Examples#

Here is a gallery of several examples demonstrating what PyVista can do!

All of these examples are live and available on MyBinder.

Mesh Creation#

These examples demo how to read various file types into PyVista mesh objects, create meshes from NumPy arrays, and how to create primitive geometric objects like spheres, arrows, cubes, ellipsoids and more! Once a mesh is loaded, it is ready for plotting with just a few lines of code - explore these examples to get started with using PyVista for your data.

Creating an Explicit Structured Grid

Geometric Objects

Create a Kochanek Spline

Parametric Geometric Objects

Pixel Art of ALIEN MONSTERS

Creating a Structured Surface

Drape 2D Surface From Line

Create Triangulated Surface

Plot Truss-like FEA Solution with Cylinders

Creating a Uniform Grid

Creating an Unstructured Grid

Linear Cells

Working with glTF Files

Working with VRML Files

Read FEniCS/Dolfin Meshes

Load and Plot from a File

Read Image Files

Parallel Files

Load data using a Reader

Terrain Following Mesh

Wrapping Other Objects

Filtering#

These examples show case various mesh analysis and filtering routines present in the Filters module. Explore these demos to perform tasks such as:

Slicing and cutting meshes
Computing mesh properties like volume, area, and surface normals
Mesh decimation
Extract regions of one mesh using another mesh’s surface
Ray tracing through surface meshes
Resampling and interpolating scalar/vector values across meshes
Integrating a vector field to generate streamlines
Smoothing surfaces

Boolean Operations

Extract Cell Centers

Clipping with a Surface

Clipping with Planes & Boxes

Collision

Computing Surface Normals

Distance Between Two Surfaces

Extract Cells Inside Surface

Plotting Glyphs (Vectors or PolyData)

Table of Glyphs

Compute Gradients of a Field

Fast Fourier Transform with Perlin Noise

Fast Fourier Transform

Integrate Data

Interpolating

Computing Mesh Quality

Sample Function: Perlin Noise in 2D

Sample Function: Perlin Noise in 3D

Surface Reconstruction

Using Common Filters

Voxelize a Surface Mesh

Warping by Vectors

Plotting#

These examples show case many of the possibilities for altering how you display spatial data. Explore these examples to learn how to leverage our powerful 3D plotting routines to perform tasks like:

Color mapping scalar values with matplotlib colormaps
Creating animations as GIFs or movie files
Showing the edges and nodes of different mesh types
Use sophisticated lighting techniques like smooth shading or Eye Dome Lighting
Glyph a vector or scalar field on a mesh (place/orient a mesh on another mesh’s nodes and scale/orient based on data values)
Label points in 3D space along side your meshes
Creating side-by-side comparisons
Making a dataset transparent or using a scalar value to map opacity
Adding textures/images draped over a mesh (texture mapping)
Rendering a depth image

Clearing a Mesh or the Entire Plot

Colormap Choices

Composite Picking

Depth Peeling

Depth of Field Plotting

Label based on Distance on Line

Show Edges

Eye Dome Lighting

Plot with Floors

Hide Cells with Ghosting

Create a GIF Movie

Render a depth image

Interpolate Before Mapping

Moving Isovalue

Label Points

Lighting Properties

Linked Views in Subplots

Picking Meshes

Create a MP4 Movie

Save a Movie Using Glyphs

Create a GIF Movie of a Static Object with a Moving Colormap

Physically Based Rendering

Plot Scalars Over a Circular Arc

Plot Over Line

Point Cell Scalars

Picking points on a mesh

Customize Scalar Bars

Saving Screenshots

Types of Shading

Silhouette Highlight

Plot data in spherical coordinates

Surface Space Ambient Occlusion

Picking a Point on the Surface of a Mesh

Applying Textures

Control Global and Local Plotting Themes

Topographic Map

Plot Vector Component

Volume Rendering

Widgets#

PyVista has several widgets that can be added to the rendering scene to control filters like clipping, slicing, and thresholding - specifically there are widgets to control the positions of boxes, planes, and lines or slider bars which can all be highly customized through the use of custom callback functions.

Here we’ll take a look at the various widgets, some helper methods that leverage those widgets to do common tasks, and demonstrate how to leverage the widgets for user defined tasks and processing routines.

Box Widget

Checkbox Widget

Line Widget

Multiple Slider Widgets

Lighting#

These examples demonstrate how to take fine-tuned control over lighting conditions in a scene. Explore them to learn how to go beyond the default lighting setup to truly bring out the best of your visualization: