General Utilities

core.utilities.VtkErrorCatcher([...])	Context manager to temporarily catch VTK errors.
core.utilities.axis_rotation(points, angle)	Rotate points by angle about an axis.
core.utilities.is_inside_bounds(point, bounds)	Check if a point is inside a set of bounds.
core.utilities.set_error_output_file(filename)	Set a file to write out the VTK errors.

Object Conversions or Wrapping

array_from_vtkmatrix(matrix)	Convert a vtk matrix to an array.
cubemap([path, prefix, ext])	Construct a cubemap from 6 images from a directory.
cubemap_from_filenames(image_paths)	Construct a cubemap from 6 images.
image_to_texture(image)	Convert pyvista.ImageData to a pyvista.Texture.
is_pyvista_dataset(obj)	Return True if the object is a PyVista wrapped dataset.
numpy_to_texture(image)	Convert a NumPy image array to a pyvista.Texture.
pyvista_ndarray(*args, **kwargs)	A ndarray which references the owning dataset and the underlying vtk array.
vtkmatrix_from_array(array)	Convert a numpy.ndarray or array-like to a vtk matrix.
wrap(dataset)	Wrap any given VTK data object to its appropriate PyVista data object.

Features

cartesian_to_spherical(x, y, z)	Convert 3D Cartesian coordinates to spherical coordinates.
cell_quality_info(cell_type, quality_measure)	Return information about a cell's quality measure.
create_grid(dataset[, dimensions])	Create a uniform grid surrounding the given dataset.
grid_from_sph_coords(theta, phi, r)	Create a structured grid from arrays of spherical coordinates.
merge(datasets[, merge_points, ...])	Merge several datasets.
perlin_noise(amplitude, freq, phase)	Return the implicit function that implements Perlin noise.
principal_axes(points, *[, return_std])	Compute the principal axes of a set of points.
sample_function(function[, bounds, dim, ...])	Sample an implicit function over a structured point set.
spherical_to_cartesian(r, phi, theta)	Convert Spherical coordinates to 3D Cartesian coordinates.
transform_vectors_sph_to_cart(theta, phi, r, ...)	Transform vectors from spherical (r, phi, theta) to cartesian coordinates (z, y, x).
voxelize(mesh[, density, check_surface, ...])	Voxelize mesh to UnstructuredGrid.
voxelize_volume(mesh[, density, ...])	Voxelize mesh to create a RectilinearGrid voxel volume.

File IO

from_meshio(mesh)	Convert a meshio mesh instance to a PyVista mesh.
get_ext(filename)	Extract the extension of the filename.
is_meshio_mesh(obj)	Test if passed object is instance of meshio.Mesh.
read(filename[, force_ext, file_format, ...])	Read any file type supported by vtk or meshio.
read_exodus(filename[, animate_mode_shapes, ...])	Read an ExodusII file ('.e' or '.exo').
read_grdecl(filename[, elevation, ...])	Read a GRDECL file ('.GRDECL').
read_meshio(filename[, file_format])	Read any mesh file using meshio.
read_texture(filename[, progress_bar])	Load a texture from an image file.
save_meshio(filename, mesh[, file_format])	Save mesh to file using meshio.
set_pickle_format(format)	Set the format used to serialize pyvista.DataObject when pickled.
set_vtkwriter_mode(vtk_writer[, use_binary, ...])	Set any vtk writer to write as binary or ascii.
to_meshio(mesh)	Convert a PyVista mesh to a meshio mesh instance.

Mesh Creation

CellType(*values)	Define types of cells.
fit_line_to_points(points, *[, resolution, ...])	Fit a line to points using its principal_axes().
fit_plane_to_points(points[, return_meta, ...])	Fit a plane to points using its principal_axes().
lines_from_points(points[, close])	Make a connected line set given an array of points.
vector_poly_data(orig, vec)	Create a pyvista.PolyData object composed of vectors.
vtk_points(points[, deep, force_float, ...])	Convert numpy array or array-like to a vtkPoints object.

Array Access

cell_array(obj, name)	Return cell array of a pyvista or vtk object.
convert_array(arr[, name, deep, array_type])	Convert a NumPy array to a vtkDataArray or vice versa.
field_array(obj, name)	Return field data of a pyvista or vtk object.
get_array(mesh, name[, preference, err])	Search point, cell and field data for an array.
point_array(obj, name)	Return point array of a pyvista or vtk object.

Transformations

Transform(*args, **kwargs)

Describes linear transformations via a 4x4 matrix.

Image Comparison and Regression

compare_images(im1, im2[, threshold, use_vtk])

Compare two different images of the same size.

Colors

Color(*args, **kwargs)	Helper class to convert between different color representations used in the pyvista library.
ColorLike	Any object convertible to a Color.

Named colors supported by Color, Plotter, and other plotting-related methods:

• Named Colors
  • Sorted by Name
  • Sorted by Color

Named colormaps supported by LookupTable, Plotter, and other plotting-related methods:

• Named Colormaps
  • Linear (Sequential)
  • Diverging
  • Multi-Sequential
  • Cyclic
  • Categorical (Qualitative)
  • Miscellaneous
• CET Colormaps
  • Linear (Sequential)
  • Diverging
  • Cyclic
  • Rainbow
  • Isoluminant

Miscellaneous

set_new_attribute(obj, name, value)	Set a new attribute for this object.
allow_new_attributes	Context manager to control setting new attributes on PyVista classes.
start_xvfb([wait, window_size])	Start the virtual framebuffer Xvfb.
Report([additional, ncol, text_width, sort, ...])	Generate a PyVista software environment report.
vtk_verbosity	Context manager to set VTK verbosity level.
vtk_snake_case	Context manager to control access to VTK's pythonic snake_case API.

PyVista Version Information

The PyVista library provides a way of getting the version installed in your environment.

>>> # Output the version of PyVista.
>>> import pyvista
>>> pyvista.version_info
(0, 44, 0)

VTK Version Information

The PyVista library is heavily dependent on VTK and provides an easy way of getting the version of VTK in your environment.

>>> # Output the version of VTK.
>>> import pyvista
>>> pyvista.vtk_version_info
VTKVersionInfo(major=9, minor=1, micro=0)

>>> # Get the major version of VTK
>>> pyvista.vtk_version_info.major
9