pyvista.DataObjectFilters.transform

pyvista.DataObjectFilters.transform#

DataObjectFilters.transform(
trans: TransformLike,
transform_all_input_vectors: bool = False,
inplace: bool | None = None,
progress_bar: bool = False,
) DataSet | MultiBlock[source]#

Transform this mesh with a 4x4 transform.

Warning

When using transform_all_input_vectors=True, there is no distinction in VTK between vectors and arrays with three components. This may be an issue if you have scalar data with three components (e.g. RGB data). This will be improperly transformed as if it was vector data rather than scalar data. One possible (albeit ugly) workaround is to store the three components as separate scalar arrays.

Warning

In general, transformations give non-integer results. This method converts integer-typed vector data to float before performing the transformation. This applies to the points array, as well as any vector-valued data that is affected by the transformation. To prevent subtle bugs arising from in-place transformations truncating the result to integers, this conversion always applies to the input mesh.

Warning

Shear transformations are not supported for ImageData. If present, any shear component is removed by the filter.

Note

Transforming ImageData modifies its origin, spacing, and direction_matrix properties.

Deprecated since version 0.45.0: inplace was previously defaulted to True. In the future this will change to False.

Parameters:
transTransformLike

Accepts a vtk transformation object or a 4x4 transformation matrix.

transform_all_input_vectorsbool, default: False

When True, all arrays with three components are transformed. Otherwise, only the normals and vectors are transformed. See the warning for more details.

inplacebool, default: True

When True, modifies the dataset inplace.

progress_barbool, default: False

Display a progress bar to indicate progress.

Returns:
DataSet | MultiBlock

Transformed dataset. Return type matches input unless input dataset is a RectilinearGrid, in which case the output datatype is a StructuredGrid.

See also

pyvista.Transform

Describe linear transformations via a 4x4 matrix.

pyvista.Prop3D.transform

Transform an actor.

Examples

Translate a mesh by (50, 100, 200).

>>> import numpy as np
>>> from pyvista import examples
>>> mesh = examples.load_airplane()

Here a 4x4 numpy.ndarray is used, but any TransformLike is accepted.

>>> transform_matrix = np.array(
...     [
...         [1, 0, 0, 50],
...         [0, 1, 0, 100],
...         [0, 0, 1, 200],
...         [0, 0, 0, 1],
...     ]
... )
>>> transformed = mesh.transform(transform_matrix, inplace=False)
>>> transformed.plot(show_edges=True)
../../../_images/pyvista-DataObjectFilters-transform-1_00_00.png