Live figure with jupyter notebook (or pure python file) using matplotlib

Source Codes: https://github.com/bridget462/live-figure

To make a live graph, which update constantly to reflect real-time data, use following method instead of normal plt.show()

The Key methods for live graph are:

• plt.draw(): to display plot
• plt.pause(): keep displaying current frame certain duration
• plt.cla(): to clear previous frame

Use methods above in loop to constantly update figure.

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Codes

we only use 2 libraries

import numpy as np # to generate random data
import matplotlib.pyplot as plt # to make figure

# optional (just for figure appearence)
plt.style.use('seaborn-colorblind')
plt.style.use('seaborn-whitegrid')

print('library imported')

if using jupyter, excute command below to create intractive figure instead of displaying in the jupyter cell.

%matplotlib qt

To make live figure, use key methods explained above in loop to update figures. Also replace random number with your actual data.

MEASUREMENT_TIME = 50
INTERVAL_SEC = 0.1

for i in range(MEASUREMENT_TIME):
    # replace with your data
    data = np.random.rand(100)

    plt.plot(data)

    # figure appearence adjustments
    plt.ylim(-0.2, 1.2)
    plt.title(f'FRAME {i+1}')

    # to avoid clearing last plot
    if (i != MEASUREMENT_TIME-1):
        plt.draw()
        plt.pause(INTERVAL_SEC)
        plt.cla()
    else:
        plt.show()

And that's about it. plt.draw(), plt.pause(), plt.cla() can be used to any other figures, such as 3D, polar and etc.