blocks|key|189476|text|官方文档：Matplotlib,+pyplot+and+pylab:+how+are+they+related?|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|189477|这两个导入可以归结为做完全相同的事情，并将运行完全相同的代码，只是导入模块的方式不同。|189478|还要注意，matplotlib有两个接口层，一个是由pyplot管理的状态机层，另一个是构建在之上的OO接口pyplot，请参见How+can+I+attach+a+pyplot+function+to+a+figure+instance?|style|CODE|189479|pylab是一种干净的方法，可以将大量有用的函数(+pyplot状态机函数，numpy的大部分)大容量导入到单个名称空间中。它存在的主要原因(据我所知)是为了与ipython合作制作一个非常好的交互式外壳，它或多或少地复制了MATLAB+(使转换更容易，因为它很适合玩)。请参阅pylab.py和matplotlib/pylab.py|189480|在某种程度上，这纯粹是一个品味问题，有点取决于你在做什么。|189481|如果您没有在gui中嵌入(使用批量脚本的非交互式后端，或者使用所提供的交互式后端之一)，典型的做法是|189482|import+matplotlib.pyplot+as+plt
import+numpy+as+np

plt.plot(....)|code-block|syntax|javascript|189483|这不会污染名称空间。我更喜欢这样，这样我就可以跟踪这些东西的来源。|189484|如果您使用|189485|ipython+--pylab|189486|这等同于运行|189487|from+pylab+import+*+|189488|现在，对于新版本的ipython，建议使用|189489|ipython+--matplotlib|189490|这将设置所有适当的背景细节，以使交互式后端工作良好，但不会批量导入任何东西。您将需要显式导入所需的模块。|189491|import+numpy+as+np
import+matplotlib.pyplot+as+plt|189492|是一个很好的开始。|189493|如果你在一个gui中嵌入matplotlib，你不会想要导入pyplot，因为那会启动额外的gui主循环，你到底应该导入什么取决于你到底在做什么。|189494|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/faq/usage_faq.html#matplotlib-pyplot-and-pylab-how-are-they-related|1|https://stackoverflow.com/questions/14254379/how-can-i-attach-a-pyplot-function-to-a-figure-instance/14261698#1426169|2|https://github.com/matplotlib/matplotlib/blob/master/lib/pylab.py|3|https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/pylab.py^0|5|1F|0|0|0|5|A|Q|6|1I|6|1S|1K|1|0|0|5|Q|6|12|5|28|7|3V|8|44|J|3V|8|2|44|J|3|0|0|0|0|0|0|0|0|0|9|7|0|0|0|0|0|C|A|0^^$0|@$1|2|3|4|5|6|7|1U|8|@]|9|@$A|1V|B|1W|1|1X]]|C|$]]|$1|D|3|E|5|6|7|1Y|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|1Z|8|@$A|20|B|21|H|I]|$A|22|B|23|H|I]|$A|24|B|25|H|I]]|9|@$A|26|B|27|1|28]]|C|$]]|$1|J|3|K|5|6|7|29|8|@$A|2A|B|2B|H|I]|$A|2C|B|2D|H|I]|$A|2E|B|2F|H|I]|$A|2G|B|2H|H|I]|$A|2I|B|2J|H|I]|$A|2K|B|2L|H|I]]|9|@$A|2M|B|2N|1|2O]|$A|2P|B|2Q|1|2R]]|C|$]]|$1|L|3|M|5|6|7|2S|8|@]|9|@]|C|$]]|$1|N|3|O|5|6|7|2T|8|@]|9|@]|C|$]]|$1|P|3|Q|5|R|7|2U|8|@]|9|@]|C|$S|T]]|$1|U|3|V|5|6|7|2V|8|@]|9|@]|C|$]]|$1|W|3|X|5|6|7|2W|8|@]|9|@]|C|$]]|$1|Y|3|Z|5|R|7|2X|8|@]|9|@]|C|$S|T]]|$1|10|3|11|5|6|7|2Y|8|@]|9|@]|C|$]]|$1|12|3|13|5|R|7|2Z|8|@]|9|@]|C|$S|T]]|$1|14|3|15|5|6|7|30|8|@$A|31|B|32|H|I]]|9|@]|C|$]]|$1|16|3|17|5|R|7|33|8|@]|9|@]|C|$S|T]]|$1|18|3|19|5|6|7|34|8|@]|9|@]|C|$]]|$1|1A|3|1B|5|R|7|35|8|@]|9|@]|C|$S|T]]|$1|1C|3|1D|5|6|7|36|8|@]|9|@]|C|$]]|$1|1E|3|1F|5|6|7|37|8|@$A|38|B|39|H|I]]|9|@]|C|$]]|$1|1G|3|-4|5|6|7|3A|8|@]|9|@]|C|$]]]|1H|$1I|$5|1J|1K|1L|C|$1M|1N]]|1O|$5|1J|1K|1L|C|$1M|1P]]|1Q|$5|1J|1K|1L|C|$1M|1R]]|1S|$5|1J|1K|1L|C|$1M|1T]]]]

Official docs: <a href="https://matplotlib.org/faq/usage_faq.html#matplotlib-pyplot-and-pylab-how-are-they-related" rel="noreferrer">Matplotlib, pyplot and pylab: how are they related?</a>

Both of those imports boil down do doing exactly the same thing and will run the exact same code, it is just different ways of importing the modules. 

