points or lines

• (Union[None (vertex_attr) – Number associated to an element

• pd.DataFrame – Number associated to an element

• Dict[str – Number associated to an element

• xr.DataArray]]] – Number associated to an element

• (Union[None – Number associated to points

• pd.DataFrame – Number associated to points

• Dict[str – Number associated to points

• xr.DataArray]]] – Number associated to points

• coords –

• xarray_attributes –

• attributes –

• default_cells_attr_name –

• default_points_attr_name –

Returns:

classmethod from_data_arrays_dict(xarray_dict: Dict[str, xarray.core.dataarray.DataArray], coords: Optional[Mapping[Hashable, Any]] = None, xarray_attributes: Optional[Mapping[Hashable, Any]] = None, default_cells_attributes_name='cell_attrs', default_points_attributes_name='vertex_attrs')

classmethod from_raw_data(raw_data: subsurface.reader.readers_data.RawDataUnstructured, coords: Optional[Mapping[Hashable, Any]] = None, xarray_attributes: Optional[Mapping[Hashable, Any]] = None, default_cells_attributes_name: str = 'cell_attrs', default_points_attributes_name: str = 'vertex_attrs')

classmethod raw_attributes_to_dict_data_arrays(default_attributes_name: str, n_items: int, dims: List[str], raw_attributes: Union[None, pandas.core.frame.DataFrame, Dict[str, xarray.core.dataarray.DataArray]]) → Dict[str, xarray.core.dataarray.DataArray]

to_binary(order='F')

to_xarray()

classmethod vertex_and_cells_arrays_to_data_array(cells: Union[numpy.ndarray, Literal[lines, points]], vertex: numpy.ndarray)