library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) Cabarete <- sunrise.set(19.7511111,-70.4083333, "2022/01/01", timezone="MET", num.days=370) sunrise <- Cabarete$sunrise sunset <- Cabarete$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") Cabarete["sr"] <- as.POSIXct(sunrise, format = "%H:%M") Cabarete["ss"] <- as.POSIXct(sunset, format = "%H:%M") Cabarete["timestamp"] <- align.time(Cabarete$sunrise, 60*10) Cabarete <- Cabarete[c("timestamp", "sr", "ss")] locsrss <- ggplot(Cabarete, aes(x=Cabarete$timestamp)) + geom_line(aes(y=Cabarete$sr)) + geom_line(aes(y=Cabarete$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cabarete 2022", x = "Datum", y = "Zeit") pdf("Cabarete_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="Cabarete_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() Cabarete["Sonnenaufgang"] <- strftime(Cabarete$sr, format="%H:%M") Cabarete["Sonnenuntergang"] <- strftime(Cabarete$ss, format="%H:%M") write.table(Cabarete, file="Cabarete_SaSu.csv", dec=',', sep=';', row.names=FALSE)