blocks|key|376427|text|首先，如果您使用的是savefig，请注意，除非您另外指定(例如fig.savefig('blah.png',+transparent=True))，否则在保存时它将覆盖地物的背景颜色。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|376428|但是，要在屏幕上删除轴和图形的背景，您需要将ax.patch和fig.patch都设置为不可见。|376429|例如。|376430|import+matplotlib.pyplot+as+plt

fig,+ax+=+plt.subplots()
ax.plot(range(10))

for+item+in+[fig,+ax]:
++++item.patch.set_visible(False)

with+open('test.png',+'w')+as+outfile:
++++fig.canvas.print_png(outfile)|code-block|syntax|javascript|376431|​|376432|📷|atomic|376433|376434|(当然，你不能区分SO的白色背景，但一切都是透明的……)|376435|如果您不想显示线以外的任何内容，也可以使用ax.axis('off')关闭轴|376436|import+matplotlib.pyplot+as+plt

fig,+ax+=+plt.subplots()
ax.plot(range(10))

fig.patch.set_visible(False)
ax.axis('off')

with+open('test.png',+'w')+as+outfile:
++++fig.canvas.print_png(outfile)|376437|376438|376439|376440|但是，在这种情况下，您可能希望使轴占据完整的图形。如果手动指定轴的位置，则可以告诉它采用完整的图形(或者，也可以使用subplots_adjust，但对于单个轴的情况更简单)。|376441|import+matplotlib.pyplot+as+plt

fig+=+plt.figure(frameon=False)
ax+=+fig.add_axes([0,+0,+1,+1])
ax.axis('off')

ax.plot(range(10))

with+open('test.png',+'w')+as+outfile:
++++fig.canvas.print_png(outfile)|376442|376443|376444|376445|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/bb909e54d2f9af82ff2c9834432e9fd9.png|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/41b634cab902dd049ce7e2f23b5a85ea.png|2|https://ask.qcloudimg.com/http-save/yehe-900000/8a60517fd79a445b4cc0dc379d74fac9.png^0|A|7|W|15|0|M|8|V|9|0|0|0|0|0|1|0|0|0|0|L|E|0|0|0|0|1|1|0|0|1M|F|0|0|0|0|1|2|0|0^^$0|@$1|2|3|4|5|6|7|1N|8|@$9|1O|A|1P|B|C]|$9|1Q|A|1R|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1S|8|@$9|1T|A|1U|B|C]|$9|1V|A|1W|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|1X|8|@]|D|@]|E|$]]|$1|J|3|K|5|L|7|1Y|8|@]|D|@]|E|$M|N]]|$1|O|3|P|5|6|7|1Z|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|20|8|@]|D|@$9|21|A|22|1|23]]|E|$]]|$1|T|3|P|5|6|7|24|8|@]|D|@]|E|$]]|$1|U|3|V|5|6|7|25|8|@]|D|@]|E|$]]|$1|W|3|X|5|6|7|26|8|@$9|27|A|28|B|C]]|D|@]|E|$]]|$1|Y|3|Z|5|L|7|29|8|@]|D|@]|E|$M|N]]|$1|10|3|P|5|6|7|2A|8|@]|D|@]|E|$]]|$1|11|3|R|5|S|7|2B|8|@]|D|@$9|2C|A|2D|1|2E]]|E|$]]|$1|12|3|P|5|6|7|2F|8|@]|D|@]|E|$]]|$1|13|3|14|5|6|7|2G|8|@$9|2H|A|2I|B|C]]|D|@]|E|$]]|$1|15|3|16|5|L|7|2J|8|@]|D|@]|E|$M|N]]|$1|17|3|P|5|6|7|2K|8|@]|D|@]|E|$]]|$1|18|3|R|5|S|7|2L|8|@]|D|@$9|2M|A|2N|1|2O]]|E|$]]|$1|19|3|P|5|6|7|2P|8|@]|D|@]|E|$]]|$1|1A|3|-4|5|6|7|2Q|8|@]|D|@]|E|$]]]|1B|$1C|$5|1D|1E|1F|E|$1G|1H|1I|-4]]|1J|$5|1D|1E|1F|E|$1G|1K|1I|-4]]|1L|$5|1D|1E|1F|E|$1G|1M|1I|-4]]]]

First off, if you're using <code>savefig</code>, be aware that it will override the figure's background color when saving unless you specify otherwise (e.g. <code>fig.savefig('blah.png', transparent=True)</code>).

