blocks|key|2197332|text|编辑|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|entityRanges|data|2197333|将aspect='normal更改为aspect='auto'，因为这在matplotlib的最新版本中发生了变化(多亏了@Luke19+19)。|CODE|2197334|假设：|2197335|import+matplotlib.pyplot+as+plt|code-block|syntax|javascript|2197336|在没有框架的情况下制作一个图形：|2197337|fig+=+plt.figure(frameon=False)
fig.set_size_inches(w,h)|2197338|使内容填充整个数字|2197339|ax+=+plt.Axes(fig,+[0.,+0.,+1.,+1.])
ax.set_axis_off()
fig.add_axes(ax)|2197340|然后在上面画你的图像：|2197341|ax.imshow(your_image,+aspect='auto')
fig.savefig(fname,+dpi)|2197342|aspect参数更改像素大小，以确保它们填充fig.set_size_inches(…)中指定的图形大小。要了解如何处理这类事情，请阅读matplotlib文档，特别是关于轴、轴和艺术家的主题。|2197343|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.sourceforge.net/api/^0|0|2|0|1|E|I|D|0|0|0|0|0|0|0|0|0|0|6|M|M|1W|C|0|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]|$9|1H|A|1I|B|H]]|D|@]|E|$]]|$1|I|3|J|5|6|7|1J|8|@]|D|@]|E|$]]|$1|K|3|L|5|M|7|1K|8|@]|D|@]|E|$N|O]]|$1|P|3|Q|5|6|7|1L|8|@]|D|@]|E|$]]|$1|R|3|S|5|M|7|1M|8|@]|D|@]|E|$N|O]]|$1|T|3|U|5|6|7|1N|8|@]|D|@]|E|$]]|$1|V|3|W|5|M|7|1O|8|@]|D|@]|E|$N|O]]|$1|X|3|Y|5|6|7|1P|8|@]|D|@]|E|$]]|$1|Z|3|10|5|M|7|1Q|8|@]|D|@]|E|$N|O]]|$1|11|3|12|5|6|7|1R|8|@$9|1S|A|1T|B|H]|$9|1U|A|1V|B|H]]|D|@$9|1W|A|1X|1|1Y]]|E|$]]|$1|13|3|-4|5|6|7|1Z|8|@]|D|@]|E|$]]]|14|$15|$5|16|17|18|E|$19|1A]]]]

EDIT

Changed <code>aspect='normal</code> to <code>aspect='auto'</code> since that changed in more recent versions of matplotlib (thanks to @Luke19).

<hr>

Assuming : 



<pre class="lang-py prettyprint-override"><code>import matplotlib.pyplot as plt
</code></pre>

To make a figure without the frame :

<pre class="lang-py prettyprint-override"><code>fig = plt.figure(frameon=False)
fig.set_size_inches(w,h)
</code></pre>

To make the content fill the whole figure 

<pre class="lang-py prettyprint-override"><code>ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
</code></pre>

Then draw your image on it :

<pre class="lang-py prettyprint-override"><code>ax.imshow(your_image, aspect='auto')
fig.savefig(fname, dpi)
</code></pre>

The <code>aspect</code> parameter changes the pixel size to make sure they fill the figure size specified in <code>fig.set_size_inches(…)</code>. To get a feel of how to play with this sort of things, read through <a href="http://matplotlib.sourceforge.net/api/" rel="noreferrer">matplotlib's documentation</a>, particularly on the subject of Axes, Axis and Artist.

blocks|key|2197389|text|一个更容易的解决办法似乎是：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2197390|fig.savefig('out.png',+bbox_inches='tight',+pad_inches=0)|code-block|syntax|javascript|2197391|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|$]]

An easier solution seems to be:

<pre><code>fig.savefig('out.png', bbox_inches='tight', pad_inches=0)
</code></pre>

blocks|key|2197358|text|您可以在轴内找到图像的bbox+(使用get_window_extent)，并使用bbox_inches参数只保存图像的这一部分：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2197359|import+numpy+as+np
import+matplotlib.pyplot+as+plt

data=np.arange(9).reshape((3,3))
fig=plt.figure()
ax=fig.add_subplot(1,1,1)
plt.axis('off')
plt.imshow(data)

extent+=+ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig('/tmp/test.png',+bbox_inches=extent)|code-block|syntax|javascript|2197360|我从乔·金顿(+Joe+这里+)那里学到了这个技巧。|2197361|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/4325733/save-a-subplot-in-matplotlib/4328608#4328608^0|J|H|15|B|0|0|C|2|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@$9|V|A|W|B|C]|$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|10|8|@]|D|@$9|11|A|12|1|13]]|E|$]]|$1|M|3|-4|5|6|7|14|8|@]|D|@]|E|$]]]|N|$O|$5|P|Q|R|E|$S|T]]]]

