pyvista.UnstructuredGrid

class UnstructuredGrid(*args, deep=False, **kwargs)

Dataset used for arbitrary combinations of all possible cell types.

Can be initialized by the following:

• Creating an empty grid

• From a vtk.vtkPolyData or vtk.vtkStructuredGrid object

• From cell, offset, and node arrays

• From a file

Parameters:

argsvarious

See below examples.

deepoptional

Whether to deep copy a vtkUnstructuredGrid object. Default is False. Keyword only.

Examples

>>> import pyvista
>>> from pyvista import examples
>>> import vtk

Create an empty grid

>>> grid = pyvista.UnstructuredGrid()

Copy a vtk.vtkUnstructuredGrid

>>> vtkgrid = vtk.vtkUnstructuredGrid()
>>> grid = pyvista.UnstructuredGrid(vtkgrid)

From a filename.

>>> grid = pyvista.UnstructuredGrid(examples.hexbeamfile)
>>> grid.plot(show_edges=True)

From arrays (VTK >= 9). Here we create a single tetrahedron.

>>> cells = [4, 0, 1, 2, 3]
>>> celltypes = [pyvista.CellType.TETRA]
>>> points = [
...     [1.0, 1.0, 1.0],
...     [1.0, -1.0, -1.0],
...     [-1.0, 1.0, -1.0],
...     [-1.0, -1.0, 1.0],
... ]
>>> grid = pyvista.UnstructuredGrid(cells, celltypes, points)
>>> grid.plot(show_edges=True)

See the Creating an Unstructured Grid example for more details on creating unstructured grids within PyVista.