However, to remove the axes' and figure's background on-screen, you'll need to set both <code>ax.patch</code> and <code>fig.patch</code> to be invisible. 

E.g.

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

fig, ax = plt.subplots()
ax.plot(range(10))

for item in [fig, ax]:
 item.patch.set_visible(False)

with open('test.png', 'w') as outfile:
 fig.canvas.print_png(outfile)
</code></pre>

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

(Of course, you can't tell the difference on SO's white background, but everything is transparent...)

If you don't want to show anything other than the line, turn the axis off as well using <code>ax.axis('off')</code>:

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

fig, ax = plt.subplots()
ax.plot(range(10))

fig.patch.set_visible(False)
ax.axis('off')

with open('test.png', 'w') as outfile:
 fig.canvas.print_png(outfile)
</code></pre>

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

In that case, though, you may want to make the axes take up the full figure. If you manually specify the location of the axes, you can tell it to take up the full figure (alternately, you can use <code>subplots_adjust</code>, but this is simpler for the case of a single axes). 

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

fig = plt.figure(frameon=False)
ax = fig.add_axes([0, 0, 1, 1])
ax.axis('off')

ax.plot(range(10))

with open('test.png', 'w') as outfile:
 fig.canvas.print_png(outfile)
</code></pre>

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

blocks|key|158549|text|我过去常常这样做：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|158550|from+pylab+import+*
axes(frameon+=+0)
...
show()|code-block|syntax|javascript|158551|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 use to do so:

<pre><code>from pylab import *
axes(frameon = 0)
...
show()
</code></pre>

blocks|key|158629|text|正如Joe+Kington指出的那样，ax.axis('off')将删除除绘制线之外的所有内容。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|158630|对于那些只想移除框架(边框)并保留标签、滚动条等的人，可以通过访问轴上的spines对象来实现。给定轴对象ax，下面的代码应该删除所有四个边的边界：|158631|ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)|code-block|syntax|javascript|158632|而且，如果从绘图中删除了x和y标记：|158633|+ax.get_xaxis().set_ticks([])
+ax.get_yaxis().set_ticks([])|158634|entityMap^0|J|E|0|10|6|1H|2|0|0|C|1|E|1|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|V|8|@$9|W|A|X|B|C]|$9|Y|A|Z|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|10|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|11|8|@$9|12|A|13|B|C]|$9|14|A|15|B|C]]|D|@]|E|$]]|$1|O|3|P|5|J|7|16|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|17|8|@]|D|@]|E|$]]]|R|$]]

<code>ax.axis('off')</code>, will as Joe Kington pointed out, remove everything except the plotted line.

For those wanting to only remove the frame (border), and keep labels, tickers etc, one can do that by accessing the <code>spines</code> object on the axis. Given an axis object <code>ax</code>, the following should remove borders on all four sides:

<pre><code>ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
</code></pre>

And, in case of removing <code>x</code> and <code>y</code> ticks from the plot: 

<pre><code> ax.get_xaxis().set_ticks([])
 ax.get_yaxis().set_ticks([])
</code></pre>

blocks|key|158721|text|在@peeol's+excellent+answer上构建，您还可以通过执行以下操作来删除框架|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|158722|for+spine+in+plt.gca().spines.values():
++++spine.set_visible(False)|code-block|syntax|javascript|158723|举个例子(整个代码样本可以在这篇文章的末尾找到)，假设你有一个像这样的条形图，|158724|​|158725|📷|atomic|158726|158727|您可以使用上面的命令删除框架，然后保留x-和ytick标签(图中未显示)或删除它们|style|CODE|158728|plt.tick_params(top='off',+bottom='off',+left='off',+right='off',+labelleft='off',+labelbottom='on')|158729|在这种情况下，可以直接标记条形图；最终的绘图可能如下所示(代码可以在下面找到)：|158730|158731|158732|158733|以下是生成绘图所需的完整代码：|158734|import+matplotlib.pyplot+as+plt
import+numpy+as+np

plt.figure()

xvals+=+list('ABCDE')
yvals+=+np.array(range(1,+6))

position+=+np.arange(len(xvals))

mybars+=+plt.bar(position,+yvals,+align='center',+linewidth=0)
plt.xticks(position,+xvals)

plt.title('My+great+data')
#+plt.show()

