library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Dessau <- sunrise.set(51.84563355810624,12.242365769311505, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Dessau$sunrise
sunset <- Dessau$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Dessau["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Dessau["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Dessau["timestamp"] <- align.time(Dessau$sunrise, 60*10)
Dessau <- Dessau[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Dessau, aes(x=Dessau$timestamp)) + geom_line(aes(y=Dessau$sr)) + geom_line(aes(y=Dessau$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Dessau 2024", x = "Datum", y = "Zeit")
pdf("Dessau_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Dessau_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Dessau["Sonnenaufgang"] <- strftime(Dessau$sr, format="%H:%M")
Dessau["Sonnenuntergang"] <- strftime(Dessau$ss, format="%H:%M")
write.table(Dessau, file="Dessau_SaSu.csv", dec=',', sep=';', row.names=FALSE)