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.
# 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.
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.
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:
