How Can I Efficiently Update Matplotlib Plots with New Data?

Updating Plots in Matplotlib

When working with interactive plots in Matplotlib, it's often necessary to update the plot with new data. This can be achieved in two ways:

Option 1: Clear and Replot

This approach involves clearing the existing plot and redrawing it from scratch. To do this:

1. Call graph1.clear() and graph2.clear() to remove the current data.
2. Recalculate and plot the new data as before.

While this method is simple, it's also the slowest.

Option 2: Update Data

To avoid replotting the entire graph, you can directly update the data of the existing plot objects. This is much faster, but requires:

1. Modifying your code to separate the plotting logic from the data acquisition logic.
2. Ensuring that the data shape remains constant.
3. Manually resetting the x and y axis limits if the data range changes.

Example:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 6*np.pi, 100)
y = np.sin(x)

fig = plt.figure()
ax = fig.add_subplot(111)
line1, = ax.plot(x, y, 'r-')

for phase in np.linspace(0, 10*np.pi, 500):
    line1.set_ydata(np.sin(x + phase))
    fig.canvas.draw()
    fig.canvas.flush_events()

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