blocks|key|891669|text|自动执行此操作的一种方法是对plt.savefig执行bbox_inches='tight'+kwarg。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|891670|例如。|891671|import+matplotlib.pyplot+as+plt
import+numpy+as+np
data+=+np.arange(3000).reshape((100,30))
plt.imshow(data)
plt.savefig('test.png',+bbox_inches='tight')|code-block|syntax|javascript|891672|另一种方法是使用fig.tight_layout()|891673|import+matplotlib.pyplot+as+plt
import+numpy+as+np

xs+=+np.linspace(0,+1,+20);+ys+=+np.sin(xs)

fig+=+plt.figure()
axes+=+fig.add_subplot(1,1,1)
axes.plot(xs,+ys)

#+This+should+be+called+after+all+axes+have+been+added
fig.tight_layout()
fig.savefig('test.png')|891674|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.savefig|1|https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.tight_layout^0|E|B|R|J|E|B|0|0|0|0|8|I|8|I|1|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@$9|11|A|12|B|C]|$9|13|A|14|B|C]]|D|@$9|15|A|16|1|17]]|E|$]]|$1|F|3|G|5|6|7|18|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|19|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1A|8|@$9|1B|A|1C|B|C]]|D|@$9|1D|A|1E|1|1F]]|E|$]]|$1|O|3|P|5|J|7|1G|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|1H|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X]]|Y|$5|T|U|V|E|$W|Z]]]]

One way to automatically do this is the <code>bbox_inches='tight'</code> kwarg to <a href="https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.savefig" rel="noreferrer"><code>plt.savefig</code></a>.

E.g.

<pre><code>import matplotlib.pyplot as plt
import numpy as np
data = np.arange(3000).reshape((100,30))
plt.imshow(data)
plt.savefig('test.png', bbox_inches='tight')
</code></pre>

Another way is to use <a href="https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.tight_layout" rel="noreferrer"><code>fig.tight_layout()</code></a>

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

xs = np.linspace(0, 1, 20); ys = np.sin(xs)

fig = plt.figure()
axes = fig.add_subplot(1,1,1)
axes.plot(xs, ys)

# This should be called after all axes have been added
fig.tight_layout()
fig.savefig('test.png')
</code></pre>

blocks|key|1106668|text|您可以使用subplots_adjust()函数调整matplotlib图形周围的间距：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1106669|import+matplotlib.pyplot+as+plt
plt.plot(whatever)
plt.subplots_adjust(left=0.1,+right=0.9,+top=0.9,+bottom=0.1)|code-block|syntax|javascript|1106670|这对屏幕上的图形和保存到文件中的图形都有效，即使在一个图形上没有多个绘图，它也是可以调用的正确函数。|1106671|这些数字是地物尺寸的分数，需要进行调整以允许使用地物标签。|1106672|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|P|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

You can adjust the spacing around matplotlib figures using the subplots_adjust() function:

<pre><code>import matplotlib.pyplot as plt
plt.plot(whatever)
plt.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.1)
</code></pre>

This will work for both the figure on screen and saved to a file, and it is the right function to call even if you don't have multiple plots on the one figure.

The numbers are fractions of the figure dimensions, and will need to be adjusted to allow for the figure labels.

blocks|key|891760|text|plt.savefig("circle.png",+bbox_inches='tight',pad_inches=-1)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|891761|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>plt.savefig("circle.png", bbox_inches='tight',pad_inches=-1)
</code></pre>

