2017-06-09 72 views
3

这geom_abline使用不同的斜率是我的数据集的结构:跨越方面

> dput(data) 
structure(list(es = c(0.29603085763985, 0.421393627439682, 0.189653473156549, 
0.226685054608428, 0.291373762079697, 0.166533544378467, 0.250586529054368, 
0.146320008054403, 0.199565119644333, -0.0819047677231083, 0.15963948187092, 
-0.154628141843561, 0.201121044198443, 0.0867981239977565, 0.543870310978598, 
0.34547921143505, 0.37557241352574, -0.287318919407836, 0.207937483228907, 
0.190143660810163, 0.276182673435993, 0.128596803172119, 0.454753165843559, 
0.399237234440439, 0.32075358541748, 0.362664873575803, -0.0865925288159671, 
0.51290512543514, 0.186308318839249, 0.147936083867325, 0.243792477087184, 
0.625169403695832, 0.110317782120045, 0.217836235313289, 0.171468156841181, 
0.50548821117127, 0.164418265301427, -0.00246305543239786, 0.325552346507191, 
0.381240606108843, 0.19337350462531, 0.0408803528990759, 0.321815078821239, 
0.307642815014319, 0.29603085763985, 0.421393627439682, 0.189653473156549, 
0.226685054608428, 0.291373762079697, 0.166533544378467, 0.250586529054368, 
0.146320008054403, 0.199565119644333, -0.0819047677231083, 0.15963948187092, 
-0.154628141843561, 0.201121044198443, 0.0867981239977565, 
0.543870310978598, 
0.34547921143505, 0.37557241352574, -0.287318919407836, 0.207937483228907, 
0.190143660810163, 0.276182673435993, 0.128596803172119, 0.454753165843559, 
0.399237234440439, 0.32075358541748, 0.362664873575803, -0.0865925288159671, 
0.51290512543514, 0.186308318839249, 0.147936083867325, 0.243792477087184, 
0.625169403695832, 0.110317782120045, 0.217836235313289, 0.171468156841181, 
0.50548821117127, 0.164418265301427, -0.00246305543239786, 0.325552346507191, 
0.381240606108843, 0.19337350462531, 0.0408803528990759, 0.321815078821239, 
0.307642815014319, 0.29603085763985, 0.421393627439682, 0.189653473156549, 
0.226685054608428, 0.291373762079697, 0.166533544378467, 0.250586529054368, 
0.146320008054403, 0.199565119644333, -0.0819047677231083, 0.15963948187092, 
-0.154628141843561, 0.201121044198443, 0.0867981239977565, 0.543870310978598, 
0.34547921143505, 0.37557241352574, -0.287318919407836, 0.207937483228907, 
0.190143660810163, 0.276182673435993, 0.128596803172119, 0.454753165843559, 
0.399237234440439, 0.32075358541748, 0.362664873575803, 
-0.0865925288159671, 
0.51290512543514, 0.186308318839249, 0.147936083867325, 0.243792477087184, 
0.625169403695832, 0.110317782120045, 0.217836235313289, 0.171468156841181, 
0.50548821117127, 0.164418265301427, -0.00246305543239786, 0.325552346507191, 
0.381240606108843, 0.19337350462531, 0.0408803528990759, 0.321815078821239, 
0.307642815014319), MAT = c(4.9, 4.9, 15.5, 14.1, 14.1, 14.1, 
11.5, 11.5, 11.5, 17, 6.1, 2.7, 2.2, 2.2, 14.1, 14.1, 14.1, 9.5, 
9.5, 9.5, 9.5, 9.3, 8.3, 8.266666651, 8.266666651, 4.3, 4.3, 
22.3, 14.1, 14.1, 14.1, 8.5, 8.5, 8.5, 8.5, 21.5, 21.5, 3.8, 
3.8, 6, 6, 6, 6, 6, 4.9, 4.9, 15.5, 14.1, 14.1, 14.1, 11.5, 11.5, 
11.5, 17, 6.1, 2.7, 2.2, 2.2, 14.1, 14.1, 14.1, 9.5, 9.5, 9.5, 
9.5, 9.3, 8.3, 8.266666651, 8.266666651, 4.3, 4.3, 22.3, 14.1, 
14.1, 14.1, 8.5, 8.5, 8.5, 8.5, 21.5, 21.5, 3.8, 3.8, 6, 6, 6, 
6, 6, 4.9, 4.9, 15.5, 14.1, 14.1, 14.1, 11.5, 11.5, 11.5, 17, 
6.1, 2.7, 2.2, 2.2, 14.1, 14.1, 14.1, 9.5, 9.5, 9.5, 9.5, 9.3, 
8.3, 8.266666651, 8.266666651, 4.3, 4.3, 22.3, 14.1, 14.1, 14.1, 
8.5, 8.5, 8.5, 8.5, 21.5, 21.5, 3.8, 3.8, 6, 6, 6, 6, 6), CO2dif = c(162L, 
162L, 190L, 165L, 165L, 165L, 200L, 200L, 200L, 150L, 335L, 335L, 
335L, 335L, 348L, 348L, 348L, 200L, 200L, 200L, 200L, 220L, 350L, 
350L, 350L, 350L, 350L, 350L, 180L, 180L, 180L, 130L, 130L, 130L, 
130L, 320L, 320L, 360L, 360L, 345L, 345L, 350L, 348L, 348L, 162L, 
162L, 190L, 165L, 165L, 165L, 200L, 200L, 200L, 150L, 335L, 335L, 
335L, 335L, 348L, 348L, 348L, 200L, 200L, 200L, 200L, 220L, 350L, 
350L, 350L, 350L, 350L, 350L, 180L, 180L, 180L, 130L, 130L, 130L, 
130L, 320L, 320L, 360L, 360L, 345L, 345L, 350L, 348L, 348L, 162L, 
162L, 190L, 165L, 165L, 165L, 200L, 200L, 200L, 150L, 335L, 335L, 
335L, 335L, 348L, 348L, 348L, 200L, 200L, 200L, 200L, 220L, 350L, 
350L, 350L, 350L, 350L, 350L, 180L, 180L, 180L, 130L, 130L, 130L, 
130L, 320L, 320L, 360L, 360L, 345L, 345L, 350L, 348L, 348L)), row.names = c(NA, 
-132L), class = "data.frame", .Names = c("es", "MAT", "CO2dif" 
)) 

