blocks|key|438695|text|在这里，colorRampPalette可以成为你的朋友：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|438696|colfunc+<-+colorRampPalette(c("black",+"white"))
colfunc(10)
#+[1]+"#000000"+"#1C1C1C"+"#383838"+"#555555"+"#717171"+"#8D8D8D"+"#AAAAAA"
#+[8]+"#C6C6C6"+"#E2E2E2"+"#FFFFFF"|code-block|syntax|javascript|438697|为了证明它是有效的：|438698|plot(rep(1,10),col=colfunc(10),pch=19,cex=3)|438699|​|438700|📷|atomic|438701|438702|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/db94e26fdc11a09ac63d52adf343636c.png|imageAlt^0|4|G|0|0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@$9|14|A|15|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|16|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|17|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|18|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|19|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|1A|8|@]|D|@$9|1B|A|1C|1|1D]]|E|$]]|$1|T|3|P|5|6|7|1E|8|@]|D|@]|E|$]]|$1|U|3|-4|5|6|7|1F|8|@]|D|@]|E|$]]]|V|$W|$5|X|Y|Z|E|$10|11|12|-4]]]]

<code>colorRampPalette</code> could be your friend here:

<pre><code>colfunc &lt;- colorRampPalette(c("black", "white"))
colfunc(10)
# [1] "#000000" "#1C1C1C" "#383838" "#555555" "#717171" "#8D8D8D" "#AAAAAA"
# [8] "#C6C6C6" "#E2E2E2" "#FFFFFF"
</code></pre>

And just to show it works:

<pre><code>plot(rep(1,10),col=colfunc(10),pch=19,cex=3)
</code></pre>

<img src="https://i.stack.imgur.com/dGQU0.png" alt="enter image description here">

blocks|key|220632|text|仅对上一个答案进行扩展，colorRampPalette可以处理两种以上的颜色。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|220633|因此，要获得更多扩展的“热图”类型，您可以...|220634|colfunc<-colorRampPalette(c("red","yellow","springgreen","royalblue"))
plot(rep(1,50),col=(colfunc(50)),+pch=19,cex=2)|code-block|syntax|javascript|220635|生成的图像：|220636|​|220637|📷|atomic|220638|220639|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/6414f0815af15356d99e1d0eaac0c578.png|imageAlt^0|C|G|0|0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|13|8|@$9|14|A|15|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|16|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|17|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|18|8|@]|D|@]|E|$]]|$1|O|3|P|5|6|7|19|8|@]|D|@]|E|$]]|$1|Q|3|R|5|S|7|1A|8|@]|D|@$9|1B|A|1C|1|1D]]|E|$]]|$1|T|3|P|5|6|7|1E|8|@]|D|@]|E|$]]|$1|U|3|-4|5|6|7|1F|8|@]|D|@]|E|$]]]|V|$W|$5|X|Y|Z|E|$10|11|12|-4]]]]

Just to expand on the previous answer <code>colorRampPalette</code>can handle more than two colors.

So for a more expanded "heat map" type look you can....

<pre><code>colfunc&lt;-colorRampPalette(c("red","yellow","springgreen","royalblue"))
plot(rep(1,50),col=(colfunc(50)), pch=19,cex=2)
</code></pre>



The resulting image:

<img src="https://i.stack.imgur.com/28xXQ.png" alt="enter image description here">

blocks|key|220670|text|尝试以下操作：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|220671|color.gradient+<-+function(x,+colors=c("red","yellow","green"),+colsteps=100)+{
++return(+colorRampPalette(colors)+(colsteps)+[+findInterval(x,+seq(min(x),max(x),+length.out=colsteps))+]+)
}
x+<-+c((1:100)%5E2,+(100:1)%5E2)
plot(x,col=color.gradient(x),+pch=19,cex=2)|code-block|syntax|javascript|220672|​|220673|📷|atomic|offset|length|220674|220675|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/3ce01050dc414aeadc14a5bb990614bc.png|imageAlt^0|0|0|0|0|1|0|0|0^^$0|@$1|2|3|4|5|6|7|X|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|Y|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Z|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|10|8|@]|9|@$L|11|M|12|1|13]]|A|$]]|$1|N|3|H|5|6|7|14|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|15|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V|W|-4]]]]

Try the following:

<pre><code>color.gradient &lt;- function(x, colors=c("red","yellow","green"), colsteps=100) {
 return( colorRampPalette(colors) (colsteps) [ findInterval(x, seq(min(x),max(x), length.out=colsteps)) ] )
}
x &lt;- c((1:100)^2, (100:1)^2)
plot(x,col=color.gradient(x), pch=19,cex=2)
</code></pre>

