blocks|key|982609|text|标准色彩映射表也都有反向版本。它们具有相同的名称，并在末尾附加了_r。(Documentation+here.)|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|982610|entityMap|0|LINK|mutability|MUTABLE|url|http://matplotlib.org/api/pyplot_summary.html?highlight=colormaps#matplotlib.pyplot.colormaps^0|W|2|10|J|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@$9|O|A|P|B|C]]|D|@$9|Q|A|R|1|S]]|E|$]]|$1|F|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|G|$H|$5|I|J|K|E|$L|M]]]]

The standard colormaps also all have reversed versions. They have the same names with <code>_r</code> tacked on to the end. (<a href="http://matplotlib.org/api/pyplot_summary.html?highlight=colormaps#matplotlib.pyplot.colormaps" rel="noreferrer">Documentation here.</a>)

blocks|key|1197126|text|在matplotlib中，颜色映射表不是一个列表，但它包含colormap.colors形式的颜色列表。并且模块matplotlib.colors提供从列表生成色彩映射表的函数ListedColormap()。因此，您可以通过执行以下操作来反转任何颜色映射|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1197127|colormap_r+=+ListedColormap(colormap.colors[::-1])|code-block|syntax|javascript|1197128|entityMap^0|T|F|1K|H|2G|G|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]|$9|P|A|Q|B|C]|$9|R|A|S|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|T|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|U|8|@]|D|@]|E|$]]]|L|$]]

In matplotlib a color map isn't a list, but it contains the list of its colors as <code>colormap.colors</code>. And the module <code>matplotlib.colors</code> provides a function <code>ListedColormap()</code> to generate a color map from a list. So you can reverse any color map by doing 

<pre><code>colormap_r = ListedColormap(colormap.colors[::-1])
</code></pre>

blocks|key|1197259|text|解决方案非常简单。假设您想要使用“秋季”色彩映射方案。标准版本：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1197260|cmap+=+matplotlib.cm.autumn|code-block|syntax|javascript|1197261|若要反转色彩映射表的颜色光谱，请使用get_cmap()函数并将'_r‘附加到色彩映射表标题，如下所示：|1197262|cmap_reversed+=+matplotlib.cm.get_cmap('autumn_r')|1197263|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]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

The solution is pretty straightforward. Suppose you want to use the "autumn" colormap scheme. The standard version:

<pre><code>cmap = matplotlib.cm.autumn
</code></pre>

To reverse the colormap color spectrum, use get_cmap() function and append '_r' to the colormap title like this:

<pre><code>cmap_reversed = matplotlib.cm.get_cmap('autumn_r')
</code></pre>

blocks|key|982856|text|从Matplotlib2.0开始，有一个用于ListedColormap和LinearSegmentedColorMap对象的reversed()方法，所以你可以这样做|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|982857|cmap_reversed+=+cmap.reversed()|982858|Here是文档。|982859|entityMap|0|LINK|mutability|MUTABLE|url|https://matplotlib.org/api/_as_gen/matplotlib.colors.ListedColormap.html?highlight=reverse#matplotlib.colors.ListedColormap.reversed^0|M|E|11|N|1R|A|0|0|V|0|0|4|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@$9|S|A|T|B|C]|$9|U|A|V|B|C]|$9|W|A|X|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|Y|8|@$9|Z|A|10|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|11|8|@]|D|@$9|12|A|13|1|14]]|E|$]]|$1|J|3|-4|5|6|7|15|8|@]|D|@]|E|$]]]|K|$L|$5|M|N|O|E|$P|Q]]]]

As of Matplotlib 2.0, there is a <code>reversed()</code> method for <code>ListedColormap</code> and <code>LinearSegmentedColorMap</code> objects, so you can just do

<code>cmap_reversed = cmap.reversed()
</code>

<a href="https://matplotlib.org/api/_as_gen/matplotlib.colors.ListedColormap.html?highlight=reverse#matplotlib.colors.ListedColormap.reversed" rel="noreferrer">Here</a> is the documentation.

