在Jupyter Notebook中内联％matplotlib后无法使用％matplotlib笔记本 [英] Using %matplotlib notebook after %matplotlib inline in Jupyter Notebook doesn't work

问题描述

我正在使用Jupyter Notebook绘制饼图图形.

I am using Jupyter Notebook for plotting piechart figures.

在我的代码的第一个单元格中，我有一个魔术命令%matplotlib inline，在执行了此魔术命令之后，我运行了代码，一切正常，并且图形呈现.

In first cell with my code I have a magic command %matplotlib inline and after this magic command I run my code, everything works fine and my figure renders.

但是在第二个单元格中，当我设置%matplotlib notebook进行交互式绘图时，运行第二个单元格后，我的图形将无法渲染.

But in second cell when I set %matplotlib notebook for interactive plotting my figure won't render after running this second cell.

我需要重新启动内核并再次使用%matplotlib notebook运行单元，并且在此之前无法运行%matplotlib inline命令.

I need to restart kernel and run cell with %matplotlib notebook again and cannot run %matplotlib inline command before that.

这是我的第一个单元格和%matplotlib inline的代码，可以很好地呈现:

Here is my code for first cell with %matplotlib inline, which renders fine:

import matplotlib.pyplot as plt

%matplotlib inline

labels = "No", "Yes"
sizes = [100, 50]

fig, ax = plt.subplots(figsize=(6, 6))

_, texts, autotexts = ax.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%',
             shadow=False, startangle=90)

ax.axis('equal')

之后，我用相同的代码创建了第二个单元格，只是将%matplotlib inline更改为%matplotlib notebook.运行此单元格后，该图将无法渲染，我需要重新启动内核并再次运行此单元格.

After that I have second cell with same code, just %matplotlib inline is changed to %matplotlib notebook. Figure won't render after I run this cell and I need to restart kernel and run this cell again.

为什么?

推荐答案

您的命令顺序错误.在jupyter中导入pyplot之前，应先设置一个后端.换句话说，更改后端后，需要再次导入pyplot.

You just have the wrong order of your commands. A backend should be set before importing pyplot in jupyter. Or in other words, after changing the backend, pyplot needs to be imported again.

因此，在导入pyplot之前，请先调用%matplotlib ....

Therefore call %matplotlib ... prior to importing pyplot.

在第一个单元格中:

%matplotlib inline
import matplotlib.pyplot as plt
plt.plot([1,1.6,3])

在第二个单元格中:

%matplotlib notebook
#calling it a second time may prevent some graphics errors
%matplotlib notebook  
import matplotlib.pyplot as plt
plt.plot([1,1.6,3])

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