pyvista.UnstructuredGrid

class UnstructuredGrid(*args, **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

Examples

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

Create an empty grid

>>> grid = pyvista.UnstructuredGrid()

Copy a vtkUnstructuredGrid

>>> vtkgrid = vtk.vtkUnstructuredGrid()
>>> grid = pyvista.UnstructuredGrid(vtkgrid)  # Initialize from a vtkUnstructuredGrid

>>> # from arrays (vtk9)
>>> #grid = pyvista.UnstructuredGrid(cells, celltypes, points)

>>> # from arrays (vtk<9)
>>> #grid = pyvista.UnstructuredGrid(offset, cells, celltypes, points)

From a string filename

>>> grid = pyvista.UnstructuredGrid(examples.hexbeamfile)

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_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_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_meta_from(ido)	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.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([progress_bar])	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.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.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.plot([off_screen, ...])	Plot a vtk or numpy 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.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.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.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_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.surface_indices([progress_bar])	Return the surface indices of a grid.
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.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.extent	Return the range 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	Compute the volume of the point grid.