Matplotlib: implementing Dynamic Updating of Line Plot Data in Real-Time Application
I'm not sure how to approach I'm building a feature where Quick question that's been bugging me - I'm working on a real-time data visualization application using Matplotlib (version 3.4.3) where I need to dynamically update a line plot with new data received from a sensor every second... The scenario I’m working with is that the plot does not update as expected; it only reflects the latest data on the first update, and subsequent updates cause the plot to flicker or become unresponsive. I've tried using `plt.pause(0.1)` and `plt.draw()` after updating the data, but it seems like the plot does not refresh correctly. Here’s a simplified version of my code: ```python import matplotlib.pyplot as plt import numpy as np import time plt.ion() # Turn on interactive mode fig, ax = plt.subplots() line, = ax.plot([], [], 'r-') ax.set_xlim(0, 10) ax.set_ylim(-1, 1) x_data = [] y_data = [] for i in range(100): # Simulating real-time data from a sensor new_x = i / 10.0 new_y = np.sin(new_x) + np.random.normal(0, 0.1) # Adding some noise x_data.append(new_x) y_data.append(new_y) line.set_xdata(x_data) line.set_ydata(y_data) fig.canvas.draw() plt.pause(0.1) # Pause for a moment to update the plot plt.ioff() # Turn off interactive mode plt.show() ``` When I run this code, the plot updates initially but starts to lag significantly with additional data points, and the flickering makes it hard to read. I’ve also tried using `set_data()` on the line object, but the question continues. Is there any recommended approach or best practice for updating a Matplotlib plot in real-time without running into performance optimization? Am I missing something in terms of how the figure and canvas are being managed? Any suggestions would be appreciated! My development environment is Ubuntu. The project is a microservice built with Python. What's the best practice here?