You can find the bbox of the image inside the axis (using <code>get_window_extent</code>), and use the <code>bbox_inches</code> parameter to save only that portion of the image:

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

data=np.arange(9).reshape((3,3))
fig=plt.figure()
ax=fig.add_subplot(1,1,1)
plt.axis('off')
plt.imshow(data)

extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig('/tmp/test.png', bbox_inches=extent)
</code></pre>

I learned this trick from Joe Kington <a href="https://stackoverflow.com/questions/4325733/save-a-subplot-in-matplotlib/4328608#4328608">here</a>.

blocks|key|374847|text|在我的案例中，我尝试了几种选择，最好的解决方案是：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|374848|fig.subplots_adjust(bottom+=+0)
fig.subplots_adjust(top+=+1)
fig.subplots_adjust(right+=+1)
fig.subplots_adjust(left+=+0)|code-block|syntax|javascript|374849|然后用savefig保存您的数字|offset|length|style|CODE|374850|entityMap^0|0|0|3|7|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@$I|R|J|S|K|L]]|9|@]|A|$]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

I've tried several options in my case, and the best solution was this:

<pre><code>fig.subplots_adjust(bottom = 0)
fig.subplots_adjust(top = 1)
fig.subplots_adjust(right = 1)
fig.subplots_adjust(left = 0)
</code></pre>

then save your figure with <code>savefig</code>

blocks|key|173926|text|任何想用木星做这件事的人|type|unstyled|depth|inlineStyleRanges|entityRanges|data|173927|+plt.axis('off')

+spec+=+plt.imshow

+plt.savefig('spec',bbox_inches='tight',transparent=True,+pad_inches=0)|code-block|syntax|javascript|173928|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|$]]

For anybody trying to do this in Jupyter

<pre><code> plt.axis('off')

 spec = plt.imshow

 plt.savefig('spec',bbox_inches='tight',transparent=True, pad_inches=0)
</code></pre>

blocks|key|173888|text|因此，我建议heron13回答时，从这里处借用一点，以便在将bbox设置为紧模式后移除左边的填充，因此：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|173889|axes+=+fig.axes()
axes.get_xaxis().set_visible(False)
axes.get_yaxis().set_visible(False)
fig.savefig('out.png',+bbox_inches='tight',+pad_inches=0)|code-block|syntax|javascript|173890|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/2176424/hiding-axis-text-in-matplotlib-plots^0|I|2|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

I will suggest heron13 answer with a slight addition borrowed from <a href="https://stackoverflow.com/questions/2176424/hiding-axis-text-in-matplotlib-plots">here</a> to remove the padding left after setting the bbox to tight mode, therefore:

<pre><code>axes = fig.axes()
axes.get_xaxis().set_visible(False)
axes.get_yaxis().set_visible(False)
fig.savefig('out.png', bbox_inches='tight', pad_inches=0)
</code></pre>

blocks|key|2197467|text|这个为我工作|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2197468|plt.savefig('filename',bbox_inches='tight',transparent=True,+pad_inches=0)|code-block|syntax|javascript|2197469|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|$]]

This one work for me

<pre><code>plt.savefig('filename',bbox_inches='tight',transparent=True, pad_inches=0)
</code></pre>

blocks|key|2197635|text|实际上，我最近已经尝试过了，而不是所有这些行，您可以使用|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2197636|plt.imsave(image_path,+image)|code-block|syntax|javascript|2197637|就像一种魅力。只有一条线和问题解决了。|2197638|imsave()|2197639|文档(+gen/matplotlib.pyplot.imsave.html+)|offset|length|2197640|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.imsave.html^0|0|0|0|0|4|X|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|X|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Y|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|Z|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|10|8|@]|9|@$M|11|N|12|1|13]]|A|$]]|$1|O|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V]]]]

Actually I have tried this recently and instead of all these lines, you can use

<pre><code>plt.imsave(image_path, image)
</code></pre>

Works like a charm. just one line and problem solved. 

