R图：在图外操作轴上的小数位数和图例大小
[英]R plot: manipulating decimal digits on axis and legend size outside the plot
问题描述
亲爱的社区！ 使用R绘图使我的绘图完美漂亮时，我遇到了一些问题。 我对此主题进行了大量研究，但无法解决最后剩下的问题（此外，我对RStudio和一般编码还很陌生）。 我有这个情节plot_example是用下面的代码创建的：
df1 <- read.csv2("df1.csv", header=T, sep=";", dec=".")
el_x1 <- df1$element
el_y1 <- df1$ratio
df2 <- read.csv2("df2.csv", header=T, sep=";", dec=".")
el_x2 <- df2$element
el_y2 <- df2$ratio
df3 <- read.csv2("df3.csv", header=T, sep=";", dec=".")
el_x3 <- df3$element
el_y3 <- df3$ratio
df4 <- read.csv2("df4.csv", header=T, sep=";", dec=".")
el_x4 <- df4$element
el_y4 <- df4$ratio
df5 <- read.csv2("df5.csv", header=T, sep=";", dec=".")
el_x5 <- df5$element
el_y5 <- df5$ratio
df6 <- read.csv2("df6.csv", header=T, sep=";", dec=".")
el_x6 <- df6$element
el_y6 <- df6$ratio
df7 <- read.csv2("df7.csv", header=T, sep=";", dec=".")
el_x7 <- df7$element
el_y7 <- df7$ratio
df8 <- read.csv2("df8.csv", header=T, sep=";", dec=".")
el_x8 <- df8$element
el_y8 <- df8$ratio
df9 <- read.csv2("df9.csv", header=T, sep=";", dec=".")
el_x9 <- df9$element
el_y9 <- df9$ratio
df10 <- read.csv2("df10.csv", header=T, sep=";", dec=".")
el_x10 <- df10$element
el_y10 <- df10$ratio
df11 <- read.csv2("df11.csv", header=T, sep=";", dec=".")
el_x11 <- df11$element
el_y11 <- df11$ratio
par(fin = c (5,5), mar = c(5,5,6,1), xpd = "true")
plot (xlim = c(0.1,250), ylim = c(0.003,4), el_x1, el_y1, log = "xy", xlab = "element (ppm)", ylab = "ratio", pch = 0, cex = 0.7, col = "orange1", las = 1, cex.axis = 1, cex.lab = 1.8, yaxs = "i", xaxs = "i")
points (el_x2, el_y2, pch = 3, cex = 0.7, col = "olivedrab2", las = 1, yaxs = "i", xaxs = "i")
points (el_x3, el_y3, pch = 4, cex = 0.7, col = "darkseagreen1", las = 1, yaxs = "i", xaxs = "i")
points (el_x4, el_y4, pch = 2, cex = 0.7, col = "khaki1", las = 1, yaxs = "i", xaxs = "i")
points (el_x5, el_y5, pch = 1, cex = 0.7, col = "lavender", las = 1, yaxs = "i", xaxs = "i")
points (el_x6, el_y6, pch = 15, cex = 0.7, col = "seagreen", las = 1, yaxs = "i", xaxs = "i")
points (el_x7, el_y7, pch = 15, cex = 1, col = "indianred1", las = 1, yaxs = "i", xaxs = "i")
points (el_x8, el_y8, pch = 16, cex = 1, col = "royalblue1", las = 1, yaxs = "i", xaxs = "i")
points (el_x9, el_y9, pch = 15, cex = 1, col = "red2", las = 1, yaxs = "i", xaxs = "i")
points (el_x10, el_y10, pch = 16, cex = 1, col = "navy", las = 1, yaxs = "i", xaxs = "i")
points (el_x11, el_y11, pch = 16, cex = 1, col = "darkmagenta", las = 1, yaxs = "i", xaxs = "i")
legend ("topright", inset=c(-0.46,0), legend=c("df1verylongname", "df2verylongname", "df3verylongname", "df4verylongname", "df5verylongname", "df6verylongname", "df7verylongname","df8verylongname", "df9verylongname", "df10verylongname", "df11verylongname"), pch=c(0,3,4,2,1,15,15,15,16,16,16), col=c("orange1","olivedrab2","darkseagreen1","khaki1", "lavender", "seagreen", "indianred1", "red2", "royalblue2", "navy", "darkmagenta"))
现在，我想作一些修改。
- （最重要）我必须操纵两个轴上的小数位。 我想保留0.005，但是我想摆脱50.0（应该是：50）。 我还无法使用“ sprintf”正确地操作它。 那么，如何删除所有不需要的.0xxx数字？ 如果还有其他解决方案，而不是使用图片编辑程序来处理情节，那将是很好的...
