library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) DE_24340 <- sunrise.set(54.487890279847285,9.842119216918945, "2023/01/01", timezone="MET", num.days=370) sunrise <- DE_24340$sunrise sunset <- DE_24340$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") DE_24340["sr"] <- as.POSIXct(sunrise, format = "%H:%M") DE_24340["ss"] <- as.POSIXct(sunset, format = "%H:%M") DE_24340["timestamp"] <- align.time(DE_24340$sunrise, 60*10) DE_24340 <- DE_24340[c("timestamp", "sr", "ss")] locsrss <- ggplot(DE_24340, aes(x=DE_24340$timestamp)) + geom_line(aes(y=DE_24340$sr)) + geom_line(aes(y=DE_24340$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DE_24340 2023", x = "Datum", y = "Zeit") pdf("DE_24340_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="DE_24340_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() DE_24340["Sonnenaufgang"] <- strftime(DE_24340$sr, format="%H:%M") DE_24340["Sonnenuntergang"] <- strftime(DE_24340$ss, format="%H:%M") write.table(DE_24340, file="DE_24340_SaSu.csv", dec=',', sep=';', row.names=FALSE)