Matplotlib Fails to Update Axis Limits with ipywidgets in Jupyter Lab

首先运行 issue 中使用 ipywidgets 下拉菜单和 Matplotlib widget backend 的 Jupyter Lab reproducer，然后按照列出的选择、平移和重置顺序操作。将恢复的坐标轴范围与为每个数据集设置的范围进行比较；从 b 切换到 a 后，重置视图与当前选中的数据匹配即表示完成。

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?