1
ggplot2によって作成されたいくつかの面取りされたプロットに傾向と重要度を追加しようとしています。テキストには下付き文字が含まれていますが、これは問題が発生したときです。R - 面取りされたプロットに上付きの文字列を追加
library(ggplot2)
dat <- structure(list(year = c(2012L, 2013L, 2014L, 2015L, 2016L, 2017L,
2018L, 2019L, 2020L, 2021L, 2022L, 2023L, 2024L, 2025L, 2026L,
2027L, 2028L, 2029L, 2030L, 2031L, 2032L, 2033L, 2034L, 2035L,
2036L, 2037L, 2038L, 2039L, 2040L, 2041L, 2042L, 2043L, 2044L,
2045L, 2046L, 2047L, 2048L, 2049L, 2050L, 2051L, 2052L, 2053L,
2054L, 2055L, 2056L, 2057L, 2058L, 2059L, 2060L, 2061L, 2062L,
2063L, 2064L, 2065L, 2066L, 2067L, 2068L, 2069L, 2070L, 2071L,
2072L, 2073L, 2074L, 2075L, 2076L, 2077L, 2078L, 2079L, 2080L,
2081L, 2082L, 2083L, 2084L, 2085L, 2086L, 2087L, 2088L, 2089L,
2090L, 2091L, 2092L, 2093L, 2094L, 2095L, 2096L, 2097L, 2098L,
2099L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 2018L, 2019L,
2020L, 2021L, 2022L, 2023L, 2024L, 2025L, 2026L, 2027L, 2028L,
2029L, 2030L, 2031L, 2032L, 2033L, 2034L, 2035L, 2036L, 2037L,
2038L, 2039L, 2040L, 2041L, 2042L, 2043L, 2044L, 2045L, 2046L,
2047L, 2048L, 2049L, 2050L, 2051L, 2052L, 2053L, 2054L, 2055L,
2056L, 2057L, 2058L, 2059L, 2060L, 2061L, 2062L, 2063L, 2064L,
2065L, 2066L, 2067L, 2068L, 2069L, 2070L, 2071L, 2072L, 2073L,
2074L, 2075L, 2076L, 2077L, 2078L, 2079L, 2080L, 2081L, 2082L,
2083L, 2084L, 2085L, 2086L, 2087L, 2088L, 2089L, 2090L, 2091L,
2092L, 2093L, 2094L, 2095L, 2096L, 2097L, 2098L, 2099L), scen = c("RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 4.5",
"RCP 4.5", "RCP 4.5", "RCP 4.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5", "RCP 8.5",
"RCP 8.5"), mean = c(331.679093983488, 336.675841932168, 356.757081318776,
340.794923663589, 361.141206264033, 322.781918204685, 385.433918818759,
380.702401030404, 328.154492680223, 375.056187891587, 347.508793315836,
329.683327634971, 366.301636247352, 305.269460861638, 318.325452041009,
340.040273546697, 325.61840639099, 332.701705036009, 305.419280480644,
355.881017126304, 341.705597163198, 364.689829628731, 336.100633972456,
310.993566815872, 318.7211477292, 383.093389414867, 362.683808979847,
353.366601045305, 337.455762950249, 327.204334366791, 353.944525594788,
365.569618044337, 316.609658092386, 365.492509562037, 338.823736230177,
326.990255170755, 337.12880224233, 364.018173018607, 355.559313186275,
345.835649384861, 293.344988355919, 350.2548370495, 326.503131882392,
347.887581770452, 339.261222911228, 356.961652791314, 345.493946556441,
356.664486187732, 313.817590707126, 320.579682130737, 353.26217280519,
364.193121331002, 314.969531819531, 318.071678726834, 337.395178039222,
360.837824180377, 374.228500679098, 340.846453091398, 327.251036512267,
330.593965621599, 330.419870983545, 320.366991284311, 344.864360664964,
352.257307469967, 365.111966274704, 331.293272934474, 322.518548693901,
340.297573036132, 340.917774500577, 329.804655233008, 327.124699614286,
300.365317850756, 342.861653935517, 311.358349249704, 328.453339172631,
346.038216932353, 346.766752960328, 319.190762615461, 325.559678273368,
332.168944750783, 320.473543271376, 344.039703666605, 340.735082598786,
330.317665822525, 320.239744179718, 360.765596287051, 319.215582620153,
329.397678349641, 367.425644582558, 351.405690877457, 327.764435329283,
320.911673923194, 379.596203115623, 327.124563391652, 355.993699861717,
364.836645848153, 343.546366089566, 316.597684965416, 319.633607826233,
351.626592751372, 325.431155017843, 319.106889321875, 357.303044581657,
349.645502396967, 330.835305913427, 329.695569944562, 328.533509632532,
348.577454519246, 320.803612550699, 349.175559755207, 362.507923544398,