Methods

UnstructuredGrid.add_field_array(scalars, name)	Add field data.
UnstructuredGrid.add_field_data(array, name)	Add field data.
UnstructuredGrid.cast_to_explicit_structured_grid()	Cast to an explicit structured grid.
UnstructuredGrid.cast_to_pointset([deep])	Get a new representation of this object as a pyvista.PointSet.
UnstructuredGrid.cast_to_unstructured_grid()	Get a new representation of this object as a pyvista.UnstructuredGrid.
UnstructuredGrid.cell_bounds(ind)	Return the bounding box of a cell.
UnstructuredGrid.cell_centers([vertex, ...])	Generate points at the center of the cells in this dataset.
UnstructuredGrid.cell_data_to_point_data([...])	Transform cell data into point data.
UnstructuredGrid.cell_n_points(ind)	Return the number of points in a cell.
UnstructuredGrid.cell_point_ids(ind)	Return the point ids in a cell.
UnstructuredGrid.cell_points(ind)	Return the points in a cell.
UnstructuredGrid.cell_type(ind)	Return the type of a cell.
UnstructuredGrid.center_of_mass([scalars_weight])	Return the coordinates for the center of mass of the mesh.
UnstructuredGrid.clear_arrays()	Remove all arrays from point/cell/field data.
UnstructuredGrid.clear_cell_arrays()	Remove all cell data.
UnstructuredGrid.clear_cell_data()	Remove all cell arrays.
UnstructuredGrid.clear_data()	Remove all arrays from point/cell/field data.
UnstructuredGrid.clear_field_arrays()	Remove all field data.
UnstructuredGrid.clear_field_data()	Remove all field data.
UnstructuredGrid.clear_point_arrays()	Remove all point data.
UnstructuredGrid.clear_point_data()	Remove all point arrays.
UnstructuredGrid.clear_textures()	Clear the textures from this mesh.
UnstructuredGrid.clip([normal, origin, ...])	Clip a dataset by a plane by specifying the origin and normal.
UnstructuredGrid.clip_box([bounds, invert, ...])	Clip a dataset by a bounding box defined by the bounds.
UnstructuredGrid.clip_scalar([scalars, ...])	Clip a dataset by a scalar.
UnstructuredGrid.clip_surface(surface[, ...])	Clip any mesh type using a pyvista.PolyData surface mesh.
UnstructuredGrid.compute_cell_quality([...])	Compute a function of (geometric) quality for each cell of a mesh.
UnstructuredGrid.compute_cell_sizes([...])	Compute sizes for 1D (length), 2D (area) and 3D (volume) cells.
UnstructuredGrid.compute_derivative([...])	Compute derivative-based quantities of point/cell scalar field.
UnstructuredGrid.compute_implicit_distance(surface)	Compute the implicit distance from the points to a surface.
UnstructuredGrid.connectivity([largest, ...])	Find and label connected bodies/volumes.
UnstructuredGrid.contour([isosurfaces, ...])	Contour an input self by an array.
UnstructuredGrid.copy([deep])	Return a copy of the object.
UnstructuredGrid.copy_attributes(dataset)	Copy the data attributes of the input dataset object.
UnstructuredGrid.copy_from(mesh)	Overwrite this dataset inplace with the new dataset's geometries and data.
UnstructuredGrid.copy_meta_from(ido[, deep])	Copy pyvista meta data onto this object from another object.
UnstructuredGrid.copy_structure(dataset)	Copy the structure (geometry and topology) of the input dataset object.
UnstructuredGrid.ctp([pass_cell_data, ...])	Transform cell data into point data.
UnstructuredGrid.decimate_boundary([...])	Return a decimated version of a triangulation of the boundary.
UnstructuredGrid.deep_copy(to_copy)	Overwrite this data object with another data object as a deep copy.
UnstructuredGrid.delaunay_2d([tol, alpha, ...])	Apply a 2D Delaunay filter along the best fitting plane.
UnstructuredGrid.delaunay_3d([alpha, tol, ...])	Construct a 3D Delaunay triangulation of the mesh.
UnstructuredGrid.elevation([low_point, ...])	Generate scalar values on a dataset.
UnstructuredGrid.explode([factor])	Push each individual cell away from the center of the dataset.
UnstructuredGrid.extract_all_edges([...])	Extract all the internal/external edges of the dataset as PolyData.
UnstructuredGrid.extract_cells(ind[, ...])	Return a subset of the grid.
UnstructuredGrid.extract_feature_edges([...])	Extract edges from the surface of the mesh.
UnstructuredGrid.extract_geometry([extent, ...])	Extract the outer surface of a volume or structured grid dataset.
UnstructuredGrid.extract_largest([inplace, ...])	Extract largest connected set in mesh.
UnstructuredGrid.extract_points(ind[, ...])	Return a subset of the grid (with cells) that contains any of the given point indices.
UnstructuredGrid.extract_surface([...])	Extract surface mesh of the grid.
UnstructuredGrid.find_cells_along_line(...)	Find the index of cells in this mesh along a line.
UnstructuredGrid.find_cells_within_bounds(bounds)	Find the index of cells in this mesh within bounds.
UnstructuredGrid.find_closest_cell(point[, ...])	Find index of closest cell in this mesh to the given point.
UnstructuredGrid.find_closest_point(point[, n])	Find index of closest point in this mesh to the given point.
UnstructuredGrid.find_containing_cell(point)	Find index of a cell that contains the given point.
UnstructuredGrid.flip_normal(normal[, ...])	Flip mesh about the normal.
UnstructuredGrid.flip_x([point, ...])	Flip mesh about the x-axis.
UnstructuredGrid.flip_y([point, ...])	Flip mesh about the y-axis.
UnstructuredGrid.flip_z([point, ...])	Flip mesh about the z-axis.
UnstructuredGrid.get_array(name[, preference])	Search both point, cell and field data for an array.
UnstructuredGrid.get_array_association(name)	Get the association of an array.
UnstructuredGrid.get_data_range([arr_var, ...])	Get the non-NaN min and max of a named array.
UnstructuredGrid.glyph([orient, scale, ...])	Copy a geometric representation (called a glyph) to the input dataset.
UnstructuredGrid.head([display, html])	Return the header stats of this dataset.
UnstructuredGrid.integrate_data([progress_bar])	Integrate point and cell data.