<a href="https://i.stack.imgur.com/9HJJN.png" rel="noreferrer"><img src="https://i.stack.imgur.com/9HJJN.png" alt="enter image description here"></a>

blocks|key|438899|text|另一种方法(不一定比前面的答案更好！)就是使用viridis包。正如here所解释的，它允许基于两种以上颜色的各种颜色渐变。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|438900|该软件包非常易于使用-您只需将ggplot2+scale+fill函数(例如，scale_fill_gradient(low+=+"skyblue",+high+=+"dodgerblue4"))替换为等效的viridis函数。|438901|因此，更改此图的代码：|438902|ggplot(mtcars,+aes(wt*1000,+mpg))+%2B
++geom_point(size+=+4,+aes(colour+=+hp))+%2B
++xlab("Weight+(pounds)")+%2B+ylab("Miles+per+gallon+(MPG)")+%2B+labs(color='Horse+power')+%2B
++scale_x_continuous(limits+=+c(1000,+6000),+
+++++++++++++++++++++breaks+=+c(seq(1000,6000,1000)),+
+++++++++++++++++++++labels+=+c("1,000",+"2,000",+"3,000",+"4,000",+"5,000",+"6,000"))+%2B+
++scale_fill_gradient(low+=+"skyblue",+high+=+"dodgerblue4")+%2B
++theme_classic()|code-block|syntax|javascript|438903|这会产生：|438904|​|438905|📷|atomic|438906|438907|，它使用了viridis|438908|ggplot(mtcars,+aes(wt*1000,+mpg))+%2B
++geom_point(size+=+4,+aes(colour+=+factor(cyl)))+%2B
++xlab("Weight+(pounds)")+%2B+ylab("Miles+per+gallon+(MPG)")+%2B+labs(color='Number\nof+cylinders')+%2B
++scale_x_continuous(limits+=+c(1000,+6000),+
+++++++++++++++++++++breaks+=+c(seq(1000,6000,1000)),+
+++++++++++++++++++++labels+=+c("1,000",+"2,000",+"3,000",+"4,000",+"5,000",+"6,000"))+%2B+
++scale_color_viridis(discrete+=+TRUE)+%2B
++theme_classic()|438909|唯一的区别在于倒数第二行：scale_color_viridis(discrete+=+TRUE)。|438910|这是使用viridis生成的图|438911|438912|438913|438914|希望有人发现这是有用的，因为这是我在回答这个问题后最终使用的解决方案。|438915|entityMap|0|LINK|mutability|MUTABLE|url|https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html|1|IMAGE|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/ec29283f74a3f5e6211092056ace2703.jpeg|imageAlt|2|https://ask.qcloudimg.com/http-save/yehe-900000/ee497a6b623e9dd0ef69b609922f2ed0.jpeg^0|N|7|Y|4|0|0|F|7|13|1M|2W|7|0|0|0|0|0|0|1|1|0|0|5|7|0|0|D|10|0|4|7|0|0|0|1|2|0|0|0^^$0|@$1|2|3|4|5|6|7|1P|8|@$9|1Q|A|1R|B|C]]|D|@$9|1S|A|1T|1|1U]]|E|$]]|$1|F|3|G|5|6|7|1V|8|@$9|1W|A|1X|B|C]|$9|1Y|A|1Z|B|C]|$9|20|A|21|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|22|8|@]|D|@]|E|$]]|$1|J|3|K|5|L|7|23|8|@]|D|@]|E|$M|N]]|$1|O|3|P|5|6|7|24|8|@]|D|@]|E|$]]|$1|Q|3|R|5|6|7|25|8|@]|D|@]|E|$]]|$1|S|3|T|5|U|7|26|8|@]|D|@$9|27|A|28|1|29]]|E|$]]|$1|V|3|R|5|6|7|2A|8|@]|D|@]|E|$]]|$1|W|3|X|5|6|7|2B|8|@$9|2C|A|2D|B|C]]|D|@]|E|$]]|$1|Y|3|Z|5|L|7|2E|8|@]|D|@]|E|$M|N]]|$1|10|3|11|5|6|7|2F|8|@$9|2G|A|2H|B|C]]|D|@]|E|$]]|$1|12|3|13|5|6|7|2I|8|@$9|2J|A|2K|B|C]]|D|@]|E|$]]|$1|14|3|R|5|6|7|2L|8|@]|D|@]|E|$]]|$1|15|3|T|5|U|7|2M|8|@]|D|@$9|2N|A|2O|1|2P]]|E|$]]|$1|16|3|R|5|6|7|2Q|8|@]|D|@]|E|$]]|$1|17|3|18|5|6|7|2R|8|@]|D|@]|E|$]]|$1|19|3|-4|5|6|7|2S|8|@]|D|@]|E|$]]]|1A|$1B|$5|1C|1D|1E|E|$1F|1G]]|1H|$5|1I|1D|1J|E|$1K|1L|1M|-4]]|1N|$5|1I|1D|1J|E|$1K|1O|1M|-4]]]]

