在iPython Notebook中动态更新图 [英] Dynamically update plot in iPython notebook

问题描述

如

As referred in this question, I am trying to update a plot dynamically in an iPython notebook (in one cell). The difference is that I don't want to plot new lines, but that my x_data and y_data are growing at each iteration of some loop.

我想做的是:

import numpy as np
import time
plt.axis([0, 10, 0, 100]) # supoose I know what the limits are going to be
plt.ion()
plt.show()
x = []
y = []
for i in range(10):
     x = np.append(x, i)
     y = np.append(y, i**2)
     # update the plot so that it shows y as a function of x
     time.sleep(0.5) 

但是我希望剧情有一个图例，如果我愿意，那么

but I want the plot to have a legend, and if I do

from IPython import display
import time
import numpy as np
plt.axis([0, 10, 0, 100]) # supoose I know what the limits are going to be
plt.ion()
plt.show()
x = []
y = []
for i in range(10):
    x = np.append(x, i)
    y = np.append(y, i**2)
    plt.plot(x, y, label="test")
    display.clear_output(wait=True)
    display.display(plt.gcf())
    time.sleep(0.3)
plt.legend()

我最终得到一个包含10个项目的图例.如果将plt.legend()放入循环中，则图例会在每次迭代时都增长...有什么解决方案吗?

I end up with a legend which contains 10 items. If I put the plt.legend() inside the loop, the legend grows at each iteration... Any solution?

推荐答案

当前，您每次在循环中plt.plot都将创建一个新的Axes对象.

Currently, you are creating a new Axes object for every time you plt.plot in the loop.

因此，如果在使用plt.plot之前清除了当前轴(plt.gca().cla())，并将图例放入循环中，则该图例不会每次都增长图例:

So, if you clear the current axis (plt.gca().cla()) before you use plt.plot, and put the legend inside the loop, it works without the legend growing each time:

import numpy as np
import time
from IPython import display

x = []
y = []
for i in range(10):
    x = np.append(x, i)
    y = np.append(y, i**2)
    plt.gca().cla() 
    plt.plot(x,y,label='test')
    plt.legend()
    display.clear_output(wait=True)
    display.display(plt.gcf()) 
    time.sleep(0.5) 

正如@tcaswell在评论中指出的那样，使用%matplotlib notebook magic命令可以为您提供一个可以更新和重绘的实时图形.

As @tcaswell pointed out in comments, using the %matplotlib notebook magic command gives you a live figure which can update and redraw.

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