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copied!<p>I don't know of any native Matplotlib file format which includes your data; in fact, I'm not sure the Matploblib objects even have a write function defined.</p> <p>What I do instead to simulate the Matlab .fig concept is to save the processed data (as a numpy array, or pickled) and run a separate .py script to recreate the Matplotlib plots.</p> <p>So in steps:</p> <ol> <li>Process your data and make some pretty plots until you are fully content</li> <li>Save/pickle your processed data as close to the plot commands as possible (you might even want to store the data going into a histogram if making the histogram takes a long time)</li> <li>Write a new script in which you import the data and copy/paste the plotting commands from the original script</li> </ol> <p>It is a bit clumsy, but it works. If you really want, you could embed the pickled data as a string in your plotting script (<a href="https://stackoverflow.com/questions/1887968/embed-pickle-or-arbitrary-data-in-python-script">Embed pickle (or arbitrary) data in python script</a>). This gives you the benefit of working with a single python script containing both the data as well as the plotting code.</p> <h2>Edit</h2> <p>You can check for the existence of your stored processed data file and skip the processing steps if this file exists. So:</p> <pre><code>if not processed_data.file exists: my_data = process_raw_data() else: my_data = read_data_from_file(processed_data.file) plot(my_data) </code></pre> <p>In this way, you can have one script for both creating the graph in the first place, and re-plotting the graph using pre-processed data.</p> <p>You might want to add a runtime argument for forcing a re-processing of the data in case you change something to the processing script and don't want to manually remove your processed data file.</p>

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