geom_vline（ggplot）中没有线型并自定义图例
[英]No linetype in geom_vline (ggplot) and customize legend
问题描述
I have a weird problem with geom_vline . 
我对geom_vline有一个奇怪的问题。 It seems I cannot change the linetype . 看来我无法更改linetype 。 Here the data: 这里的数据：
dput(gf)
structure(list(variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
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3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), .Label = c("As", "Cd_totale", "Cr_totale"), class = "factor"),
Area = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
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1L, 1L, 1L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("candiano",
"Lido_Spina", "Porto_Corsini", "Punta_Marina", "Sito1", "Sito2"
), class = "factor"), Campione = structure(c(40L, 39L, 38L,
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118L, 119L, 117L), .Label = c("A_1", "A_2", "A_LS", "A_PC",
"A_PM", "B_1", "B1_1", "B1_2", "B1_LS", "B1_PC", "B1_PM",
"B_2", "B2_1", "B2_2", "B2_LS", "B2_PC", "B2_PM", "B_LS",
"B_PC", "B_PM", "C_1", "C_2", "C386", "C387", "C388", "C389",
"C390", "C391", "C392", "C393", "C394", "C395", "C396", "C397",
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"C438", "C439", "C440", "C441", "C442", "C443", "C444", "C445",
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"C478", "C479", "C480", "C481", "C482", "C483", "C484", "C485",
"C486", "C487", "C488", "C489", "C490", "C491", "C492", "C493",
"C494", "C495", "C496", "C497", "C498", "C499", "C500", "C501",
"C502", "C503", "C504", "C505", "C506", "C507", "C508", "C509",
"C510", "C511", "C512", "C513", "C514", "C515", "C516", "C517",
"C518", "C519", "C520", "C521", "C522", "C523", "C524", "D_1",
"D_2", "E_1", "E_2", "F_1", "F_2"), class = "factor"), zona = structure(c(1L,
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1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("campione", "controllo"
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0.11, 0.1, 0.08, 0.1, 0.1, 0.11, 0.1, 0.1, 0.15, 0.13, 0.15,
0.1, 0.16, 0.13, 0.12, 0.1, 0.1, 0.12, 0.1, 0.14, 0.14, 0.025,
0.12, 0.12, 0.11, 0.12, 0.13, 0.13, 0.11, 0.09, 0.1, 0.08,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.2, 0.13, 0.1, 0.1, 0.1, 0.11,
0.09, 0.15, 0.1, 0.1, 0.1, 0.11, 0.09, 0.12, 0.12, 0.12,
0.12, 0.16, 0.1, 0.1, 0.1, 0.1, 0.2, 0.15, 0.1, 0.14, 0.12,
0.15, 0.025, 0.16, 0.18, 0.16, 0.025, 0.15, 0.08, 0.09, 0.1,
0.15, 0.17, 0.11, 0.05, 0.05, 0.12, 0.15, 0.12, 0.025, 0.1,
0.11, 0.17, 0.16, 0.12, 0.05, 0.12, 0.12, 0.13, 0.17, 0.13,
0.14, 0.12, 0.12, 0.11, 0.12, 0.13, 0.15, 0.12, 0.12, 0.1,
0.1, 0.12, 0.1, 0.13, 0.13, 0.18, 0.1, 0.14, 0.12, 0.1, 0.1,
0.18, 0.2, 0.15, 0.1, 0.11, 0.13, 0.11, 0.24, 0.16, 0.13,
0.15, 0.15, 0.22, 0.1, 85.75, 63.25, 43.6, 84.5, 84, 95.4,
98, 35.6, 79.6, 71.6, 73.2, 84, 54, 89, 99, 94.75, 70.6,
92.25, 84.83, 78.5, 70.17, 92.5, 94.67, 93.75, 75.2, 64.75,
66, 75.6, 82.4, 80.2, 78.8, 81, 79, 75.6, 79.2, 85.9, 57,
93.9, 97.9, 96.25, 84, 53.9, 56.1, 108.5, 111.75, 104.5,
78.25, 82.75, 87.25, 86.05, 85, 96, 102.25, 100.5, 100, 77,
84.3, 83.9, 52, 90.67, 85.75, 76.67, 86.33, 93.67, 70.5,
86.6, 77.67, 86.33, 74, 73.67, 86.67, 87.5, 72, 89.67, 93,
95, 93.5, 96, 88, 91, 86, 104.5, 90, 86.5, 85, 100.25, 81.25,
93.2, 109.75, 105, 104, 87.8, 99.75, 92.67, 47, 88.2, 73,
95, 94, 98.7, 100.4, 91.5, 63, 94.2, 89.33, 90.33, 83.67,
75.6, 86.8, 99.7, 90, 88.7, 88.4, 99.8, 76.4, 57.8, 52.5,
93, 91, 108, 91.5, 105, 98, 69.5, 79.75, 68.6, 103, 81, 90,
101.2, 102.6, 96.6, 100.8, 81, 90, 65, 79, 102.67, 102, 107,
107.5, 93, 70.2, 70.2, 67, 90.33, 71.5, 61.17, 64.6, 84.8,
87.5, 96.67, 76, 101, 100.75, 97.8, 77.4, 83.4, 79, 79, 55,
59.33, 98, 95.25, 82, 87, 70, 91), LCB_pelite = c(17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17,
17, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2,
0.2, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50), LCB = c(25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,
25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100), LCL = c(32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32,
32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360,
360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 360)), .Names = c("variable",
"Area", "Campione", "zona", "variable_value", "LCB_pelite", "LCB",
"LCL"), row.names = c(NA, -504L), class = "data.frame")
and here the code: 这里的代码：
require("reshape2")
require("ggplot2")
require("plyr")
gf<-rename(gf, c("value"="variable_value"))
gf_melt<-melt(gf, id=c("variable", "Area", "Campione", "zona", "variable_value"), variable.name="limite")
gf_melt<-rename(gf_melt, c("value"="valore_limite"))
ggplot(gf_melt)+
stat_ecdf(aes(x=variable_value, color=zona))+
facet_wrap(~variable, scales="free_x")+
geom_vline(aes(xintercept=valore_limite, color=limite, linetype="dotted"))
This the result: 结果：
Why the linetype of geom_vline are not dotted? 为什么geom_vline的linetype不加点？
And a last question. 还有最后一个问题。 Can I separate the legend of geom_vline from that of stat_ecdf in order to have 2 legends: the first with campione and controllo and the second with LCB_pelite , LCB and LCL ? 我可以单独的传说geom_vline从的stat_ecdf为了有2个传说：先用皮庸和controllo，第二个具有LCB_pelite，LCB和LCL？
1 个解决方案
解决方案1
2 2015-02-27 13:08:57
The following should work and give the solution to your problem! 以下应该可以解决您的问题！ The trick is to put color and linetype in separate parentheses: 诀窍是将颜色和线型放在单独的括号中：
p1<-ggplot(gf_melt) + stat_ecdf(aes(x=variable_value, color=zona))
p1<-p1+facet_wrap(~variable, scales="free_x")
p1<-p1+geom_vline(aes(xintercept=valore_limite, color=limite), linetype="dotted")
p1
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