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matplotlib. Widgets are easy to use
2022-07-06 07:59:00 【The story has turned several pages】
matplotlib Official document website :https://matplotlib.org/
My idea is to learn from cases rather than looking at them one by one , Learning in cases can quickly master , And can keep learning enthusiasm , Let's start .
List of articles
1. Introduce
This module is matplotlib Medium GUI modular , Can be adjusted by bottom To change the displayed results in real time
2. structure
Don't talk much , Directly on the official documents
3. Case study 1
The experimental environment is python3.6
Mission : Realize a small program that can change the value and image in real time
1. First , We import the required libraries
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
2. Define the main function :
if __name__ == '__main__':
fig = plt.figure() # Create an image object
ax1 = fig.add_subplot(111) # take ax1 Set to place in image , There is only one sub picture in the image
plt.subplots_adjust(bottom=0.3)# Set the distance between the image and the bottom in the last display box 40% It's about , So as to drag the display of the bar later .
s1 = plt.axes([0.25, 0.1, 0.6, 0.05], facecolor='yellow') # Set up slider1 The location of
slider1 = Slider(s1, 'gamma',valmin=0.0, valmax=100.0, valinit=10.0 ,valstep=1.0)
slider1.on_changed(update)# This code is crucial , For real-time updates
slider1.reset()#Reset the slider to the initial value.
slider1.set_val(10.0)#Set slider value to val.
plt.show()
3. then , We add update function
To achieve real-time updates, we must first establish a update Function to get the value updated in real time update Function can only have one argument , namely val,val yes validation Abbreviation , Means variable .
def update(val):
gamma = slider1.val
x = np.linspace(1,100,100)
y = np.sin(x*np.log(gamma))
plt.plot(x,y)
ax1.clear()
ax1.plot(x,y)
The complete code is as follows :
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider
def update(val):
gamma = slider1.val
x = np.linspace(1,100,100)
y = np.sin(x*np.log(gamma))# Set a beautiful function casually
plt.plot(x,y)
ax1.clear()
ax1.plot(x,y)
if __name__ == '__main__':
fig = plt.figure()
ax1 = fig.add_subplot(111)
plt.subplots_adjust(bottom=0.3)
s1 = plt.axes([0.25, 0.1, 0.6, 0.05], facecolor='yellow') # Set up slider1 The location of
slider1 = Slider(s1, 'gamma',valmin=0.0, valmax=100.0, valinit=10.0 ,valstep=1.0)# Set the properties of the slider
slider1.on_changed(update)
slider1.reset()#Reset the slider to the initial value.
slider1.set_val(10.0)#Set slider value to val.
plt.show()
After running, it first appears like this
Try to jump the sliding shaft below , Something amazing happened
To be continued 2022.2.12
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