Typing#

Type aliases and type variable used by PyVista.

Numeric Array-Like Types#

pyvista.NumberType#

Type variable for numeric data types.

NumberType = TypeVar(NumberType, bound=Union)#

Type:    TypeVar

Invariant TypeVar bound to typing.Union[numpy.floating, numpy.integer, numpy.bool, float, int, bool].

pyvista.ArrayLike#

Any-dimensional array-like object with numerical values.

Includes sequences, nested sequences, and numpy arrays. Scalar values are not included.

ArrayLike = numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]] | collections.abc.Sequence[~NumberType] | collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]] | collections.abc.Sequence[collections.abc.Sequence[~NumberType]] | collections.abc.Sequence[collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]]] | collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[~NumberType]]] | collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]]]] | collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[~NumberType]]]] | collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]]]]]#

Represent a union type

E.g. for int | str

pyvista.MatrixLike#

Two-dimensional array-like object with numerical values.

Includes singly nested sequences and numpy arrays.

MatrixLike = numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]] | collections.abc.Sequence[collections.abc.Sequence[~NumberType]] | collections.abc.Sequence[collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]]]#

Represent a union type

E.g. for int | str

pyvista.VectorLike#

One-dimensional array-like object with numerical values.

Includes sequences and numpy arrays.

VectorLike = numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]] | collections.abc.Sequence[~NumberType] | collections.abc.Sequence[numpy.ndarray[tuple[typing.Any, ...], numpy.dtype[~NumberType]]]#

Represent a union type

E.g. for int | str