How Can I Efficiently Update Matplotlib Plots in a Tkinter Application After Changing the Time Scale?

Updating Plots in Matplotlib for Tkinter

You've encountered difficulties in updating plots in Matplotlib within a Tkinter application. You're allowing users to adjust the time scale units, which necessitates recalculating and updating the plot without creating new plots.

Approach 1: Clearing and Replotting

A straightforward method is to clear the existing plot by calling graph1.clear() and graph2.clear(), then replot the data. While it's simpler, it's also slower.

Approach 2: Updating Plot Data

An alternative approach, which is significantly faster, involves updating the data of existing plot objects. This requires adjusting your code slightly:

def plots():
    global vlgaBuffSorted
    cntr()

    result = collections.defaultdict(list)
    for d in vlgaBuffSorted:
        result[d['event']].append(d)

    result_list = result.values()

    f = Figure()
    graph1 = f.add_subplot(211)
    graph2 = f.add_subplot(212, sharex=graph1)

    # Create plot objects
    vds_line, = graph1.plot([], [], 'bo', label='a')
    vgs_line, = graph1.plot([], [], 'rp', label='b')
    isub_line, = graph2.plot([], [], 'b-', label='c')

    for item in result_list:
        # Update plot data
        vds_line.set_data([], [])
        vgs_line.set_data([], [])
        isub_line.set_data([], [])

        tL = []
        vgsL = []
        vdsL = []
        isubL = []
        for dict in item:
            tL.append(dict['time'])
            vgsL.append(dict['vgs'])
            vdsL.append(dict['vds'])
            isubL.append(dict['isub'])

        # Update plot data
        vds_line.set_data(tL, vdsL)
        vgs_line.set_data(tL, vgsL)
        isub_line.set_data(tL, isubL)

    # Draw the plot
    f.canvas.draw()
    f.canvas.flush_events()

In this approach, you create plot objects (e.g., vds_line), then update their data with each iteration. The draw() and flush_events() methods are used to display the updated plot on the Tkinter window.

By choosing the appropriate approach, you can effectively update plots in Matplotlib within your Tkinter application.

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