UnstructuredGrid.interpolate(target[, ...])	Interpolate values onto this mesh from a given dataset.
UnstructuredGrid.linear_copy([deep])	Return a copy of the unstructured grid containing only linear cells.
UnstructuredGrid.merge([grid, merge_points, ...])	Join one or many other grids to this grid.
UnstructuredGrid.outline([generate_faces, ...])	Produce an outline of the full extent for the input dataset.
UnstructuredGrid.outline_corners([factor, ...])	Produce an outline of the corners for the input dataset.
UnstructuredGrid.overwrite(mesh)	Overwrite this dataset inplace with the new dataset's geometries and data.
UnstructuredGrid.partition(n_partitions[, ...])	Break down input dataset into a requested number of partitions.
UnstructuredGrid.plot([off_screen, ...])	Plot a PyVista, numpy, or vtk object.
UnstructuredGrid.plot_curvature([curv_type])	Plot the curvature of the external surface of the grid.
UnstructuredGrid.plot_over_circular_arc(...)	Sample a dataset along a circular arc and plot it.
UnstructuredGrid.plot_over_circular_arc_normal(center)	Sample a dataset along a resolution circular arc defined by a normal and polar vector and plot it.
UnstructuredGrid.plot_over_line(pointa, pointb)	Sample a dataset along a high resolution line and plot.
UnstructuredGrid.point_data_to_cell_data([...])	Transform point data into cell data.
UnstructuredGrid.point_is_inside_cell(ind, point)	Return whether one or more points are inside a cell.
UnstructuredGrid.points_to_double()	Convert the points datatype to double precision.
UnstructuredGrid.probe(points[, tolerance, ...])	Sample data values at specified point locations.
UnstructuredGrid.ptc([pass_point_data, ...])	Transform point data into cell data.
UnstructuredGrid.reconstruct_surface([...])	Reconstruct a surface from the points in this dataset.
UnstructuredGrid.reflect(normal[, point, ...])	Reflect a dataset across a plane.
UnstructuredGrid.remove_cells(ind[, inplace])	Remove cells.
UnstructuredGrid.rename_array(old_name, new_name)	Change array name by searching for the array then renaming it.
UnstructuredGrid.rotate_vector(vector, angle)	Rotate mesh about a vector.
UnstructuredGrid.rotate_x(angle[, point, ...])	Rotate mesh about the x-axis.
UnstructuredGrid.rotate_y(angle[, point, ...])	Rotate mesh about the y-axis.
UnstructuredGrid.rotate_z(angle[, point, ...])	Rotate mesh about the z-axis.
UnstructuredGrid.sample(target[, tolerance, ...])	Resample array data from a passed mesh onto this mesh.
UnstructuredGrid.sample_over_circular_arc(...)	Sample a dataset over a circular arc.
UnstructuredGrid.sample_over_circular_arc_normal(center)	Sample a dataset over a circular arc defined by a normal and polar vector and plot it.
UnstructuredGrid.sample_over_line(pointa, pointb)	Sample a dataset onto a line.
UnstructuredGrid.sample_over_multiple_lines(points)	Sample a dataset onto a multiple lines.
UnstructuredGrid.save(filename[, binary, ...])	Save this vtk object to file.
UnstructuredGrid.scale(xyz[, ...])	Scale the mesh.
UnstructuredGrid.select_enclosed_points(surface)	Mark points as to whether they are inside a closed surface.
UnstructuredGrid.separate_cells()	Return a copy of the dataset with separated cells with no shared points.
UnstructuredGrid.set_active_scalars(name[, ...])	Find the scalars by name and appropriately sets it as active.
UnstructuredGrid.set_active_tensors(name[, ...])	Find the tensors by name and appropriately sets it as active.
UnstructuredGrid.set_active_vectors(name[, ...])	Find the vectors by name and appropriately sets it as active.
UnstructuredGrid.shallow_copy(to_copy)	Create a shallow copy from a different dataset into this one.
UnstructuredGrid.shrink([shrink_factor, ...])	Shrink the individual faces of a mesh.
UnstructuredGrid.slice([normal, origin, ...])	Slice a dataset by a plane at the specified origin and normal vector orientation.
UnstructuredGrid.slice_along_axis([n, axis, ...])	Create many slices of the input dataset along a specified axis.
UnstructuredGrid.slice_along_line(line[, ...])	Slice a dataset using a polyline/spline as the path.
UnstructuredGrid.slice_implicit(...[, ...])	Slice a dataset by a VTK implicit function.
UnstructuredGrid.slice_orthogonal([x, y, z, ...])	Create three orthogonal slices through the dataset on the three cartesian planes.
UnstructuredGrid.split_bodies([label, ...])	Find, label, and split connected bodies/volumes.
UnstructuredGrid.streamlines([vectors, ...])	Integrate a vector field to generate streamlines.
UnstructuredGrid.streamlines_evenly_spaced_2D([...])	Generate evenly spaced streamlines on a 2D dataset.
UnstructuredGrid.streamlines_from_source(source)	Generate streamlines of vectors from the points of a source mesh.
UnstructuredGrid.subdivide_tetra()	Subdivide each tetrahedron into twelve tetrahedrons.
UnstructuredGrid.surface_indices([progress_bar])	Return the surface indices of a grid.
UnstructuredGrid.tessellate([...])	Tessellate a mesh.
UnstructuredGrid.texture_map_to_plane([...])	Texture map this dataset to a user defined plane.
UnstructuredGrid.texture_map_to_sphere([...])	Texture map this dataset to a user defined sphere.
UnstructuredGrid.threshold([value, scalars, ...])	Apply a vtkThreshold filter to the input dataset.
UnstructuredGrid.threshold_percent([...])	Threshold the dataset by a percentage of its range on the active scalars array.
UnstructuredGrid.transform(trans[, ...])	Transform this mesh with a 4x4 transform.
UnstructuredGrid.translate(xyz[, ...])	Translate the mesh.
UnstructuredGrid.triangulate([inplace, ...])	Return an all triangle mesh.
UnstructuredGrid.warp_by_scalar([scalars, ...])	Warp the dataset's points by a point data scalars array's values.
UnstructuredGrid.warp_by_vector([vectors, ...])	Warp the dataset's points by a point data vectors array's values.

