library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eberstalzell <- sunrise.set(48.0439107,13.9815714, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Eberstalzell$sunrise
sunset <- Eberstalzell$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eberstalzell["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eberstalzell["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eberstalzell["timestamp"] <- align.time(Eberstalzell$sunrise, 60*10)
Eberstalzell <- Eberstalzell[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eberstalzell, aes(x=Eberstalzell$timestamp)) + geom_line(aes(y=Eberstalzell$sr)) + geom_line(aes(y=Eberstalzell$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eberstalzell 2023", x = "Datum", y = "Zeit")
pdf("Eberstalzell_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eberstalzell_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eberstalzell["Sonnenaufgang"] <- strftime(Eberstalzell$sr, format="%H:%M")
Eberstalzell["Sonnenuntergang"] <- strftime(Eberstalzell$ss, format="%H:%M")
write.table(Eberstalzell, file="Eberstalzell_SaSu.csv", dec=',', sep=';', row.names=FALSE)