- 我可以将图例的大小调整为剧情的高度吗？ 它应该从右侧框的底部到顶部（在这种情况下，从y值0.003到4）到达。
- 除了“ xpd = true”之外，还有另一种方法可以将图例放置在绘图旁边吗？ 因为我想摆脱一些似乎离群的数据点。 当然，我可以调整图的大小或删除异常值，但是如果框外的点未如一般/在添加xpd之前那样总体上显示出来，则会更容易。
- 是否有一种很好的方法可以在轴数字和轴标签之间获得更多的空间？ 要使绘图达到这样的大小非常困难，并且我尝试调整空间会破坏所有内容，我并不是真的想使轴的数字更小... :( :(
这是一些输入数据，我将df简化为必要的东西：
sample element ratio
1 0.6175 0.063568046
2 4.678133548 0.008924568
3 3.638120051 0.005707297
4 4.116887372 0.007867378
5 3.090387742 0.059814081
6 10.3098635 0.040600128
7 10.29649952 0.019962218
8 8.241753356 0.012910088
9 26.76850701 0.294731393
10 8.136495793 0.031161747
11 7.993317894 0.021593337
12 10.48361696 0.025802074
13 14.37169851 0.030482194
14 13.19394369 0.032786504
15 3.756483892 0.027182974
16 12.21848391 0.032594756
17 6.560291802 0.049019108
18 10.71912771 0.072430938
19 1.708155726 0.007771124
20 10.0684893 0.054408104
21 16.38043254 0.076730258
22 11.50283707 0.044073631
23 10.11554913 0.064254448
24 13.52364219 0.0707148
25 10.51594695 0.060657727
26 14.51045122 0.07431958
27 16.46248665 0.059498267
28 12.17582522 0.04927026
29 20.83513461 0.059772704
30 18.10278099 0.069570053
31 8.404223175 0.051083018
32 13.96869871 0.069607707
33 9.396932425 0.044899193
34 12.39775022 0.066800258
35 1.625963393 0.009627417
36 16.9934813 0.059799741
37 75.5 0.3775
38 73 0.350961538
39 45.3 0.191949153
40 92.5 0.409292035
41 39.8 0.176106195
42 48.2 0.194354839
43 48.9 0.188076923
44 52.6 0.219166667
45 44.4 0.1734375
46 53.9 0.245
47 168.4 0.559468439
48 165.8 0.587943262
49 87.9 0.412676056
50 99.5 0.328382838
51 105.9 0.318975904
52 172.7 0.579530201
53 190.4 0.602531646
54 206.6 0.586931818
55 101 0.321656051
56 101.8 0.329449838
57 117.7 0.346176471
58 97.9 0.337586207
59 90.5 0.285488959
60 182.1 0.550151057
61 109.9 0.399636364
62 8 0.053619303
63 4.9 0.039294306
64 4.7 0.035768645
65 6.3 0.041888298
66 8.3 0.035698925
67 6.7 0.043733681
68 25.2 0.193548387
69 24.7 0.168600683
70 59.1 0.226610429
71 30.6 0.234303216
72 45.1 0.223710317
73 93.2 0.315611243
74 83.1 0.309151786
75 88.8 0.311360449
76 34.8 0.169014085
77 36.6 0.183550652
78
79 4.47 0.071565802
80 1.62 0.012413793
81 2.08 0.021010101
82 1.27 0.012330097
83 1.34 0.019705882
84 2.54 0.030274136
85 3.96 0.057641921
86 32.9 0.115438596
87 19.4 0.067595819
88 27.6 0.088461538
89 14.5 0.050699301
90 31 0.096875
91 36.3 0.078232759
92 27.8 0.072395833
93 8.56 0.039447005
94 10.1 0.040239044
95 4.44 0.056060606
96 3.94 0.05317139
97 4.18 0.059123055
98 5.23 0.07568741
如果需要更多输入数据，请联系。 如果有人能在这种情况下帮助我，我会很高兴。 问候！
2 个解决方案
解决方案1
0 2017-04-27 07:51:52
这是ggplot2的解决方案。 它不能满足您的所有要求，因为您仅提供了1个元素的数据，而我还没有完全理解所有要求。 轴标签是荒谬的，但是您明白了。
library(ggplot2)
df <- read.table(stringsAsFactors = FALSE, header = TRUE, text = "sample element ratio
1 0.6175 0.063568046
2 4.678133548 0.008924568
3 3.638120051 0.005707297
4 4.116887372 0.007867378
5 3.090387742 0.059814081
6 10.3098635 0.040600128
7 10.29649952 0.019962218
8 8.241753356 0.012910088
9 26.76850701 0.294731393
10 8.136495793 0.031161747
11 7.993317894 0.021593337
12 10.48361696 0.025802074
13 14.37169851 0.030482194
