Image VisualizationΒΆ
It is often useful to incorporate bitmap images into a visualization. To
facilitate this, Toyplot provides toyplot.canvas.Canvas.image()
and toyplot.image() functions, which can display image data
supplied in a couple of different formats. Note that as a visualization
library Toyplot does not provide functionality for reading, writing,
or manipulating images - you should do that with libraries such as
PIL or scikit-image instead.
For example, you can pass any PIL.Image.Image directly to
Toyplot:
import PIL.Image
import toyplot
image = PIL.Image.open("../artwork/toyplot.png")
canvas, mark = toyplot.image(image, width=300)
As always, the width parameter in the above example is the width of
the Toyplot canvas. The image is then scaled uniformly to fit. Of
course, you can use any Canvas Layout method you like to
combine images and marks together on the canvas:
import numpy
canvas = toyplot.Canvas(width=600, height=300)
mark = canvas.image(image, grid=(1,2,0))
axes = canvas.cartesian(grid=(1,2,1))
axes.plot(numpy.linspace(0, 1) ** 2)
canvas.text(150, 250, "( Toyplot Logo )", style={"font-size":"14px"});