Matplotlib Rendering Support

Matplotlib Support. See here for the vast amount of matplotlib's plotting features.

Requirements

You need to have pip/conda install matplotlib and optionally also pip/conda install numpy within your environment.

Examples

Works within Admonitions

LP Source:

 ```python lp:python addsrc eval=always
 import matplotlib.pyplot as plt
 import numpy as np
 x = np.linspace(0, 2, 100)
 plt.plot(x, x, label='linear')
 plt.plot(x, x**2, label='quadratic')
 plt.plot(x, x**3, label='cubic')
 plt.xlabel('x label')
 plt.ylabel('y label')
 plt.title("Simple Plot")
 plt.legend()
 show(plt, fn='img/testplot.svg')
 show('??? hint "You can create *markdown* via the `show()` function"')
 show('    this was created from the python block')
 ```

Result:

You can create markdown via the show() function

this was created from the python block

• The plot is created as svg directly into your html site directory, i.e. will not show up within your docs tree.

• If for some reason you can not create the svg on the system where you build your docs:

  1. supply a fn (filename) argument to the show function, relative to your page, e.g. show(plt, fn='img/myplot'). This will result in the plot created within your docs dir, so that you can commit it, from a system, where you can build the docs.
  2. commit the cache file
  3. optionally, set the eval policy to always page wide, and to on_change for the block, if you want the other blocks on the page to be evaluated on the build system (e.g. for assertion checks).

Implicit plt.clf() (clear plot) call

The show function applied to a pyplot will call plt.clear() after having created the svg. This is necessary since we exec the lp code in process (of the mkdocs build but also mkdocs serve). For serve this is a problem since subsequent runs after page edits will therefore remember the imported pyplot module, with all state.

If you do NOT want to clear the plot but subsequently further extend it, then add clf=False: show(plt, clf=False)