blocks|key|287757|text|我不能说我确切地知道我的“解决方案”是如何工作的，但当我想要将几个机翼截面的轮廓绘制到PDF文件中时，我不得不这样做。(请注意，我在带有-pylab标志的IPython笔记本中使用了matplotlib。)|type|unstyled|depth|inlineStyleRanges|entityRanges|data|287758|plt.gca().set_axis_off()
plt.subplots_adjust(top+=+1,+bottom+=+0,+right+=+1,+left+=+0,+
++++++++++++hspace+=+0,+wspace+=+0)
plt.margins(0,0)
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.savefig("filename.pdf",+bbox_inches+=+'tight',
++++pad_inches+=+0)|code-block|syntax|javascript|287759|我试过停用它的不同部分，但这总会导致某个地方出现白边距。您甚至可以对此进行修改，以避免由于缺少页边距而使图形边界附近的粗线条被修剪。|287760|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|$]]

I cannot claim I know exactly why or how my &ldquo;solution&rdquo; works, but this is what I had to do when I wanted to plot the outline of a couple of aerofoil sections &mdash; without white margins &mdash; to a PDF file. 
(Note that I used matplotlib inside an IPython notebook, with the -pylab flag.)

<pre><code>plt.gca().set_axis_off()
plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0, 
 hspace = 0, wspace = 0)
plt.margins(0,0)
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.gca().yaxis.set_major_locator(plt.NullLocator())
plt.savefig("filename.pdf", bbox_inches = 'tight',
 pad_inches = 0)
</code></pre>

I have tried to deactivate different parts of this, but this always lead to a white margin somewhere. You may even have modify this to keep fat lines near the limits of the figure from being shaved by the lack of margins.

blocks|key|287785|text|我从Arvind+Pereira+(http://robotics.usc.edu/~ampereir/wordpress/?p=626)那里找到了一些东西，似乎对我很有效：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|287786|plt.savefig(filename,+transparent+=+True,+bbox_inches+=+'tight',+pad_inches+=+0)|code-block|syntax|javascript|287787|entityMap|0|LINK|mutability|MUTABLE|url|http://robotics.usc.edu/~ampereir/wordpress/?p=626^0|I|1E|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 found something from Arvind Pereira (<a href="http://robotics.usc.edu/~ampereir/wordpress/?p=626" rel="noreferrer">http://robotics.usc.edu/~ampereir/wordpress/?p=626</a>) and seemed to work for me:

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

blocks|key|504561|text|这对我将使用imshow绘制的numpy数组保存到文件中很有效|type|unstyled|depth|inlineStyleRanges|entityRanges|data|504562|import+matplotlib.pyplot+as+plt

fig+=+plt.figure(figsize=(10,10))
plt.imshow(img)+#+your+image+here
plt.axis("off")
plt.subplots_adjust(top+=+1,+bottom+=+0,+right+=+1,+left+=+0,+
++++++++hspace+=+0,+wspace+=+0)
plt.savefig("example2.png",+box_inches='tight',+dpi=100)
plt.show()|code-block|syntax|javascript|504563|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 works for me saving a numpy array plotted with imshow to file

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

fig = plt.figure(figsize=(10,10))
plt.imshow(img) # your image here
plt.axis("off")
plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0, 
 hspace = 0, wspace = 0)
plt.savefig("example2.png", box_inches='tight', dpi=100)
plt.show()
</code></pre>

blocks|key|287881|text|我发现以下代码非常适合这项工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|287882|fig+=+plt.figure(figsize=[6,6])
ax+=+fig.add_subplot(111)
ax.imshow(data)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.set_frame_on(False)
plt.savefig('data.png',+dpi=400,+bbox_inches='tight',pad_inches=0)|code-block|syntax|javascript|287883|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|$]]

I found the following codes work perfectly for the job.

