blocks|key|43588|text|使用matplotlib+AxisDivider可以很容易地做到这一点。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|43589|链接页面中的示例在不使用子图的情况下也可以使用：|43590|import+matplotlib.pyplot+as+plt
from+mpl_toolkits.axes_grid1+import+make_axes_locatable
import+numpy+as+np
++++
plt.figure()
ax+=+plt.gca()
im+=+ax.imshow(np.arange(100).reshape((10,10)))
++++
#+create+an+axes+on+the+right+side+of+ax.+The+width+of+cax+will+be+5%25
#+of+ax+and+the+padding+between+cax+and+ax+will+be+fixed+at+0.05+inch.
divider+=+make_axes_locatable(ax)
cax+=+divider.append_axes("right",+size="5%25",+pad=0.05)
+++
plt.colorbar(im,+cax=cax)|code-block|syntax|javascript|43591|​|43592|📷|atomic|43593|43594|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.org/mpl_toolkits/axes_grid/users/overview.html#axesdivider|1|IMAGE|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/d16faf06830361d2c3770e99549d9819.png|imageAlt^0|D|B|0|0|0|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@$A|15|B|16|1|17]]|C|$]]|$1|D|3|E|5|6|7|18|8|@]|9|@]|C|$]]|$1|F|3|G|5|H|7|19|8|@]|9|@]|C|$I|J]]|$1|K|3|L|5|6|7|1A|8|@]|9|@]|C|$]]|$1|M|3|N|5|O|7|1B|8|@]|9|@$A|1C|B|1D|1|1E]]|C|$]]|$1|P|3|L|5|6|7|1F|8|@]|9|@]|C|$]]|$1|Q|3|-4|5|6|7|1G|8|@]|9|@]|C|$]]]|R|$S|$5|T|U|V|C|$W|X]]|Y|$5|Z|U|10|C|$11|12|13|-4]]]]

<p>You can do this easily with a matplotlib <a href="http://matplotlib.org/mpl_toolkits/axes_grid/users/overview.html#axesdivider" rel="noreferrer">AxisDivider</a>.</p>
<p>The example from the linked page also works without using subplots:</p>
<pre class="lang-py prettyprint-override"><code>import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
    
plt.figure()
ax = plt.gca()
im = ax.imshow(np.arange(100).reshape((10,10)))
    
# create an axes on the right side of ax. The width of cax will be 5%
# of ax and the padding between cax and ax will be fixed at 0.05 inch.
divider = make_axes_locatable(ax)
cax = divider.append_axes(&quot;right&quot;, size=&quot;5%&quot;, pad=0.05)
   
plt.colorbar(im, cax=cax)
</code></pre>
<p><a href="https://i.stack.imgur.com/wgFtO.png" rel="noreferrer"><img src="https://i.stack.imgur.com/wgFtO.png" alt="enter image description here" /></a></p>


blocks|key|43662|text|这种组合(以及接近这些值的值)似乎对我来说是“神奇的”，无论显示器的大小如何，都可以保持颜色条按比例缩放到绘图。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|43663|plt.colorbar(im,fraction=0.046,+pad=0.04)|code-block|syntax|javascript|43664|它也不需要共享轴，这可以使绘图脱离正方形。|43665|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|$]]

<p>This combination (and values near to these) seems to "magically" work for me to keep the colorbar scaled to the plot, no matter what size the display.</p>

<pre><code>plt.colorbar(im,fraction=0.046, pad=0.04)
</code></pre>

<p>It also does not require sharing the axis which can get the plot out of square. </p>