#+get+rid+of+the+frame
for+spine+in+plt.gca().spines.values():
++++spine.set_visible(False)

#+plt.show()
#+remove+all+the+ticks+and+directly+label+each+bar+with+respective+value
plt.tick_params(top='off',+bottom='off',+left='off',+right='off',+labelleft='off',+labelbottom='on')

#+plt.show()

#+direct+label+each+bar+with+Y+axis+values
for+bari+in+mybars:
++++height+=+bari.get_height()
++++plt.gca().text(bari.get_x()+%2B+bari.get_width()/2,+bari.get_height()-0.2,+str(int(height)),
+++++++++++++++++ha='center',+color='white',+fontsize=15)
plt.show()|158735|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/a/28720127/1534017|1|IMAGE|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/03d3508e21f32f0d6de4cc9fda749a0f.png|imageAlt|2|https://ask.qcloudimg.com/http-save/yehe-900000/e15f6d219f782ae622682a70bf430e21.png^0|1|P|0|0|0|0|0|0|1|1|0|0|J|2|M|5|0|0|0|0|0|1|2|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1L|8|@]|9|@$A|1M|B|1N|1|1O]]|C|$]]|$1|D|3|E|5|F|7|1P|8|@]|9|@]|C|$G|H]]|$1|I|3|J|5|6|7|1Q|8|@]|9|@]|C|$]]|$1|K|3|L|5|6|7|1R|8|@]|9|@]|C|$]]|$1|M|3|N|5|O|7|1S|8|@]|9|@$A|1T|B|1U|1|1V]]|C|$]]|$1|P|3|L|5|6|7|1W|8|@]|9|@]|C|$]]|$1|Q|3|R|5|6|7|1X|8|@$A|1Y|B|1Z|S|T]|$A|20|B|21|S|T]]|9|@]|C|$]]|$1|U|3|V|5|F|7|22|8|@]|9|@]|C|$G|H]]|$1|W|3|X|5|6|7|23|8|@]|9|@]|C|$]]|$1|Y|3|L|5|6|7|24|8|@]|9|@]|C|$]]|$1|Z|3|N|5|O|7|25|8|@]|9|@$A|26|B|27|1|28]]|C|$]]|$1|10|3|L|5|6|7|29|8|@]|9|@]|C|$]]|$1|11|3|12|5|6|7|2A|8|@]|9|@]|C|$]]|$1|13|3|14|5|F|7|2B|8|@]|9|@]|C|$G|H]]|$1|15|3|-4|5|6|7|2C|8|@]|9|@]|C|$]]]|16|$17|$5|18|19|1A|C|$1B|1C]]|1D|$5|1E|19|1F|C|$1G|1H|1I|-4]]|1J|$5|1E|19|1F|C|$1G|1K|1I|-4]]]]

Building up on <a href="https://stackoverflow.com/a/28720127/1534017">@peeol's excellent answer</a>, you can also remove the frame by doing

<pre><code>for spine in plt.gca().spines.values():
 spine.set_visible(False)
</code></pre>

To give an example (the entire code sample can be found at the end of this post), let's say you have a bar plot like this, 

<a href="https://i.stack.imgur.com/8csGd.png" rel="noreferrer"><img src="https://i.stack.imgur.com/h36QT.png" alt="enter image description here"></a>

you can remove the frame with the commands above and then either keep the <code>x-</code> and <code>ytick</code> labels (plot not shown) or remove them as well doing

<pre><code>plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')
</code></pre>

In this case, one can then label the bars directly; the final plot could look like this (code can be found below):

<a href="https://i.stack.imgur.com/8csGd.png" rel="noreferrer"><img src="https://i.stack.imgur.com/8csGd.png" alt="enter image description here"></a>

Here is the entire code that is necessary to generate the plots:

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

plt.figure()

xvals = list('ABCDE')
yvals = np.array(range(1, 6))

position = np.arange(len(xvals))

mybars = plt.bar(position, yvals, align='center', linewidth=0)
plt.xticks(position, xvals)

plt.title('My great data')
# plt.show()

# get rid of the frame
for spine in plt.gca().spines.values():
 spine.set_visible(False)

# plt.show()
# remove all the ticks and directly label each bar with respective value
plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')

