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---
title: "PyVista: 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK)"
tags:
- Python
- visualization
- 3D
authors:
- name: Bane Sullivan
orcid: 0000-0001-8628-4566
affiliation: 1
- name: Alexander A. Kaszynski
orcid: 0000-0002-8232-7212
affiliation: 2
affiliations:
- name: Department of Geophysics, Colorado School of Mines, Golden, CO, USA
index: 1
- name: Universal Technology Corporation, Dayton, OH, USA
index: 2
date: 10 February 2019
bibliography: paper.bib
---
# Summary
There are several options for 3D visualization in Python, a few notable projects
include Matplotlib [@matplotlib], Mayavi [@mayavi], the yt Project [@ytproject],
and the Visualization Toolkit (VTK) [@vtkbook].
However, few open-source packages are capable of handling large,
spatially-referenced datasets and some are powerful yet have inherently complex
application programming interfaces (APIs), which might create a barrier to entry
for new users.
Notably, VTK is a powerful scientific visualization software library, and with
Python bindings, it combines the speed of C++ with the rapid prototyping of
Python.
Despite this, VTK code programmed in Python using the base VTK Python package
is unnecessarily complicated as its API binds existing C++ calls.
The PyVista Python package provides a concise, well-documented interface
exposing VTK’s powerful visualization backend; enabling researchers to
rapidly explore large datasets, communicate their spatial findings, and
facilitate reproducibility. PyVista further seeks to simplify standard mesh
creation and plotting routines without compromising on the speed of the C++
VTK backend.
Plotting VTK datasets using only the VTK Python package or a similar
visualization library is often an ambitious programming endeavor.
Reading a VTK supported file and plotting it requires a user to write a
complicated sequence of routines to render the data object while
having to remember which VTK classes to use for file reading and dataset mapping.
PyVista includes plotting routines that are intended to be intuitive and
highly controllable with syntax and keyword arguments similar to Matplotlib
[@matplotlib]. These plotting routines are defined to make the process of
visualizing spatially referenced data straightforward and easily implemented
by novice programmers; streamlining the process for creating integrated scenes
like that shown in Figure 1.
VTK implements an object-oriented approach to 3D visualization [@vtkbook],
and PyVista adheres to that underlying structure to provide an API that
expands on VTK's data types. These expanded, wrapped types hold methods and
attributes for quickly accessing scalar arrays, inspecting properties of
the dataset, or using filtering algorithms to transform datasets.
PyVista wrapped objects have a suite of common filters ready for immediate
use directly on the objects. These filters are commonly used algorithms in the
VTK library that have been made more accessible by binding a method to control
that algorithm directly onto all PyVista datasets, providing a shared set of
functionality. Through the use of these bound filtering methods, powerful VTK
algorithms can be leveraged and controlled via keyword arguments designed to
be intuitive for novice users.
At its core, PyVista is a pure Python helper module for VTK
that interfaces back to VTK data objects through NumPy [@numpy]
and direct array access adhering to VTK's object-oriented approach to
3D visualization [@vtkbook].
The PyVista Python package provides an accessible and intuitive interface back
to the VTK library to facilitate rapid prototyping, analysis, and visual
integration of spatially referenced datasets.
Figure 1 demonstrates an integrated scene of geospatial data
generated by PyVista; to learn more about how this visualization was created,
please visit PVGeo's FORGE project website
([forge.pvgeo.org](http://forge.pvgeo.org)).
## Mentions
PyVista is used extensively by the Air Force Research Labs (AFRL) for
data visualization and plotting in research articles including
figures visualizing 3D tessellated models generated from structured
light optical scanner and results from finite element analysis.
AFRL publications leveraging PyVista for 3D visualization include:
[@Gillaugh2017], [@Brown2018], [@Brown2018_pro], [@Beck2018_subspace],
[@Kaszynski2018], [@Gillaugh2018_art], [@Gillaugh2019]
PVGeo ([github.com/OpenGeoVis/PVGeo](https://github.com/OpenGeoVis/PVGeo)) is
a Python package of VTK-based algorithms to analyze geoscientific data and models.
PyVista is used to make the inputs and outputs of PVGeo's algorithms more
accessible and to streamline the process of visualizing geoscientific data.
## References
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