blocks|key|3106476|text|补充道：我发现了一些可以立即解决问题的方法，但下面的其余代码也提供了另一种选择。|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|3106477|使用subplots_adjust()函数向上移动子图的底部：|CODE|3106478|fig.subplots_adjust(bottom=0.2)+#+<--+Change+the+0.02+to+work+for+your+plot.|code-block|syntax|javascript|3106479|然后使用图例命令的图例bbox_to_anchor部分中的偏移量，将图例框放在您想要的位置。设置figsize和使用subplots_adjust(bottom=...)的某种组合应该会为您生成高质量的绘图。|3106480|Alternative:我只是简单地更改了这一行：|3106481|fig+=+plt.figure(1)|3106482|至：|3106483|fig+=+plt.figure(num=1,+figsize=(13,+13),+dpi=80,+facecolor='w',+edgecolor='k')|3106484|并且改变了|3106485|lgd+=+ax.legend(loc=9,+bbox_to_anchor=(0.5,0))|3106486|至|3106487|lgd+=+ax.legend(loc=9,+bbox_to_anchor=(0.5,-0.02))|3106488|它在我的屏幕(24英寸的CRT显示器)上显示得很好。|3106489|在这里，figsize=(M,N)将图形窗口设置为M英寸x+N英寸。试着使用它，直到它看起来适合你。将其转换为更具可伸缩性的图像格式，并在必要时使用GIMP进行编辑，或者在包含图形时仅使用LaTeX+viewport选项进行裁剪。|3106490|entityMap^0|0|4|0|2|H|0|0|B|E|1C|7|1M|R|0|0|C|0|0|0|0|0|0|0|0|0|4|D|2S|8|0^^$0|@$1|2|3|4|5|6|7|1B|8|@$9|1C|A|1D|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1E|8|@$9|1F|A|1G|B|H]]|D|@]|E|$]]|$1|I|3|J|5|K|7|1H|8|@]|D|@]|E|$L|M]]|$1|N|3|O|5|6|7|1I|8|@$9|1J|A|1K|B|H]|$9|1L|A|1M|B|H]|$9|1N|A|1O|B|H]]|D|@]|E|$]]|$1|P|3|Q|5|6|7|1P|8|@$9|1Q|A|1R|B|C]]|D|@]|E|$]]|$1|R|3|S|5|K|7|1S|8|@]|D|@]|E|$L|M]]|$1|T|3|U|5|6|7|1T|8|@]|D|@]|E|$]]|$1|V|3|W|5|K|7|1U|8|@]|D|@]|E|$L|M]]|$1|X|3|Y|5|6|7|1V|8|@]|D|@]|E|$]]|$1|Z|3|10|5|K|7|1W|8|@]|D|@]|E|$L|M]]|$1|11|3|12|5|6|7|1X|8|@]|D|@]|E|$]]|$1|13|3|14|5|K|7|1Y|8|@]|D|@]|E|$L|M]]|$1|15|3|16|5|6|7|1Z|8|@]|D|@]|E|$]]|$1|17|3|18|5|6|7|20|8|@$9|21|A|22|B|H]|$9|23|A|24|B|H]]|D|@]|E|$]]|$1|19|3|-4|5|6|7|25|8|@]|D|@]|E|$]]]|1A|$]]

Added: I found something that should do the trick right away, but the rest of the code below also offers an alternative.

Use the <code>subplots_adjust()</code> function to move the bottom of the subplot up:

<pre><code>fig.subplots_adjust(bottom=0.2) # &lt;-- Change the 0.02 to work for your plot.
</code></pre>

Then play with the offset in the legend <code>bbox_to_anchor</code> part of the legend command, to get the legend box where you want it. Some combination of setting the <code>figsize</code> and using the <code>subplots_adjust(bottom=...)</code> should produce a quality plot for you.

