如何在geom_text中同时显示科学数字和非科学数字？
如何在geom_text中同时显示科学数字和非科学数字？
提问于 2021-06-12 17:43:06
我想在非科学记数法中显示R，而在科学记数法中显示MBE。我正在使用下面的代码
library(tidyverse)
library(hydroGOF)
summ <- df %>%
group_by(Date) %>%
summarise(R = cor(x, y, use="pairwise.complete.obs"),
MBE = me(obs=x, sim=y, na.rm=TRUE)) %>%
mutate(across(MBE, ~round(., 5))) %>%
mutate(across(R, ~round(., 2)))
p <- ggplot(data=df, aes(x = x, y = y)) +
geom_point(fill="lightgray", color = "black",alpha = 1/3) +
facet_wrap(Date ~ ., scales="free") +
geom_smooth(method=lm, fill="lightgray", formula = y ~ x) +
theme_bw() +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())
# Here we create our annotations data frame.
df.annotations <- data.frame(
Date = rep(summ$Date, ncol(summ)-1),#Number depends on the no. of model evaluation parameters
label = c(
paste0("~R == ", summ$R),
paste0("~MBE == ", summ$MBE)
)
)
vertical_adjustment = ifelse(grepl("R",df.annotations$label),1.5,3)
p +
geom_text(data=df.annotations,aes(x=-Inf,y=+Inf,label=label),
hjust = 0, vjust = vertical_adjustment, size= 4, parse = TRUE)
从图中可以看到，对于右侧面板，MBE使用科学记数法，而左侧面板使用非科学记数法。当R应该在非科学记数法中时，我如何在科学记数法中进行MBE？
数据
df = structure(list(Date = structure(c(18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590, 18590,
18590, 18590, 18590, 18590, 18614, 18614, 18614, 18614, 18614,
18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614,
18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614,
18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614,
18614, 18614, 18614, 18614, 18614, 18614, 18614, 18614), class = "Date"),
x = c(0.0673029521110164, 0.0854163780659409, 0.134210186321464,
0.0643945521023818, 0.0534072925548605, 0.120585968026977,
0.171766787541948, 0.0529322841140877, 0.0389151124667283,
0.065932816556064, 0.0716104225646635, 0.0480367073546261,
0.0537788251427076, 0.100325805042952, 0.162239359083627,
0.103732829973447, 0.0970357338162893, 0.10603901085665,
0.0519899928560691, 0.0881320707200356, 0.0367170059526139,
0.121845733235219, 0.122459218176886, 0.0425359089683653,
0.0666875634912124, 0.0464243831679725, 0.0664988270937391,
0.0777430803707978, 0.0573249856899528, 0.0888259984184133,
0.0520454150074231, 0.0633639832058288, 0.0756093060434679,
0.0907648362839996, 0.0409180444460348, 0.117772012019805,
0.160504051083046, 0.10242517144965, 0.104937932574452, 0.0527662976624684,
0.0566003076702597, 0.14336552685814, 0.0338041955729706,
0.0364078719337135, 0.0296346837015176, 0.0405151452292794,
0.0326617631513927, 0.0383537061987076, 0.0560937860237775,
0.0662505348148382, 0.130741306761004, 0.0382284958039881,
0.0377009798726168, 0.047621161734172, 0.0356923968905919,
0.0516794984004681, 0.0777089536097421, 0.0879614340700801,
0.0664604119732582, 0.0951825936041895, 0.0581670432364461,
0.0614073175261606, 0.0621596045142233, 0.125973936545876,
0.0518735765008042, 0.0582112269727801, 0.0541847270530605,
0.0970492801742658, 0.0855089208077924, 0.0900662233655072,
0.0553091996406284, 0.045398746284043, 0.0747212626723072,
0.0468059595214467, 0.0715252644180638, 0.0392926648647701,
0.0401031176420515, 0.0393664661556453, 0.0454529539530989,
0.0432804905060738, 0.0928468023207638, 0.0814411322724173,
0.0826901703538189, 0.0394121791543224, 0.0846930951222448,
0.0851496310212468, 0.0800223696662629, 0.0739057775607218,
0.0654718923457129, 0.0597189681733721, 0.0518238375517588,
0.0811966642411631, 0.0484268967172088, 0.0398812336217731,
0.0408737243973982, 0.0722437508279481, 0.0567807507661876,
0.108055811705416, 0.0455713198571915, 0.0911207949375208,
0.0562274957486631, 0.0453506947793071, 0.0643281114150967,
0.0451974642392855, 0.0583516194132318, 0.0603141601370974,
0.0474342976516535, 0.0665490689121699, 0.0656781730798187,
0.0809471751886296, 0.0580192064282883), y = c(0.06919, 0.06378,
0.1046, 0.0963, 0.08835, 0.14248, 0.13096, 0.09829, 0.04209,
0.05926, 0.06029, 0.06975, 0.07061, 0.09682, 0.14988, 0.13158,
0.04941, 0.06607, 0.08155, 0.09832, 0.05956, 0.14679, 0.08054,
0.04512, 0.0705, 0.05925, 0.08821, 0.09841, 0.08305, 0.07885,
0.05957, 0.05032, 0.06938, 0.04775, 0.0528, 0.11204, 0.12149,
0.065, 0.09006, 0.05126, 0.05475, 0.11013, 0.06336, 0.04926,
0.03237, 0.04511, 0.04268, 0.04304, 0.0537, 0.07389, 0.10452,
0.05579, 0.05091, 0.0618, 0.04891, 0.05373, 0.07665, 0.07958,
0.05465, 0.08265, 0.06703, 0.04129, 0.05235, 0.11724, 0.06877,
0.07079, 0.06365, 0.10306, 0.07579, 0.07818, 0.04264, 0.05456,
0.07916, 0.05683, 0.06361, 0.05798, 0.06058, 0.04364, 0.05638,
0.05134, 0.07837, 0.08028, 0.07875, 0.06031, 0.09279, 0.07135,
0.07104, 0.06089, 0.04861, 0.05516, 0.05096, 0.07485, 0.06711,
0.06142, 0.05964, 0.06668, 0.06389, 0.08934, 0.03986, 0.08812,
0.05291, 0.04459, 0.04609, 0.05507, 0.04233, 0.04497, 0.05065,
0.05746, 0.08027, 0.06171, 0.05248)), row.names = c(NA, 111L
), class = "data.frame")回答 1
Stack Overflow用户
回答已采纳
发布于 2021-06-12 18:48:28
使用包scales并保留parse = F。我还调整了注释的文本格式。
library(scales)
# Here we create our annotations data frame.
df.annotations <- data.frame(
Date = rep(summ$Date, ncol(summ)-1),#Number depends on the no. of model evaluation parameters
label = c(
paste0(" R = ", summ$R),
# paste0("~MBE == ", summ$MBE)
paste0(" MBE = ", scientific(summ$MBE, digits = 3)) # set format
)
)
vertical_adjustment = ifelse(grepl("R",df.annotations$label),1.5,3)
p +
geom_text(data=df.annotations,aes(x=-Inf,y=+Inf,label=label),
hjust = 0, vjust = vertical_adjustment, size= 4, parse = F)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/67947567
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