Python实时绘图

问题描述

我以两个数组获取一些数据:一个用于时间，一个用于值.当我达到1000点时，我会触发信号并绘制这些点(x =时间，y =值).

I acquire some data in two arrays: one 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).

我需要保持先前绘制的图形不变，但只有一个合理的数字，以免减慢处理速度.例如，我想在图表上保留10,000点.matplotlib交互式绘图工作正常，但我不知道如何删除第一个点，这会很快减慢计算机速度.我查看了matplotlib.animation，但它似乎只重复了相同的情节，并没有真正实现它.

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 interactive 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.

我真的在寻找一种简便的解决方案，以避免速度变慢.

I'm really looking for a light solution, to avoid any slowing.

在获取大量时间后，我会擦除每个循环上的输入数据(第1001个点存储在第1行中，依此类推).

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).

这是我现在拥有的，但是它使所有要点保持在图形上:

Here is what I have for now, but it keeps all the points on the graph:

import matplotlib.pyplot as plt

def init_plot():
  plt.ion()
  plt.figure()
  plt.title("Test d\'acqusition", fontsize=20)
  plt.xlabel("Temps(s)", fontsize=20)
  plt.ylabel("Tension (V)", fontsize=20)
  plt.grid(True)

def continuous_plot(x, fx, x2, fx2):
  plt.plot(x, fx, 'bo', markersize=1)
  plt.plot(x2, fx2, 'ro', markersize=1)
  plt.draw()

我调用了一次init函数，并且continous_plot处于进程中，每次我的数组中有1000点时都会调用该函数.

I call the init function once, and the continous_plot is in a process, called every time I have 1000 points in my array.

推荐答案

您可能拥有的最简单的解决方案是替换现有图的X和Y值. (或者，如果您的X数据不变，则仅使用Y值.一个简单的示例:

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
ax.relim()
ax.autoscale_view(True,True,True)
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

该解决方案也非常快.上面代码的最大速度是每秒100次重绘(受time.sleep限制)，我得到大约70-80，这意味着一次重绘大约需要4毫秒.但是YMMV取决于后端等.

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.

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