blocks|key|1106736|text|matplotlibs+subplots_adjust的问题是，您输入的值与图形的x和y图形大小相关。此示例用于打印pdf的正确图形大小：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1106737|为此，我将相对间距重新计算为绝对值，如下所示：|1106738|pyplot.subplots_adjust(left+=+(5/25.4)/figure.xsize,+bottom+=+(4/25.4)/figure.ysize,+right+=+1+-+(1/25.4)/figure.xsize,+top+=+1+-+(3/25.4)/figure.ysize)|code-block|syntax|javascript|1106739|X维度为'figure.xsize‘英寸，y维度为'figure.ysize’英寸的图形。因此整个图形的左边距为5毫米，底边距为4毫米，右边距为1毫米，顶部为3毫米。完成(x/25.4)的转换是因为我需要将mm转换为英寸。|1106740|请注意，x的纯图表大小将是"figure.xsize+-+left+margin+right+margin“，y的纯图表大小将是"figure.ysize+-+bottom+margin+top+margin”(英寸)。|1106741|其他sniplet(对这些不太确定，我只想提供其他参数)|1106742|pyplot.figure(figsize+=+figureSize,+dpi+=+None)|1106743|和|1106744|pyplot.savefig("outputname.eps",+dpi+=+100)|1106745|entityMap^0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|X|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|Y|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|Z|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|10|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|11|8|@]|9|@]|A|$]]|$1|O|3|P|5|F|7|12|8|@]|9|@]|A|$G|H]]|$1|Q|3|R|5|6|7|13|8|@]|9|@]|A|$]]|$1|S|3|T|5|F|7|14|8|@]|9|@]|A|$G|H]]|$1|U|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|V|$]]

The problem with matplotlibs subplots_adjust is that the values you enter are relative to the x and y figsize of the figure. This example is for correct figuresizing for printing of a pdf:

For that, I recalculate the relative spacing to absolute values like this:

<pre><code>pyplot.subplots_adjust(left = (5/25.4)/figure.xsize, bottom = (4/25.4)/figure.ysize, right = 1 - (1/25.4)/figure.xsize, top = 1 - (3/25.4)/figure.ysize)
</code></pre>

for a figure of 'figure.xsize' inches in x-dimension and 'figure.ysize' inches in y-dimension. So the whole figure has a left margin of 5 mm, bottom margin of 4 mm, right of 1 mm and top of 3 mm within the labels are placed. The conversion of (x/25.4) is done because I needed to convert mm to inches.

Note that the pure chart size of x will be "figure.xsize - left margin - right margin" and the pure chart size of y will be "figure.ysize - bottom margin - top margin" in inches

Other sniplets (not sure about these ones, I just wanted to provide the other parameters)

<pre><code>pyplot.figure(figsize = figureSize, dpi = None)
</code></pre>

and

<pre><code>pyplot.savefig("outputname.eps", dpi = 100)
</code></pre>

blocks|key|1106783|text|你所需要的是|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1106784|plt.tight_layout()|code-block|syntax|javascript|1106785|在你的输出之前。|1106786|除了减少页边距外，这还将任何子图之间的空间紧密地组合在一起：|1106787|x+=+[1,2,3]
y+=+[1,4,9]
import+matplotlib.pyplot+as+plt
fig+=+plt.figure()
subplot1+=+fig.add_subplot(121)
subplot1.plot(x,y)
subplot2+=+fig.add_subplot(122)
subplot2.plot(y,x)
fig.tight_layout()
plt.show()|1106788|entityMap^0|0|0|0|0|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]]|$1|G|3|H|5|6|7|Q|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|R|8|@]|9|@]|A|$]]|$1|K|3|L|5|D|7|S|8|@]|9|@]|A|$E|F]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

All you need is

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

before your output.

In addition to cutting down the margins, this also tightly groups the space between any subplots:

<pre><code>x = [1,2,3]
y = [1,4,9]
import matplotlib.pyplot as plt
fig = plt.figure()
subplot1 = fig.add_subplot(121)
subplot1.plot(x,y)
subplot2 = fig.add_subplot(122)
subplot2.plot(y,x)
fig.tight_layout()
plt.show()
</code></pre>

blocks|key|891924|text|对我来说，上面的答案不适用于Win7上的matplotlib.__version__+=+1.4.3。因此，如果我们只对图像本身感兴趣(例如，如果我们不需要注释、轴、刻度、标题、ylabel等)，那么最好将numpy数组保存为image而不是savefig。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|891925|from+pylab+import+*

ax+=+subplot(111)
ax.imshow(some_image_numpyarray)
imsave('test.tif',+some_image_numpyarray)

#+or,+if+the+image+came+from+tiff+or+png+etc
RGBbuffer+=+ax.get_images()[0].get_array()
imsave('test.tif',+RGBbuffer)|code-block|syntax|javascript|891926|此外，使用opencv绘图函数(cv2.line，cv2.polyines)，我们可以直接在numpy数组上进行一些绘图。http://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html|891927|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html^0|K|U|3D|7|0|0|1P|1U|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]]]]

For me, the answers above did not work with <code>matplotlib.__version__ = 1.4.3</code> on Win7. So, if we are only interested in the image itself (i.e., if we don't need annotations, axis, ticks, title, ylabel etc), then it's better to simply save the numpy array as image instead of <code>savefig</code>.

