重写一个geom_line对图例的调用，同时保留另一个

Question

我一直试图找到解决这一问题的办法，但没有成功，因为我不能百分之百地确定是什么导致了这一问题。因为这是最后一件小事情阻止我完成这个项目，任何想法都会非常感谢！

我的传说是这样的：

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正如您所看到的，linetype和colour是合并显示的，但是在行类型中似乎有一条额外的实线，这使得它们很难读懂。我认为这来自一个额外的geom_line调用来显示灰线(原始数据)。

这是我的代码减去主题和标签

ggplot(table_mean_a, mapping= aes(x = phase_bins, y = Mean)) +
  geom_point(aes(x = phase_bins, y = Mean, colour = cond_f))+
  geom_line(df_plotting_a, 
            mapping = aes(x=phase_bins, y = mean_change_to_base, group=interaction(ID, cond_f)),
            alpha = 0.3, size  =0.5, colour = "grey", inherit.aes = FALSE)+ 
  geom_hline(yintercept=0, colour="#666766", linetype = "dashed")+
  geom_errorbar(subset(table_mean_a, phase_bins!= "baseline"), 
                mapping=aes(ymin=Mean-SD, ymax=Mean+SD, colour = cond_f), 
                width=.4, size = 0.7)+
  geom_line(aes(group=as.numeric(cond_f),  colour = cond_f, linetype=cond_f), size = 1.2)+
  facet_wrap(sample~., labeller=labeller(sample = labels), ncol=2, scales = "free_x") +
  scale_colour_manual(values=apa)+
  labs(colour = "Condition:", linetype = "Condition:")+
     guides(colour = guide_legend(override.aes = list(shape = NA, alpha = 1), byrow = TRUE))+   
     scale_x_discrete(labels= c("base", "stim1", "stim2", "recovery", "break"), drop = T, expand = c(0,0.25))+
     scale_y_continuous(limits = c(-1,1), breaks = c(-1,-0.5,0,0.5,1), 
                     labels = scales::number_format(accuracy = 1))+
     scale_linetype_manual(values=c("solid", "81", "11", "5111"))

这是数据

table_mean_a <-
structure(list(cond_f = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L), .Label = c("artificial", "cry", "laugh", "babble"
), class = "factor"), phase_bins = structure(c(2L, 3L, 4L, 5L, 
6L, 2L, 3L, 4L, 5L, 6L), .Label = c("pre", "baseline", "stim_bin1", 
"stim_bin2", "recovery", "break"), class = "factor"), age_group = c("adult", 
"adult", "adult", "adult", "adult", "adult", "adult", "adult", 
"adult", "adult"), sample = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L), .Label = c("UKi", "UGi", "UKa"), class = "factor"), 
    Mean = c(0, -0.0616666666666667, -0.143333333333333, -0.0983333333333328, 
    -0.0231666666666662, 0, -0.0949999999999997, -0.1625, -0.113333333333333, 
    -0.155833333333333), SD = c(0, 0.154096119467973, 0.24172866718288, 
    0.423777912706934, 0.633257128379362, 0, 0.13934894565432, 
    0.248908435688157, 0.350921926972951, 0.677239732274149), 
    Min. = c(0, -0.366666666666667, -0.583333333333337, -0.716666666666667, 
    -0.98, 0, -0.466666666666665, -0.650000000000003, -0.783333333333337, 
    -1.96), Max. = c(0, 0.283333333333334, 0.383333333333336, 
    1.08333333333334, 1.72666666666667, 0, 0.199999999999996, 
    0.233333333333333, 0.5, 0.846666666666667), count = c(20L, 
    20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L)), row.names = c(NA, 
-10L), groups = structure(list(cond_f = structure(c(1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L), .Label = c("artificial", "cry", 
"laugh", "babble"), class = "factor"), phase_bins = structure(c(2L, 
3L, 4L, 5L, 6L, 2L, 3L, 4L, 5L, 6L), .Label = c("pre", "baseline", 
"stim_bin1", "stim_bin2", "recovery", "break"), class = "factor"), 
    age_group = c("adult", "adult", "adult", "adult", "adult", 
    "adult", "adult", "adult", "adult", "adult"), .rows = structure(list(
        1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))


