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Matplotlib – Button Widget

  • Difficulty Level : Easy
  • Last Updated : 30 Aug, 2021

In Matplotlib a button is one of the important widgets by which we can perform various operations. They are mostly used for making a good functional graph having different properties. There are three types of buttons

  • Button
  • Radio Buttons
  • Check Buttons

In this article, we will learn how to use different buttons in the matplotlib plot. For this, we will use some data, plot a graph, then form a button and use it. Let’s understand buttons one by one with the help of some examples.

Simple Button

This is a simple button that is responsible for performing only one function. 

Syntax: simple_button=Button()

Parameters:

  • ax– defines the axes where the button should be located
  • label– the name that we want on the button
  • color– color of the button
  • hover color– color of the button when it gets clicked

In this example, we will create a simple button, and we will use this button to add one more line to the existing graph.

Python3




# importing libraries
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Button
 
 
# creating data
x1=np.array([0,1,2,3])
y1=np.array([5,2,8,6])
 
# creating plot
fig = plt.figure()
ax = fig.subplots()
plt.subplots_adjust(left = 0.3, bottom = 0.25)
p,=ax.plot(x1,y1,color="blue", marker="o")
 
 
# defining function to add line plot
def add(val):
  x2=np.array([0,1,2,3])
  y2=np.array([10,2,0,12])
  ax.plot(x2,y2,color="green", marker="o")
 
 
# defining button and add its functionality
axes = plt.axes([0.81, 0.000001, 0.1, 0.075])
bnext = Button(axes, 'Add',color="yellow")
bnext.on_clicked(add)
plt.show()

 

 

Output:

 

Radio Button

 

This type of button consists of a series of circular buttons that can be used to enable/disable one of the functions of our graph. 

 

Syntax: radio_button=RadioButtons()

Parameters:

  • ax– defines the axes where the button should be located
  • label– list of names that we want on every button
  • active– list of booleans describing the state of each button
  • active color– color of the active button

 

Here we created a simple sin graph where the radio buttons show the color of the line in the plot.

 

Python3




import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import RadioButtons
   
   
# creating an array starting from
# 0 to 1 with step size 0.01
t = np.arange(0.0, 1.0, 0.01)
   
# the values of sin values of t
s0 = np.sin(2*np.pi*t)
   
# depict visualization
fig, ax = plt.subplots()
l, = ax.plot(t, s0, lw=2, color='red')
plt.subplots_adjust(left=0.3)
   
# adjust radio buttons
axcolor = 'lightgoldenrodyellow'
rax = plt.axes([0.05, 0.4, 0.15, 0.30],
               facecolor=axcolor)
   
radio = RadioButtons(rax, ['red', 'blue', 'green'],
                     [True,False,False,False],
                     activecolor='r')
 
def color(labels):
    l.set_color(labels)
    fig.canvas.draw()
radio.on_clicked(color)
   
plt.show()

 

 

Output:

 

Check Button

 

Unlike Radio Button where we can select only one option, Check Button allows us to select multiple options. This feature is useful when we want to perform 2 or more functions on the plot. 

 

Syntax: check_button=CheckButtons()

Parameters:

  • ax– defines the axes where the button should be located
  • label– list of names that we want on every button
  • actives– list of booleans describing the state of each button

 

We created the same plot as a simple button but added 2 more graphs for the check button. We plotted it simultaneously.

 

Python3




import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Button, RadioButtons, CheckButtons
 
 
fig = plt.figure()
ax = fig.subplots()
plt.subplots_adjust(left=0.3, bottom=0.25)
 
x1 = np.array([0, 1, 2, 3])
y1 = np.array([5, 2, 8, 6])
p, = ax.plot(x1, y1, color="blue", marker="o")
 
x2 = np.array([0, 1, 2, 3])
y2 = np.array([10, 2, 0, 12])
p1, = ax.plot(x2, y2, color="green", marker="o")
 
x3 = np.array([0, 1, 2, 3])
y3 = np.array([0, 3, 2, 19])
p2, = ax.plot(x3, y3, color="yellow", marker="o")
lines = [p, p1, p2]
labels = ["plot1", "plot2", "plot3"]
 
 
def func(label):
    index = labels.index(label)
    lines[index].set_visible(not lines[index].get_visible())
    fig.canvas.draw()
 
 
label = [True, True, True]
 
# xposition, yposition, width and height
ax_check = plt.axes([0.9, 0.001, 0.2, 0.3])
plot_button = CheckButtons(ax_check, labels, label)
plot_button.on_clicked(func)
 
plt.show()

Output:


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