DataSetFilters.warp_by_scalar(scalars=None, factor=1.0, normal=None, inplace=False, progress_bar=False, **kwargs)[source]#

Warp the dataset’s points by a point data scalars array’s values.

This modifies point coordinates by moving points along point normals by the scalar amount times the scale factor.

scalarsstr, optional

Name of scalars to warp by. Defaults to currently active scalars.

factorfloat, default: 1.0

A scaling factor to increase the scaling effect. Alias scale_factor also accepted - if present, overrides factor.

normalsequence, optional

User specified normal. If given, data normals will be ignored and the given normal will be used to project the warp.

inplacebool, default: False

If True, the points of the given dataset will be updated.

progress_barbool, default: False

Display a progress bar to indicate progress.

**kwargsdict, optional

Accepts scale_factor instead of factor.


Warped Dataset. Return type matches input.


First, plot the unwarped mesh.

>>> from pyvista import examples
>>> mesh = examples.download_st_helens()
>>> mesh.plot(cmap='gist_earth', show_scalar_bar=False)

Now, warp the mesh by the 'Elevation' scalars.

>>> warped = mesh.warp_by_scalar('Elevation')
>>> warped.plot(cmap='gist_earth', show_scalar_bar=False)

See Computing Surface Normals for more examples using this filter.