Matplotlib Fails to Update Axis Limits with ipywidgets in Jupyter Lab

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?

まず、ipywidgets のドロップダウンと Matplotlib のウィジェットバックエンドを使用して、issue にある Jupyter Lab の再現手順を実行し、次に記載された選択、パン、リセットのシーケンスに従います。復元された軸の範囲を各データセットに設定された範囲と比較します。b から a に切り替えた後、リセットされたビューが現在選択されているデータと一致すれば完了です。