<pre><code>imsave()
</code></pre>

Documentation ( <a href="https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.imsave.html" rel="noreferrer">https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.imsave.html</a> )

blocks|key|174779|text|对我来说，这段代码使输入的图像大小类似，没有框架和轴。我组合了来自马蒂帽、乌图布和WHZW的片段|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|174780|fig+=+plt.figure()
ax+=+fig.add_subplot(1,1,1)
plt.axis('off')
viridis+=+cm.get_cmap('gist_gray',+256)
plt.imshow(data,+aspect='auto',+cmap=viridis)
plt.tight_layout()
plt.savefig(out_file,+bbox_inches='tight',+transparent=True,+pad_inches=0)|code-block|syntax|javascript|174781|运行时环境：|174782|基本Python:+3.6.10|174783|主要材料库:+3.2.1|174784|操作系统:+Windows+10|174785|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/a/8218887/5595995|1|https://stackoverflow.com/a/8219171/5595995|2^0|X|3|0|11|3|1|15|4|2|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|11|8|@]|9|@$A|12|B|13|1|14]|$A|15|B|16|1|17]|$A|18|B|19|1|1A]]|C|$]]|$1|D|3|E|5|F|7|1B|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|1C|8|@]|9|@]|C|$]]|$1|K|3|L|5|6|7|1D|8|@]|9|@]|C|$]]|$1|M|3|N|5|6|7|1E|8|@]|9|@]|C|$]]|$1|O|3|P|5|6|7|1F|8|@]|9|@]|C|$]]|$1|Q|3|-4|5|6|7|1G|8|@]|9|@]|C|$]]]|R|$S|$5|T|U|V|C|$W|X]]|Y|$5|T|U|V|C|$W|Z]]|10|$5|T|U|V|C|$W|X]]]]

For me, this code made similar the input image size without frame and axes. I combined snippets from <a href="https://stackoverflow.com/a/8218887/5595995">matehat</a>, <a href="https://stackoverflow.com/a/8219171/5595995">unutbu</a>, and <a href="https://stackoverflow.com/a/8218887/5595995">WHZW</a>:
<pre><code>fig = plt.figure()
ax = fig.add_subplot(1,1,1)
plt.axis('off')
viridis = cm.get_cmap('gist_gray', 256)
plt.imshow(data, aspect='auto', cmap=viridis)
plt.tight_layout()
plt.savefig(out_file, bbox_inches='tight', transparent=True, pad_inches=0)
</code></pre>
Runtime environment: 
  Python: 3.6.10 
  Matplotlib: 3.2.1 
  OS: Windows 10

blocks|key|374884|text|在使用利布罗萨进行可视化时，我也遇到了同样的问题，在这里，我想在没有任何其他信息的情况下提取情节的内容。所以这是我的方法。你的回答也能帮助我去工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|374885|++++figure+=+plt.figure(figsize=(500,+600),+dpi=1)
++++axis+=+plt.subplot(1,+1,+1)
++++plt.axis('off')
++++plt.tick_params(axis='both',+left='off',+top='off',+right='off',+bottom='off',+labelleft='off',+labeltop='off',
++++++++++++++++++++labelright='off',+labelbottom='off')

+++++#+your+code+goes+here.+e.g:+I+used+librosa+function+to+draw+a+image
++++result+=+np.array(clip.feature_list['fft'].get_logamplitude()[0:2])
++++librosa.display.specshow(result,+sr=api.Clip.RATE,+x_axis='time',+y_axis='mel',+cmap='RdBu_r')


++++extent+=+axis.get_window_extent().transformed(figure.dpi_scale_trans.inverted())
++++plt.savefig((clip.filename+%2B+str("_.jpg")),+format='jpg',+bbox_inches=extent,+pad_inches=0)
++++plt.close()|code-block|syntax|javascript|374886|entityMap|0|LINK|mutability|MUTABLE|url|https://librosa.github.io/librosa/generated/librosa.display.waveplot.html^0|3|4|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

I had the same problem while doing some visualization using <a href="https://librosa.github.io/librosa/generated/librosa.display.waveplot.html" rel="nofollow noreferrer">librosa</a> where I wanted to extract content of the plot without any other information. So this my approach. unutbu answer also helps me to make to work.

