pyvista.StructuredGrid

class StructuredGrid(*args, **kwargs)

Dataset used for topologically regular arrays of data.

Can be initialized in one of the following several ways:

  • Create empty grid

  • Initialize from a vtk.vtkStructuredGrid object

  • Initialize directly from the point arrays

See _from_arrays in the documentation for more details on initializing from point arrays

Examples

>>> import pyvista
>>> import vtk
>>> import numpy as np

Create empty grid

>>> grid = pyvista.StructuredGrid()

Initialize from a vtk.vtkStructuredGrid object

>>> vtkgrid = vtk.vtkStructuredGrid()
>>> grid = pyvista.StructuredGrid(vtkgrid)

Create from NumPy arrays

>>> xrng = np.arange(-10, 10, 2)
>>> yrng = np.arange(-10, 10, 2)
>>> zrng = np.arange(-10, 10, 2)
>>> x, y, z = np.meshgrid(xrng, yrng, zrng)
>>> grid = pyvista.StructuredGrid(x, y, z)

Methods

StructuredGrid.add_field_array(scalars, name)

Add field data.

StructuredGrid.add_field_data(array, name[, ...])

Add field data.

StructuredGrid.cast_to_unstructured_grid()

Get a new representation of this object as a pyvista.UnstructuredGrid.

StructuredGrid.cell_bounds(ind)

Return the bounding box of a cell.

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

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

StructuredGrid.cell_data_to_point_data([...])

Transform cell data into point data.

StructuredGrid.cell_n_points(ind)

Return the number of points in a cell.

StructuredGrid.cell_points(ind)

Return the points in a cell.

StructuredGrid.cell_type(ind)

Return the type of a cell.

StructuredGrid.center_of_mass([scalars_weight])

Return the coordinates for the center of mass of the mesh.

StructuredGrid.clear_arrays()

Remove all arrays from point/cell/field data.

StructuredGrid.clear_cell_arrays()

Remove all cell data.

StructuredGrid.clear_cell_data()

Remove all cell arrays.

StructuredGrid.clear_data()

Remove all arrays from point/cell/field data.

StructuredGrid.clear_field_arrays()

Remove all field data.

StructuredGrid.clear_field_data()

Remove all field data.

StructuredGrid.clear_point_arrays()

Remove all point data.

StructuredGrid.clear_point_data()

Remove all point arrays.

StructuredGrid.clear_textures()

Clear the textures from this mesh.

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

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

StructuredGrid.clip_box([bounds, invert, ...])

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

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

Clip a dataset by a scalar.

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

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

StructuredGrid.compute_cell_quality([...])

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

StructuredGrid.compute_cell_sizes([length, ...])

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

StructuredGrid.compute_derivative([scalars, ...])

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

StructuredGrid.compute_implicit_distance(surface)

Compute the implicit distance from the points to a surface.

StructuredGrid.concatenate(other, axis[, ...])

Concatenate a structured grid to this grid.

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

Find and label connected bodies/volumes.

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

Contour an input self by an array.

StructuredGrid.copy([deep])

Return a copy of the object.

StructuredGrid.copy_attributes(dataset)

Copy the data attributes of the input dataset object.

StructuredGrid.copy_meta_from(ido)

Copy pyvista meta data onto this object from another object.

StructuredGrid.copy_structure(dataset)

Copy the structure (geometry and topology) of the input dataset object.

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

Transform cell data into point data.

StructuredGrid.decimate_boundary([...])

Return a decimated version of a triangulation of the boundary.

StructuredGrid.deep_copy(to_copy)

Overwrite this data object with another data object as a deep copy.

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

Construct a 3D Delaunay triangulation of the mesh.

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

Generate scalar values on a dataset.

StructuredGrid.extract_all_edges([progress_bar])

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

StructuredGrid.extract_cells(ind[, progress_bar])

Return a subset of the grid.

StructuredGrid.extract_feature_edges([...])

Extract edges from the surface of the mesh.

StructuredGrid.extract_geometry([progress_bar])

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

StructuredGrid.extract_largest([inplace, ...])