df_plotting_a <- 
structure(list(ID = structure(c(69L, 69L, 69L, 69L, 69L), .Label = c("UG201", 
"UG208", "UG209", "UG211", "UG215", "UG217", "UG219", "UG220", 
"UG221", "UG222", "UG228", "UG243", "UG247", "UG254", "UG268", 
"UG271", "UG272", "UG273", "UG274", "UG275", "UG280", "UG283", 
"UG284", "UG286", "UG297", "UG299", "UG308", "UG310", "UG315", 
"UG316", "UG330", "UG331", "UG334", "UG335", "UK103", "UK104", 
"UK105", "UK106", "UK107", "UK108", "UK110", "UK111", "UK112", 
"UK113", "UK115", "UK116", "UK117", "UK119", "UK122", "UK123", 
"UK130", "UK132", "UK135", "UK136", "UK138", "UK139", "UK140", 
"UK142", "UK145", "UK147", "UK150", "UK153", "UK155", "UK156", 
"UK159", "UK160", "UK162", "UK164", "UKA102", "UKA103", "UKA104", 
"UKA105", "UKA106", "UKA107", "UKA108", "UKA109", "UKA110", "UKA111", 
"UKA112", "UKA113", "UKA114", "UKA115", "UKA116", "UKA117", "UKA119", 
"UKA120", "UKA121", "UKA122"), class = "factor"), sex = structure(c(2L, 
2L, 2L, 2L, 2L), .Label = c("f", "m"), class = "factor"), trial = structure(c(1L, 
1L, 1L, 1L, 1L), .Label = c("1", "2", "3", "4"), class = "factor"), 
    cond_f = structure(c(4L, 4L, 4L, 4L, 4L), .Label = c("artificial", 
    "cry", "laugh", "babble"), class = "factor"), age_group = c("adult", 
    "adult", "adult", "adult", "adult"), stimulus = structure(c(7L, 
    7L, 7L, 7L, 7L), .Label = c("a1", "a2", "a3", "a4", "b1", 
    "b2", "b3", "b4", "c1", "c2", "c3", "c4", "l1", "l2", "l3", 
    "l4"), class = "factor"), phase_bins = structure(2:6, .Label = c("pre", 
    "baseline", "stim_bin1", "stim_bin2", "recovery", "break"
    ), class = "factor"), mean_change_to_base = c(0, -0.149999999999997, 
    -0.399999999999996, -0.299999999999996, -0.0733333333333306
    ), max_change_to_base = c(0, -0.333333333333329, -0.533333333333331, 
    -0.43333333333333, -0.333333333333329), sample = structure(c(3L, 
    3L, 3L, 3L, 3L), .Label = c("UKi", "UGi", "UKa"), class = "factor")), row.names = c(NA, 
-5L), groups = structure(list(ID = structure(69L, .Label = c("UG201", 
"UG208", "UG209", "UG211", "UG215", "UG217", "UG219", "UG220", 
"UG221", "UG222", "UG228", "UG243", "UG247", "UG254", "UG268", 
"UG271", "UG272", "UG273", "UG274", "UG275", "UG280", "UG283", 
"UG284", "UG286", "UG297", "UG299", "UG308", "UG310", "UG315", 
"UG316", "UG330", "UG331", "UG334", "UG335", "UK103", "UK104", 
"UK105", "UK106", "UK107", "UK108", "UK110", "UK111", "UK112", 
"UK113", "UK115", "UK116", "UK117", "UK119", "UK122", "UK123", 
"UK130", "UK132", "UK135", "UK136", "UK138", "UK139", "UK140", 
"UK142", "UK145", "UK147", "UK150", "UK153", "UK155", "UK156", 
"UK159", "UK160", "UK162", "UK164", "UKA102", "UKA103", "UKA104", 
"UKA105", "UKA106", "UKA107", "UKA108", "UKA109", "UKA110", "UKA111", 
"UKA112", "UKA113", "UKA114", "UKA115", "UKA116", "UKA117", "UKA119", 
"UKA120", "UKA121", "UKA122"), class = "factor"), trial = structure(1L, .Label = c("1", 
"2", "3", "4"), class = "factor"), cond_f = structure(4L, .Label = c("artificial", 
"cry", "laugh", "babble"), class = "factor"), .rows = structure(list(
    1:5), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr", 
"list"))), row.names = c(NA, -1L), class = c("tbl_df", "tbl", 
"data.frame"), .drop = TRUE), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"))

Answer 1

geom_errorbar和geom_line的传说是重叠在一起的，因此您可以看到实线。您可以在show.legend = FALSE中使用geom_errorbar来隐藏它。

由于您在ggplot中使用的一些元素丢失了，这里我只包含geom_errorbar的代码。

geom_errorbar(subset(table_mean_a, phase_bins!= "baseline"), 
                mapping=aes(ymin=Mean-SD, ymax=Mean+SD, colour = cond_f), 
                width=.4, size = 0.7, show.legend = F)

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