<pre><code> figure = plt.figure(figsize=(500, 600), dpi=1)
 axis = plt.subplot(1, 1, 1)
 plt.axis('off')
 plt.tick_params(axis='both', left='off', top='off', right='off', bottom='off', labelleft='off', labeltop='off',
 labelright='off', labelbottom='off')

 # your code goes here. e.g: I used librosa function to draw a image
 result = np.array(clip.feature_list['fft'].get_logamplitude()[0:2])
 librosa.display.specshow(result, sr=api.Clip.RATE, x_axis='time', y_axis='mel', cmap='RdBu_r')


 extent = axis.get_window_extent().transformed(figure.dpi_scale_trans.inverted())
 plt.savefig((clip.filename + str("_.jpg")), format='jpg', bbox_inches=extent, pad_inches=0)
 plt.close()
</code></pre>

blocks|key|173918|text|虽然上面的答案解决了删除边距和填充的问题，但它们在删除标签方面对我不起作用。对于那些后来偶然发现这个问题的人来说，以下是起作用的原因：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|173919|假设您需要存储在images中的四个图像中的2x2个子图网格|offset|length|style|CODE|173920|matplotlib.pyplot.figure(figsize+=+(16,12))+#+or+whatever+image+size+you+require
for+i+in+range(4):
++++ax+=+matplotlib.pyplot.subplot(2,2,i%2B1)
++++ax.axis('off')
++++imshow(images[i])
matplotlib.pyplot.savefig(path,+bbox_inches='tight')|code-block|syntax|javascript|173921|entityMap^0|0|8|6|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|P|8|@$D|Q|E|R|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|S|8|@]|9|@]|A|$K|L]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

While the above answers address removing margins and padding, they did not work for me in removing labels. Here's what worked, for anyone who stumbles upon this question later:

Assuming you want a 2x2 grid of subplots from four images stored in <code>images</code>:

<pre><code>matplotlib.pyplot.figure(figsize = (16,12)) # or whatever image size you require
for i in range(4):
 ax = matplotlib.pyplot.subplot(2,2,i+1)
 ax.axis('off')
 imshow(images[i])
matplotlib.pyplot.savefig(path, bbox_inches='tight')
</code></pre>

blocks|key|374999|text|我也试图摆脱边界，在这里使用提示，但没有真正的工作。一些人摆弄着，我发现在朱皮特实验室里，改变脸的颜色没有给我带来任何边界(任何颜色都会导致去掉白色的边框)。希望这能有所帮助。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|375000|def+show_num(data):
data+=+np.rot90(data.reshape((16,16)),+k=3)
data+=+np.fliplr(data)
fig+=+plt.figure(frameon=False,+facecolor='white')
ax+=+plt.Axes(fig,+[0.,+0.,+1.,+1.])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(data)
plt.show()|code-block|syntax|javascript|375001|​|375002|📷|atomic|offset|length|375003|375004|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/5612b60aba7b23a5f69fe8f89dd6c3ae.png|imageAlt^0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|X|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|Y|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Z|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|10|8|@]|9|@$L|11|M|12|1|13]]|A|$]]|$1|N|3|H|5|6|7|14|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V|W|-4]]]]

I tried to get rid of the border too, using tips here but nothing really worked.
Some fiddling about and I found that changing the faceolor gave me no border in jupyter labs (Any color resulted in getting rid of the white border). 
Hope this helps.

<pre><code>def show_num(data):
data = np.rot90(data.reshape((16,16)), k=3)
data = np.fliplr(data)
fig = plt.figure(frameon=False, facecolor='white')
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
ax.imshow(data)
plt.show()
</code></pre>

<a href="https://i.stack.imgur.com/EaEGd.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/EaEGd.png" alt="enter image description here"></a>

In numpy/scipy I have an image stored in an array. I can display it, I want to save it using <code>savefig</code> without any borders, axes, labels, titles,... Just pure image, nothing else.

I want to avoid packages like <code>PyPNG</code> or <code>scipy.misc.imsave</code>, they are sometimes problematic (they do not always install well, only basic <code>savefig()</code> for me

scipy: savefig without frames, axes, only content

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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在numpy/scipy中，我将图像存储在数组中。我可以显示它，我想保存它使用savefig没有任何边框，轴，标签，标题，.只是纯粹的形象，没有别的。我想避免像PyPNG或scipy.misc.imsave这样的软件包，它们有时是有问题的(它们并不总是安装得很好，只对我来说是基本的savefig() )

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