pyvista.DataSetFilters

class DataSetFilters(*args, **kwargs)

A set of common filters that can be applied to any vtkDataSet.

Methods

DataSetFilters.align(target[, ...])	Align a dataset to another.
DataSetFilters.align_xyz(*[, centered, ...])	Align a dataset to the x-y-z axes.
DataSetFilters.bounding_box([box_style, ...])	Return a bounding box for this dataset.
DataSetFilters.clip_scalar([scalars, ...])	Clip a dataset by a scalar.
DataSetFilters.clip_surface(surface[, ...])	Clip any mesh type using a pyvista.PolyData surface mesh.
DataSetFilters.color_labels([colors, ...])	Add RGB(A) scalars to labeled data.
DataSetFilters.compute_boundary_mesh_quality(*)	Compute metrics on the boundary faces of a mesh.
DataSetFilters.compute_cell_quality([...])	Compute a function of (geometric) quality for each cell of a mesh.
DataSetFilters.compute_derivative([scalars, ...])	Compute derivative-based quantities of point/cell scalar field.
DataSetFilters.compute_implicit_distance(surface)	Compute the implicit distance from the points to a surface.
DataSetFilters.connectivity([...])	Find and label connected regions.
DataSetFilters.contour([isosurfaces, ...])	Contour an input self by an array.
DataSetFilters.decimate_boundary([...])	Return a decimated version of a triangulation of the boundary.
DataSetFilters.delaunay_3d([alpha, tol, ...])	Construct a 3D Delaunay triangulation of the mesh.
DataSetFilters.explode([factor])	Push each individual cell away from the center of the dataset.
DataSetFilters.extract_cells(ind[, invert, ...])	Return a subset of the grid.
DataSetFilters.extract_cells_by_type(cell_types)	Extract cells of a specified type.
DataSetFilters.extract_feature_edges([...])	Extract edges from the surface of the mesh.
DataSetFilters.extract_geometry([extent, ...])	Extract the outer surface of a volume or structured grid dataset.
DataSetFilters.extract_largest([inplace, ...])	Extract largest connected set in mesh.
DataSetFilters.extract_points(ind[, ...])	Return a subset of the grid (with cells) that contains any of the given point indices.
DataSetFilters.extract_surface([...])	Extract surface mesh of the grid.
DataSetFilters.extract_values([values, ...])	Return a subset of the mesh based on the value(s) of point or cell data.
DataSetFilters.gaussian_splatting(*[, ...])	Splat points into a volume using a Gaussian distribution.
DataSetFilters.glyph([orient, scale, ...])	Copy a geometric representation (called a glyph) to the input dataset.
DataSetFilters.integrate_data([progress_bar])	Integrate point and cell data.
DataSetFilters.interpolate(target[, ...])	Interpolate values onto this mesh from a given dataset.
DataSetFilters.merge([grid, merge_points, ...])	Join one or many other grids to this grid.
DataSetFilters.merge_points([tolerance, ...])	Merge duplicate points in this mesh.
DataSetFilters.oriented_bounding_box([...])	Return an oriented bounding box (OBB) for this dataset.
DataSetFilters.outline([generate_faces, ...])	Produce an outline of the full extent for the input dataset.
DataSetFilters.outline_corners([factor, ...])	Produce an outline of the corners for the input dataset.
DataSetFilters.pack_labels([sort, scalars, ...])	Renumber labeled data such that labels are contiguous.
DataSetFilters.partition(n_partitions[, ...])	Break down input dataset into a requested number of partitions.
DataSetFilters.plot_over_circular_arc(...[, ...])	Sample a dataset along a circular arc and plot it.
DataSetFilters.plot_over_circular_arc_normal(center)	Sample a dataset along a circular arc defined by a normal and polar vector and plot it.
DataSetFilters.plot_over_line(pointa, pointb)	Sample a dataset along a high resolution line and plot.
DataSetFilters.sample_over_circular_arc(...)	Sample a dataset over a circular arc.
DataSetFilters.sample_over_circular_arc_normal(center)	Sample a dataset over a circular arc defined by a normal and polar vector and plot it.
DataSetFilters.sample_over_line(pointa, pointb)	Sample a dataset onto a line.
DataSetFilters.sample_over_multiple_lines(points)	Sample a dataset onto a multiple lines.
DataSetFilters.select_enclosed_points(surface)	Mark points as to whether they are inside a closed surface.
DataSetFilters.separate_cells()	Return a copy of the dataset with separated cells with no shared points.
DataSetFilters.shrink([shrink_factor, ...])	Shrink the individual faces of a mesh.
DataSetFilters.sort_labels([scalars, ...])	Sort labeled data by number of points or cells.
DataSetFilters.split_bodies([label, ...])	Find, label, and split connected bodies/volumes.
DataSetFilters.split_values([values, ...])	Split mesh into separate sub-meshes using point or cell data.
DataSetFilters.streamlines([vectors, ...])	Integrate a vector field to generate streamlines.
DataSetFilters.streamlines_evenly_spaced_2D([...])	Generate evenly spaced streamlines on a 2D dataset.
DataSetFilters.streamlines_from_source(source)	Generate streamlines of vectors from the points of a source mesh.
DataSetFilters.surface_indices([progress_bar])	Return the surface indices of a grid.
DataSetFilters.tessellate([max_n_subdivide, ...])	Tessellate a mesh.
DataSetFilters.texture_map_to_plane([...])	Texture map this dataset to a user defined plane.
DataSetFilters.texture_map_to_sphere([...])	Texture map this dataset to a user defined sphere.
DataSetFilters.threshold([value, scalars, ...])	Apply a vtkThreshold filter to the input dataset.
DataSetFilters.threshold_percent([percent, ...])	Threshold the dataset by a percentage of its range on the active scalars array.
DataSetFilters.voxelize(*[, ...])	Voxelize mesh to UnstructuredGrid.
DataSetFilters.voxelize_binary_mask(*[, ...])	Voxelize mesh as a binary ImageData mask.
DataSetFilters.voxelize_rectilinear(*[, ...])	Voxelize mesh to create a RectilinearGrid voxel volume.
DataSetFilters.warp_by_scalar([scalars, ...])	Warp the dataset's points by a point data scalars array's values.
DataSetFilters.warp_by_vector([vectors, ...])	Warp the dataset's points by a point data vectors array's values.

Attributes

DataSetFilters.points