Typing

Type aliases for annotating code that uses PyVista.

Added in version 0.50: The pyvista.typing module.

Deprecated since version 0.50: Accessing these aliases from pyvista, for example pyvista.ColorLike, is deprecated. Use pyvista.typing.ColorLike instead.

Deprecated since version 0.50: pyvista.Number, pyvista.NumberType and pyvista.NumpyArray are deprecated. Use float, a TypeVar and numpy.typing.NDArray instead.

Deprecated since version 0.50: pyvista.ArrayLike, pyvista.MatrixLike and pyvista.VectorLike are deprecated. Use the Float, Int or Bool array-like types instead, for example VectorLikeFloat in place of VectorLike[float].

Numeric Array-Like Types

Each array-like accepts NumPy arrays and sequences of one kind of value. As in Python type hints, Float means float, which also accepts int and bool, so the Float types accept integer and boolean arrays too; likewise the Int types accept boolean arrays. A sequence holds either Python values or NumPy scalars, not a mix of both, and a lone scalar or zero-dimensional array is not array-like. Complex, string, and object arrays are not included; annotate an input that accepts them as NDArray[Any] | Sequence[Any].

pyvista.typing.VectorLikeFloat

One-dimensional array-like object with numerical values.

Accepts NumPy arrays of numpy.floating, numpy.integer or numpy.bool dtype, and sequences of float, int and bool values or of NumPy scalars of those dtypes.

Includes sequences and one-dimensional NumPy arrays.

VectorLikeFloat = collections.abc.Sequence[float] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]

pyvista.typing.VectorLikeInt

One-dimensional array-like object with integer values.

Accepts NumPy arrays of numpy.integer or numpy.bool dtype, and sequences of int and bool values or of NumPy scalars of those dtypes. Floating values are not included.

Includes sequences and one-dimensional NumPy arrays.

VectorLikeInt = collections.abc.Sequence[int] | collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]]

pyvista.typing.VectorLikeBool

One-dimensional array-like object with boolean values.

Accepts NumPy arrays of numpy.bool dtype and sequences of bool values or of numpy.bool scalars only. Integer and floating values are not included.

Includes sequences and one-dimensional NumPy arrays.

VectorLikeBool = collections.abc.Sequence[bool] | collections.abc.Sequence[numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.bool]]

pyvista.typing.MatrixLikeFloat

Two-dimensional array-like object with numerical values.

Accepts NumPy arrays of numpy.floating, numpy.integer or numpy.bool dtype, and sequences of float, int and bool values or of NumPy scalars of those dtypes.

Includes sequences of vectors and two-dimensional NumPy arrays.

MatrixLikeFloat = collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]

pyvista.typing.MatrixLikeInt

Two-dimensional array-like object with integer values.

Accepts NumPy arrays of numpy.integer or numpy.bool dtype, and sequences of int and bool values or of NumPy scalars of those dtypes. Floating values are not included.

Includes sequences of vectors and two-dimensional NumPy arrays.

MatrixLikeInt = collections.abc.Sequence[collections.abc.Sequence[int]] | collections.abc.Sequence[collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.integer | numpy.bool]]

pyvista.typing.MatrixLikeBool

Two-dimensional array-like object with boolean values.

Accepts NumPy arrays of numpy.bool dtype and sequences of bool values or of numpy.bool scalars only. Integer and floating values are not included.

Includes sequences of vectors and two-dimensional NumPy arrays.

MatrixLikeBool = collections.abc.Sequence[collections.abc.Sequence[bool]] | collections.abc.Sequence[collections.abc.Sequence[numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.bool]]

pyvista.typing.ArrayLikeFloat

Any-dimensional array-like object with numerical values.

Accepts NumPy arrays of numpy.floating, numpy.integer or numpy.bool dtype, and sequences of float, int and bool values or of NumPy scalars of those dtypes.

Includes NumPy arrays and sequences nested up to four deep. Scalar values are not included.

ArrayLikeFloat = collections.abc.Sequence[float | collections.abc.Sequence[float] | collections.abc.Sequence[float | collections.abc.Sequence[float]] | collections.abc.Sequence[float | collections.abc.Sequence[float] | collections.abc.Sequence[float | collections.abc.Sequence[float]]]] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool]]] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool | NDArray[numpy.floating | numpy.integer | numpy.bool]]]]] | numpy.ndarray[tuple[int, typing.Unpack[tuple[int, ...]]], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]

pyvista.typing.ArrayLikeInt

Any-dimensional array-like object with integer values.

