Matplotlib live plot relim after using navigation bar in tkinter gui

I am making a gui in tkinter with live, embedded matplotlib graphs. I am using FigureCanvasTkAgg for the canvas, NavigationToolbar2Tk for the navigation bar, and FuncAnimation to handle periodic updates of the given source of data.

The callback tied to FuncAnimation resets the data on a given line (i.e. the return value from Axes.plot(...)) every invocation (i.e. Line2D.set_data(...)). The callback also redetermines and applies the appropriate x- and y-axis limits to fit the new data via

axis.relim()
axis.autoscale_view()

where axis is an instance of AxesSubplot.

Before the navigation bar is used, this works great; any new data added is appropriately reflected in the graph and the axes automatically re-scale to fit it, which was my goal.

The problem I am facing is that if any of the functions on the navigation bar are used (pan, zoom, etc.) the re-scaling fails to work any longer, meaning the graph may grow out of view and the user's only way to see new data is to manually pan over to it or to manually zoom out, which is undesirable.

Realistically, this functionality make sense since it would be annoying to, for example, try to zoom in a part of the plot only to have it zoom out immediately to refit the axes to new data, which is why I had intended to add a tkinter.Checkbutton to temporarily disable the re-scaling.

I've tried to look into the source for the navigation bar, and it seems to change state on the axes and canvas which I can only assume is the problem, but I have so far been unsuccessful at finding a way to "undo" these changes. If such a way exists, I would bind it to a tkinter.Button or something so the automatic re-scaling can be re-enabled.

How might I fix this problem?

Below is a minimal example that demonstrates this problem.

import math
import itertools
import tkinter as tk
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.animation import FuncAnimation


def xydata_generator(func, div):
    for num in itertools.count():
        num = num / div
        yield num, func(num)


class Plot(tk.Frame):

    def __init__(self, master, data_source, interval=100, *args, **kwargs):
        super().__init__(master, *args, **kwargs)

        self.data_source = data_source
        self.figure = Figure((5, 5), 100)
        self.canvas = FigureCanvasTkAgg(self.figure, self)
        self.nav_bar = NavigationToolbar2Tk(self.canvas, self)
        self.canvas.get_tk_widget().pack(fill=tk.BOTH, expand=True)
        self.axis = self.figure.add_subplot(111)
        self.x_data = []
        self.y_data = []
        self.line = self.axis.plot([], [])[0]  # Axes.plot returns a list
        # Set the data to a mutable type so we only need to append to it then force the line to invalidate its cache
        self.line.set_data(self.x_data, self.y_data)
        self.ani = FuncAnimation(self.figure, self.update_plot, interval=interval)

    def update_plot(self, _):
        x, y = next(self.data_source)  # (realistically the data source wouldn't be restricted to be a generator)
        # Because the Line2D object stores a reference to the two lists, we need only update the lists and signal
        # that the line needs to be updated.
        self.x_data.append(x)
        self.y_data.append(y)
        self.line.recache_always()
        self._refit_artists()

    def _refit_artists(self):
        self.axis.relim()
        self.axis.autoscale_view()


root = tk.Tk()
data = xydata_generator(math.sin, 5)
plot = Plot(root, data)
plot.pack(fill=tk.BOTH, expand=True)
root.mainloop()