Saving interactive Matplotlib figures


Question

Is there a way to save a Matplotlib figure such that it can be re-opened and have typical interaction restored? (Like the .fig format in MATLAB?)

I find myself running the same scripts many times to generate these interactive figures. Or I'm sending my colleagues multiple static PNG files to show different aspects of a plot. I'd rather send the figure object and have them interact with it themselves.

1
104
6/5/2016 7:49:07 AM

Accepted Answer

This would be a great feature, but AFAIK it isn't implemented in Matplotlib and likely would be difficult to implement yourself due to the way figures are stored.

I'd suggest either (a) separate processing the data from generating the figure (which saves data with a unique name) and write a figure generating script (loading a specified file of the saved data) and editing as you see fit or (b) save as PDF/SVG/PostScript format and edit in some fancy figure editor like Adobe Illustrator (or Inkscape).

EDIT post Fall 2012: As other's pointed out below (though mentioning here as this is the accepted answer), Matplotlib since version 1.2 has had allowed you to pickle figures. As the release notes state, it is an experimental feature and does not support saving a figure in one matplotlib version and opening in another. It's also generally insecure to restore a pickle from an untrusted source.

For sharing/later editing plots (that require significant data processing first and may need to be tweaked months later say during peer review for a scientific publication), I still recommend the workflow of (1) have a data processing script that before generating a plot saves the processed data (that goes into your plot) into a file, and (2) have a separate plot generation script (that you adjust as necessary) to recreate the plot. This way for each plot you can quickly run a script and re-generate it (and quickly copy over your plot settings with new data). That said, pickling a figure could be convenient for short term/interactive/exploratory data analysis.

23
5/24/2018 5:56:46 PM

I just found out how to do this. The "experimental pickle support" mentioned by @pelson works quite well.

Try this:

# Plot something
import matplotlib.pyplot as plt
fig,ax = plt.subplots()
ax.plot([1,2,3],[10,-10,30])

After your interactive tweaking, save the figure object as a binary file:

import pickle
pickle.dump(fig, open('FigureObject.fig.pickle', 'wb')) # This is for Python 3 - py2 may need `file` instead of `open`

Later, open the figure and the tweaks should be saved and GUI interactivity should be present:

import pickle
figx = pickle.load(open('FigureObject.fig.pickle', 'rb'))

figx.show() # Show the figure, edit it, etc.!

You can even extract the data from the plots:

data = figx.axes[0].lines[0].get_data()

(It works for lines, pcolor & imshow - pcolormesh works with some tricks to reconstruct the flattened data.)

I got the excellent tip from Saving Matplotlib Figures Using Pickle.


Licensed under: CC-BY-SA with attribution
Not affiliated with: Stack Overflow
Icon