LookupTable.apply_opacity(opacity, interpolate: bool = True, kind: str = 'quadratic')[source]#

Assign custom opacity to this lookup table.

opacityfloat | array_like[float] | str

The opacity mapping to use. Can be a str name of a predefined mapping including 'linear', 'geom', 'sigmoid', 'sigmoid_3-10'. Append an '_r' to any of those names to reverse that mapping. This can also be a custom array or list of values that will be interpolated across the n_color range for user defined mappings. Values must be between 0 and 1.

If a float, simply applies the same opacity across the entire colormap and must be between 0 and 1. Note that int values are interpreted as if they were floats.

interpolatebool, default: True

Flag on whether or not to interpolate the opacity mapping for all colors.

kindstr, default: ‘quadratic’

The interpolation kind if interpolate is True and scipy is available. See scipy.interpolate.interp1d for the available interpolation kinds.

If scipy is not available, 'linear' interpolation is used.


Apply a user defined custom opacity to a lookup table and plot the random hills example.

>>> import pyvista as pv
>>> from pyvista import examples
>>> mesh = examples.load_random_hills()
>>> lut = pv.LookupTable(cmap='viridis')
>>> lut.apply_opacity([1.0, 0.4, 0.0, 0.4, 0.9])
>>> lut.scalar_range = (
...     mesh.active_scalars.min(),
...     mesh.active_scalars.max(),
... )
>>> pl = pv.Plotter()
>>> _ = pl.add_mesh(mesh, cmap=lut)