Attributes

UnstructuredGrid.active_normals	Return the active normals as an array.
UnstructuredGrid.active_scalars	Return the active scalars as an array.
UnstructuredGrid.active_scalars_info	Return the active scalar's association and name.
UnstructuredGrid.active_scalars_name	Return the name of the active scalars.
UnstructuredGrid.active_t_coords	Return or set the active texture coordinates on the points.
UnstructuredGrid.active_tensors	Return the active tensors array.
UnstructuredGrid.active_tensors_info	Return the active tensor's field and name: [field, name].
UnstructuredGrid.active_tensors_name	Return the name of the active tensor array.
UnstructuredGrid.active_vectors	Return the active vectors array.
UnstructuredGrid.active_vectors_info	Return the active vector's association and name.
UnstructuredGrid.active_vectors_name	Return the name of the active vectors array.
UnstructuredGrid.actual_memory_size	Return the actual size of the dataset object.
UnstructuredGrid.area	Return the mesh area if 2D.
UnstructuredGrid.array_names	Return a list of array names for the dataset.
UnstructuredGrid.arrows	Return a glyph representation of the active vector data as arrows.
UnstructuredGrid.bounds	Return the bounding box of this dataset.
UnstructuredGrid.cell_arrays	Return vtkCellData as DataSetAttributes.
UnstructuredGrid.cell_connectivity	Return a the vtk cell connectivity as a numpy array.
UnstructuredGrid.cell_data	Return vtkCellData as DataSetAttributes.
UnstructuredGrid.cells	Return a pointer to the cells as a numpy object.
UnstructuredGrid.cells_dict	Return a dictionary that contains all cells mapped from cell types.
UnstructuredGrid.celltypes	Return the cell types array.
UnstructuredGrid.center	Return the center of the bounding box.
UnstructuredGrid.field_arrays	Return vtkFieldData as DataSetAttributes.
UnstructuredGrid.field_data	Return FieldData as DataSetAttributes.
UnstructuredGrid.length	Return the length of the diagonal of the bounding box.
UnstructuredGrid.memory_address	Get address of the underlying VTK C++ object.
UnstructuredGrid.n_arrays	Return the number of arrays present in the dataset.
UnstructuredGrid.n_cells	Return the number of cells in the entire dataset.
UnstructuredGrid.n_points	Return the number of points in the entire dataset.
UnstructuredGrid.number_of_cells	Return the number of cells.
UnstructuredGrid.number_of_points	Return the number of points.
UnstructuredGrid.offset	Return the cell locations array.
UnstructuredGrid.point_arrays	Return vtkPointData as DataSetAttributes.
UnstructuredGrid.point_data	Return vtkPointData as DataSetAttributes.
UnstructuredGrid.points	Return a reference to the points as a numpy object.
UnstructuredGrid.t_coords	Return the active texture coordinates on the points.
UnstructuredGrid.textures	Return a dictionary to hold compatible vtk.vtkTexture objects.
UnstructuredGrid.vectors	Return active vectors.
UnstructuredGrid.volume	Return the mesh volume.