ImageData.dimensionality

property ImageData.dimensionality: _Dimensionality

Return the number of spatial dimensions spanned by this dataset’s points.

This is equivalent to computing the matrix rank of the points.

Changed in version 0.47: This property is now generalized for all datasets. Previously, it was only available for datasets with a dimensions property.

Returns:

int

The dimensionality of the dataset.

See also

max_cell_dimensionality, min_cell_dimensionality

Notes

dimensionality:

• ranges from 0 to 3 for all mesh types.

• is equivalent to max_cell_dimensionality and min_cell_dimensionality for gridded data types ImageData and RectilinearGrid.

Examples

Download Python source code | Download Jupyter notebook

A single point has 0 dimensionality.

>>> import pyvista as pv
>>> mesh = pv.PointSet([[0.0, 0.0, 0.0]])
>>> mesh.dimensionality
0

With two points, the dimensionality is 1.

>>> mesh = pv.PointSet([[0.0, 0.0, 0.0], [1.0, 1.0, 1.0]])
>>> mesh.dimensionality
1

Two-dimensional ImageData (i.e. where one of its dimensions is one) has a dimensionality of 2.

>>> mesh = pv.ImageData(dimensions=(100, 100, 1))
>>> mesh.dimensionality
2

A Plane() also has dimensionality of 2, even if it’s arbitrarily rotated in space.

>>> mesh = pv.Plane().rotate_vector((1, 2, 3), 30)
>>> mesh.dimensionality
2

A Cube() has a dimensionality of 3.

>>> mesh = pv.Cube()
>>> mesh.dimensionality
3