library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 83125 <- sunrise.set(47.93122886764902,12.385626319604512, "2024/01/01", timezone="MET", num.days=370) sunrise <- 83125$sunrise sunset <- 83125$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 83125["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 83125["ss"] <- as.POSIXct(sunset, format = "%H:%M") 83125["timestamp"] <- align.time(83125$sunrise, 60*10) 83125 <- 83125[c("timestamp", "sr", "ss")] locsrss <- ggplot(83125, aes(x=83125$timestamp)) + geom_line(aes(y=83125$sr)) + geom_line(aes(y=83125$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 83125 2024", x = "Datum", y = "Zeit") pdf("83125_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="83125_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 83125["Sonnenaufgang"] <- strftime(83125$sr, format="%H:%M") 83125["Sonnenuntergang"] <- strftime(83125$ss, format="%H:%M") write.table(83125, file="83125_SaSu.csv", dec=',', sep=';', row.names=FALSE)