DataObjectFilters.scale

DataObjectFilters.scale#

DataObjectFilters.scale( xyz: float | VectorLike[float], transform_all_input_vectors: bool = False, inplace: bool = False, point: VectorLike[float] | None = None, ) → _MeshType_co[source]#

Scale the mesh.

Note

See also the notes at transform() which is used by this filter under the hood.

Parameters:

xyzfloat | VectorLike[float]: A vector sequence defining the scale factors along x, y, and z. If a scalar, the same uniform scale is used along all three axes.
transform_all_input_vectorsbool, default: False: When True, all input vectors are transformed. Otherwise, only the points, normals, and active vectors are transformed.
inplacebool, default: False: Updates mesh in-place.
pointVectorLike[float], optional: Point to scale from. Defaults to origin.

Returns:

outputDataSet | MultiBlock: Scaled dataset. Return type matches input.

Examples#

Download Python source code | Download Jupyter notebook

>>> import pyvista as pv
>>> from pyvista import examples
>>> mesh1 = examples.download_teapot()
>>> mesh2 = mesh1.scale([10.0, 10.0, 10.0], inplace=False)

Plot meshes side-by-side

>>> pl = pv.Plotter(shape=(1, 2))
>>> # Create plot with unscaled mesh
>>> pl.subplot(0, 0)
>>> _ = pl.add_mesh(mesh1)
>>> pl.show_axes()
>>> _ = pl.show_grid()
>>> # Create plot with scaled mesh
>>> pl.subplot(0, 1)
>>> _ = pl.add_mesh(mesh2)
>>> pl.show_axes()
>>> _ = pl.show_grid()
>>> pl.show(cpos='xy')