Accepts NumPy arrays of numpy.integer or numpy.bool dtype, and sequences of int and bool values or of NumPy scalars of those dtypes. Floating values are not included.

Includes NumPy arrays and sequences nested up to four deep. Scalar values are not included.

ArrayLikeInt = collections.abc.Sequence[int | collections.abc.Sequence[int] | collections.abc.Sequence[int | collections.abc.Sequence[int]] | collections.abc.Sequence[int | collections.abc.Sequence[int] | collections.abc.Sequence[int | collections.abc.Sequence[int]]]] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool]] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool]]] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool]] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool] | collections.abc.Sequence[numpy.integer | numpy.bool | NDArray[numpy.integer | numpy.bool]]]]] | numpy.ndarray[tuple[int, typing.Unpack[tuple[int, ...]]], numpy.dtype[numpy.integer | numpy.bool]]

pyvista.typing.ArrayLikeBool

Any-dimensional array-like object with boolean values.

Accepts NumPy arrays of numpy.bool dtype and sequences of bool values or of numpy.bool scalars only. Integer and floating values are not included.

Includes NumPy arrays and sequences nested up to four deep. Scalar values are not included.

ArrayLikeBool = collections.abc.Sequence[bool | collections.abc.Sequence[bool] | collections.abc.Sequence[bool | collections.abc.Sequence[bool]] | collections.abc.Sequence[bool | collections.abc.Sequence[bool] | collections.abc.Sequence[bool | collections.abc.Sequence[bool]]]] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool]] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool]]] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool]] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool] | collections.abc.Sequence[numpy.bool | NDArray[numpy.bool]]]]] | numpy.ndarray[tuple[int, typing.Unpack[tuple[int, ...]]], numpy.dtype[numpy.bool]]

VTK Related Types

pyvista.typing.WrappableType

Object accepted by wrap().

Includes PyVista and VTK data objects, VTK data arrays, NumPy arrays, sequences of points, trimesh meshes, meshio meshes, and None.

WrappableType = vtkmodules.vtkCommonDataModel.vtkDataSet | vtkmodules.vtkCommonDataModel.vtkMultiBlockDataSet | vtkmodules.vtkCommonDataModel.vtkPartitionedDataSet | ForwardRef('DataSet') | ForwardRef('MultiBlock') | ForwardRef('PartitionedDataSet') | NDArray[numpy.float64 | numpy.float32 | numpy.float16 | numpy.int64 | numpy.int32 | numpy.int16 | numpy.int8 | numpy.uint64 | numpy.uint32 | numpy.uint16 | numpy.uint8 | numpy.bool | numpy.complex64 | numpy.complex128] | collections.abc.Sequence[float] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | ForwardRef('trimesh.Trimesh') | ForwardRef('meshio.Mesh') | vtkmodules.vtkCommonDataModel.vtkDataObject | ForwardRef('DataObject') | vtkmodules.vtkCommonCore.vtkDataArray | None

pyvista.BoundsTuple

class BoundsTuple(

x_min: float,

x_max: float,

y_min: float,

y_max: float,

z_min: float,

z_max: float,

)

Tuple of six values representing 3D bounds.

Has the form (x_min, x_max, y_min, y_max, z_min, z_max).

pyvista.typing.CellsLike

CellsLike = collections.abc.Sequence[collections.abc.Sequence[int]] | collections.abc.Sequence[collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.integer | numpy.bool]] | collections.abc.Sequence[int] | collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]]

pyvista.typing.CellArrayLike

CellArrayLike = collections.abc.Sequence[collections.abc.Sequence[int]] | collections.abc.Sequence[collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.integer | numpy.bool]] | collections.abc.Sequence[int] | collections.abc.Sequence[numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.integer | numpy.bool]] | vtkmodules.vtkCommonDataModel.vtkCellArray

pyvista.typing.RotationLike

Array or object representing a spatial rotation.

Includes 3x3 arrays and SciPy Rotation objects.

RotationLike = collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | vtkmodules.vtkCommonMath.vtkMatrix3x3 | scipy.spatial.transform._rotation.Rotation

pyvista.typing.TransformLike

Array or object representing a spatial transformation.

