Transform.scale

Transform.scale(

*factor: float | VectorLike[float],

point: VectorLike[float] | None = None,

multiply_mode: Literal['pre', 'post'] | None = None,

) → Transform

Compose a scale matrix.

Create a scale matrix and compose() it with the current transformation matrix according to pre-multiply or post-multiply semantics.

Internally, the matrix is stored in the matrix_list.

Parameters:

*factorfloat | VectorLike[float]

Scale factor(s) to use. Use a single number for uniform scaling or three numbers for non-uniform scaling. The three factors may be passed as a single vector (one arg) or an unpacked vector (three args).

pointVectorLike[float], optional

Point to scale from. By default, the object’s point is used, but this can be overridden. If set, two additional transformations are composed and added to the matrix_list:

• translate() to point before the scaling

• translate() away from point after the scaling

multiply_mode‘pre’ | ‘post’, optional

Multiplication mode to use when composing the matrix. By default, the object’s multiply_mode is used, but this can be overridden. Set this to 'pre' for pre-multiplication or 'post' for post-multiplication.

See also

pyvista.DataObjectFilters.scale

Scale a mesh.

pyvista.DataObjectFilters.resize

Resize a mesh.

scale_factors, has_scale

Get info about the transform’s scale component.

Examples

Download Python source code | Download Jupyter notebook

Compose a scale matrix.

>>> import pyvista as pv
>>> transform = pv.Transform().scale(1, 2, 3)
>>> transform.matrix
array([[1., 0., 0., 0.],
       [0., 2., 0., 0.],
       [0., 0., 3., 0.],
       [0., 0., 0., 1.]])

Compose a second scale matrix using *.

>>> transform = transform * 2
>>> transform.matrix
array([[2., 0., 0., 0.],
       [0., 4., 0., 0.],
       [0., 0., 6., 0.],
       [0., 0., 0., 1.]])

Scale from a point. Check the matrix_list to see that a translation is added before and after the scaling.

>>> transform = pv.Transform().scale(7, point=(1, 2, 3))
>>> translation_to_origin = transform.matrix_list[0]
>>> translation_to_origin
array([[ 1.,  0.,  0., -1.],
       [ 0.,  1.,  0., -2.],
       [ 0.,  0.,  1., -3.],
       [ 0.,  0.,  0.,  1.]])

>>> scale = transform.matrix_list[1]
>>> scale
array([[7., 0., 0., 0.],
       [0., 7., 0., 0.],
       [0., 0., 7., 0.],
       [0., 0., 0., 1.]])

>>> translation_from_origin = transform.matrix_list[2]
>>> translation_from_origin
array([[1., 0., 0., 1.],
       [0., 1., 0., 2.],
       [0., 0., 1., 3.],
       [0., 0., 0., 1.]])