# plt.show()

# direct label each bar with Y axis values
for bari in mybars:
 height = bari.get_height()
 plt.gca().text(bari.get_x() + bari.get_width()/2, bari.get_height()-0.2, str(int(height)),
 ha='center', color='white', fontsize=15)
plt.show()
</code></pre>

blocks|key|376672|text|在更新版本的matplotlib中摆脱丑陋框架的最简单方法是：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|376673|import+matplotlib.pyplot+as+plt
plt.box(False)|code-block|syntax|javascript|376674|如果您真的必须始终使用面向对象的方法，那么就这样做：ax.set_frame_on(False)。|offset|length|style|CODE|376675|entityMap^0|0|0|Q|M|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|$]]

The easiest way to get rid of the the ugly frame in newer versions of matplotlib:

<pre><code>import matplotlib.pyplot as plt
plt.box(False)
</code></pre>

If you really must always use the object oriented approach, then do: <code>ax.set_frame_on(False)</code>.

blocks|key|376679|text|df+=+pd.DataFrame({
'client_scripting_ms'+:+client_scripting_ms,
+'apimlayer'+:+apimlayer,+'server'+:+server
},+index+=+index)

ax+=+df.plot(kind+=+'barh',+
+++++stacked+=+True,
+++++title+=+"Chart",
+++++width+=+0.20,+
+++++align='center',+
+++++figsize=(7,5))

plt.legend(loc='upper+right',+frameon=True)

ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('right')|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|376680|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>df = pd.DataFrame({
'client_scripting_ms' : client_scripting_ms,
 'apimlayer' : apimlayer, 'server' : server
}, index = index)

ax = df.plot(kind = 'barh', 
 stacked = True,
 title = "Chart",
 width = 0.20, 
 align='center', 
 figsize=(7,5))

plt.legend(loc='upper right', frameon=True)

ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('right')
</code></pre>

blocks|key|376691|text|正如我回答的here，您可以通过样式设置(+sheet或rcParams)从所有绘图中删除主线：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|376692|import+matplotlib+as+mpl

mpl.rcParams['axes.spines.left']+=+False
mpl.rcParams['axes.spines.right']+=+False
mpl.rcParams['axes.spines.top']+=+False
mpl.rcParams['axes.spines.bottom']+=+False|code-block|syntax|javascript|376693|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/925024/how-can-i-remove-the-top-and-right-axis-in-matplotlib/57617515#57617515^0|6|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]]]]

As I answered <a href="https://stackoverflow.com/questions/925024/how-can-i-remove-the-top-and-right-axis-in-matplotlib/57617515#57617515">here</a>, you can remove spines from all your plots through style settings (style sheet or rcParams):

<pre><code>import matplotlib as mpl

mpl.rcParams['axes.spines.left'] = False
mpl.rcParams['axes.spines.right'] = False
mpl.rcParams['axes.spines.top'] = False
mpl.rcParams['axes.spines.bottom'] = False
</code></pre>

blocks|key|158841|text|问题|type|unstyled|depth|inlineStyleRanges|entityRanges|data|158842|我在使用轴时也遇到了类似的问题。类参数是frameon，但是kwarg是frame_on。axes_api|offset|length|style|CODE|158843|>>>+plt.gca().set(frameon=False)|158844|AttributeError:+Unknown+property+frameon|158845|解决方案|158846|frame_on|158847|示例|158848|data+=+range(100)
import+matplotlib.pyplot+as+plt
fig,+ax+=+plt.subplots()
ax.plot(data)
#ax.set(frameon=False)++#+Old
ax.set(frame_on=False)++#+New
plt.show()|code-block|syntax|javascript|158849|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/api/axes_api.html^0|0|K|7|10|8|19|8|0|0|0|W|0|0|14|0|0|0|8|0|0|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|15|8|@$D|16|E|17|F|G]|$D|18|E|19|F|G]]|9|@$D|1A|E|1B|1|1C]]|A|$]]|$1|H|3|I|5|6|7|1D|8|@$D|1E|E|1F|F|G]]|9|@]|A|$]]|$1|J|3|K|5|6|7|1G|8|@$D|1H|E|1I|F|G]]|9|@]|A|$]]|$1|L|3|M|5|6|7|1J|8|@]|9|@]|A|$]]|$1|N|3|O|5|6|7|1K|8|@$D|1L|E|1M|F|G]]|9|@]|A|$]]|$1|P|3|Q|5|6|7|1N|8|@]|9|@]|A|$]]|$1|R|3|S|5|T|7|1O|8|@]|9|@]|A|$U|V]]|$1|W|3|-4|5|6|7|1P|8|@]|9|@]|A|$]]]|X|$Y|$5|Z|10|11|A|$12|13]]]]

