library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Diepoldsau <- sunrise.set(47.3852825,9.6572948, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Diepoldsau$sunrise
sunset <- Diepoldsau$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Diepoldsau["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Diepoldsau["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Diepoldsau["timestamp"] <- align.time(Diepoldsau$sunrise, 60*10)
Diepoldsau <- Diepoldsau[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Diepoldsau, aes(x=Diepoldsau$timestamp)) + geom_line(aes(y=Diepoldsau$sr)) + geom_line(aes(y=Diepoldsau$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Diepoldsau 2023", x = "Datum", y = "Zeit")
pdf("Diepoldsau_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Diepoldsau_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Diepoldsau["Sonnenaufgang"] <- strftime(Diepoldsau$sr, format="%H:%M")
Diepoldsau["Sonnenuntergang"] <- strftime(Diepoldsau$ss, format="%H:%M")
write.table(Diepoldsau, file="Diepoldsau_SaSu.csv", dec=',', sep=';', row.names=FALSE)