<pre><code>fig = plt.figure(figsize=[6,6])
ax = fig.add_subplot(111)
ax.imshow(data)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.set_frame_on(False)
plt.savefig('data.png', dpi=400, bbox_inches='tight',pad_inches=0)
</code></pre>

blocks|key|504651|text|在尝试了上面的答案都没有成功(以及许多其他堆栈帖子)之后，最终对我起作用的是|type|unstyled|depth|inlineStyleRanges|entityRanges|data|504652|plt.gca().set_axis_off()
plt.subplots_adjust(top+=+1,+bottom+=+0,+right+=+1,+left+=+0,+
++++++++++++hspace+=+0,+wspace+=+0)
plt.margins(0,0)
plt.savefig("myfig.pdf")|code-block|syntax|javascript|504653|重要的是，这不包括bbox或padding参数。|504654|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|$]]

After trying the above answers with no success (and a slew of other stack posts) what finally worked for me was just

<pre class="lang-py prettyprint-override"><code>plt.gca().set_axis_off()
plt.subplots_adjust(top = 1, bottom = 0, right = 1, left = 0, 
 hspace = 0, wspace = 0)
plt.margins(0,0)
plt.savefig("myfig.pdf")
</code></pre>

Importantly this does not include the bbox or padding arguments.

blocks|key|287987|text|我遵循了这个序列，它就像一个护身符。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|287988|plt.axis("off")
fig=plt.imshow(image+array,interpolation='nearest')
fig.axes.get_xaxis().set_visible(False)
fig.axes.get_yaxis().set_visible(False)
plt.savefig('destination_path.pdf',
++++bbox_inches='tight',+pad_inches=0,+format='pdf',+dpi=1200)|code-block|syntax|javascript|287989|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|$]]

i followed this sequence and it worked like a charm.

<pre><code>plt.axis("off")
fig=plt.imshow(image array,interpolation='nearest')
fig.axes.get_xaxis().set_visible(False)
fig.axes.get_yaxis().set_visible(False)
plt.savefig('destination_path.pdf',
 bbox_inches='tight', pad_inches=0, format='pdf', dpi=1200)
</code></pre>

blocks|key|288023|text|下面的函数包含了上面约翰尼斯的答案。我已经用多轴的plt.figure和plt.subplots()测试了它，它工作得很好。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|288024|def+save(filepath,+fig=None):
++++'''Save+the+current+image+with+no+whitespace
++++Example+filepath:+"myfig.png"+or+r"C:\myfig.pdf"+
++++'''
++++import+matplotlib.pyplot+as+plt
++++if+not+fig:
++++++++fig+=+plt.gcf()

++++plt.subplots_adjust(0,0,1,1,0,0)
++++for+ax+in+fig.axes:
++++++++ax.axis('off')
++++++++ax.margins(0,0)
++++++++ax.xaxis.set_major_locator(plt.NullLocator())
++++++++ax.yaxis.set_major_locator(plt.NullLocator())
++++fig.savefig(filepath,+pad_inches+=+0,+bbox_inches='tight')|code-block|syntax|javascript|288025|entityMap^0|P|A|10|E|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|S|8|@]|D|@]|E|$]]]|L|$]]

The following function incorporates johannes-s answer above. I have tested it with <code>plt.figure</code> and <code>plt.subplots()</code> with multiple axes, and it works nicely.

<pre><code>def save(filepath, fig=None):
 '''Save the current image with no whitespace
 Example filepath: "myfig.png" or r"C:\myfig.pdf" 
 '''
 import matplotlib.pyplot as plt
 if not fig:
 fig = plt.gcf()

 plt.subplots_adjust(0,0,1,1,0,0)
 for ax in fig.axes:
 ax.axis('off')
 ax.margins(0,0)
 ax.xaxis.set_major_locator(plt.NullLocator())
 ax.yaxis.set_major_locator(plt.NullLocator())
 fig.savefig(filepath, pad_inches = 0, bbox_inches='tight')
</code></pre>

blocks|key|288085|text|我发现一种更简单的方法是使用plt.imsave：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|288086|++++import+matplotlib.pyplot+as+plt
++++arr+=+plt.imread(path)
++++plt.imsave('test.png',+arr)|code-block|syntax|javascript|288087|entityMap^0|E|A|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

A much simpler approach I found is to use <code>plt.imsave</code> :

<pre><code> import matplotlib.pyplot as plt
 arr = plt.imread(path)
 plt.imsave('test.png', arr)
</code></pre>

blocks|key|288135|text|最直接的方法是使用plt.tight_layout转换，这实际上更可取，因为它在使用plt.savefig时不会进行不必要的裁剪|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|288136|import+matplotlib+as+plt++++
plt.plot([1,2,3],+[1,2,3])
plt.tight_layout(pad=0)
plt.savefig('plot.png')|code-block|syntax|javascript|288137|但是，对于修改图形的复杂绘图，这可能并不可取。如果是这样，请参考使用plt.subplots_adjust的Johannes+S's+answer。|288138|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/a/27227718/7898913^0|9|G|16|B|0|0|Y|J|1I|J|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|@$9|11|A|12|B|C]]|D|@$9|13|A|14|1|15]]|E|$]]|$1|M|3|-4|5|6|7|16|8|@]|D|@]|E|$]]]|N|$O|$5|P|Q|R|E|$S|T]]]]

