Examples — PyVista 0.31.dev0 documentation

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¶

Parametric Geometric Objects¶

Create Point Cloud¶

Create PolyData¶

Creating a Spline¶

Creating a Structured Surface¶

Drape 2D Surface From Line¶

Create Triangulated Surface¶

Creating a Uniform Grid¶

Creating an Unstructured Grid¶

Working with a glTF Files¶

Read FEniCS/Dolfin Meshes¶

Load and Plot from a File¶

Read Image Files¶

Parallel Files¶

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¶

Computing Surface Normals¶

Distance Between Two Surfaces¶

Extract Cells Inside Surface¶

Plotting Glyphs (Vectors or PolyData)¶

Table of Glyphs¶

Compute Gradients of a Field¶

Interpolating¶

Computing Mesh Quality¶

Sample Function: Perlin Noise in 2D¶

Sample Function: Perlin Noise in 3D¶

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 anther 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

Background Image¶

Clearing a Mesh or the Entire Plot¶

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¶

Physically Based Rendering¶

Plot Scalars Over a Circular Arc¶

Plot Over Line¶

Customize Scalar Bars¶

Saving Screenshots¶

Types of Shading¶

Silhouette Highlight¶

Plot data in spherical coordinates¶

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: