blocks|key|605722|text|当您调用figure时，只需对绘图进行编号。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|605723|x+=+arange(5)
y+=+np.exp(5)
plt.figure(0)
plt.plot(x,+y)

z+=+np.sin(x)
plt.figure(1)
plt.plot(x,+z)

w+=+np.cos(x)
plt.figure(0)+#+Here's+the+part+I+need
plt.plot(x,+w)|code-block|syntax|javascript|605724|编辑:请注意，您可以随心所欲地对图进行编号(这里，从0开始)，但是如果您在创建新图时根本没有提供图形编号，则自动编号将从1开始(文档中的“Matlab”)。|605725|entityMap^0|4|6|0|0|Q|1|1O|1|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|X|8|@]|D|@]|E|$]]]|N|$]]

When you call <code>figure</code>, simply number the plot.

<pre><code>x = arange(5)
y = np.exp(5)
plt.figure(0)
plt.plot(x, y)

z = np.sin(x)
plt.figure(1)
plt.plot(x, z)

w = np.cos(x)
plt.figure(0) # Here's the part I need
plt.plot(x, w)
</code></pre>

Edit: Note that you can number the plots however you want (here, starting from <code>0</code>) but if you don't provide figure with a number at all when you create a new one, the automatic numbering will start at <code>1</code> ("Matlab Style" according to the docs).

blocks|key|605790|text|但是，编号从1开始，因此：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|605791|x+=+arange(5)
y+=+np.exp(5)
plt.figure(1)
plt.plot(x,+y)

z+=+np.sin(x)
plt.figure(2)
plt.plot(x,+z)

w+=+np.cos(x)
plt.figure(1)+#+Here's+the+part+I+need,+but+numbering+starts+at+1!
plt.plot(x,+w)|code-block|syntax|javascript|605792|此外，如果图形上有多个轴，例如子图，请使用axes(h)命令，其中h是所需轴对象的句柄，以将焦点放在该轴上。|605793|(还没有评论权限，很抱歉有新的答案！)|605794|entityMap^0|6|1|0|0|L|7|X|1|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|T|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|U|8|@$9|V|A|W|B|C]|$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|M|3|N|5|6|7|Z|8|@]|D|@]|E|$]]|$1|O|3|-4|5|6|7|10|8|@]|D|@]|E|$]]]|P|$]]

However, numbering starts at <code>1</code>, so:

<pre><code>x = arange(5)
y = np.exp(5)
plt.figure(1)
plt.plot(x, y)

z = np.sin(x)
plt.figure(2)
plt.plot(x, z)

w = np.cos(x)
plt.figure(1) # Here's the part I need, but numbering starts at 1!
plt.plot(x, w)
</code></pre>

Also, if you have multiple axes on a figure, such as subplots, use the <code>axes(h)</code> command where <code>h</code> is the handle of the desired axes object to focus on that axes.

(don't have comment privileges yet, sorry for new answer!)

blocks|key|605852|text|如果您发现自己经常做这样的事情，那么研究matplotlib的面向对象接口可能是值得的。在您的案例中：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|605853|import+matplotlib.pyplot+as+plt
import+numpy+as+np

x+=+np.arange(5)
y+=+np.exp(x)
fig1,+ax1+=+plt.subplots()
ax1.plot(x,+y)
ax1.set_title("Axis+1+title")
ax1.set_xlabel("X-label+for+axis+1")

z+=+np.sin(x)
fig2,+(ax2,+ax3)+=+plt.subplots(nrows=2,+ncols=1)+#+two+axes+on+figure
ax2.plot(x,+z)
ax3.plot(x,+-z)

w+=+np.cos(x)
ax1.plot(x,+w)+#+can+continue+plotting+on+the+first+axis|code-block|syntax|javascript|605854|它有点冗长，但更清晰，更容易跟踪，特别是有几个数字，每个数字都有多个子图。|605855|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

If you find yourself doing things like this regularly it may be worth investigating the object-oriented interface to matplotlib. In your case:

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

x = np.arange(5)
y = np.exp(x)
fig1, ax1 = plt.subplots()
ax1.plot(x, y)
ax1.set_title("Axis 1 title")
ax1.set_xlabel("X-label for axis 1")

z = np.sin(x)
fig2, (ax2, ax3) = plt.subplots(nrows=2, ncols=1) # two axes on figure
ax2.plot(x, z)
ax3.plot(x, -z)

w = np.cos(x)
ax1.plot(x, w) # can continue plotting on the first axis
</code></pre>

It is a little more verbose but it's much clearer and easier to keep track of, especially with several figures each with multiple subplots.

blocks|key|605931|text|经过一番挣扎后，我发现的一种方法是创建一个函数，该函数获取data_plot矩阵、文件名和顺序作为参数，从有序图形中的给定数据创建箱图(不同的顺序=不同的图形)，并将其保存在给定的file_name下。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|605932|def+plotFigure(data_plot,file_name,order):
++++fig+=+plt.figure(order,+figsize=(9,+6))
++++ax+=+fig.add_subplot(111)
++++bp+=+ax.boxplot(data_plot)
++++fig.savefig(file_name,+bbox_inches='tight')
++++plt.close()|code-block|syntax|javascript|605933|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

One way I found after some struggling is creating a function which gets data_plot matrix, file name and order as parameter to create boxplots from the given data in the ordered figure (different orders = different figures) and save it under the given file_name.

<pre><code>def plotFigure(data_plot,file_name,order):
 fig = plt.figure(order, figsize=(9, 6))
 ax = fig.add_subplot(111)
 bp = ax.boxplot(data_plot)
 fig.savefig(file_name, bbox_inches='tight')
 plt.close()
</code></pre>

blocks|key|821130|text|为每个迭代绘制单独的帧的一种简单方法是：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|821131|import+matplotlib.pyplot+as+plt++
for+grp+in+list_groups:
++++++++plt.figure()
++++++++plt.plot(grp)
++++++++plt.show()|code-block|syntax|javascript|821132|然后python将绘制不同的帧。|821133|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

An easy way to plot separate frame for each iteration could be:
<pre><code>import matplotlib.pyplot as plt 
for grp in list_groups:
 plt.figure()
 plt.plot(grp)
 plt.show()
</code></pre>
Then python will plot different frames.

I want to plot data, then create a new figure and plot data2, and finally come back to the original plot and plot data3, kinda like this:

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

x = arange(5)
y = np.exp(5)
plt.figure()
plt.plot(x, y)

z = np.sin(x)
plt.figure()
plt.plot(x, z)

w = np.cos(x)
plt.figure("""first figure""") # Here's the part I need
plt.plot(x, w)
</code></pre>

FYI <a href="https://stackoverflow.com/questions/741877/how-do-i-tell-matplotlib-that-i-am-done-with-a-plot">How do I tell matplotlib that I am done with a plot?</a> does something similar, but not quite! It doesn't let me get access to that original plot.

How do I tell Matplotlib to create a second (new) plot, then later plot on the old one?

我想绘制数据，然后创建一个新的图形并绘制data2，最后回到原始的plot和plot data3，有点像这样：import numpy as npimport matplotlib as pltx = arange(5)y = np.exp(5)plt.figure()plt.plot(x, y)z = np.sin(...

问我如何告诉Matplotlib创建第二个(新的)图，然后在旧的图上绘制？
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问我如何告诉Matplotlib创建第二个(新的)图，然后在旧的图上绘制？
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