The most straightforward method is to use <code>plt.tight_layout</code> transformation which is actually more preferable as it doesn't do unnecessary cropping when using <code>plt.savefig</code>
<pre><code>import matplotlib as plt 
plt.plot([1,2,3], [1,2,3])
plt.tight_layout(pad=0)
plt.savefig('plot.png')
</code></pre>
However, this may not be preferable for complex plots that modifies the figure. Refer to <a href="https://stackoverflow.com/a/27227718/7898913">Johannes S's answer</a> that uses <code>plt.subplots_adjust</code> if that's the case.

blocks|key|288262|text|对于任何想要使用像素而不是英寸的人来说，这是可行的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|288263|再加上通常你还需要的|288264|from+matplotlib.transforms+import+Bbox|code-block|syntax|javascript|288265|然后，您可以使用以下内容：|288266|my_dpi+=+100+#+Good+default+-+doesn't+really+matter

#+Size+of+output+in+pixels
h+=+224
w+=+224

fig,+ax+=+plt.subplots(1,+figsize=(w/my_dpi,+h/my_dpi),+dpi=my_dpi)

ax.set_position([0,+0,+1,+1])+#+Critical!

#+Do+some+stuff
ax.imshow(img)
ax.imshow(heatmap)+#+4-channel+RGBA
ax.plot([50,+100,+150],+[50,+100,+150],+color="red")

ax.axis("off")

fig.savefig("saved_img.png",
++++++++++++bbox_inches=Bbox([[0,+0],+[w/my_dpi,+h/my_dpi]]),
++++++++++++dpi=my_dpi)|288267|​|288268|📷|atomic|offset|length|288269|288270|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/dbcd9e6b36716425687a94d9fffe06fc.png|imageAlt^0|0|0|0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|14|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|15|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|16|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|17|8|@]|9|@]|A|$G|H]]|$1|M|3|N|5|6|7|18|8|@]|9|@]|A|$]]|$1|O|3|P|5|Q|7|19|8|@]|9|@$R|1A|S|1B|1|1C]]|A|$]]|$1|T|3|N|5|6|7|1D|8|@]|9|@]|A|$]]|$1|U|3|-4|5|6|7|1E|8|@]|9|@]|A|$]]]|V|$W|$5|X|Y|Z|A|$10|11|12|-4]]]]

For anyone who wants to work in pixels rather than inches this will work.

Plus the usual you will also need

<pre><code>from matplotlib.transforms import Bbox
</code></pre>

Then you can use the following:

<pre><code>my_dpi = 100 # Good default - doesn't really matter

# Size of output in pixels
h = 224
w = 224

fig, ax = plt.subplots(1, figsize=(w/my_dpi, h/my_dpi), dpi=my_dpi)

ax.set_position([0, 0, 1, 1]) # Critical!

# Do some stuff
ax.imshow(img)
ax.imshow(heatmap) # 4-channel RGBA
ax.plot([50, 100, 150], [50, 100, 150], color="red")

ax.axis("off")

fig.savefig("saved_img.png",
 bbox_inches=Bbox([[0, 0], [w/my_dpi, h/my_dpi]]),
 dpi=my_dpi)
</code></pre>

<a href="https://i.stack.imgur.com/0ktoi.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/0ktoi.png" alt="enter image description here"></a>

blocks|key|288288|text|你可以试试这个。它解决了我的问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|288289|import+matplotlib.image+as+mpimg
img+=+mpimg.imread("src.png")
mpimg.imsave("out.png",+img,+cmap=cmap)|code-block|syntax|javascript|288290|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|$]]

You may try this. It solved my issue.
<pre><code>import matplotlib.image as mpimg
img = mpimg.imread(&quot;src.png&quot;)
mpimg.imsave(&quot;out.png&quot;, img, cmap=cmap)
</code></pre>

blocks|key|288301|text|这对我很有效，plt.savefig(save_path,bbox_inches='tight',+pad_inches=0,+transparent=True)|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|288302|entityMap^0|7|22|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|K|8|@]|D|@]|E|$]]]|G|$]]