Alternative:
I simply changed the line:

<pre><code>fig = plt.figure(1)
</code></pre>

to:

<pre><code>fig = plt.figure(num=1, figsize=(13, 13), dpi=80, facecolor='w', edgecolor='k')
</code></pre>

and changed

<pre><code>lgd = ax.legend(loc=9, bbox_to_anchor=(0.5,0))
</code></pre>

to

<pre><code>lgd = ax.legend(loc=9, bbox_to_anchor=(0.5,-0.02))
</code></pre>

and it shows up fine on my screen (a 24-inch CRT monitor). 

Here <code>figsize=(M,N)</code> sets the figure window to be M inches by N inches. Just play with this until it looks right for you. Convert it to a more scalable image format and use GIMP to edit if necessary, or just crop with the LaTeX <code>viewport</code> option when including graphics.

blocks|key|3106569|text|抱歉，EMS，但实际上我刚刚从matplotlib邮件列表中得到了另一个回复(感谢本杰明·鲁特)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3106570|我正在寻找的代码是将savefig调用调整为：|3106571|fig.savefig('samplefigure',+bbox_extra_artists=(lgd,),+bbox_inches='tight')
#Note+that+the+bbox_extra_artists+must+be+an+iterable|code-block|syntax|javascript|3106572|这显然类似于调用tight_layout，但是您允许savefig在计算中考虑额外的艺术家。这实际上根据需要调整了数字框的大小。|3106573|import+matplotlib.pyplot+as+plt
import+numpy+as+np

plt.gcf().clear()
x+=+np.arange(-2*np.pi,+2*np.pi,+0.1)
fig+=+plt.figure(1)
ax+=+fig.add_subplot(111)
ax.plot(x,+np.sin(x),+label='Sine')
ax.plot(x,+np.cos(x),+label='Cosine')
ax.plot(x,+np.arctan(x),+label='Inverse+tan')
handles,+labels+=+ax.get_legend_handles_labels()
lgd+=+ax.legend(handles,+labels,+loc='upper+center',+bbox_to_anchor=(0.5,-0.1))
text+=+ax.text(-0.2,1.05,+"Aribitrary+text",+transform=ax.transAxes)
ax.set_title("Trigonometry")
ax.grid('on')
fig.savefig('samplefigure',+bbox_extra_artists=(lgd,text),+bbox_inches='tight')|3106574|这会产生以下结果：|3106575|​|3106576|📷|atomic|offset|length|3106577|3106578|编辑这个问题的目的是完全避免使用任意文本的任意坐标位置，因为这是这些问题的传统解决方案。尽管如此，最近的许多编辑都坚持将它们放入其中，通常是以导致代码引发错误的方式。现在，我已经修复了这些问题，并整理了任意文本，以显示如何在bbox_extra_artists算法中考虑这些问题。|3106579|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/2f78be82562f27fc417c8933c63fc71f.png|imageAlt^0|0|0|0|0|0|0|0|0|1|0|0|0|0^^$0|@$1|2|3|4|5|6|7|17|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|18|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|19|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|1A|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|1B|8|@]|9|@]|A|$G|H]]|$1|M|3|N|5|6|7|1C|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|1D|8|@]|9|@]|A|$]]|$1|Q|3|R|5|S|7|1E|8|@]|9|@$T|1F|U|1G|1|1H]]|A|$]]|$1|V|3|P|5|6|7|1I|8|@]|9|@]|A|$]]|$1|W|3|X|5|6|7|1J|8|@]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|1K|8|@]|9|@]|A|$]]]|Z|$10|$5|11|12|13|A|$14|15|16|-4]]]]

Sorry EMS, but I actually just got another response from the matplotlib mailling list (Thanks goes out to Benjamin Root).

The code I am looking for is adjusting the savefig call to:

<pre><code>fig.savefig('samplefigure', bbox_extra_artists=(lgd,), bbox_inches='tight')
#Note that the bbox_extra_artists must be an iterable
</code></pre>

This is apparently similar to calling tight_layout, but instead you allow savefig to consider extra artists in the calculation. This did in fact resize the figure box as desired.