An alternative approach (not necessarily better than the previous answers!) is to use the <code>viridis</code> package. As explained <a href="https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html" rel="nofollow noreferrer">here</a>, it allows for a variety of color gradients that are based on more than two colors.
The package is pretty easy to use - you just need to replace the <code>ggplot2</code> scale fill function (e.g., <code>scale_fill_gradient(low = &quot;skyblue&quot;, high = &quot;dodgerblue4&quot;)</code>) with the equivalent <code>viridis</code> function.
So, change the code for this plot:
<pre><code>ggplot(mtcars, aes(wt*1000, mpg)) +
 geom_point(size = 4, aes(colour = hp)) +
 xlab(&quot;Weight (pounds)&quot;) + ylab(&quot;Miles per gallon (MPG)&quot;) + labs(color='Horse power') +
 scale_x_continuous(limits = c(1000, 6000), 
 breaks = c(seq(1000,6000,1000)), 
 labels = c(&quot;1,000&quot;, &quot;2,000&quot;, &quot;3,000&quot;, &quot;4,000&quot;, &quot;5,000&quot;, &quot;6,000&quot;)) + 
 scale_fill_gradient(low = &quot;skyblue&quot;, high = &quot;dodgerblue4&quot;) +
 theme_classic()
</code></pre>
Which produces:
<a href="https://i.stack.imgur.com/HnREA.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/HnREA.jpg" alt="enter image description here" /></a>
To this, which uses <code>viridis</code>:
<pre><code>ggplot(mtcars, aes(wt*1000, mpg)) +
 geom_point(size = 4, aes(colour = factor(cyl))) +
 xlab(&quot;Weight (pounds)&quot;) + ylab(&quot;Miles per gallon (MPG)&quot;) + labs(color='Number\nof cylinders') +
 scale_x_continuous(limits = c(1000, 6000), 
 breaks = c(seq(1000,6000,1000)), 
 labels = c(&quot;1,000&quot;, &quot;2,000&quot;, &quot;3,000&quot;, &quot;4,000&quot;, &quot;5,000&quot;, &quot;6,000&quot;)) + 
 scale_color_viridis(discrete = TRUE) +
 theme_classic()
</code></pre>
The only difference is in the second to last line: <code>scale_color_viridis(discrete = TRUE)</code>.
This is the plot that is produced using <code>viridis</code>:
<a href="https://i.stack.imgur.com/md2Lv.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/md2Lv.jpg" alt="enter image description here" /></a>
Hoping someone finds this useful, as its the solution I ended up using after coming to this question.

I often work with <code>ggplot2</code> that makes gradients nice (<a href="http://www.r-bloggers.com/ggtutorial-day-5-gradient-colors-and-brewer-palettes/" rel="noreferrer">click here for an example</a>). I have a need to work in base and I think <code>scales</code> can be used there to create color gradients as well but I'm severely off the mark on how. The basic goal is generate a palette of n colors that ranges from x color to y color. The solution needs to work in base though. This was a starting point but there's no place to input an n. 

<pre><code> scale_colour_gradientn(colours=c("red", "blue"))
</code></pre>

I am well aware of:

<pre><code>brewer.pal(8, "Spectral") 
</code></pre>

from <code>RColorBrewer</code>. I'm looking more for the approach similar to how <code>ggplot2</code> handles gradients that says I have these two colors and I want 15 colors along the way. How can I do that?

Gradient of n colors ranging from color 1 and color 2

我经常使用让渐变变得更好的ggplot2 ()。我需要在base中工作，我认为scales也可以在那里创建颜色渐变，但我严重偏离了如何创建颜色渐变的标记。基本目标是生成从x色到y色的n种颜色的调色板。不过，解决方案需要在base中工作。这是一个起点，但没有地方输入n。 scale_colour_gradientn(colours=c("red", "blue"))我很清楚：brewer.pal(8

问从颜色1到颜色2的n种颜色的渐变
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