问题描述
我很难理解为什么我的情节会表现出这种奇怪的行为。我在我的哑铃图中添加了一个文本，但是当我尝试时，我收到一个警告（“'x' 的比例已经存在。为'x' 添加另一个比例，这将替换现有的比例”）。此外，在“保留”块下复制了一个额外的“Contralateral_RLR”，该块不应该属于传输块。我尝试了很多方法来摆脱它，但我不知道为什么会发生这种行为
data10 <- structure(list(Trial_type = structure(c(2L,1L,2L,2L),.Label = c("1","2"),class = "factor"),Trial_type2 = c(2,1,2,2),GROUP = c("LRL","RRR","LRL","LLL","RLR","RLR"),conditon2 = c("Central_LRL","Central_RRR","Lateral_LRL","Lateral_RRR","Contralateral_LRL","Contralateral_RRR","Central_LLL","Central_RLR","Lateral_LLL","Lateral_RLR","Contralateral_LLL","Contralateral_RLR"),condition20 = c(1,3,3),Training = c("right","right","left","left"),Pathlength_102 = c(3.187250625,2.922721625,3.405212,2.775334063,2.776401875,3.149278375,2.847822,3.03391925,3.674062375,2.726527125,2.78150325,3.6662945),Pathlength_104 = c(2.8958505,2.540974188,3.413019688,2.639986,2.675723688,2.761517625,2.631161188,2.664713,2.889202063,2.6051525,2.568229875,2.911062813),MovementTime_102 = c(1586.5625,1977.5,2181.25,1664.6875,2658.125,2384.375,1931.875,1595,2140.9375,1652.8125,1962.1875,3074.375),MovementTime_104 = c(1445.625,1327.1875,2008.75,1312.1875,2302.8125,1658.75,1589.6875,1387.1875,1627.8125,1611.25,1519.0625,2316.5625),AveResultantVel_102 = c(2.40919925,2.069098625,2.010902313,1.943953438,1.174490563,1.548894813,1.958885813,2.343926125,1.904319375,2.122309625,1.7739885,1.391745563),AveResultantVel_104 = c(2.771204063,2.5431425,2.053414375,2.505344125,1.298380563,1.983456875,2.314399688,2.350340875,2.187628625,2.051979125,2.110770188,1.434088938
),normalizedJerk_102 = c(1270.168699,2099.703957,3259.268053,1152.257445,3810.890123,4601.918336,1792.371775,1288.768888,2699.08162,1650.968794,2018.457394,6159.567785),normalizedJerk_104 = c(853.7034116,924.8554548,2268.966702,675.7160839,2442.874632,1603.954653,1010.111276,794.1752256,1313.813984,1197.638788,1039.577947,3125.131019),EndpointError_102 = c(1.441449813,1.899916938,1.666946063,1.493975375,1.945765938,2.001344875,1.530830188,1.197009313,2.1758275,1.990092563,2.106561813,2.593554438
),EndpointError_104 = c(1.196976438,1.203483813,1.32090125,1.176485125,1.648146125,1.253227125,0.86855425,0.803545313,1.502868938,1.338789625,1.499023188,1.504206125),RV_diff = c(0.36,0.47,0.04,0.56,0.12,0.43,0.36,0.01,0.28,-0.07,0.34,0.04),EE_diff = c(-0.24,-0.7,-0.35,-0.32,-0.3,-0.75,-0.66,-0.39,-0.67,-0.65,-0.61,-1.09),PL_diff = c(-0.29,-0.38,-0.14,-0.1,-0.22,-0.37,-0.78,-0.12,-0.21,-0.76),NJ_diff = c(-416.47,-1174.85,-990.3,-476.54,-1368.02,-2997.96,-782.26,-494.59,-1385.27,-453.33,-978.88,-3034.44),MT_diff = c(-140.94,-650.31,-172.5,-352.5,-355.31,-725.63,-342.19,-207.81,-513.13,-41.56,-443.13,-757.81)),row.names = c(NA,-12L),spec = structure(list(
cols = list(Trial_type = structure(list(),class = c("collector_character","collector")),Trial_type2 = structure(list(),class = c("collector_double",GROUP = structure(list(),conditon2 = structure(list(),condition20 = structure(list(),Training = structure(list(),Pathlength_102 = structure(list(),Pathlength_104 = structure(list(),MovementTime_102 = structure(list(),MovementTime_104 = structure(list(),AveResultantVel_102 = structure(list(),AveResultantVel_104 = structure(list(),normalizedJerk_102 = structure(list(),normalizedJerk_104 = structure(list(),EndpointError_102 = structure(list(),EndpointError_104 = structure(list(),RV_diff = structure(list(),EE_diff = structure(list(),PL_diff = structure(list(),NJ_diff = structure(list(),MT_diff = structure(list(),"collector"))),default = structure(list(),class = c("collector_guess",skip = 1),class = "col_spec"),class = c("spec_tbl_df","tbl_df","tbl","data.frame"))
library(tidyverse)
library(ggplot2)
library(rlang)
library(utils)
library(data.table)
library(dumbbell)
data10$conditon2 <- forcats::fct_reorder(data10$conditon2,data10$conditon2,.desc = TRUE)
data10A<-data10 %>% select(conditon2,Trial_type,EndpointError_102,EndpointError_104) %>% mutate("key"="Change In Endpoint Error (cm)")
data10B<-data10A %>% mutate("diff"=EndpointError_104-EndpointError_102) %>% arrange(desc(diff))
data10A$conditon2<-factor(data10A$conditon2,data10B$conditon2)
dumbbell::dumbbell(data10A,id="conditon2",key="Trial_type",leg = "Test time",column1 = "EndpointError_102",column2="EndpointError_104",delt=1,lab1="Pretest",lab2="Posttest",p_col1 = "black",p_col2 = "grey40",textsize = 3,segsize = 1.5,pointsize = 2.5,title = "Change in Endpoint error (cm)") +
xlim(0.7,3.0) + facet_wrap( Trial_type ~.,scales="free",ncol=1) +
theme(axis.text.x = element_text(size = 11,face="bold"),axis.text.y = element_text(size = 10,face = "bold")) + theme(legend.position="right") + annotate('text',x = 2.8,y = "Contralateral_RLR",label="*",size =6)
解决方法
您可以使用 geom_text 而不是 annotate 来仅在一个方面获取标签。
答案不会消除有关添加另一个比例的警告。我想这与 dumbbell::dumbbell 有它自己的 x 轴比例这一事实有关，我们试图用 xlim 或 scale_x_continuous 覆盖它，因此我们收到警告。
library(ggplot2)
dumbbell::dumbbell(data10A,id="conditon2",key="Trial_type",leg = "Test time",column1 = "EndpointError_102",column2="EndpointError_104",delt=1,lab1="Pretest",lab2="Posttest",p_col1 = "black",p_col2 = "grey40",textsize = 3,segsize = 1.5,pointsize = 2.5,title = "Change in Endpoint error (cm)") +
facet_wrap( Trial_type ~.,scales="free",ncol=1) +
theme(axis.text.x = element_text(size = 11,face="bold"),axis.text.y = element_text(size = 10,face = "bold"),legend.position="right") +
geom_text(data = data.frame(x = 2.8,y = 'Contralateral_RLR',Trial_type = 2),aes(x,y),label = '*',size = 6) +
scale_x_continuous(limits = c(0.7,3.0))
