library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) AT,4753 <- sunrise.set(48.287912,13.5661657, "2024/01/01", timezone="MET", num.days=370) sunrise <- AT,4753$sunrise sunset <- AT,4753$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") AT,4753["sr"] <- as.POSIXct(sunrise, format = "%H:%M") AT,4753["ss"] <- as.POSIXct(sunset, format = "%H:%M") AT,4753["timestamp"] <- align.time(AT,4753$sunrise, 60*10) AT,4753 <- AT,4753[c("timestamp", "sr", "ss")] locsrss <- ggplot(AT,4753, aes(x=AT,4753$timestamp)) + geom_line(aes(y=AT,4753$sr)) + geom_line(aes(y=AT,4753$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - AT,4753 2024", x = "Datum", y = "Zeit") pdf("AT,4753_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="AT,4753_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() AT,4753["Sonnenaufgang"] <- strftime(AT,4753$sr, format="%H:%M") AT,4753["Sonnenuntergang"] <- strftime(AT,4753$ss, format="%H:%M") write.table(AT,4753, file="AT,4753_SaSu.csv", dec=',', sep=';', row.names=FALSE)