How to Optimize Matplotlib Animations for Real-Time Data Collection?

Animating Matplotlib Plots: Optimizing for Data Collection

In data collection applications, it's crucial to update plots dynamically without redrawing the entire graph. This optimization enhances performance, especially when collecting data for extended periods.

The Problem: Redrawing or Interval-Based Animation?

Traditionally, plot updates involved either clearing and redrawing the plot or animating it at fixed intervals. However, neither method is ideal for real-time data collection. Redrawing becomes slow over time, while interval-based animation fails to update the plot promptly when data arrives.

The Solution: Incremental Point Addition

To dynamically update the plot only when new data is received, consider using matplotlib's animation API, specifically the FuncAnimation function. This function allows you to define a function that continuously updates the plot.

import matplotlib.pyplot as plt
import numpy

hl, = plt.plot([], [])

def update_line(hl, new_data):
    hl.set_xdata(numpy.append(hl.get_xdata(), new_data))
    hl.set_ydata(numpy.append(hl.get_ydata(), new_data))
    plt.draw()

In this example, hl is the line object, and the update_line function extends its data with new data points. When new data is received, simply call update_line to update the plot smoothly and efficiently.

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