Matplotlib Fails to Update Axis Limits with ipywidgets in Jupyter Lab

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

```python
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:

[![enter image description here][1]][1]

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?

[1]: https://i.stack.imgur.com/nCOHG.png

Inizia eseguendo il reproducer di Jupyter Lab nell’issue con il menu a discesa di ipywidgets e il backend per widget di Matplotlib, quindi segui la sequenza indicata di selezione, panoramica e ripristino. Confronta i limiti degli assi ripristinati con i limiti impostati per ciascun dataset; il lavoro è completato quando, dopo il passaggio da b ad a, la vista ripristinata corrisponde ai dati attualmente selezionati.

Scritto dal modello di indicizzazione a partire dal testo della issue.