blocks|key|982808|text|还没有内置的方法来反转任意颜色映射，但一个简单的解决方案是实际上不修改colorbar，而是创建一个反转规格化对象：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|982809|from+matplotlib.colors+import+Normalize

class+InvertedNormalize(Normalize):
++++def+__call__(self,+*args,+**kwargs):
++++++++return+1+-+super(InvertedNormalize,+self).__call__(*args,+**kwargs)|code-block|syntax|javascript|982810|然后，您可以通过执行以下操作将其与plot_surface和其他Matplotlib绘图函数一起使用。|offset|length|style|CODE|982811|inverted_norm+=+InvertedNormalize(vmin=10,+vmax=100)
ax.plot_surface(...,+cmap=<your+colormap>,+norm=inverted_norm)|982812|这将适用于任何Matplotlib色彩映射。|982813|entityMap^0|0|0|H|C|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|U|8|@$I|V|J|W|K|L]]|9|@]|A|$]]|$1|M|3|N|5|D|7|X|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|Y|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|Z|8|@]|9|@]|A|$]]]|R|$]]

There is no built-in way (yet) of reversing arbitrary colormaps, but one simple solution is to actually not modify the colorbar but to create an inverting Normalize object:

<pre><code>from matplotlib.colors import Normalize

class InvertedNormalize(Normalize):
 def __call__(self, *args, **kwargs):
 return 1 - super(InvertedNormalize, self).__call__(*args, **kwargs)
</code></pre>

You can then use this with <code>plot_surface</code> and other Matplotlib plotting functions by doing e.g.

<pre><code>inverted_norm = InvertedNormalize(vmin=10, vmax=100)
ax.plot_surface(..., cmap=&lt;your colormap&gt;, norm=inverted_norm)
</code></pre>

This will work with any Matplotlib colormap.

blocks|key|1197184|text|有两种类型的LinearSegmentedColormaps。在某些情况下，_segmentdata是明确给出的，例如，对于jet：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1197185|>>>+cm.jet._segmentdata
{'blue':+((0.0,+0.5,+0.5),+(0.11,+1,+1),+(0.34,+1,+1),+(0.65,+0,+0),+(1,+0,+0)),+'red':+((0.0,+0,+0),+(0.35,+0,+0),+(0.66,+1,+1),+(0.89,+1,+1),+(1,+0.5,+0.5)),+'green':+((0.0,+0,+0),+(0.125,+0,+0),+(0.375,+1,+1),+(0.64,+1,+1),+(0.91,+0,+0),+(1,+0,+0))}|code-block|syntax|javascript|1197186|对于彩虹，_segmentdata如下所示：|1197187|>>>+cm.rainbow._segmentdata
{'blue':+<function+<lambda>+at+0x7fac32ac2b70>,+'red':+<function+<lambda>+at+0x7fac32ac7840>,+'green':+<function+<lambda>+at+0x7fac32ac2d08>}|1197188|我们可以在matplotlib的源代码中找到函数，其中的函数如下所示|1197189|_rainbow_data+=+{
++++++++'red':+gfunc[33],+++#+33:+lambda+x:+np.abs(2+*+x+-+0.5),
++++++++'green':+gfunc[13],+#+13:+lambda+x:+np.sin(x+*+np.pi),
++++++++'blue':+gfunc[10],++#+10:+lambda+x:+np.cos(x+*+np.pi+/+2)
}|1197190|你想要的一切都已经在matplotlib中完成了，只需调用cm.revcmap，它会颠倒两种类型的段数据，所以|1197191|cm.revcmap(cm.rainbow._segmentdata)|1197192|应该可以完成这项工作-您可以简单地从它创建一个新的LinearSegmentData。在revcmap中，基于函数的SegmentData的反转是通过|1197193|def+_reverser(f):
++++def+freversed(x):
++++++++return+f(1+-+x)
++++return+freversed|1197194|而其他列表则像往常一样颠倒|1197195|valnew+=+[(1.0+-+x,+y1,+y0)+for+x,+y0,+y1+in+reversed(val)]+|1197196|所以实际上你想要的就是|1197197|def+reverse_colourmap(cmap,+name+=+'my_cmap_r'):
+++++return+mpl.colors.LinearSegmentedColormap(name,+cm.revcmap(cmap._segmentdata))+|1197198|entityMap^0|0|0|0|0|0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|16|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|17|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|18|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|19|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|1A|8|@]|9|@]|A|$]]|$1|M|3|N|5|D|7|1B|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1C|8|@]|9|@]|A|$]]|$1|Q|3|R|5|D|7|1D|8|@]|9|@]|A|$E|F]]|$1|S|3|T|5|6|7|1E|8|@]|9|@]|A|$]]|$1|U|3|V|5|D|7|1F|8|@]|9|@]|A|$E|F]]|$1|W|3|X|5|6|7|1G|8|@]|9|@]|A|$]]|$1|Y|3|Z|5|D|7|1H|8|@]|9|@]|A|$E|F]]|$1|10|3|11|5|6|7|1I|8|@]|9|@]|A|$]]|$1|12|3|13|5|D|7|1J|8|@]|9|@]|A|$E|F]]|$1|14|3|-4|5|6|7|1K|8|@]|9|@]|A|$]]]|15|$]]