blocks|key|43725|text|上面所有的解决方案都很好，但我最喜欢@Steve和@bejota的解决方案，因为它们不涉及花哨的呼叫，而且是通用的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|43726|所谓通用，我的意思是它适用于任何类型的轴，包括GeoAxes。例如，如果您有用于映射的投影轴：|offset|length|style|CODE|43727|projection+=+cartopy.crs.UTM(zone='17N')
ax+=+plt.axes(projection=projection)
im+=+ax.imshow(np.arange(200).reshape((20,+10)))|code-block|syntax|javascript|43728|调用|43729|cax+=+divider.append_axes("right",+size=width,+pad=pad)|43730|将失败，并显示：KeyException:+map_projection|43731|因此，处理所有类型的轴的颜色条大小的唯一通用方法是：|43732|ax.colorbar(im,+fraction=0.046,+pad=0.04)|43733|使用从0.035到0.046的分数来获得最佳尺寸。但是，分数和paddig的值需要调整，以获得最适合您的绘图，并且将根据颜色栏的方向是垂直位置还是水平位置而有所不同。|43734|entityMap^0|0|N|7|0|0|0|0|8|S|0|0|0|0^^$0|@$1|2|3|4|5|6|7|10|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|11|8|@$D|12|E|13|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|14|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|15|8|@]|9|@]|A|$]]|$1|O|3|P|5|J|7|16|8|@]|9|@]|A|$K|L]]|$1|Q|3|R|5|6|7|17|8|@$D|18|E|19|F|G]]|9|@]|A|$]]|$1|S|3|T|5|6|7|1A|8|@]|9|@]|A|$]]|$1|U|3|V|5|J|7|1B|8|@]|9|@]|A|$K|L]]|$1|W|3|X|5|6|7|1C|8|@]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|1D|8|@]|9|@]|A|$]]]|Z|$]]

<p>All the above solutions are good, but I like @Steve's and @bejota's the best as they do not involve fancy calls and are universal. </p>

<p>By universal I mean that works with any type of axes including <code>GeoAxes</code>. For example, it you have projected axes for mapping: </p>

<pre><code>projection = cartopy.crs.UTM(zone='17N')
ax = plt.axes(projection=projection)
im = ax.imshow(np.arange(200).reshape((20, 10)))
</code></pre>

<p>a call to </p>

<pre><code>cax = divider.append_axes("right", size=width, pad=pad)
</code></pre>

<p>will fail with: <code>KeyException: map_projection</code></p>

<p>Therefore, the only universal way of dealing colorbar size with all types of axes is:</p>

<pre><code>ax.colorbar(im, fraction=0.046, pad=0.04)
</code></pre>

<p>Work with fraction from 0.035 to 0.046 to get your best size. However, the values for the fraction and paddig will need to be adjusted to get the best fit for your plot and  will differ depending if the orientation of the colorbar is in vertical position or horizontal.</p>


blocks|key|43821|text|我很欣赏上面所有的答案。然而，正如一些答案和评论指出的那样，axes_grid1模块不能处理GeoAxes，而调整fraction、pad、shrink和其他类似参数不一定能给出非常精确的顺序，这真的让我很困扰。我认为，给colorbar自己的axes可能是解决上述所有问题的更好的解决方案。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|43822|代码|43823|import+matplotlib.pyplot+as+plt
import+numpy+as+np

fig=plt.figure()
ax+=+plt.axes()
im+=+ax.imshow(np.arange(100).reshape((10,10)))

#+Create+an+axes+for+colorbar.+The+position+of+the+axes+is+calculated+based+on+the+position+of+ax.
#+You+can+change+0.01+to+adjust+the+distance+between+the+main+image+and+the+colorbar.
#+You+can+change+0.02+to+adjust+the+width+of+the+colorbar.
#+This+practice+is+universal+for+both+subplots+and+GeoAxes.