Extract largest connected set in mesh.

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

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

StructuredGrid.extract_subset(voi[, rate, ...])

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

StructuredGrid.extract_surface([...])

Extract surface mesh of the grid.

StructuredGrid.find_closest_cell(point)

Find index of closest cell in this mesh to the given point.

StructuredGrid.find_closest_point(point[, n])

Find index of closest point in this mesh to the given point.

StructuredGrid.flip_normal(normal[, point, ...])

Flip mesh about the normal.

StructuredGrid.flip_x([point, ...])

Flip mesh about the x-axis.

StructuredGrid.flip_y([point, ...])

Flip mesh about the y-axis.

StructuredGrid.flip_z([point, ...])

Flip mesh about the z-axis.

StructuredGrid.get_array(name[, preference])

Search both point, cell and field data for an array.

StructuredGrid.get_array_association(name[, ...])

Get the association of an array.

StructuredGrid.get_data_range([arr_var, ...])

Get the non-NaN min and max of a named array.

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

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

StructuredGrid.head([display, html])

Return the header stats of this dataset.

StructuredGrid.hide_cells(ind)

Hide cells without deleting them.

StructuredGrid.hide_points(ind)

Hide points without deleting them.

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

Interpolate values onto this mesh from a given dataset.

StructuredGrid.merge([grid, merge_points, ...])

Join one or many other grids to this grid.

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

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

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

Produce an outline of the corners for the input dataset.

StructuredGrid.overwrite(mesh)

Overwrite this dataset inplace with the new dataset's geometries and data.

StructuredGrid.plot([off_screen, ...])

Plot a vtk or numpy object.

StructuredGrid.plot_curvature([curv_type])

Plot the curvature of the external surface of the grid.

StructuredGrid.plot_over_circular_arc(...[, ...])

Sample a dataset along a circular arc and plot it.

StructuredGrid.plot_over_circular_arc_normal(center)

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

StructuredGrid.plot_over_line(pointa, pointb)

Sample a dataset along a high resolution line and plot.

StructuredGrid.point_data_to_cell_data([...])

Transform point data into cell data.

StructuredGrid.points_to_double()

Convert the points datatype to double precision.

StructuredGrid.probe(points[, tolerance, ...])

Sample data values at specified point locations.

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

Transform point data into cell data.

StructuredGrid.reconstruct_surface([nbr_sz, ...])

Reconstruct a surface from the points in this dataset.

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

Reflect a dataset across a plane.

StructuredGrid.remove_cells(ind[, inplace])

Remove cells.

StructuredGrid.rename_array(old_name, new_name)

Change array name by searching for the array then renaming it.

StructuredGrid.rotate_vector(vector, angle)

Rotate mesh about a vector.

StructuredGrid.rotate_x(angle[, point, ...])

Rotate mesh about the x-axis.

StructuredGrid.rotate_y(angle[, point, ...])

Rotate mesh about the y-axis.

StructuredGrid.rotate_z(angle[, point, ...])

Rotate mesh about the z-axis.

StructuredGrid.sample(target[, tolerance, ...])

Resample array data from a passed mesh onto this mesh.

StructuredGrid.sample_over_circular_arc(...)

Sample a dataset over a circular arc.

StructuredGrid.sample_over_circular_arc_normal(center)

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

StructuredGrid.sample_over_line(pointa, pointb)

Sample a dataset onto a line.

StructuredGrid.save(filename[, binary, texture])

Save this vtk object to file.

StructuredGrid.scale(xyz)

Scale the mesh.

StructuredGrid.select_enclosed_points(surface)

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

StructuredGrid.set_active_scalars(name[, ...])

Find the scalars by name and appropriately sets it as active.

StructuredGrid.set_active_tensors(name[, ...])

Find the tensors by name and appropriately sets it as active.

StructuredGrid.set_active_vectors(name[, ...])

Find the vectors by name and appropriately sets it as active.

StructuredGrid.shallow_copy(to_copy)

Create a shallow copy from a different dataset into this one.

