Converting matplotlib plots to Igor Pro graphs

In my experience dealing with PhD students, who know python well, their difficulty transitioning to Igor Pro for data visualization and analysis is that it's not easy to reproduce a matplotlib graph as an Igor Pro graph. 

Although they realize the power of Igor Pro once the graph is displayed and we have cursors, zoom, pan, fitting, etc, the process of converting numpy data into Igor Pro and then displaying it is complex.

Python integration in Igor Pro 10 is great progress towards leveraging the benefits of both, but I would like an additional feature to convert a matplotlib graph into an Igor Pro graph.  This could be implemented as

1. Standalone python module which exports a graph `pxp` given a matplotlib plot

2. In an Igor Pro 10 python session, a function in the `igorpro` module which, given a matplotlib plot object, generates the Window recreation procedure to create the corresponding graph 

This is not an easy task as matplotlib is a huge module, but the conversion module could be built incrementally, focusing on the simplest types of plots first.  For Python users who are adept with matplotlib, seeing the equivalent Igor Pro code to generate their plot would help them learn Igor Pro.

I would be happy to help develop this.

Here's an example, coded with Claude:

    # Create a sample matplotlib plot
    x = np.linspace(0, 10, 100)
    y1 = np.sin(x)
    y2 = np.cos(x) * 0.5
    
    fig, ax = plt.subplots(figsize=(6, 4))
    ax.plot(x, y1, 'r-', linewidth=2, label='sin(x)')
    ax.plot(x, y2, 'b--', marker='o', markersize=4, 
            markevery=10, label='0.5*cos(x)')
    ax.set_xlabel('Time (s)')
    ax.set_ylabel('Amplitude')
    ax.grid(True)
    ax.legend()
    
    # Convert to Igor Pro format
    matplotlib_to_igor_itx(fig, 'example_output.itx', 'ExampleGraph')

 

Python plot (454.37 KB) Converted igor pro graph (453.42 KB)