cax+=+fig.add_axes([ax.get_position().x1%2B0.01,ax.get_position().y0,0.02,ax.get_position().height])
plt.colorbar(im,+cax=cax)+#+Similar+to+fig.colorbar(im,+cax+=+cax)|code-block|syntax|javascript|43824|结果|43825|​|43826|📷|atomic|43827|43828|后来，我发现matplotlib.pyplot.colorbar+official+documentation还提供了ax选项，这是为颜色栏提供空间的现有轴。因此，它对于多个子图很有用，请参见下文。|43829|43830|fig,+ax+=+plt.subplots(2,1,figsize=(12,8))+#+Caution,+figsize+will+also+influence+positions.
im1+=+ax[0].imshow(np.arange(100).reshape((10,10)),+vmin+=+-100,+vmax+=100)
im2+=+ax[1].imshow(np.arange(-100,0).reshape((10,10)),+vmin+=+-100,+vmax+=100)
fig.colorbar(im1,+ax=ax)|43831|43832|43833|43834|43835|同样，您也可以通过指定cax来实现类似的效果，从我的角度来看，这是一种更准确的方法。|43836|43837|fig,+ax+=+plt.subplots(2,1,figsize=(12,8))
im1+=+ax[0].imshow(np.arange(100).reshape((10,10)),+vmin+=+-100,+vmax+=100)
im2+=+ax[1].imshow(np.arange(-100,0).reshape((10,10)),+vmin+=+-100,+vmax+=100)
cax+=+fig.add_axes([ax[1].get_position().x1-0.25,ax[1].get_position().y0,0.02,ax[0].get_position().y1-ax[1].get_position().y0])
fig.colorbar(im1,+cax=cax)|43838|43839|43840|43841|43842|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/c9911b2a3a0e8cc9895c7cac91b6c771.png|imageAlt|1|LINK|MUTABLE|url|https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.colorbar.html|2|https://ask.qcloudimg.com/http-save/yehe-900000/6f1c0f3034a5c2eb18e2be4e9126756e.png|3|https://ask.qcloudimg.com/http-save/yehe-900000/57dc71b477d086d341e40aeddadad450.png^0|U|A|1L|8|1U|3|1Y|6|33|8|3E|4|0|0|0|0|0|0|1|0|0|0|6|Q|1N|2|6|1D|1|0|0|0|0|0|0|1|2|0|0|0|0|0|0|0|0|1|3|0|0^^$0|@$1|2|3|4|5|6|7|1U|8|@$9|1V|A|1W|B|C]|$9|1X|A|1Y|B|C]|$9|1Z|A|20|B|C]|$9|21|A|22|B|C]|$9|23|A|24|B|C]|$9|25|A|26|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|27|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|28|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|29|8|@]|D|@]|E|$]]|$1|O|3|P|5|6|7|2A|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|2B|8|@]|D|@$9|2C|A|2D|1|2E]]|E|$]]|$1|T|3|P|5|6|7|2F|8|@]|D|@]|E|$]]|$1|U|3|V|5|6|7|2G|8|@$9|2H|A|2I|B|C]|$9|2J|A|2K|B|C]]|D|@$9|2L|A|2M|1|2N]]|E|$]]|$1|W|3|G|5|6|7|2O|8|@]|D|@]|E|$]]|$1|X|3|Y|5|J|7|2P|8|@]|D|@]|E|$K|L]]|$1|Z|3|N|5|6|7|2Q|8|@]|D|@]|E|$]]|$1|10|3|P|5|6|7|2R|8|@]|D|@]|E|$]]|$1|11|3|R|5|S|7|2S|8|@]|D|@$9|2T|A|2U|1|2V]]|E|$]]|$1|12|3|P|5|6|7|2W|8|@]|D|@]|E|$]]|$1|13|3|14|5|6|7|2X|8|@]|D|@]|E|$]]|$1|15|3|G|5|6|7|2Y|8|@]|D|@]|E|$]]|$1|16|3|17|5|J|7|2Z|8|@]|D|@]|E|$K|L]]|$1|18|3|N|5|6|7|30|8|@]|D|@]|E|$]]|$1|19|3|P|5|6|7|31|8|@]|D|@]|E|$]]|$1|1A|3|R|5|S|7|32|8|@]|D|@$9|33|A|34|1|35]]|E|$]]|$1|1B|3|P|5|6|7|36|8|@]|D|@]|E|$]]|$1|1C|3|-4|5|6|7|37|8|@]|D|@]|E|$]]]|1D|$1E|$5|1F|1G|1H|E|$1I|1J|1K|-4]]|1L|$5|1M|1G|1N|E|$1O|1P]]|1Q|$5|1F|1G|1H|E|$1I|1R|1K|-4]]|1S|$5|1F|1G|1H|E|$1I|1T|1K|-4]]]]

<p>I appreciate all the answers above. However, like some answers and comments pointed out, the <code>axes_grid1</code> module cannot address GeoAxes, whereas adjusting <code>fraction</code>, <code>pad</code>, <code>shrink</code>, and other similar parameters cannot necessarily give the very precise order, which really bothers me. I believe that giving the <code>colorbar</code> its own <code>axes</code> might be a better solution to address all the issues that have been mentioned.</p>

