library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Casablanca <- sunrise.set(33.5333333,-7.583333300000049, "2023/01/01", timezone="MET", num.days=370) sunrise <- Casablanca$sunrise sunset <- Casablanca$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Casablanca["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Casablanca["ss"] <- as.POSIXct(sunset, format = "%H:%M") Casablanca["timestamp"] <- align.time(Casablanca$sunrise, 60*10) Casablanca <- Casablanca[c("timestamp", "sr", "ss")] locsrss <- ggplot(Casablanca, aes(x=Casablanca$timestamp)) + geom_line(aes(y=Casablanca$sr)) + geom_line(aes(y=Casablanca$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Casablanca 2023", x = "Datum", y = "Zeit") pdf("Casablanca_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Casablanca_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Casablanca["Sonnenaufgang"] <- strftime(Casablanca$sr, format="%H:%M") Casablanca["Sonnenuntergang"] <- strftime(Casablanca$ss, format="%H:%M") write.table(Casablanca, file="Casablanca_SaSu.csv", dec=',', sep=';', row.names=FALSE)