14 13.19394369 0.032786504
15 3.756483892 0.027182974
16 12.21848391 0.032594756
17 6.560291802 0.049019108
18 10.71912771 0.072430938
19 1.708155726 0.007771124
20 10.0684893 0.054408104
21 16.38043254 0.076730258
22 11.50283707 0.044073631
23 10.11554913 0.064254448
24 13.52364219 0.0707148
25 10.51594695 0.060657727
26 14.51045122 0.07431958
27 16.46248665 0.059498267
28 12.17582522 0.04927026
29 20.83513461 0.059772704
30 18.10278099 0.069570053
31 8.404223175 0.051083018
32 13.96869871 0.069607707
33 9.396932425 0.044899193
34 12.39775022 0.066800258
35 1.625963393 0.009627417
36 16.9934813 0.059799741
37 75.5 0.3775
38 73 0.350961538
39 45.3 0.191949153
40 92.5 0.409292035
41 39.8 0.176106195
42 48.2 0.194354839
43 48.9 0.188076923
44 52.6 0.219166667
45 44.4 0.1734375
46 53.9 0.245
47 168.4 0.559468439
48 165.8 0.587943262
49 87.9 0.412676056
50 99.5 0.328382838
51 105.9 0.318975904
52 172.7 0.579530201
53 190.4 0.602531646
54 206.6 0.586931818
55 101 0.321656051
56 101.8 0.329449838
57 117.7 0.346176471
58 97.9 0.337586207
59 90.5 0.285488959
60 182.1 0.550151057
61 109.9 0.399636364
62 8 0.053619303
63 4.9 0.039294306
64 4.7 0.035768645
65 6.3 0.041888298
66 8.3 0.035698925
67 6.7 0.043733681
68 25.2 0.193548387
69 24.7 0.168600683
70 59.1 0.226610429
71 30.6 0.234303216
72 45.1 0.223710317
73 93.2 0.315611243
74 83.1 0.309151786
75 88.8 0.311360449
76 34.8 0.169014085
77 36.6 0.183550652
79 4.47 0.071565802
80 1.62 0.012413793
81 2.08 0.021010101
82 1.27 0.012330097
83 1.34 0.019705882
84 2.54 0.030274136
85 3.96 0.057641921
86 32.9 0.115438596
87 19.4 0.067595819
88 27.6 0.088461538
89 14.5 0.050699301
90 31 0.096875
91 36.3 0.078232759
92 27.8 0.072395833
93 8.56 0.039447005
94 10.1 0.040239044
95 4.44 0.056060606
96 3.94 0.05317139
97 4.18 0.059123055
98 5.23 0.07568741")
#
ggplot(df, aes(element, ratio, fill="Element 1")) +
geom_point(color="red2") +
#geom_point(color=factor(1), size=1)
coord_cartesian( xlim=c(0, 300), ylim=c(0.0003, 4)) +
scale_x_continuous(labels=c(0, "hundred", 200, ">=300"), breaks=c(0, 100, 200, 300)) +
labs(x = "X axis", y = "Y axis (ratio/ppm)", fill = "Elements") +
theme_minimal() +
theme(#legend.position = "right",
legend.position = c(0.05, 0.95),
legend.justification = c(0.05, 0.95),
axis.title.x = element_text(color="black", hjust = 0),
axis.title.y = element_text(color="black", hjust = 0))
解决方案2
0 2017-04-28 02:10:44
我无法真正解决项目2到4。但是，项目1的关键是使用signif创建标签，并使用axis创建自定义轴。
首先，一些样本数据跨越几个数量级：
set.seed(14)
x <- 10^(rnorm(30))
y <- 10^(rnorm(30))
接下来，选择要让轴刻度线位于的位置，并设置一个包含标签的向量。
tick_pos <- c(.03, .1, .3, 1, 3, 10, 30, 100, 300)
tick_lbl <- character(length(tick_pos))
然后从刻度位置计算适当的标签：
for (i in seq_along(tick_pos)) {
tick_lbl[i] <- signif(tick_pos[i], 1)
}
请注意，您不能将整个tick_pos向量传递给signif因为该函数会强制结果使用单一格式。
> signif(tick_pos, 1)
[1] 3e-02 1e-01 3e-01 1e+00 3e+00 1e+01 3e+01 1e+02 3e+02
最后，创建没有轴的图，添加自定义轴，然后添加框架：
plot(x, y, log = 'xy', axes = FALSE)
axis(1, labels = tick_lbl, at = tick_pos)
axis(2, labels = tick_lbl, at = tick_pos)
box()
在R中的图外绘制图例
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