CompositeAttributes.get_block

CompositeAttributes.get_block(index)

Return a block by its flat index.

Parameters:

indexint

Flat index of the block to retrieve.

Returns:

pyvista.DataObject

PyVista data object.

Notes

This method employs VTK’s flat indexing and allows for accessing both the blocks of a composite dataset as well as the entire composite dataset. If there is only one composite dataset, A, which contains datasets [b, c], the indexing would be [A, b, c].

If there are two composite datasets [B, C] in one composite dataset, A, each of which containing three additional datasets [d, e, f], and [g, h, i], respectively, then the head node, A, would be the zero index, followed by the first child, B, followed by all the children of B, [d, e, f]. In data structures, this flat indexing would be known as “Depth-first search” and the entire indexing would be:

[A, B, d, e, f, C, g, h, i]

Note how the composite datasets themselves are capitalized and are accessible in the flat indexing, and not just the datasets.

Examples

Download Python source code | Download Jupyter notebook

Add a composite dataset to a plotter and access its block attributes. Note how the zero index is the entire multiblock and you can use 1 and 2 to access the individual sub-blocks.

>>> import pyvista as pv
>>> dataset = pv.MultiBlock([pv.Cube(), pv.Sphere(center=(0, 0, 1))])
>>> pl = pv.Plotter()
>>> actor, mapper = pl.add_composite(dataset)
>>> mapper.block_attr.get_block(0)
MultiBlock (...)
  N Blocks:   2
  X Bounds:   -5.000e-01, 5.000e-01
  Y Bounds:   -5.000e-01, 5.000e-01
  Z Bounds:   -5.000e-01, 1.500e+00

Note this is the same as using __getitem__

>>> mapper.block_attr[0]
Composite Block Addr=... Attributes
Visible:   None
Opacity:   None
Color:     None
Pickable   None