There are two types of LinearSegmentedColormaps. In some, the _segmentdata is given explicitly, e.g., for jet:

<pre><code>&gt;&gt;&gt; cm.jet._segmentdata
{'blue': ((0.0, 0.5, 0.5), (0.11, 1, 1), (0.34, 1, 1), (0.65, 0, 0), (1, 0, 0)), 'red': ((0.0, 0, 0), (0.35, 0, 0), (0.66, 1, 1), (0.89, 1, 1), (1, 0.5, 0.5)), 'green': ((0.0, 0, 0), (0.125, 0, 0), (0.375, 1, 1), (0.64, 1, 1), (0.91, 0, 0), (1, 0, 0))}
</code></pre>

For rainbow, _segmentdata is given as follows:

<pre><code>&gt;&gt;&gt; cm.rainbow._segmentdata
{'blue': &lt;function &lt;lambda&gt; at 0x7fac32ac2b70&gt;, 'red': &lt;function &lt;lambda&gt; at 0x7fac32ac7840&gt;, 'green': &lt;function &lt;lambda&gt; at 0x7fac32ac2d08&gt;}
</code></pre>

We can find the functions in the source of matplotlib, where they are given as

<pre><code>_rainbow_data = {
 'red': gfunc[33], # 33: lambda x: np.abs(2 * x - 0.5),
 'green': gfunc[13], # 13: lambda x: np.sin(x * np.pi),
 'blue': gfunc[10], # 10: lambda x: np.cos(x * np.pi / 2)
}
</code></pre>

Everything you want is already done in matplotlib, just call cm.revcmap, which reverses both types of segmentdata, so

<pre><code>cm.revcmap(cm.rainbow._segmentdata)
</code></pre>

should do the job - you can simply create a new LinearSegmentData from that. In revcmap, the reversal of function based SegmentData is done with

<pre><code>def _reverser(f):
 def freversed(x):
 return f(1 - x)
 return freversed
</code></pre>

while the other lists are reversed as usual

<pre><code>valnew = [(1.0 - x, y1, y0) for x, y0, y1 in reversed(val)] 
</code></pre>

So actually the whole thing you want, is

<pre><code>def reverse_colourmap(cmap, name = 'my_cmap_r'):
 return mpl.colors.LinearSegmentedColormap(name, cm.revcmap(cmap._segmentdata)) 
</code></pre>

I would like to know how to simply reverse the color order of a given colormap in order to use it with plot_surface.

Reverse colormap in matplotlib

我想知道如何简单地颠倒给定色彩映射表的颜色顺序，以便在plot_surface中使用它。

问matplotlib中的反转色彩映射
EN

回答 6

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问matplotlib中的反转色彩映射EN

回答 6

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问matplotlib中的反转色彩映射
EN