<pre><code>from pylab import *

ax = subplot(111)
ax.imshow(some_image_numpyarray)
imsave('test.tif', some_image_numpyarray)

# or, if the image came from tiff or png etc
RGBbuffer = ax.get_images()[0].get_array()
imsave('test.tif', RGBbuffer)
</code></pre>

Also, using opencv drawing functions (cv2.line, cv2.polylines), we can do some drawings directly on the numpy array. <a href="http://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html" rel="nofollow">http://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html</a>

blocks|key|1106860|text|如果你想精确控制图形布局，只需使用ax+=+fig.add_axes([left,+bottom,+width,+height])即可。例如：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1106861|left+=+0.05
bottom+=+0.05
width+=+0.9
height+=+0.9
ax+=+fig.add_axes([left,+bottom,+width,+height])|code-block|syntax|javascript|1106862|entityMap^0|H|1C|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|$]]

Just use <code>ax = fig.add_axes([left, bottom, width, height])</code>
 if you want exact control of the figure layout. eg.

<pre><code>left = 0.05
bottom = 0.05
width = 0.9
height = 0.9
ax = fig.add_axes([left, bottom, width, height])
</code></pre>

blocks|key|891980|text|受上面Sammys答案的启发：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|891981|margins+=+{++#+++++vvv+margin+in+inches
++++"left"+++:+++++1.5+/+figsize[0],
++++"bottom"+:+++++0.8+/+figsize[1],
++++"right"++:+1+-+0.3+/+figsize[0],
++++"top"++++:+1+-+1+++/+figsize[1]
}
fig.subplots_adjust(**margins)|code-block|syntax|javascript|891982|其中figsize是您在fig+=+pyplot.figure(figsize=...)中使用的元组|offset|length|style|CODE|891983|entityMap^0|0|0|C|W|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|$]]

inspired by Sammys answer above:

<pre><code>margins = { # vvv margin in inches
 "left" : 1.5 / figsize[0],
 "bottom" : 0.8 / figsize[1],
 "right" : 1 - 0.3 / figsize[0],
 "top" : 1 - 1 / figsize[1]
}
fig.subplots_adjust(**margins)
</code></pre>

Where figsize is the tuple that you used in <code>fig = pyplot.figure(figsize=...)</code>

blocks|key|1106969|text|如果有人想知道如何在应用plt.tight_layout()或fig.tight_layout()后消除剩余的白边距:使用参数pad+(默认情况下为1.08+)，您可以使其更紧凑：“在图形边缘和子图边缘之间填充，作为字体大小的一部分。”举个例子|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1106970|plt.tight_layout(pad=0.05)|code-block|syntax|javascript|1106971|会把它缩小到一个非常小的边际。放置0对我来说不起作用，因为它也会将子情节的框切掉一点。|1106972|entityMap^0|C|I|V|I|1R|3|22|4|0|0|H|1|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]|$9|R|A|S|B|C]|$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|X|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|11|8|@]|D|@]|E|$]]]|N|$]]

In case anybody wonders how how to get rid of the rest of the white margin after applying <code>plt.tight_layout()</code> or <code>fig.tight_layout()</code>: With the parameter <code>pad</code> (which is <code>1.08</code> by default), you're able to make it even tighter:
"Padding between the figure edge and the edges of subplots, as a fraction of the font size."
So for example

<pre><code>plt.tight_layout(pad=0.05)
</code></pre>

will reduce it to a very small margin. Putting <code>0</code> doesn't work for me, as it makes the box of the subplot be cut off a little, too.