Also note that <code>matplotlib</code> has two interface layers, a state-machine layer managed by <code>pyplot</code> and the OO interface <code>pyplot</code> is built on top of, see <a href="https://stackoverflow.com/questions/14254379/how-can-i-attach-a-pyplot-function-to-a-figure-instance/14261698#1426169">How can I attach a pyplot function to a figure instance?</a>

<code>pylab</code> is a clean way to bulk import a whole slew of helpful functions (the <code>pyplot</code> state machine function, most of <code>numpy</code>) into a single name space. The main reason this exists (to my understanding) is to work with <code>ipython</code> to make a very nice interactive shell which more-or-less replicates MATLAB (to make the transition easier and because it is good for playing around). See <a href="https://github.com/matplotlib/matplotlib/blob/master/lib/pylab.py" rel="noreferrer"><code>pylab.py</code></a> and <a href="https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/pylab.py" rel="noreferrer"><code>matplotlib/pylab.py</code></a>

At some level, this is purely a matter of taste and depends a bit on what you are doing. 

If you are not embedding in a gui (either using a non-interactive backend for bulk scripts or using one of the provided interactive backends) the typical thing to do is

<pre><code>import matplotlib.pyplot as plt
import numpy as np

plt.plot(....)
</code></pre>

which doesn't pollute the name space. I prefer this so I can keep track of where stuff came from.

If you use 

<pre><code>ipython --pylab
</code></pre>

this is equivalent to running

<pre><code>from pylab import * 
</code></pre>

It is now recommended that for new versions of <code>ipython</code> you use

<pre><code>ipython --matplotlib
</code></pre>

which will set up all the proper background details to make the interactive backends to work nicely, but will not bulk import anything. You will need to explicitly import the modules want.

<pre><code>import numpy as np
import matplotlib.pyplot as plt
</code></pre>

is a good start.

If you are embedding <code>matplotlib</code> in a gui you don't want to import pyplot as that will start extra gui main loops, and exactly what you should import depends on exactly what you are doing.

blocks|key|187327|text|如下所示，从官方文档来看，建议使用matplotlib.pyplot。这不是一个观点。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|BOLD|entityRanges|data|187328|Matplotlib,+pyplot+and+pylab:+how+are+they+related?上的文档也描述了pyplot和pylab之间的区别，它指出：“尽管许多示例使用pylab，但不再推荐它。”|187329|2021-05-06编辑：|187330|来自The+pylab+API+(disapproved)的|187331|unordered-list-item|187332|187333|187334|由于大量导入到全局命名空间中可能会导致意外的行为，因此强烈建议不要使用pylab。改为使用matplotlib.pyplot。|blockquote|187335|187336|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot|1|https://matplotlib.org/2.0.2/faq/usage_faq.html#matplotlib-pyplot-and-pylab-how-are-they-related|2|https://matplotlib.org/stable/api/index.html?highlight=pylab#module-pylab|3^0|H|H|Z|8|H|H|0|0|0|1F|1|0|0|2|R|2|0|0|0|0|19|H|3|0|0^^$0|@$1|2|3|4|5|6|7|17|8|@$9|18|A|19|B|C]|$9|1A|A|1B|B|D]]|E|@$9|1C|A|1D|1|1E]]|F|$]]|$1|G|3|H|5|6|7|1F|8|@]|E|@$9|1G|A|1H|1|1I]]|F|$]]|$1|I|3|J|5|6|7|1J|8|@]|E|@]|F|$]]|$1|K|3|L|5|6|7|1K|8|@]|E|@$9|1L|A|1M|1|1N]]|F|$]]|$1|M|3|-4|5|N|7|1O|8|@]|E|@]|F|$]]|$1|O|3|-4|5|6|7|1P|8|@]|E|@]|F|$]]|$1|P|3|-4|5|6|7|1Q|8|@]|E|@]|F|$]]|$1|Q|3|R|5|S|7|1R|8|@]|E|@$9|1S|A|1T|1|1U]]|F|$]]|$1|T|3|-4|5|6|7|1V|8|@]|E|@]|F|$]]|$1|U|3|-4|5|6|7|1W|8|@]|E|@]|F|$]]]|V|$W|$5|X|Y|Z|F|$10|11]]|12|$5|X|Y|Z|F|$10|13]]|14|$5|X|Y|Z|F|$10|15]]|16|$5|X|Y|Z|F|$10|11]]]]

From the official documentation, as shown below, the recommendation is to use <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot" rel="nofollow noreferrer"><code>matplotlib.pyplot</code></a>. This is not an opinion.
The documentation at <a href="https://matplotlib.org/2.0.2/faq/usage_faq.html#matplotlib-pyplot-and-pylab-how-are-they-related" rel="nofollow noreferrer">Matplotlib, pyplot and pylab: how are they related?</a>, which also describes the difference between pyplot and pylab, states: &quot;Although many examples use pylab, it is no longer recommended.&quot;.
<h2>2021-05-06 Edit:</h2>
<ul>
<li>From <a href="https://matplotlib.org/stable/api/index.html?highlight=pylab#module-pylab" rel="nofollow noreferrer">The pylab API (disapproved)</a></li>
</ul>
<blockquote>
Since heavily importing into the global namespace may result in unexpected behavior, the use of pylab is strongly discouraged. Use <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot" rel="nofollow noreferrer">matplotlib.pyplot</a> instead.
</blockquote>

I can plot in Python using either:
<pre><code>import matplotlib
matplotlib.pyplot.plot(...)
</code></pre>
Or:
<pre><code>import pylab
pylab.plot(...)
</code></pre>
Both of these use <code>matplotlib</code>.
Which is recommend as the correct method to plot? Why?

Which is the recommended way to plot: matplotlib or pylab?

Python

我可以使用以下任一方法在Python中plot：import matplotlibmatplotlib.pyplot.plot(...)或者：import pylabpylab.plot(...)这两种方法都使用matplotlib。推荐哪种方法作为正确的绘图方法？为什么？

问推荐的绘图方式是: matplotlib还是pylab？
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