pyvista.Transform.apply_to_dataset#

Transform.apply_to_dataset(

dataset: _DataSetOrMultiBlockType,

/,

mode: Literal['active_vectors', 'all_vectors'] = 'active_vectors',

copy: bool = True,

inverse: bool = False,

) → _DataSetOrMultiBlockType[source]#

Apply the current transformation matrix to a dataset.

This is equivalent to apply(dataset, mode). See apply() for details and examples.

Parameters:

datasetDataSet | MultiBlock

Object to apply the transformation to.

mode‘active_vectors’ | ‘all_vectors’, default: ‘active_vectors’

Mode for transforming the dataset’s vectors:

• 'active_vectors' transforms active normals and active vectors arrays only.

• 'all_vectors' transforms all input vectors, i.e. all arrays with three components. This mode is equivalent to setting transform_all_input_vectors=True with pyvista.DataObjectFilters.transform().

inversebool, default: False

Apply the transformation using the inverse_matrix instead of the matrix.

copybool, default: True

Return a copy of the input with the transformation applied. Set this to False to transform the input directly and return it.

Returns:

DataSet | MultiBlock

Transformed dataset.

See also

apply

Apply this transformation to any input.

apply_to_points

Apply this transformation to points.

apply_to_vectors

Apply this transformation to vectors.

pyvista.DataObjectFilters.transform

Transform a dataset.