blocks|key|1107075|text|有时，plt.tight_layout()不能给我最好的视图或我想要的视图。那么为什么不先绘制任意边距，然后再固定边距呢？因为我们从那里得到了很好的所见即所得。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1107076|import+matplotlib.pyplot+as+plt

fig,ax+=+plt.subplots(figsize=(8,8))

plt.plot([2,5,7,8,5,3,5,7,])
plt.show()|code-block|syntax|javascript|1107077|​|1107078|📷|atomic|1107079|1107080|然后将设置粘贴到边距函数中，使其成为永久性的：|1107081|fig,ax+=+plt.subplots(figsize=(8,8))

plt.plot([2,5,7,8,5,3,5,7,])
fig.subplots_adjust(
++++top=0.981,
++++bottom=0.049,
++++left=0.042,
++++right=0.981,
++++hspace=0.2,
++++wspace=0.2
)
plt.show()|1107082|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/2a084ab2688accb7cea169e91502ec55.png|imageAlt^0|3|I|0|0|0|0|1|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@$9|14|A|15|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|16|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|17|8|@]|D|@]|E|$]]|$1|M|3|N|5|O|7|18|8|@]|D|@$9|19|A|1A|1|1B]]|E|$]]|$1|P|3|L|5|6|7|1C|8|@]|D|@]|E|$]]|$1|Q|3|R|5|6|7|1D|8|@]|D|@]|E|$]]|$1|S|3|T|5|H|7|1E|8|@]|D|@]|E|$I|J]]|$1|U|3|-4|5|6|7|1F|8|@]|D|@]|E|$]]]|V|$W|$5|X|Y|Z|E|$10|11|12|-4]]]]

Sometimes, the <code>plt.tight_layout()</code> doesn't give me the best view or the view I want. Then why don't plot with arbitrary margin first and do fixing the margin after plot?
Since we got nice WYSIWYG from there.
<pre><code>import matplotlib.pyplot as plt

fig,ax = plt.subplots(figsize=(8,8))

plt.plot([2,5,7,8,5,3,5,7,])
plt.show()
</code></pre>
<a href="https://i.stack.imgur.com/J5QL4.png" rel="noreferrer"><img src="https://i.stack.imgur.com/J5QL4.png" alt="Change border and spacing GUI here" /></a>
Then paste settings into margin function to make it permanent:
<pre><code>fig,ax = plt.subplots(figsize=(8,8))

plt.plot([2,5,7,8,5,3,5,7,])
fig.subplots_adjust(
 top=0.981,
 bottom=0.049,
 left=0.042,
 right=0.981,
 hspace=0.2,
 wspace=0.2
)
plt.show()
</code></pre>

blocks|key|892159|text|#+import+pyplot
import+matplotlib.pyplot+as+plt

#+your+code+to+plot+the+figure

#+set+tight+margins
plt.margins(0.015,+tight=True)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|892160|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

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

# your code to plot the figure

# set tight margins
plt.margins(0.015, tight=True)
</code></pre>

blocks|key|1107195|text|请删除你程序中的"sharex=True和sharey=True“键。我想你还没有在这里上传完整的程序。希望我的回答对你的问题有所帮助。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1107196|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

kindly delete the keys &quot;sharex=True and sharey=True&quot; in your program. I think which you have not uploaded the complete program here. Hope my answer may help your query.

I'm struggling to deal with my plot margins in matplotlib. I've used the code below to produce my chart:

<pre><code>plt.imshow(g)
c = plt.colorbar()
c.set_label("Number of Slabs")
plt.savefig("OutputToUse.png")
</code></pre>

However, I get an output figure with lots of white space on either side of the plot. I've searched google and read the matplotlib documentation, but I can't seem to find how to reduce this.

Reduce left and right margins in matplotlib plot

我正在努力处理matplotlib中的绘图边距。我使用了下面的代码来生成我的图表：plt.imshow(g)c = plt.colorbar()c.set_label("Number of Slabs")plt.savefig("OutputToUse.png")但是，我得到的输出图形在绘图的两边都有很多空格。我搜索了...

问缩小matplotlib图中的左右边距
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