blocks|key|898786|text|目前直接在matplotlib上做这件事很笨拙，但“将来”他们计划在图上支持set_gray(True)调用(参见邮件列表线程here)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|898787|您最好的选择是将其保存为颜色并进行转换，或者在python中使用PIL：|898788|import+Image
Image.open('color.png').convert('L').save('bw.png')|code-block|syntax|javascript|898789|或者从命令行使用imagemagick：|898790|convert+-type+Grayscale+color.png+bw.png|898791|entityMap|0|LINK|mutability|MUTABLE|url|http://old.nabble.com/convert-figure-from-color-to-BW-grayscale-td29756144.html^0|12|E|1R|4|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@$9|11|A|12|1|13]]|E|$]]|$1|F|3|G|5|6|7|14|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|15|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|16|8|@]|D|@]|E|$]]|$1|O|3|P|5|J|7|17|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|18|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X]]]]

It's currently awkward to do directly from matplotlib, but in "the future" they plan to support a <code>set_gray(True)</code> call on the figure (see the mailing list thread <a href="http://old.nabble.com/convert-figure-from-color-to-BW-grayscale-td29756144.html" rel="noreferrer">here</a>).

Your best options will be to save it in color and convert it, either in python with PIL:

<pre><code>import Image
Image.open('color.png').convert('L').save('bw.png')
</code></pre>

or from the command line with imagemagick:

<pre><code>convert -type Grayscale color.png bw.png
</code></pre>

blocks|key|898834|text|并添加到Mu+Mind的解决方案中|type|unstyled|depth|inlineStyleRanges|entityRanges|data|898835|如果出于某种原因，您希望避免将其写入文件，则可以像使用文件一样使用StringIO：|898836|+import+Image
+import+pylab
+from+StringIO+import+StringIO

+pylab.plot(range(10),[x**2+for+x+in+range(10)])

+IO+=+StringIO()
+pylab.savefig(IO,format='png')
+IO.seek(0)

+#this,+I+stole+from+Mu+Mind+solution
+Image.open(IO).convert('L').show()|code-block|syntax|javascript|898837|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|L|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|M|8|@]|9|@]|A|$G|H]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

And to add to Mu Mind's solution

If for whatever reason you want to avoid writing it to a file you can use StringIO like a file:

<pre><code>
 import Image
 import pylab
 from StringIO import StringIO

 pylab.plot(range(10),[x**2 for x in range(10)])

 IO = StringIO()
 pylab.savefig(IO,format='png')
 IO.seek(0)

 #this, I stole from Mu Mind solution
 Image.open(IO).convert('L').show()
</code></pre>

blocks|key|682372|text|实际上，这是以前问过的。这是一个很好的答案，在google上排名第二(截至今天)：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|682373|Display+image+as+grayscale+using+matplotlib|offset|length|682374|其解决方案与Suki的非常相似。|682375|哦，好吧，我很无聊，所以我在这里也发布了一个完整的代码：|682376|import+numpy+as+np
import+pylab+as+p
xv=np.ones(4)*.5
yv=np.arange(0,4,1)
xv1=np.ones(4)*-.5
yv1=np.arange(0,4,1)

#red+vertical+line+on+the+right
yv2=np.arange(0,1.5,0.1)
xv2=np.ones_like(yv2)*.7

#red+vertical+line+on+the+left
yv3=np.arange(0,2,0.01)
xv3=np.ones_like(yv3)*-0.7

###
xc=np.arange(-1.4,2,0.05)
yc=np.ones_like(xc)*1

fig+=+p.figure()
ax1+=+fig.add_subplot(111)
#adjustprops+=+dict(left=0.12,+bottom=0.2,+right=0.965,+top=0.96,+wspace=0.13,+hspace=0.37)
#fig.subplots_adjust(**adjustprops)
ax1.plot(xv,yv,+color='blue',+lw=1,+linestyle='dashed')
ax1.plot(xv1,yv1,+'green',+linestyle='dashed')
ax1.plot(np.r_[-1:1:0.2],np.r_[-1:1:0.2],'red')
ax1.plot(xc,yc,+'k.',+markersize=3)

p.savefig('colored_image.png')

