blocks|key|757596|text|好了，这是我的解决方案。不是非常优雅，但也不是一个可怕的黑客。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757597|def+foo(self):
+++self.subplot.clear()
+++hb+=+self.subplot.hexbin(...)
+++if+self.cb:
++++++self.figure.delaxes(self.figure.axes[1])
++++++self.figure.subplots_adjust(right=0.90)++#default+right+padding
+++self.cb+=+self.figure.colorbar(hb)|code-block|syntax|javascript|757598|这可以满足我的需要，因为我只有一个子图。在使用多个子图或在不同位置绘制颜色条时遇到相同问题的人将需要调整。|757599|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|$]]

Alright, here's my solution. Not terribly elegant, but not a terrible hack either.

<pre><code>def foo(self):
 self.subplot.clear()
 hb = self.subplot.hexbin(...)
 if self.cb:
 self.figure.delaxes(self.figure.axes[1])
 self.figure.subplots_adjust(right=0.90) #default right padding
 self.cb = self.figure.colorbar(hb)
</code></pre>

This works for my needs since I only ever have a single subplot. People who run into the same problem when using multiple subplots or when drawing the colorbar in a different position will need to tweak.

blocks|key|757644|text|我使用的是matplotlib+1.4.0。这是我解决这个问题的方法：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757645|import+matplotlib
import+numpy+as+np
import+matplotlib.cm+as+cm
import+matplotlib.mlab+as+mlab
import+matplotlib.pyplot+as+plt

#+A+contour+plot+example:
delta+=+0.025
x+=+np.arange(-3.0,+3.0,+delta)
y+=+np.arange(-2.0,+2.0,+delta)
X,+Y+=+np.meshgrid(x,+y)
Z1+=+mlab.bivariate_normal(X,+Y,+1.0,+1.0,+0.0,+0.0)
Z2+=+mlab.bivariate_normal(X,+Y,+1.5,+0.5,+1,+1)
Z+=+10.0+*+(Z2+-+Z1)
#

#+first+drawing
fig+=+plt.figure()
ax+=+fig.add_subplot(111)++#+drawing+axes
c+=+ax.contourf(Z)+++#+contour+fill+c
cb+=+fig.colorbar(c)++#+colorbar+for+contour+c

#+clear+first+drawimg
ax.clear()++#+clear+drawing+axes
cb.ax.clear()++#+clear+colorbar+axes

#+replace+with+new+drawing
#+1.+drawing+new+contour+at+drawing+axes
c_new+=+ax.contour(Z)++
#+2.+create+new+colorbar+for+new+contour+at+colorbar+axes
cb_new+=+ax.get_figure().colorbar(c_new,+cax=cb.ax)+

plt.show()|code-block|syntax|javascript|757646|上面的代码绘制了一个带有颜色条的等高线填充图，清除它，并在同一图中使用新的颜色条绘制新的等高线图。|757647|通过使用cb.ax，我能够识别颜色条轴并清除旧的颜色条。并且指定cax=cb.ax只是在旧的颜色条轴上绘制新的颜色条。|offset|length|style|CODE|757648|entityMap^0|0|0|0|4|5|W|9|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|S|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|T|8|@$K|U|L|V|M|N]|$K|W|L|X|M|N]]|9|@]|A|$]]|$1|O|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|P|$]]

I am using matplotlib 1.4.0. This is how I solve this problem:

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

# A contour plot example:
delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = 10.0 * (Z2 - Z1)
#

# first drawing
fig = plt.figure()
ax = fig.add_subplot(111) # drawing axes
c = ax.contourf(Z) # contour fill c
cb = fig.colorbar(c) # colorbar for contour c

# clear first drawimg
ax.clear() # clear drawing axes
cb.ax.clear() # clear colorbar axes

# replace with new drawing
# 1. drawing new contour at drawing axes
c_new = ax.contour(Z) 
# 2. create new colorbar for new contour at colorbar axes
cb_new = ax.get_figure().colorbar(c_new, cax=cb.ax) 

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

Above code draws a contour fill plot with colorbar, clear it and draw a new contour plot with new colorbar at the same figure.

By using
 <code>cb.ax</code>
i am able to identify the colorbar axes and clear the old colorbar.
And specifying <code>cax=cb.ax</code> simply draws the new colorbar in the old colorbar axes.

blocks|key|757674|text|"on_mappable_changed“在我的案例中起作用了。然而，根据文档，该方法“通常……不应该手动调用”。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757675|if+self.cb:
++++self.cb.on_mappable_changed(hb)
else:
++++self.cb+=+self.fig.colorbar(hb)|code-block|syntax|javascript|757676|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|$]]

"on_mappable_changed" worked in my case. However, according to docs, the method "Typically ... should not be called manually."

