I want to plot a continuous stream of data. Here's a simplified version of what I'm doing.

x_values = []
y_values = []

index = count()


def animate(i):
    x_values.append(next(index))
    y_values.append(random.randint(0, 5))
    plt.cla()
    plt.plot(x_values, y_values)


ani = FuncAnimation(plt.gcf(), animate, 1000)

plt.tight_layout()
plt.show()

The code works as expected and the whole existing data is plotted while at the end of each iteration a new datapoint is added. The result is a growing plot. But I want to implement that only a certain section of the plot is shown which moves along with the generated data. E.g., in the first iteration the figure should show the section of the x-axis from 0-10, in the second iteration it should show the section of the x-axis from 1-11, and so on.

CodePudding user response：

Not sure why you thought that the linked example was not relevant. If matplotlib doesn't auto-update the x-axis, then we have to ask it politely. A simple implementation could look like this:

import matplotlib.pyplot as plt
import matplotlib.animation as anim
import numpy as np
rng = np.random.default_rng()

fig, ax = plt.subplots()

#intialize x and y arrays with number of display points
points = 100
x = np.linspace(0, 1, points)
x_offset = x[1]
y = np.zeros(points)

l, = ax.plot(x, y)
ax.set_ylim(-2, 2)

def update(i): 
    #set random new y-value within display range
    while True:
        y_new = y[-1]   0.2 * rng.random() - 0.1
        if -2 < y_new < 2:
            y[:] = np.roll(y, -1)
            y[-1] = y_new
            break 
    #shift x-values 
    x_new = x[-1]   x_offset
    x[:] = np.roll(x, -1)
    x[-1] = x_new
    #update line with new values
    l.set_ydata(y)
    l.set_xdata(x)
    #and update x axis
    ax.set_xlim(x[0], x[-1])
    return l,   
   
ani = anim.FuncAnimation(fig, update, frames=100 , interval=50, repeat=True)
plt.show()