import+matplotlib.image+as+mpimg
import+matplotlib.cm+as+cm
import+Image

figprops+=+dict(figsize=(10,10),+dpi=100)
fig1+=+p.figure(**figprops)
#fig1+=+p.figure()
#ax1+=+fig.add_subplot(111)
adjustprops+=+dict()
image=Image.open('colored_image.png').convert("L")
arr=np.asarray(image)
p.figimage(arr,cmap=cm.Greys_r)
p.savefig('grayed.png')
p.savefig('grayed.pdf',papertype='a4',orientation='portrait')|code-block|syntax|javascript|682377|这将产生一个彩色图形，然后读取它，将其转换为灰度，并将保存为png和pdf。|682378|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/3823752/display-image-as-grayscale-using-matplotlib/3823822#3823822^0|0|0|17|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|Z|8|@]|9|@$D|10|E|11|1|12]]|A|$]]|$1|F|3|G|5|6|7|13|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|14|8|@]|9|@]|A|$]]|$1|J|3|K|5|L|7|15|8|@]|9|@]|A|$M|N]]|$1|O|3|P|5|6|7|16|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|17|8|@]|9|@]|A|$]]]|R|$S|$5|T|U|V|A|$W|X]]]]

Actually, this was asked before. Here is a pretty good answer, which comes 2nd on google (as of today): 
<a href="https://stackoverflow.com/questions/3823752/display-image-as-grayscale-using-matplotlib/3823822#3823822">Display image as grayscale using matplotlib</a>

And the solution is VERY similar to Suki's...

Oh, well, I am bored, so I post here also a full blown code:

<pre><code>import numpy as np
import pylab as p
xv=np.ones(4)*.5
yv=np.arange(0,4,1)
xv1=np.ones(4)*-.5
yv1=np.arange(0,4,1)

#red vertical line on the right
yv2=np.arange(0,1.5,0.1)
xv2=np.ones_like(yv2)*.7

#red vertical line on the left
yv3=np.arange(0,2,0.01)
xv3=np.ones_like(yv3)*-0.7

###
xc=np.arange(-1.4,2,0.05)
yc=np.ones_like(xc)*1

fig = p.figure()
ax1 = fig.add_subplot(111)
#adjustprops = dict(left=0.12, bottom=0.2, right=0.965, top=0.96, wspace=0.13, hspace=0.37)
#fig.subplots_adjust(**adjustprops)
ax1.plot(xv,yv, color='blue', lw=1, linestyle='dashed')
ax1.plot(xv1,yv1, 'green', linestyle='dashed')
ax1.plot(np.r_[-1:1:0.2],np.r_[-1:1:0.2],'red')
ax1.plot(xc,yc, 'k.', markersize=3)

p.savefig('colored_image.png')

import matplotlib.image as mpimg
import matplotlib.cm as cm
import Image

figprops = dict(figsize=(10,10), dpi=100)
fig1 = p.figure(**figprops)
#fig1 = p.figure()
#ax1 = fig.add_subplot(111)
adjustprops = dict()
image=Image.open('colored_image.png').convert("L")
arr=np.asarray(image)
p.figimage(arr,cmap=cm.Greys_r)
p.savefig('grayed.png')
p.savefig('grayed.pdf',papertype='a4',orientation='portrait')
</code></pre>

This will produce a graph in color, than read it, convert it to gray scale, and will save a png and pdf.

blocks|key|682411|text|我也在努力解决这个问题。据我所知，matplotlib不支持直接转换为灰度，但你可以保存一个颜色pdf，然后用ghostscript将其转换为灰度：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|682412|gs+-sOutputFile=gray.pdf+-sDEVICE=pdfwrite+-sColorConversionStrategy=Gray+-dProcessColorModel=/DeviceGray+-dNOPAUSE+-dBATCH+-dAutoRotatePages=/None+color.pdf|code-block|syntax|javascript|682413|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 am struggling with this issue too. As far as I can tell, matplotlib doesn't support direct conversion to grayscale, but you can save a color pdf and then convert it to grayscale with ghostscript:

<pre><code>gs -sOutputFile=gray.pdf -sDEVICE=pdfwrite -sColorConversionStrategy=Gray -dProcessColorModel=/DeviceGray -dNOPAUSE -dBATCH -dAutoRotatePages=/None color.pdf
</code></pre>

blocks|key|898915|text|有一个简单的解决方案：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|898916|plt.imsave(filename,+image,+cmap='gray')|code-block|syntax|javascript|898917|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|$]]

There is an easy solution:

<pre><code>plt.imsave(filename, image, cmap='gray')
</code></pre>

I have some color plots that I need to be saved in grayscale. Is there an easy way to do this without changing the plotting formats?

Save matplotlib plot in grayscale

我有一些需要以灰度保存的彩色图。有没有一种简单的方法可以在不改变绘图格式的情况下做到这一点？

问将matplotlib图保存为灰度
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