library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Epfendorf <- sunrise.set(48.27596519999999,8.650750799999968, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Epfendorf$sunrise
sunset <- Epfendorf$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Epfendorf["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Epfendorf["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Epfendorf["timestamp"] <- align.time(Epfendorf$sunrise, 60*10)
Epfendorf <- Epfendorf[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Epfendorf, aes(x=Epfendorf$timestamp)) + geom_line(aes(y=Epfendorf$sr)) + geom_line(aes(y=Epfendorf$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Epfendorf 2023", x = "Datum", y = "Zeit")
pdf("Epfendorf_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Epfendorf_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Epfendorf["Sonnenaufgang"] <- strftime(Epfendorf$sr, format="%H:%M")
Epfendorf["Sonnenuntergang"] <- strftime(Epfendorf$ss, format="%H:%M")
write.table(Epfendorf, file="Epfendorf_SaSu.csv", dec=',', sep=';', row.names=FALSE)