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

plt.gcf().clear()
x = np.arange(-2*np.pi, 2*np.pi, 0.1)
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.plot(x, np.sin(x), label='Sine')
ax.plot(x, np.cos(x), label='Cosine')
ax.plot(x, np.arctan(x), label='Inverse tan')
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5,-0.1))
text = ax.text(-0.2,1.05, "Aribitrary text", transform=ax.transAxes)
ax.set_title("Trigonometry")
ax.grid('on')
fig.savefig('samplefigure', bbox_extra_artists=(lgd,text), bbox_inches='tight')
</code></pre>

This produces:

<img src="https://i.imgur.com/qysSE4t.png" alt="">

[edit] The intent of this question was to completely avoid the use of arbitrary coordinate placements of arbitrary text as was the traditional solution to these problems. Despite this, numerous edits recently have insisted on putting these in, often in ways that led to the code raising an error. I have now fixed the issues and tidied the arbitrary text to show how these are also considered within the bbox_extra_artists algorithm.

blocks|key|3106630|text|这是另一个非常手动的解决方案。您可以定义轴的大小，并相应地考虑填充(包括图例和记号)。希望对某些人有用。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3106631|示例(轴大小相同！)：|3106632|​|3106633|📷|atomic|offset|length|3106634|3106635|代码：|3106636|#==================================================
#+Plot+table

colmap+=+[(0,0,1)+#blue
+++++++++,(1,0,0)+#red
+++++++++,(0,1,0)+#green
+++++++++,(1,1,0)+#yellow
+++++++++,(1,0,1)+#magenta
+++++++++,(1,0.5,0.5)+#pink
+++++++++,(0.5,0.5,0.5)+#gray
+++++++++,(0.5,0,0)+#brown
+++++++++,(1,0.5,0)+#orange
+++++++++]


import+matplotlib.pyplot+as+plt
import+numpy+as+np

import+collections
df+=+collections.OrderedDict()
df['labels']++++++++=+['GWP100a\n[kgCO2eq]\n\nasedf\nasdf\nadfs','human\n[pts]','ressource\n[pts]']+
df['all-petroleum+long+name']+=+[3,5,2]
df['all-electric']++=+[5.5,+1,+3]
df['HEV']+++++++++++=+[3.5,+2,+1]
df['PHEV']++++++++++=+[3.5,+2,+1]

numLabels+=+len(df.values()[0])
numItems+=+len(df)-1
posX+=+np.arange(numLabels)%2B1
width+=+1.0/(numItems%2B1)

fig+=+plt.figure(figsize=(2,2))
ax+=+fig.add_subplot(111)
for+iiItem+in+range(1,numItems%2B1):
++ax.bar(posX%2B(iiItem-1)*width,+df.values()[iiItem],+width,+color=colmap[iiItem-1],+label=df.keys()[iiItem])
ax.set(xticks=posX%2Bwidth*(0.5*numItems),+xticklabels=df['labels'])

#--------------------------------------------------
#+Change+padding+and+margins,+insert+legend

fig.tight_layout()+#tight+margins
leg+=+ax.legend(loc='upper+left',+bbox_to_anchor=(1.02,+1),+borderaxespad=0)
plt.draw()+#to+know+size+of+legend

padLeft+++=+ax.get_position().x0+*+fig.get_size_inches()[0]
padBottom+=+ax.get_position().y0+*+fig.get_size_inches()[1]
padTop++++=+(+1+-+ax.get_position().y0+-+ax.get_position().height+)+*+fig.get_size_inches()[1]
padRight++=+(+1+-+ax.get_position().x0+-+ax.get_position().width+)+*+fig.get_size_inches()[0]
dpi+++++++=+fig.get_dpi()
padLegend+=+ax.get_legend().get_frame().get_width()+/+dpi+

widthAx+=+3+#inches
heightAx+=+3+#inches
widthTot+=+widthAx%2BpadLeft%2BpadRight%2BpadLegend
heightTot+=+heightAx%2BpadTop%2BpadBottom

