Plotting

When plotting with the interactive rendering windows in VTK, several keyboard shortcuts are available:

Key		Action
Linux/Windows	Mac
q		Close the rendering window
f		Focus and zoom in on a point
v		Isometric camera view
w		Switch all datasets to a wireframe representation
r		Reset the camera to view all datasets
s		Switch all datasets to a surface representation
shift+click or middle-click	shift+click	Pan the rendering scene
left-click	cmd+click	Rotate the rendering scene in 3D
ctrl+click		Rotate the rendering scene in 2D (view-plane)
mouse-wheel or right-click	ctl+click	Continuously zoom the rendering scene
shift+s		Save a screenshot (only on BackgroundPlotter)
shift+c		Enable interactive cell selection/picking
up/down		Zoom in and out
+/-		Increase/decrease the point size and line widths

Plotting in a Jupyter Notebook

Static and interactive inline plots are possible using a Jupyter notebook. The code snippet below will create a static screenshot of the rendering and display it in the Jupyter notebook:

import pyvista as pv
sphere = pv.Sphere()
sphere.plot(jupyter_backend='static')

It is possible to use the Plotter class as well.

plotter = pv.Plotter(notebook=True)
plotter.add_mesh(sphere)
plotter.show(jupyter_backend='static')

Additionally, you can generate interactive plots by leveraging our jupyter plotting backend trame. You can even use it to create interactive documentation online.

plotter = pv.Plotter(window_size=(600, 400))
plotter.background_color = 'w'
plotter.enable_anti_aliasing()
plotter.add_mesh(sphere, color='lightblue', show_edges=True)
plotter.show(jupyter_backend='static')

For more details, see the section on Jupyter Notebook Plotting.

Background Plotting

PyVista provides a plotter that enables users to create a rendering window in the background that remains interactive while the user performs their processing. This creates the ability to make a rendering scene and interactively add or remove datasets from the scene as well as has some useful menu functions for common scene manipulation or export tasks. To get started, try instantiating the pyvistaqt.BackgroundPlotter:

import pyvista as pv
import pyvistaqt as pvqt
from pyvista import examples

dataset = examples.load_hexbeam()

p = pvqt.BackgroundPlotter()
p.add_mesh(dataset)
p.show_bounds(grid=True, location='back')

Plot Time Series Data

This example outlines how to plot data where the spatial reference and data values change through time:

from threading import Thread
import time
import numpy as np
import pyvista as pv
import pyvistaqt as pvqt
from pyvista import examples


globe = examples.load_globe()
texture = examples.load_globe_texture()
globe.point_data['scalars'] = np.random.rand(globe.n_points)
globe.set_active_scalars('scalars')


plotter = pvqt.BackgroundPlotter()
plotter.add_mesh(globe, lighting=False, show_edges=True, texture=texture, scalars='scalars')
plotter.view_isometric()

# shrink globe in the background
def shrink():
    for i in range(50):
        globe.points *= 0.95
        # Update scalars
        globe.point_data['scalars'] = np.random.rand(globe.n_points)
        time.sleep(0.5)

thread = Thread(target=shrink)
thread.start()