Bokeh Integration

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()
Loading BokehJS ...
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.