Speeding up with WebGL¶

What is WebGL?¶

WebGL is a JavaScript API that allows rendering content in the browser via the Graphics Processing Unit (GPU), without the need for plugins. WebGL is standardized and available in all modern browsers.

How to enable WebGL¶

To enable WebGL, set the plot’s webgl property to True:

p = Plot(webgl=True)  # for the glyph API
p = figure(webgl=True)  # for the plotting API

Alternatively, WebGL can be explicitly enabled or disabled on a page by adding ?webgl=1 or #webgl=0 to the URL.

Support¶

Only a subset of Bokeh’s objects are capable of rendering in WebGL. Currently this is limited to the line, circle marker, and square marker. We plan to extend the support to more markers, lines, and other objects such as maps. You can safely combine multiple glyphs in a plot, of which some are rendered in WebGL, and some are not.

The performance improvements when using WebGL varies per situation. Due to overhead in some places of BokehJS, we can currently not benefit from the full speed that you might expect from WebGL. This is also something we plan to improve over time.

Notes¶

• Glyphs drawn using WebGL are drawn on top of glyphs that are not drawn in WebGL.
• When the scale is non-linear (e.g. log), the system falls back to 2D rendering.
• Making a selections of markers on Internet Explorer will reduce the size of the markers to 1 pixel (looks like a bug in IE).

Examples¶

import numpy as np

from bokeh.plotting import figure, show, output_file

N = 10000

x = np.random.normal(0, np.pi, N)
y = np.sin(x) + np.random.normal(0, 0.2, N)

output_file("scatter10k.html", title="scatter 10k points (no WebGL)")

p = figure(webgl=False)
p.scatter(x,y, alpha=0.1)
show(p)

import numpy as np

from bokeh.plotting import figure, show, output_file

N = 10000

x = np.random.normal(0, np.pi, N)
y = np.sin(x) + np.random.normal(0, 0.2, N)

output_file("scatter10k.html", title="scatter 10k points (with WebGL)")

p = figure(webgl=True)
p.scatter(x,y, alpha=0.1)
show(p)

import numpy as np

from bokeh.plotting import figure, show, output_file

N = 10000

x = np.linspace(0, 10*np.pi, N)
y = np.cos(x) + np.sin(2*x+1.25) + np.random.normal(0, 0.001, (N, ))

output_file("line10k.html", title="line10k.py example")

p = figure(title="A line consisting of 10k points", webgl=True)
p.line(x, y, color="#22aa22", line_width=3)
show(p)