Matplotlib Fails to Update Axis Limits with ipywidgets in Jupyter Lab

Question

I'm using ipywidgets along with matplotlib in Jupyter Lab and stumbled across some strange behavior. Here's an example of the code:

import matplotlib.pyplot as plt
import ipywidgets as widgets
%matplotlib widget
plt.ioff()

d = {
    "a": [1,2,3],
    "b": [2,3,4]
}

fig, ax = plt.subplots()

def update(change):
    data = d[change["new"]]
    ax.clear()  # Clear the previous plot
    ax.plot(data, data)
    ax.set_xlim(min(data), max(data))
    ax.set_ylim(min(data), max(data))
    ax.figure.canvas.draw()
    
dropdown = widgets.Dropdown(options = list(d.keys()))
dropdown.observe(update, "value")

display(dropdown, fig.canvas)
update({"new": "a"})

The steps I carry out are as follows:

• Select b from dropdown
• Pan the plot
• Select a from dropdown
• Click on the "Reset original view" button on the plot

Instead of snapping the plot extents back to what they are set for choice a, I instead get the following:

Where it looks like matplotlib has indeed plotted the data [1,2,3], but somehow failed to update the axis limits based on that data.

I really hope this isn't a bug, and that I'm doing something wrong. Has anyone seen this behavior before?