Includes 3x3 and 4x4 arrays as well as SciPy Rotation objects.

TransformLike = collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | vtkmodules.vtkCommonMath.vtkMatrix3x3 | scipy.spatial.transform._rotation.Rotation | vtkmodules.vtkCommonMath.vtkMatrix4x4 | vtkmodules.vtkCommonTransforms.vtkTransform

pyvista.typing.InteractionEventType

Interaction event mostly used for widgets.

Includes both strings such as 'end', 'start' and 'always' and vtkCommand.EventIds.

InteractionEventType = typing.Literal['end', 'start', 'always'] | vtkmodules.vtkCommonCore.vtkCommand.EventIds

pyvista.typing.LineStyle

Named style of a line, shared by the charts and the line filters.

LineStyle

alias of Literal[‘’, ‘-’, ‘–’, ‘:’, ‘-.’, ‘-..’]

pyvista.typing.CameraPositionOptions

Any object used to set a Camera.

CameraPositionOptions = typing.Literal['xy', 'xz', 'yz', 'yx', 'zx', 'zy', 'iso'] | collections.abc.Sequence[float] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[collections.abc.Sequence[float] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | pyvista.plotting.renderer.CameraPosition

pyvista.typing.JupyterBackendOptions

Jupyter backend to use.

JupyterBackendOptions

alias of Literal[‘static’, ‘client’, ‘server’, ‘trame’, ‘html’, ‘none’]

pyvista.typing.MeshValidationFields

Field options for validate_mesh().

MeshValidationFields = typing.Literal['cell_data_wrong_length', 'point_data_wrong_length'] | typing.Literal['non_finite_points', 'unused_points'] | typing.Literal['coincident_points', 'degenerate_faces', 'intersecting_edges', 'intersecting_faces', 'invalid_point_references', 'inverted_faces', 'negative_size', 'non_contiguous_edges', 'non_convex', 'non_planar_faces', 'wrong_number_of_points', 'zero_size'] | typing.Literal['data', 'points', 'cells'] | typing.Literal['memory_safe'] | pyvista.core.filters.data_object.CellStatus

Plotting Types

pyvista.typing.ColorLike

Any object that can be converted to a Color.

ColorLike = tuple[int, int, int] | tuple[int, int, int, int] | tuple[float, float, float] | tuple[float, float, float, float] | collections.abc.Sequence[int] | collections.abc.Sequence[float] | NDArray[numpy.floating] | NDArray[numpy.integer] | dict[str, int | float | str] | str | ForwardRef('Color') | vtkmodules.vtkCommonDataModel.vtkColor3ub | ForwardRef('_ALL_COLORS_LITERAL')

pyvista.typing.Chart

Any of Chart2D, ChartBox, ChartPie or ChartMPL, as accepted by add_chart().

Chart

pyvista.typing.PlottableType

Object accepted by plot() or add_mesh().

Includes PyVista and VTK datasets, multiblock and partitioned datasets, trimesh and meshio meshes, NumPy arrays of points or of volume values, sequences of points, and the path of a mesh file.

PlottableType = vtkmodules.vtkCommonDataModel.vtkDataSet | vtkmodules.vtkCommonDataModel.vtkMultiBlockDataSet | vtkmodules.vtkCommonDataModel.vtkPartitionedDataSet | ForwardRef('DataSet') | ForwardRef('MultiBlock') | ForwardRef('PartitionedDataSet') | NDArray[numpy.float64 | numpy.float32 | numpy.float16 | numpy.int64 | numpy.int32 | numpy.int16 | numpy.int8 | numpy.uint64 | numpy.uint32 | numpy.uint16 | numpy.uint8 | numpy.bool | numpy.complex64 | numpy.complex128] | collections.abc.Sequence[float] | collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | collections.abc.Sequence[collections.abc.Sequence[float]] | collections.abc.Sequence[collections.abc.Sequence[numpy.floating | numpy.integer | numpy.bool] | numpy.ndarray[tuple[int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]]] | numpy.ndarray[tuple[int, int], numpy.dtype[numpy.floating | numpy.integer | numpy.bool]] | ForwardRef('trimesh.Trimesh') | ForwardRef('meshio.Mesh') | str | pathlib.Path