<pre><code>if self.cb:
 self.cb.on_mappable_changed(hb)
else:
 self.cb = self.fig.colorbar(hb)
</code></pre>

blocks|key|757732|text|我设法用fig.clear()和display.clear_output()解决了同样的问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757733|import+matplotlib.pyplot+as+plt
import+IPython.display+as+display
import+matplotlib.tri+as+tri
from+pylab+import+*
%25matplotlib+inline

def+plot_res(fig):
++++ax=fig.add_axes([0,0,1,1])
++++ax.set_xlabel("x")
++++ax.set_ylabel('y')
++++plotted=ax.imshow(rand(250,+250))
++++ax.set_title("title")
++++cbar=fig.colorbar(mappable=plotted)
++++display.clear_output(wait=True)
++++display.display(plt.gcf())
++++fig.clear()

fig=plt.figure()
N=20
for+j+in+range(N):
++++plot_res(fig)|code-block|syntax|javascript|757734|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 managed to solve the same issue using fig.clear() and display.clear_output()

<pre><code>import matplotlib.pyplot as plt
import IPython.display as display
import matplotlib.tri as tri
from pylab import *
%matplotlib inline

def plot_res(fig):
 ax=fig.add_axes([0,0,1,1])
 ax.set_xlabel("x")
 ax.set_ylabel('y')
 plotted=ax.imshow(rand(250, 250))
 ax.set_title("title")
 cbar=fig.colorbar(mappable=plotted)
 display.clear_output(wait=True)
 display.display(plt.gcf())
 fig.clear()

fig=plt.figure()
N=20
for j in range(N):
 plot_res(fig)
</code></pre>

blocks|key|757821|text|我的解决方案是有一个轴，它的唯一目的是保持色条，并在需要时完全清除它。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|757822|例如，只需定义一次：|757823|figure,+ax+=+plt.subplots()+#+All+the+plotting+is+done+on+`ax`.
cax+=+ax.inset_axes([1.03,+0,+0.1,+1],+transform=ax.transAxes)+#+Colorbar+is+held+by+`cax`.+|code-block|syntax|javascript|757824|然后根据需要多次执行此操作：|757825|cax.clear()
colorbar+=+figure.colorbar(mpl.cm.ScalarMappable(norm=norm,+cmap=cmap),
+++++++++++++++++++++++++++ax=ax,
+++++++++++++++++++++++++++cax=cax,
+++++++++++++++++++++++++++**kwargs)|757826|​|757827|📷|atomic|offset|length|757828|757829|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/c63c1693a5a4a3b0b591af01d61a1f1a.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]]]]

My solution consists in having an Axes whose only purpose is to hold the colorbar, and clear it entirely when needed.
For example, define those once:
<pre><code>figure, ax = plt.subplots() # All the plotting is done on `ax`.
cax = ax.inset_axes([1.03, 0, 0.1, 1], transform=ax.transAxes) # Colorbar is held by `cax`. 
</code></pre>
Then do this as many times as needed:
<pre><code>cax.clear()
colorbar = figure.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),
 ax=ax,
 cax=cax,
 **kwargs)
</code></pre>
<a href="https://i.stack.imgur.com/B5yyZ.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/B5yyZ.png" alt="enter image description here" /></a>

This should be easy but I'm having a hard time with it. Basically, I have a subplot in matplotlib that I'm drawing a hexbin plot in every time a function is called, but every time I call the function I get a new colorbar, so what I'd really like to do is update the colorbar. Unfortunately, this doesn't seem to work since the object the colorbar is attached to is being recreated by subplot.hexbin.

<pre><code>def foo(self):
 self.subplot.clear()
 hb = self.subplot.hexbin(...)
 if self.cb:
 self.cb.update_bruteforce() # Doesn't work (hb is new)
 else:
 self.cb = self.figure.colorbar(hb)
</code></pre>

I'm now in this annoying place where I'm trying to delete the colorbar axes altogether and simply recreate it. Unfortunately, when I delete the colorbar axes, the subplot axes don't reclaim the space, and calling self.subplot.reset_position() isn't doing what I thought it would. 

<pre><code>def foo(self):
 self.subplot.clear()
 hb = self.subplot.hexbin(...)
 if self.cb:
 self.figure.delaxes(self.figure.axes[1])
 del self.cb
 # TODO: resize self.subplot so it fills the 
 # whole figure before adding the new colorbar
 self.cb = self.figure.colorbar(hb)
</code></pre>

Does anyone have any suggestions?

Much appreciated!
Adam

remove colorbar from figure in matplotlib

这应该很容易，但我很难做到。基本上，我在matplotlib中有一个子图，每次调用一个函数时，我都会在其中绘制一个六进制图，但每次我调用该函数时，我都会得到一个新的颜色条，所以我真正想做的是更新颜色条。不幸的是，这似乎不起作用，因为subplot.hexbin正在重新创建colorbar附加到的对象。def foo(s...

问从matplotlib中的图形中删除colorbar
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