Damon McDougall

Improving matplotlib turnaround time with IPython

When I produce a plot, I’m working in vim on a python script that I can save and reuse later for reproducibility. My workflow goes something like this:

  1. Write some basic plotting script and have the script save the plot as a pdf file.
  2. Run the script.
  3. Open the plot and decide something needs tweaking (colours, fonts, labels, etc).
  4. Go back to vim and make the tweak. Save the script.
  5. Re-run the script.
  6. Go to 3.

I do this until I am satisfied my plot will look nice in my paper/slides/poster. This is kind of a pain. It takes a lot of time because I’m a perfectionist when it comes to plotting.

Using the matplotlib GUI backends interactively from an IPython session means I can tweak my plot and get immediate visual feedback. This makes steps 3. and 4. above (sans vim) much quicker. I can also save my plot from the GUI as whatever file type I like. The downside is once I save the plot from the GUI and close my IPython session, I have lost all the commands that created the plot. I’ve lost the reproducibility.

This is what a typical session might look like:

In [1]: import matplotlib

In [2]: matplotlib.use('qt4agg')

In [3]: import matplotlib.pyplot as plt

In [4]: plt.ion()

In [5]: fig = plt.figure()

In [6]: ax = fig.add_subplot(1, 1, 1)

In [7]: ax.plot([1, 2, 3])
Out[7]: [<matplotlib.lines.Line2D at 0x11178f5d0>]

In [8]: plt.draw()  # Now look at the plot, decide tweaks

In [9]: # Some tweak here...

In [10]: plt.draw()  # Look again.  Decide it's ok.

In [11]: plt.savefig('high_quality.pdf')

In [12]: # End session
Do you really want to exit ([y]/n)?

To recover the reproducibility aspect, I’d like to be able to save everything I did to a file (a python script I can re-run later to reproduce the figure).

Turns out, there’s an IPython magic function that does this that I didn’t know about. Here’s what a typical IPython session would look like using the %save magic:

In [1]: import matplotlib

In [2]: matplotlib.use('qt4agg')

In [3]: import matplotlib.pyplot as plt

In [4]: plt.ion()

In [5]: fig = plt.figure()

In [6]: ax = fig.add_subplot(1, 1, 1)

In [7]: ax.plot([1, 2, 3])
Out[7]: [<matplotlib.lines.Line2D at 0x11178f5d0>]

In [8]: plt.draw()  # Now look at the plot, decide tweaks

In [9]: # Some tweak here...

In [10]: plt.draw()  # Look again.  Decide it's ok.

In [11]: plt.savefig('high_quality.pdf')

In [12]: %save plotting_script.py 1-11

Now I have all the commands I ran in the plotting_script.py. I can rerun this and produce exactly the same plot.