#+resize+ipython+window+(optional)
posScreenX+=+1366/2-10+#pixel
posScreenY+=+0+#pixel
canvasPadding+=+6+#pixel
canvasBottom+=+40+#pixel
ipythonWindowSize+=+'{0}x{1}%2B{2}%2B{3}'.format(int(round(widthTot*dpi))%2B2*canvasPadding
++++++++++++++++++++++++++++++++++++++++++++,int(round(heightTot*dpi))%2B2*canvasPadding%2BcanvasBottom
++++++++++++++++++++++++++++++++++++++++++++,posScreenX,posScreenY)
fig.canvas._tkcanvas.master.geometry(ipythonWindowSize)+
plt.draw()+#to+resize+ipython+window.+Has+to+be+done+BEFORE+figure+resizing!

#+set+figure+size+and+ax+position
fig.set_size_inches(widthTot,heightTot)
ax.set_position([padLeft/widthTot,+padBottom/heightTot,+widthAx/widthTot,+heightAx/heightTot])
plt.draw()
plt.show()
#--------------------------------------------------
#==================================================|code-block|syntax|javascript|3106637|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/afc9cb32ef626c58b0714a98a2353aad.png|imageAlt^0|0|0|0|0|1|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|11|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|12|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|13|8|@]|9|@]|A|$]]|$1|F|3|G|5|H|7|14|8|@]|9|@$I|15|J|16|1|17]]|A|$]]|$1|K|3|E|5|6|7|18|8|@]|9|@]|A|$]]|$1|L|3|M|5|6|7|19|8|@]|9|@]|A|$]]|$1|N|3|O|5|P|7|1A|8|@]|9|@]|A|$Q|R]]|$1|S|3|-4|5|6|7|1B|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z|10|-4]]]]

Here is another, very manual solution. You can define the size of the axis and paddings are considered accordingly (including legend and tickmarks). Hope it is of use to somebody.

Example (axes size are the same!):

<img src="https://i.stack.imgur.com/P9LNA.png" alt="enter image description here">

Code:

<pre><code>#==================================================
# Plot table

colmap = [(0,0,1) #blue
 ,(1,0,0) #red
 ,(0,1,0) #green
 ,(1,1,0) #yellow
 ,(1,0,1) #magenta
 ,(1,0.5,0.5) #pink
 ,(0.5,0.5,0.5) #gray
 ,(0.5,0,0) #brown
 ,(1,0.5,0) #orange
 ]


import matplotlib.pyplot as plt
import numpy as np

import collections
df = collections.OrderedDict()
df['labels'] = ['GWP100a\n[kgCO2eq]\n\nasedf\nasdf\nadfs','human\n[pts]','ressource\n[pts]'] 
df['all-petroleum long name'] = [3,5,2]
df['all-electric'] = [5.5, 1, 3]
df['HEV'] = [3.5, 2, 1]
df['PHEV'] = [3.5, 2, 1]

numLabels = len(df.values()[0])
numItems = len(df)-1
posX = np.arange(numLabels)+1
width = 1.0/(numItems+1)

fig = plt.figure(figsize=(2,2))
ax = fig.add_subplot(111)
for iiItem in range(1,numItems+1):
 ax.bar(posX+(iiItem-1)*width, df.values()[iiItem], width, color=colmap[iiItem-1], label=df.keys()[iiItem])
ax.set(xticks=posX+width*(0.5*numItems), xticklabels=df['labels'])

