library(lubridate) library(ggplot2) library(StreamMetabolism) library(xts) library(reshape) library(scales) 86825 <- sunrise.set(48.0100894,10.586332699999957, "2023/01/01", timezone="MET", num.days=370) sunrise <- 86825$sunrise sunset <- 86825$sunset sunrise <- strftime(sunrise, format="%R", tz="MET") sunset <- strftime(sunset, format="%R", tz="MET") 86825["sr"] <- as.POSIXct(sunrise, format = "%H:%M") 86825["ss"] <- as.POSIXct(sunset, format = "%H:%M") 86825["timestamp"] <- align.time(86825$sunrise, 60*10) 86825 <- 86825[c("timestamp", "sr", "ss")] locsrss <- ggplot(86825, aes(x=86825$timestamp)) + geom_line(aes(y=86825$sr)) + geom_line(aes(y=86825$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 86825 2023", x = "Datum", y = "Zeit") pdf("86825_SA_SU.pdf", paper="a4r", width=11) locsrss dev.off() png(filename="86825_SA_SU.png", width = 1400, height = 800, units = "px") locsrss dev.off() 86825["Sonnenaufgang"] <- strftime(86825$sr, format="%H:%M") 86825["Sonnenuntergang"] <- strftime(86825$ss, format="%H:%M") write.table(86825, file="86825_SaSu.csv", dec=',', sep=';', row.names=FALSE)