# Slider#

In this example, sliders are used to control the frequency and amplitude of a sine wave.

See Snapping Sliders to Discrete Values for an example of having the Slider snap to discrete values.

See Thresholding an Image with RangeSlider for an example of using a RangeSlider to define a range of values.

import matplotlib.pyplot as plt
import numpy as np

from matplotlib.widgets import Button, Slider

# 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)
ax.set_xlabel('Time [s]')

# adjust the main plot to make room for the sliders

# Make a horizontal slider to control the frequency.
axfreq = fig.add_axes([0.25, 0.1, 0.65, 0.03])
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):
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()


References

The use of the following functions, methods, classes and modules is shown in this example:

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