library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) DE_03054 <- sunrise.set(51.819757712306,14.346256256103515, "2024/01/01", timezone="MET", num.days=370) sunrise <- DE_03054$sunrise sunset <- DE_03054$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") DE_03054["sr"] <- as.POSIXct(sunrise, format = "%H:%M") DE_03054["ss"] <- as.POSIXct(sunset, format = "%H:%M") DE_03054["timestamp"] <- align.time(DE_03054$sunrise, 60*10) DE_03054 <- DE_03054[c("timestamp", "sr", "ss")] locsrss <- ggplot(DE_03054, aes(x=DE_03054$timestamp)) + geom_line(aes(y=DE_03054$sr)) + geom_line(aes(y=DE_03054$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DE_03054 2024", x = "Datum", y = "Zeit") pdf("DE_03054_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="DE_03054_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() DE_03054["Sonnenaufgang"] <- strftime(DE_03054$sr, format="%H:%M") DE_03054["Sonnenuntergang"] <- strftime(DE_03054$ss, format="%H:%M") write.table(DE_03054, file="DE_03054_SaSu.csv", dec=',', sep=';', row.names=FALSE)