<h3>Code</h3>

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

fig=plt.figure()
ax = plt.axes()
im = ax.imshow(np.arange(100).reshape((10,10)))

# Create an axes for colorbar. The position of the axes is calculated based on the position of ax.
# You can change 0.01 to adjust the distance between the main image and the colorbar.
# You can change 0.02 to adjust the width of the colorbar.
# This practice is universal for both subplots and GeoAxes.

cax = fig.add_axes([ax.get_position().x1+0.01,ax.get_position().y0,0.02,ax.get_position().height])
plt.colorbar(im, cax=cax) # Similar to fig.colorbar(im, cax = cax)
</code></pre>

<h3>Result</h3>

<p><a href="https://i.stack.imgur.com/rxY6d.png" rel="noreferrer"><img src="https://i.stack.imgur.com/rxY6d.png" alt="enter image description here"></a></p>

<p>Later on, I find <a href="https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.colorbar.html" rel="noreferrer"><code>matplotlib.pyplot.colorbar</code> official documentation</a> also gives <code>ax</code> option, which are existing axes that will provide room for the colorbar. Therefore, it is useful for multiple subplots, see following.</p>

<h3>Code</h3>

<pre><code>fig, ax = plt.subplots(2,1,figsize=(12,8)) # Caution, figsize will also influence positions.
im1 = ax[0].imshow(np.arange(100).reshape((10,10)), vmin = -100, vmax =100)
im2 = ax[1].imshow(np.arange(-100,0).reshape((10,10)), vmin = -100, vmax =100)
fig.colorbar(im1, ax=ax)
</code></pre>

<h3>Result</h3>

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

<p>Again, you can also achieve similar effects by specifying cax, a more accurate way from my perspective.</p>

<h3>Code</h3>

<pre><code>fig, ax = plt.subplots(2,1,figsize=(12,8))
im1 = ax[0].imshow(np.arange(100).reshape((10,10)), vmin = -100, vmax =100)
im2 = ax[1].imshow(np.arange(-100,0).reshape((10,10)), vmin = -100, vmax =100)
cax = fig.add_axes([ax[1].get_position().x1-0.25,ax[1].get_position().y0,0.02,ax[0].get_position().y1-ax[1].get_position().y0])
fig.colorbar(im1, cax=cax)
</code></pre>

<h3>Result</h3>

<p><a href="https://i.stack.imgur.com/VH6GB.png" rel="noreferrer"><img src="https://i.stack.imgur.com/VH6GB.png" alt="enter image description here"></a></p>


blocks|key|43877|text|另一种选择是|type|unstyled|depth|inlineStyleRanges|entityRanges|data|43878|shrink=0.7,+aspect=20*0.7|code-block|syntax|javascript|43879|shrink会缩放高度和宽度，但aspect参数会恢复原始宽度。默认长宽比为20。0.7由经验确定。|offset|length|style|CODE|43880|entityMap^0|0|0|0|6|G|6|15|3|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]|$I|T|J|U|K|L]|$I|V|J|W|K|L]]|9|@]|A|$]]|$1|M|3|-4|5|6|7|X|8|@]|9|@]|A|$]]]|N|$]]

<p>An alternative is</p>
<pre><code>shrink=0.7, aspect=20*0.7
</code></pre>
<p><code>shrink</code> scales the height and width, but the <code>aspect</code> argument restores the original width.  Default aspect ratio is 20.  The <code>0.7</code> is empirically determined.</p>


<p>I cannot get the colorbar on imshow graphs like this one to be the same height as the graph, short of using Photoshop after the fact. How do I get the heights to match?<img src="https://i.stack.imgur.com/EXLiY.png" alt="Example of the colorbar size mismatch" /></p>


Set Matplotlib colorbar size to match graph

我不能让imshow图形上的颜色条与图形的高度相同，因为事后使用Photoshop是不够的。我怎样才能使高度匹配？​

问设置Matplotlib颜色条大小以匹配图形
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