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

Shrink the individual faces of a mesh.

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

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

StructuredGrid.slice_along_axis([n, axis, ...])

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

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

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

StructuredGrid.slice_orthogonal([x, y, z, ...])

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

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

Find, label, and split connected bodies/volumes.

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

Integrate a vector field to generate streamlines.

StructuredGrid.streamlines_evenly_spaced_2D([...])

Generate evenly spaced streamlines on a 2D dataset.

StructuredGrid.streamlines_from_source(source)

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

StructuredGrid.surface_indices([progress_bar])

Return the surface indices of a grid.

StructuredGrid.texture_map_to_plane([...])

Texture map this dataset to a user defined plane.

StructuredGrid.texture_map_to_sphere([...])

Texture map this dataset to a user defined sphere.

StructuredGrid.threshold([value, scalars, ...])

Apply a vtkThreshold filter to the input dataset.

StructuredGrid.threshold_percent([percent, ...])

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

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

Transform this mesh with a 4x4 transform.

StructuredGrid.translate(xyz)

Translate the mesh.

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

Return an all triangle mesh.

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

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

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

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

Attributes

StructuredGrid.active_normals

Return the active normals as an array.

StructuredGrid.active_scalars

Return the active scalars as an array.

StructuredGrid.active_scalars_info

Return the active scalar's association and name.

StructuredGrid.active_scalars_name

Return the name of the active scalars.

StructuredGrid.active_t_coords

Return or set the active texture coordinates on the points.

StructuredGrid.active_tensors

Return the active tensors array.

StructuredGrid.active_tensors_info

Return the active tensor's field and name: [field, name].

StructuredGrid.active_tensors_name

Return the name of the active tensor array.

StructuredGrid.active_vectors

Return the active vectors array.

StructuredGrid.active_vectors_info

Return the active vector's association and name.

StructuredGrid.active_vectors_name

Return the name of the active vectors array.

StructuredGrid.actual_memory_size

Return the actual size of the dataset object.

StructuredGrid.array_names

Return a list of array names for the dataset.

StructuredGrid.arrows

Return a glyph representation of the active vector data as arrows.

StructuredGrid.bounds

Return the bounding box of this dataset.

StructuredGrid.cell_arrays

Return vtkCellData as DataSetAttributes.

StructuredGrid.cell_data

Return vtkCellData as DataSetAttributes.

StructuredGrid.center

Return the center of the bounding box.

StructuredGrid.dimensions

Return a length 3 tuple of the grid's dimensions.

StructuredGrid.extent

Return the range of the bounding box.

StructuredGrid.field_arrays

Return vtkFieldData as DataSetAttributes.

StructuredGrid.field_data

Return FieldData as DataSetAttributes.

StructuredGrid.length

Return the length of the diagonal of the bounding box.

StructuredGrid.memory_address

Get address of the underlying VTK C++ object.

StructuredGrid.n_arrays

Return the number of arrays present in the dataset.

StructuredGrid.n_cells

Return the number of cells in the entire dataset.

StructuredGrid.n_points

Return the number of points in the entire dataset.

StructuredGrid.number_of_cells

Return the number of cells.

StructuredGrid.number_of_points

Return the number of points.

StructuredGrid.point_arrays

Return vtkPointData as DataSetAttributes.

StructuredGrid.point_data

Return vtkPointData as DataSetAttributes.

StructuredGrid.points

Return a reference to the points as a numpy object.

StructuredGrid.points_matrix

Points as a 4-D matrix, with x/y/z along the last dimension.

StructuredGrid.t_coords

Return the active texture coordinates on the points.

StructuredGrid.textures

Return a dictionary to hold compatible vtk.vtkTexture objects.

StructuredGrid.vectors

Return active vectors.

StructuredGrid.volume

Compute the volume of the point grid.

StructuredGrid.x

Return the X coordinates of all points.

StructuredGrid.y

Return the Y coordinates of all points.

StructuredGrid.z

Return the Z coordinates of all points.