Matplotlib.pyplot.ion() in Python Example

Matplotlib.pyplot.ion() Syntax in Python

There are various example for use Matplotlib in interactive mode or How to use Matplotlib in interactive mode with Matplotlib.pyplot.ion() . Here we are discussing some generally use example those are following.

Interactive Plot with Collections
Interactive Matplotlib Plot with Multiple Lines
Interactive Matplotlib Plot with draw()

Interactive Plot with Collections

In this example code utilizes Matplotlib to generate an interactive plot with two random data collections, represented by red ‘x’ and blue ‘+’ markers. It includes a filled green region between the collections where the second one surpasses the first, and a legend with a colored background is placed at the upper center of the plot.

Python3

import matplotlib.pyplot as plt
  
#the function to turn on interactive mode
plt.ion()
 
#creating randomly generate collections/data
random_array = np.arange(-4, 5)
collection_1 = random_array ** 2
collection_2 = 10 / (random_array ** 2 + 1)
figure, axes = plt.subplots()
 
axes.plot(random_array, collection_1,
          'rx', random_array,
          collection_2, 'b+', 
          linestyle='solid')
 
axes.fill_between(random_array, 
                  collection_1, 
                  collection_2,
                  where=collection_2>collection_1, 
                  interpolate=True,
                  color='green', alpha=0.3)
 
lgnd = axes.legend(['collection-1',
                    'collection-2'], 
                   loc='upper center', 
                   shadow=True)
 
lgnd.get_frame().set_facecolor('#ffb19a')

Output:

Interactive Matplotlib Plot with Multiple Lines

In this example The code sets up an interactive Matplotlib plot, plots a line with points (1.4, 2.5), and adds a title. It retrieves the current Axes object and plots another line with points (3.1, 2.2) on the same plot

Python3

import matplotlib.pyplot as plt
  
plt.ion()
plt.plot([1.4, 2.5])
plt.title(" Sample interactive plot")
  
axes = plt.gca()
axes.plot([3.1, 2.2])

Output:

Interactive Matplotlib Plot with draw()

In this example code initializes an interactive Matplotlib plot, creating a sine wave and plotting it in blue. It then iterates through phases, updating the y-data of the sine wave and redrawing the plot, resulting in an animated sine wave with a short pause between frames.

Python3

import matplotlib.pyplot as plt
import numpy as np
 
x = np.linspace(0, 10 * np.pi, 100)
y = np.sin(x)
 
plt.ion()
fig, ax = plt.subplots()
line1, = ax.plot(x, y, 'b-')
 
for phase in np.linspace(0, 10 * np.pi, 100):
    line1.set_ydata(np.sin(0.5 * x + phase))
    fig.canvas.draw()
    plt.pause(0.1)  # Add a short pause to improve animation smoothness

Output :