<h1>Problem</h1>

I had a similar problem using axes. The class parameter is <code>frameon</code> but the kwarg is <code>frame_on</code>. <a href="https://matplotlib.org/api/axes_api.html" rel="noreferrer">axes_api</a> 
<code>&gt;&gt;&gt; plt.gca().set(frameon=False)</code> 
<code>AttributeError: Unknown property frameon</code>

<h1>Solution</h1>

<code>frame_on</code>

<h1>Example</h1>

<pre class="lang-py prettyprint-override"><code>data = range(100)
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(data)
#ax.set(frameon=False) # Old
ax.set(frame_on=False) # New
plt.show()
</code></pre>

blocks|key|376731|text|plt.box(False)
plt.xticks([])
plt.yticks([])
plt.savefig('fig.png')|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|376732|应该能行得通。|unstyled|376733|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|J|8|@]|9|@]|A|$]]|$1|G|3|-4|5|F|7|K|8|@]|9|@]|A|$]]]|H|$]]

<pre class="lang-py prettyprint-override"><code>plt.box(False)
plt.xticks([])
plt.yticks([])
plt.savefig('fig.png')
</code></pre>

should do the trick.

blocks|key|376738|text|plt.axis('off')
plt.savefig(file_path,+bbox_inches="tight",+pad_inches+=+0)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|376739|plt.savefig本身就有这些选项，只需将轴设置为关闭即可|unstyled|376740|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|J|8|@]|9|@]|A|$]]|$1|G|3|-4|5|F|7|K|8|@]|9|@]|A|$]]]|H|$]]

<pre><code>plt.axis('off')
plt.savefig(file_path, bbox_inches="tight", pad_inches = 0)
</code></pre>

plt.savefig has those options in itself, just need to set axes off before

blocks|key|158875|text|这是另一个解决方案：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|158876|img+=+io.imread(crt_path)

fig+=+plt.figure()
fig.set_size_inches(img.shape[1]/img.shape[0],+1,+forward=False)+#+normalize+the+initial+size
ax+=+plt.Axes(fig,+[0.,+0.,+1.,+1.])+#+remove+the+edges
ax.set_axis_off()+#+remove+the+axis
fig.add_axes(ax)

ax.imshow(img)

plt.savefig(file_name%2B'.png',+dpi=img.shape[0])+#+de-normalize+to+retrieve+the+original+size|code-block|syntax|javascript|158877|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|$]]

here is another solution :
<pre><code>img = io.imread(crt_path)

fig = plt.figure()
fig.set_size_inches(img.shape[1]/img.shape[0], 1, forward=False) # normalize the initial size
ax = plt.Axes(fig, [0., 0., 1., 1.]) # remove the edges
ax.set_axis_off() # remove the axis
fig.add_axes(ax)

ax.imshow(img)

plt.savefig(file_name+'.png', dpi=img.shape[0]) # de-normalize to retrieve the original size
</code></pre>

To remove frame in figure, I write 

<pre><code>frameon=False
</code></pre>

works perfect with <code>pyplot.figure</code>, but with <code>matplotlib.Figure</code> it only removes the gray background, the frame stays . Also, I only want the lines to show, and all the rest of figure be transparent.

with pyplot I can do what I want, I want to do it with matplotlib for some long reason I 'd rather not mention to extend my question.

How to remove frame from matplotlib (pyplot.figure vs matplotlib.figure ) (frameon=False Problematic in matplotlib)

为了去掉图中的框架，我写道frameon=False与pyplot.figure完美配合，但在matplotlib.Figure中，它只会移除灰色背景，框架会保留下来。另外，我只想显示线条，而图的其余部分都是透明的。使用pyplot我可以做任何我想做的事情，我想使用matplotlib来做这件事，因为有一些很长的原因，...

问如何从matplotlib中删除帧(pyplot.figure与matplotlib.figure )(matplotlib中的frameon=False问题)
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问如何从matplotlib中删除帧(pyplot.figure与matplotlib.figure )(matplotlib中的frameon=False问题)
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