I acquire some data in 2 array : 1 for the time, and one for the value. When I reach 1000 points, I trigger a signal and plot these points (x=time, y=value).
I need to keep on the same figure the previous plots, but only a reasonable number to avoid slowing down the process. For example I would like to keep 10 000 points on my graph.
The matplotlib interractive plot works fine but I don't know how to erase the first points and it slows my computer very quickly.
I looked into matplotlib.animation but it only seems to repeat the same plot, and not really actualise it.
I'm really looking for a light solution, to avoid any slowing.
EDIT: As I acquire for a very large amount of time, I erase the input data on every loop (the 1001st point is stored in the 1st row and so on)
EDIT 2: Here is what I have for now, but it keeps all the points on the graph:
import matplotlib.pyplot as plt
plt.ylabel("Tension (V)", fontsize=20)
The lightest solution you may have is to replace the X and Y values of an existing plot. (Or the Y value only, if your X data does not change. A simple example:
import matplotlib.pyplot as plt import numpy as np import time fig = plt.figure() ax = fig.add_subplot(111) # some X and Y data x = np.arange(10000) y = np.random.randn(10000) li, = ax.plot(x, y) # draw and show it fig.canvas.draw() plt.show(block=False) # loop to update the data while True: try: y[:-10] = y[10:] y[-10:] = np.random.randn(10) # set the new data li.set_ydata(y) fig.canvas.draw() time.sleep(0.01) except KeyboardInterrupt: break
This solution is quite fast, as well. The maximum speed of the above code is 100 redraws per second (limited by the
time.sleep), I get around 70-80, which means that one redraw takes around 4 ms. But YMMV depending on the backend, etc.