This worked for me
<code>plt.savefig(save_path,bbox_inches='tight', pad_inches=0, transparent=True)</code>

blocks|key|288379|text|因此，解决方案取决于您是否调整子图。如果您指定plt.subplots_adjust+(上、下、右、左)，您不希望在plt.savefig中使用bbox_inches=‘top’的kwargs，因为它矛盾地创建了空格填充。它还允许您将图像保存为与输入图像相同的暗度(600x600输入图像另存为600x600像素输出图像)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|288380|如果您不关心输出图像大小的一致性，您可以省略plt.subplots_adjust属性，只使用bbox_inches=‘care’和plt.savefig的pad_inches=0+kwargs。|288381|此解决方案适用于matplotlib版本3.0.1、3.0.3和3.2.1。当你有一个以上的子图时，它也是有效的。plt.subplots(2,2，...)。|288382|def+save_inp_as_output(_img,+c_name,+dpi=100):
++++h,+w,+_+=+_img.shape
++++fig,+axes+=+plt.subplots(figsize=(h/dpi,+w/dpi))
++++fig.subplots_adjust(top=1.0,+bottom=0,+right=1.0,+left=0,+hspace=0,+wspace=0)+
++++axes.imshow(_img)
++++axes.axis('off')
++++plt.savefig(c_name,+dpi=dpi,+format='jpeg')+|code-block|syntax|javascript|288383|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|O|8|@]|9|@]|A|$]]|$1|F|3|G|5|H|7|P|8|@]|9|@]|A|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

So the solution depend on whether you adjust the subplot. If you specify plt.subplots_adjust (top, bottom, right, left), you don't want to use the kwargs of bbox_inches='tight' with plt.savefig, as it paradoxically creates whitespace padding. It also allows you to save the image as the same dims as the input image (600x600 input image saves as 600x600 pixel output image).
If you don't care about the output image size consistency, you can omit the plt.subplots_adjust attributes and just use the bbox_inches='tight' and pad_inches=0 kwargs with plt.savefig.
This solution works for matplotlib versions 3.0.1, 3.0.3 and 3.2.1. It also works when you have more than 1 subplot (eg. plt.subplots(2,2,...).
<pre><code>def save_inp_as_output(_img, c_name, dpi=100):
 h, w, _ = _img.shape
 fig, axes = plt.subplots(figsize=(h/dpi, w/dpi))
 fig.subplots_adjust(top=1.0, bottom=0, right=1.0, left=0, hspace=0, wspace=0) 
 axes.imshow(_img)
 axes.axis('off')
 plt.savefig(c_name, dpi=dpi, format='jpeg') 
</code></pre>

I need to take an image and save it after some process. The figure looks fine when I display it, but after saving the figure, I got some white space around the saved image. I have tried the <code>'tight'</code> option for <code>savefig</code> method, did not work either. The code:
<pre><code> import matplotlib.image as mpimg
 import matplotlib.pyplot as plt

 fig = plt.figure(1)
 img = mpimg.imread(path)
 plt.imshow(img)
 ax=fig.add_subplot(1,1,1)

 extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
 plt.savefig('1.png', bbox_inches=extent)

 plt.axis('off') 
 plt.show()
</code></pre>
I am trying to draw a basic graph by using NetworkX on a figure and save it. I realized that without a graph it works, but when added a graph I get white space around the saved image;
<pre><code>import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import networkx as nx

G = nx.Graph()
G.add_node(1)
G.add_node(2)
G.add_node(3)
G.add_edge(1,3)
G.add_edge(1,2)
pos = {1:[100,120], 2:[200,300], 3:[50,75]}

fig = plt.figure(1)
img = mpimg.imread(&quot;image.jpg&quot;)
plt.imshow(img)
ax=fig.add_subplot(1,1,1)

nx.draw(G, pos=pos)

extent = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
plt.savefig('1.png', bbox_inches = extent)

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

Removing white space around a saved image

我需要拍摄一张图片，并在一些处理后保存它。当我显示该图形时，它看起来很好，但在保存图形后，我在保存的图像周围留出了一些空白。我已经尝试了savefig方法的'tight'选项，也不起作用。代码：  import matplotlib.image as mpimg  import matplotlib.pyplot as...

问删除已保存图像周围的空白
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