我想创建一个方位ggplot,其中每个方面包含在后台积分相同,但每个面都有一条线在各个方面之间进行不同的截取。换句话说,各个方面的斜率都是相同的,但截距是不同的。

首先,我复制数据number_of_facets次,在这种情况下,3次,因为每个方面绘制相同的点。每个数据集具有沿新变量precplot不同的值:500,1000或1500:

data1 <- data; data1$precplot <- 500 
data2 <- data; data2$precplot <- 1000 
data3 <- data; data3$precplot <- 1500 

加入了三个数据集

dataplot <- full_join(data1, data2) 
dataplot <- full_join(dataplot, data3) 

现在剧情:

ggplot(dataplot, aes(x = MAT, y = es, color = CO2dif)) + 
    geom_point(size = 3) + scale_color_gradient(low = "green", high = "red") + 
    geom_abline(aes(intercept = -0.1846 + 0.0002 * precplot), slope = 0.0211, color = "red", size = 3) + 
    facet_wrap(~precplot) 

注意,interceptgeom_abline取决于precplot的值,但是,结果图显示了三个截距相同的截线= 0面。

为什么ggplot不按照我的意图计算截距? enter image description here

回答

2

您只需将slope移动到美学命令中即可。 这里的解决方案:

ggplot(dataplot, aes(x = MAT, y = es, color = CO2dif)) + 
    geom_point(size = 3) + scale_color_gradient(low = "green", high = "red") + 
    geom_abline(aes(intercept = -0.1846 + 0.0002 * precplot, slope = 0.0211), color = "red", size = 3) + 
    facet_wrap(~precplot) 

enter image description here