Bokeh is a Python interactive visualization library that targets modern web browsers for presentation.
This document can be compiled to HTML with
```
stitch ex_bokeh.txt -o ex_bokeh.html --no-self-contained
```The easiest way to use stitch & Bokeh together is with the Bokeh.output_notebook method.
In [1]: from bokeh.plotting import figure, show, output_notebook
...:
...: # prepare some data
...: x = [0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0]
...: y0 = [i**2 for i in x]
...: y1 = [10**i for i in x]
...: y2 = [10**(i**2) for i in x]
...:
...: output_notebook()In [2]: # create a new plot
...: p = figure(
...: tools="pan,box_zoom,reset,save",
...: y_axis_type="log", y_range=[0.001, 10**11], title="log axis example",
...: x_axis_label='sections', y_axis_label='particles'
...: )
...:
...: # add some renderers
...: p.line(x, x, legend="y=x")
...: p.circle(x, x, legend="y=x", fill_color="white", size=8)
...: p.line(x, y0, legend="y=x^2", line_width=3)
...: p.line(x, y1, legend="y=10^x", line_color="red")
...: p.circle(x, y1, legend="y=10^x", fill_color="red", line_color="red", size=6)
...: p.line(x, y2, legend="y=10^x^2", line_color="orange", line_dash="4 4")
...:
...: # show the results
...: show(p)See also Bokeh's tools for embedding the HTML and javascript necessary to get a figure to show up in HTML output.