#--------------------------------------------------
# Change padding and margins, insert legend

fig.tight_layout() #tight margins
leg = ax.legend(loc='upper left', bbox_to_anchor=(1.02, 1), borderaxespad=0)
plt.draw() #to know size of legend

padLeft = ax.get_position().x0 * fig.get_size_inches()[0]
padBottom = ax.get_position().y0 * fig.get_size_inches()[1]
padTop = ( 1 - ax.get_position().y0 - ax.get_position().height ) * fig.get_size_inches()[1]
padRight = ( 1 - ax.get_position().x0 - ax.get_position().width ) * fig.get_size_inches()[0]
dpi = fig.get_dpi()
padLegend = ax.get_legend().get_frame().get_width() / dpi 

widthAx = 3 #inches
heightAx = 3 #inches
widthTot = widthAx+padLeft+padRight+padLegend
heightTot = heightAx+padTop+padBottom

# resize ipython window (optional)
posScreenX = 1366/2-10 #pixel
posScreenY = 0 #pixel
canvasPadding = 6 #pixel
canvasBottom = 40 #pixel
ipythonWindowSize = '{0}x{1}+{2}+{3}'.format(int(round(widthTot*dpi))+2*canvasPadding
 ,int(round(heightTot*dpi))+2*canvasPadding+canvasBottom
 ,posScreenX,posScreenY)
fig.canvas._tkcanvas.master.geometry(ipythonWindowSize) 
plt.draw() #to resize ipython window. Has to be done BEFORE figure resizing!

# set figure size and ax position
fig.set_size_inches(widthTot,heightTot)
ax.set_position([padLeft/widthTot, padBottom/heightTot, widthAx/widthTot, heightAx/heightTot])
plt.draw()
plt.show()
#--------------------------------------------------
#==================================================
</code></pre>

I'm familiar with the following questions:

<a href="https://stackoverflow.com/questions/8971834/matplotlib-savefig-with-a-legend-outside-the-plot">Matplotlib savefig with a legend outside the plot</a>

<a href="https://stackoverflow.com/questions/4700614/how-to-put-the-legend-out-of-the-plot">How to put the legend out of the plot</a>

It seems that the answers in these questions have the luxury of being able to fiddle with the exact shrinking of the axis so that the legend fits. 

Shrinking the axes, however, is not an ideal solution because it makes the data smaller making it actually more difficult to interpret; particularly when its complex and there are lots of things going on ... hence needing a large legend

The example of a complex legend in the documentation demonstrates the need for this because the legend in their plot actually completely obscures multiple data points.

<a href="http://matplotlib.sourceforge.net/users/legend_guide.html#legend-of-complex-plots" rel="noreferrer">http://matplotlib.sourceforge.net/users/legend_guide.html#legend-of-complex-plots</a> 

What I would like to be able to do is dynamically expand the size of the figure box to accommodate the expanding figure legend.

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

x = np.arange(-2*np.pi, 2*np.pi, 0.1)
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.plot(x, np.sin(x), label='Sine')
ax.plot(x, np.cos(x), label='Cosine')
ax.plot(x, np.arctan(x), label='Inverse tan')
lgd = ax.legend(loc=9, bbox_to_anchor=(0.5,0))
ax.grid('on')
</code></pre>

Notice how the final label 'Inverse tan' is actually outside the figure box (and looks badly cutoff - not publication quality!)
<img src="https://i.stack.imgur.com/0XtO2.png" alt="enter image description here">

Finally, I've been told that this is normal behaviour in R and LaTeX, so I'm a little confused why this is so difficult in python... Is there a historical reason? Is Matlab equally poor on this matter?

I have the (only slightly) longer version of this code on pastebin <a href="http://pastebin.com/grVjc007" rel="noreferrer">http://pastebin.com/grVjc007</a>

Moving matplotlib legend outside of the axis makes it cutoff by the figure box

我熟悉以下问题：似乎这些问题中的答案都可以随意调整轴的精确收缩，以便与图例相吻合。然而，缩小轴并不是一个理想的解决方案，因为它会使数据变得更小，实际上更难解释；特别是当它很复杂，有很多事情在发生时……因此需要一个大的图例文档中复杂图例的示例演示了这种需要，因为它们图中的图例实际上完全遮挡了多个数据点。我想要做的是动态扩...

问将matplotlib图例移动到轴外将使其被图形框截断
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