class UniformGridFilters(*args, **kwargs)[source]#

An internal class to manage filters/algorithms for uniform grid datasets.


UniformGridFilters.cell_centers([vertex, ...])

Generate points at the center of the cells in this dataset.


Transform cell data into point data.

UniformGridFilters.clip([normal, origin, ...])

Clip a dataset by a plane by specifying the origin and normal.

UniformGridFilters.clip_box([bounds, ...])

Clip a dataset by a bounding box defined by the bounds.

UniformGridFilters.clip_scalar([scalars, ...])

Clip a dataset by a scalar.

UniformGridFilters.clip_surface(surface[, ...])

Clip any mesh type using a pyvista.PolyData surface mesh.


Compute a function of (geometric) quality for each cell of a mesh.


Compute sizes for 1D (length), 2D (area) and 3D (volume) cells.


Compute derivative-based quantities of point/cell scalar field.


Compute the implicit distance from the points to a surface.

UniformGridFilters.connectivity([largest, ...])

Find and label connected bodies/volumes.

UniformGridFilters.contour([isosurfaces, ...])

Contour an input self by an array.

UniformGridFilters.ctp([pass_cell_data, ...])

Transform cell data into point data.


Return a decimated version of a triangulation of the boundary.

UniformGridFilters.delaunay_3d([alpha, tol, ...])

Construct a 3D Delaunay triangulation of the mesh.

UniformGridFilters.elevation([low_point, ...])

Generate scalar values on a dataset.


Push each individual cell away from the center of the dataset.


Extract all the internal/external edges of the dataset as PolyData.

UniformGridFilters.extract_cells(ind[, ...])

Return a subset of the grid.


Extract edges from the surface of the mesh.


Extract the outer surface of a volume or structured grid dataset.


Extract largest connected set in mesh.

UniformGridFilters.extract_points(ind[, ...])

Return a subset of the grid (with cells) that contains any of the given point indices.

UniformGridFilters.extract_subset(voi[, ...])

Select piece (e.g., volume of interest).


Extract surface mesh of the grid.


Apply a fast Fourier transform (FFT) to the active scalars.


Smooth the data with a Gaussian kernel.

UniformGridFilters.glyph([orient, scale, ...])

Copy a geometric representation (called a glyph) to the input dataset.

UniformGridFilters.high_pass(x_cutoff, ...)

Perform a Butterworth high pass filter in the frequency domain.


Dilates one value and erodes another.


Apply a threshold to scalar values in a uniform grid.


Integrate point and cell data.

UniformGridFilters.interpolate(target[, ...])

Interpolate values onto this mesh from a given dataset.

UniformGridFilters.low_pass(x_cutoff, ...[, ...])

Perform a Butterworth low pass filter in the frequency domain.


Smooth data using a median filter.

UniformGridFilters.merge([grid, ...])

Join one or many other grids to this grid.

UniformGridFilters.outline([generate_faces, ...])

Produce an outline of the full extent for the input dataset.

UniformGridFilters.outline_corners([factor, ...])

Produce an outline of the corners for the input dataset.

UniformGridFilters.partition(n_partitions[, ...])

Break down input dataset into a requested number of partitions.


Sample a dataset along a circular arc and plot it.


Sample a dataset along a resolution circular arc defined by a normal and polar vector and plot it.

UniformGridFilters.plot_over_line(pointa, pointb)

Sample a dataset along a high resolution line and plot.


Transform point data into cell data.

UniformGridFilters.probe(points[, ...])

Sample data values at specified point locations.

UniformGridFilters.ptc([pass_point_data, ...])

Transform point data into cell data.

UniformGridFilters.reflect(normal[, point, ...])

Reflect a dataset across a plane.


Apply a reverse fast Fourier transform (RFFT) to the active scalars.

UniformGridFilters.sample(target[, ...])

Resample array data from a passed mesh onto this mesh.


Sample a dataset over a circular arc.


Sample a dataset over a circular arc defined by a normal and polar vector and plot it.

UniformGridFilters.sample_over_line(pointa, ...)

Sample a dataset onto a line.


Sample a dataset onto a multiple lines.


Mark points as to whether they are inside a closed surface.


Return a copy of the dataset with separated cells with no shared points.

UniformGridFilters.shrink([shrink_factor, ...])

Shrink the individual faces of a mesh.

UniformGridFilters.slice([normal, origin, ...])

Slice a dataset by a plane at the specified origin and normal vector orientation.

UniformGridFilters.slice_along_axis([n, ...])

Create many slices of the input dataset along a specified axis.

UniformGridFilters.slice_along_line(line[, ...])

Slice a dataset using a polyline/spline as the path.

UniformGridFilters.slice_implicit(...[, ...])

Slice a dataset by a VTK implicit function.

UniformGridFilters.slice_orthogonal([x, y, ...])

Create three orthogonal slices through the dataset on the three cartesian planes.

UniformGridFilters.split_bodies([label, ...])

Find, label, and split connected bodies/volumes.

UniformGridFilters.streamlines([vectors, ...])

Integrate a vector field to generate streamlines.


Generate evenly spaced streamlines on a 2D dataset.


Generate streamlines of vectors from the points of a source mesh.


Return the surface indices of a grid.


Tessellate a mesh.


Texture map this dataset to a user defined plane.


Texture map this dataset to a user defined sphere.

UniformGridFilters.threshold([value, ...])

Apply a vtkThreshold filter to the input dataset.


Threshold the dataset by a percentage of its range on the active scalars array.

UniformGridFilters.transform(trans[, ...])

Transform this mesh with a 4x4 transform.

UniformGridFilters.triangulate([inplace, ...])

Return an all triangle mesh.

UniformGridFilters.warp_by_scalar([scalars, ...])

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

UniformGridFilters.warp_by_vector([vectors, ...])

Warp the dataset's points by a point data vectors array's values.