332.971101638609, 315.012143351717, 361.135215088672, 333.861975572386,
333.63069170209, 322.770000848899, 323.219699185415, 337.606463038298,
324.301435827476, 307.596445335943, 354.275656643891, 358.378815636134,
322.323420431029, 355.007944626204, 323.734865475369, 328.398173983695,
334.123595755852, 347.740272990841, 342.600839556979, 332.078058558359,
329.722800202485, 348.016231218117, 283.936542624605, 317.954962943558,
343.853292305013, 316.415594685187, 313.506610683122, 310.837729503909,
317.261464179931, 339.092730322064, 356.218725969052, 324.340904129111,
329.477747235979, 327.91232498827, 309.729236320742, 342.626327404423,
316.836359836033, 318.479932398423, 292.983254747108, 318.412394099583,
309.685068576021, 315.329740942469, 323.122255089855, 319.140169330916,
326.390173349715, 330.555480409915, 326.790038618823, 312.856556940927,
331.198281594557, 310.935485522741, 298.144092924833, 332.815595864041,
313.316276265887, 287.756945811166, 322.338512454071, 325.515444297276,
300.451757754303, 300.274937678746, 293.091256119042, 288.493754529722,
307.740644001614, 310.202440599097, 291.851698474421, 297.353643193515,
281.511755611183)), .Names = c("year", "scen", "mean"), row.names = c(NA,
176L), class = "data.frame")
ggplot(dat, aes(x=year, y=mean)) + geom_line(color="blue") +
geom_smooth(method="loess", se=F, color="red") +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
ylab("Irrigation (mm)") + xlab("") +
facet_grid(scen ~ .)
このプロットは、今世紀の終わりまで一定の地域の灌漑需要の時系列を示しています
基本的に、これは私がプロットしていたデータセットです。このファセットは、中規模（RCP 4.5）と悲観的（RCP 8.5）の気候変動シナリオを表しています。
また、時系列の傾向を決定するために、統計的検定（マン - ケンドール）の結果に基づいて、私は追加したいテキストを含むデータフレーム を作成しました：
# Here I reproduce the Mann-Kendall test results. One for each climate scenario.
test.stats1 <- structure(list(sl = 0.0511982476153832, S = -542, B = -0.166370102781674,
varS = 76985.3333333333, sl.corrected = NA, varS.corrected = NA,
partial.S = NA, partial.sl = NA, partial.varS = NA, partial.sl.corrected = NA,
partial.varS.corrected = NA, tau = -0.141588296760711), .Names = c("sl",
"S", "B", "varS", "sl.corrected", "varS.corrected", "partial.S",
"partial.sl", "partial.varS", "partial.sl.corrected", "partial.varS.corrected",
"tau"), class = "rkt")
test.stats2 <- structure(list(sl = 2.79597145436128e-09, S = -1650, B = -0.494562069956172,
varS = 76985.3333333333, sl.corrected = NA, varS.corrected = NA,
partial.S = NA, partial.sl = NA, partial.varS = NA, partial.sl.corrected = NA,
partial.varS.corrected = NA, tau = -0.431034482758621), .Names = c("sl",
"S", "B", "varS", "sl.corrected", "varS.corrected", "partial.S",
"partial.sl", "partial.varS", "partial.sl.corrected", "partial.varS.corrected",
"tau"), class = "rkt")
# Here, I create a data frame containing the text I need to add to the plot
df.stats <- data.frame(year=2090,
label=c(paste0("Trend: ", round(test.stats1$B,2), " mm year^-1"," (p=", round(test.stats1$sl,digits=2),")"),
paste0("Trend: ", round(test.stats2$B,2), " mm year^-1"," (p=", format.pval(test.stats2$sl,digits=3),")")),
scen=c("RCP 4.5","RCP 8.5"),
value=c(375,375))
しかし、 、数字に文字列を含むように私の試みは、エラーが発生します。
エラーが発生しggplot(dat, aes(x=year, y=mean)) + geom_line(color="blue") +
geom_smooth(method="loess", se=F, color="red") +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) +
ylab("Irrigation (mm)") + xlab("") +
facet_grid(scen ~ .) +
geom_text(data=df.stats, aes(x=year, y=value, label=label),
colour="black", parse=TRUE)
：
Error in parse(text = as.character(lab)) : <text>:1:14: unexpected symbol
1: Trend: -0.17 mm
私はここで何が欠けていますか？