Saving interactive Matplotlib figures

Good question. Here is the doc text from pylab.save:

pylab no longer provides a save function, though the old pylab
function is still available as matplotlib.mlab.save (you can still
refer to it in pylab as “mlab.save”). However, for plain text
files, we recommend numpy.savetxt. For saving numpy arrays,
we recommend numpy.save, and its analog numpy.load, which are
available in pylab as np.save and np.load.

Why not just send the Python script? MATLAB’s .fig files require the recipient to have MATLAB to display them, so that’s about equivalent to sending a Python script that requires Matplotlib to display.

Alternatively (disclaimer: I haven’t tried this yet), you could try pickling the figure:

import pickle
output = open('interactive figure.pickle', 'wb')
pickle.dump(gcf(), output)
output.close()

As of Matplotlib 1.2, we now have experimental pickle support. Give that a go and see if it works well for your case. If you have any issues, please let us know on the Matplotlib mailing list or by opening an issue on github.com/matplotlib/matplotlib.

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.

I figured out a relatively simple way (yet slightly unconventional) to save my matplotlib figures. It works like this:

import libscript

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2*np.pi*t)

#<plot>
plt.plot(t, s)
plt.xlabel('time (s)')
plt.ylabel('voltage (mV)')
plt.title('About as simple as it gets, folks')
plt.grid(True)
plt.show()
#</plot>

save_plot(fileName='plot_01.py',obj=sys.argv[0],sel='plot',ctx=libscript.get_ctx(ctx_global=globals(),ctx_local=locals()))

with function save_plot defined like this (simple version to understand the logic):

def save_plot(fileName='',obj=None,sel='',ctx={}):
    """
    Save of matplolib plot to a stand alone python script containing all the data and configuration instructions to regenerate the interactive matplotlib figure.

    Parameters
    ----------
    fileName : [string] Path of the python script file to be created.
    obj : [object] Function or python object containing the lines of code to create and configure the plot to be saved.
    sel : [string] Name of the tag enclosing the lines of code to create and configure the plot to be saved.
    ctx : [dict] Dictionary containing the execution context. Values for variables not defined in the lines of code for the plot will be fetched from the context.

    Returns
    -------
    Return ``'done'`` once the plot has been saved to a python script file. This file contains all the input data and configuration to re-create the original interactive matplotlib figure.
    """
    import os
    import libscript

    N_indent=4

    src=libscript.get_src(obj=obj,sel=sel)
    src=libscript.prepend_ctx(src=src,ctx=ctx,debug=False)
    src='n'.join([' '*N_indent+line for line in src.split('n')])

    if(os.path.isfile(fileName)): os.remove(fileName)
    with open(fileName,'w') as f:
        f.write('import sysn')
        f.write('sys.dont_write_bytecode=Truen')
        f.write('def main():n')
        f.write(src+'n')

        f.write('if(__name__=="__main__"):n')
        f.write(' '*N_indent+'main()n')

return 'done'

or defining function save_plot like this (better version using zip compression to produce lighter figure files):

def save_plot(fileName='',obj=None,sel='',ctx={}):

    import os
    import json
    import zlib
    import base64
    import libscript

    N_indent=4
    level=9#0 to 9, default: 6
    src=libscript.get_src(obj=obj,sel=sel)
    obj=libscript.load_obj(src=src,ctx=ctx,debug=False)
    bin=base64.b64encode(zlib.compress(json.dumps(obj),level))

    if(os.path.isfile(fileName)): os.remove(fileName)
    with open(fileName,'w') as f:
        f.write('import sysn')
        f.write('sys.dont_write_bytecode=Truen')
        f.write('def main():n')
        f.write(' '*N_indent+'import base64n')
        f.write(' '*N_indent+'import zlibn')
        f.write(' '*N_indent+'import jsonn')
        f.write(' '*N_indent+'import libscriptn')
        f.write(' '*N_indent+'bin="'+str(bin)+'"n')
        f.write(' '*N_indent+'obj=json.loads(zlib.decompress(base64.b64decode(bin)))n')
        f.write(' '*N_indent+'libscript.exec_obj(obj=obj,tempfile=False)n')

        f.write('if(__name__=="__main__"):n')
        f.write(' '*N_indent+'main()n')

return 'done'

This makes use a module libscript of my own, which mostly relies on modules inspect and ast. I can try to share it on Github if interest is expressed (it would first require some cleanup and me to get started with Github).

The idea behind this save_plot function and libscript module is to fetch the python instructions that create the figure (using module inspect), analyze them (using module ast) to extract all variables, functions and modules import it relies on, extract these from the execution context and serialize them as python instructions (code for variables will be like t=[0.0,2.0,0.01] … and code for modules will be like import matplotlib.pyplot as plt …) prepended to the figure instructions. The resulting python instructions are saved as a python script whose execution will re-build the original matplotlib figure.

As you can imagine, this works well for most (if not all) matplotlib figures.

If you are looking to save python plots as an interactive figure to modify and share with others like MATLAB .fig file then you can try to use the following code. Here z_data.values is just a numpy ndarray and so you can use the same code to plot and save your own data. No need of using pandas then.

The file generated here can be opened and interactively modified by anyone with or without python just by clicking on it and opening in browsers like Chrome/Firefox/Edge etc.

import plotly.graph_objects as go
import pandas as pd

z_data=pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/api_docs/mt_bruno_elevation.csv')

fig = go.Figure(data=[go.Surface(z=z_data.values)])

fig.update_layout(title='Mt Bruno Elevation', autosize=False,
                  width=500, height=500,
                  margin=dict(l=65, r=50, b=65, t=90))

fig.show()
fig.write_html("testfile.html")