library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Aguilas <- sunrise.set(37.47087872377926,-1.6512673685722348, "2021/01/01", timezone="MET", num.days=370) sunrise <- Aguilas$sunrise sunset <- Aguilas$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Aguilas["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Aguilas["ss"] <- as.POSIXct(sunset, format = "%H:%M") Aguilas["timestamp"] <- align.time(Aguilas$sunrise, 60*10) Aguilas <- Aguilas[c("timestamp", "sr", "ss")] locsrss <- ggplot(Aguilas, aes(x=Aguilas$timestamp)) + geom_line(aes(y=Aguilas$sr)) + geom_line(aes(y=Aguilas$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Aguilas 2021", x = "Datum", y = "Zeit") pdf("Aguilas_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Aguilas_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Aguilas["Sonnenaufgang"] <- strftime(Aguilas$sr, format="%H:%M") Aguilas["Sonnenuntergang"] <- strftime(Aguilas$ss, format="%H:%M") write.table(Aguilas, file="Aguilas_SaSu.csv", dec=',', sep=';', row.names=FALSE)