pyvista.DataSetFilters

Contents

pyvista.DataSetFilters#

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

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.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 resolution 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_binary_mask(*[, ...])

Voxelize mesh as a binary ImageData mask.

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.