%matplotlib ipympl

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

def slider_plot():
    # 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, = plt.plot(t, f(t, init_amplitude, init_frequency), lw=2)
    ax.set_xlabel('Time [s]')

    axcolor = 'lightgoldenrodyellow'
    ax.margins(x=0)

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

    # Make a horizontal slider to control the frequency.
    axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
    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 = plt.axes([0.1, 0.25, 0.0225, 0.63], facecolor=axcolor)
    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):
        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 = plt.axes([0.8, 0.025, 0.1, 0.04])
    button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')


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

    plt.show()