Utilise a slider to update the position of legend in Matplotlib

I am trying to make a slider that can adjust the x and y coordinates of the legend anchor, but this does not seem to be updating on the plot. I keep getting the message in console "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument", each time the slider value is updated.

Here is the code, taken from this example in the matplotlib docs

from cProfile import label
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button


# The parametrized function to be plotted
def f(t, amplitude, frequency):
    return amplitude * np.sin(2 * np.pi * frequency * t)

t = np.linspace(0, 1, 1000)

# Define initial parameters
init_amplitude = 5
init_frequency = 3

# Create the figure and the line that we will manipulate
fig, ax = plt.subplots()
line, = ax.plot(t, f(t, init_amplitude, init_frequency), lw=2, label = "wave")
ax.set_xlabel('Time [s]')

# adjust the main plot to make room for the sliders
fig.subplots_adjust(left=0.25, bottom=0.25)

initx = 0.4
inity = 0.2
def l(x,y):
    return (x,y)
legend = fig.legend(title = 'title', prop={'size': 8}, bbox_to_anchor = l(initx,inity))
legend.remove(  )

# Make a horizontal slider to control the frequency.
axfreq = fig.add_axes([0.25, 0.1, 0.3, 0.3])
freq_slider = Slider(
    ax=axfreq,
    label='Frequency [Hz]',
    valmin=0.1,
    valmax=30,
    valinit=init_frequency,
)

# Make a vertically oriented slider to control the amplitude
axamp = fig.add_axes([0.1, 0.25, 0.0225, 0.63])
amp_slider = Slider(
    ax=axamp,
    label="Amplitude",
    valmin=0,
    valmax=10,
    valinit=init_amplitude,
    orientation="vertical"
)


# The function to be called anytime a slider's value changes
def update(val):
    legend = plt.legend(title = '$J_{xx}$', prop={'size': 8}, bbox_to_anchor= l(amp_slider.val, freq_slider.val))
    legend.remove()
    #line.set_ydata(f(t, amp_slider.val, freq_slider.val))
    fig.canvas.draw_idle()


# register the update function with each slider
freq_slider.on_changed(update)
amp_slider.on_changed(update)

# Create a `matplotlib.widgets.Button` to reset the sliders to initial values.
resetax = fig.add_axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', hovercolor='0.975')


def reset(event):
    freq_slider.reset()
    amp_slider.reset()
button.on_clicked(reset)

plt.show()

Is it even possible to update other matplotlib plot parameters like xticks/yticks or xlim/ylim with a slider, rather than the actual plotted data? I am asking so that I can speed up the graphing process, as I tend to lose a lot of time just getting the right plot parameters whilst making plots presentable, and would like to automate this in some way.