library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Berlingerode <- sunrise.set(51.45785919999999,10.239790200000016, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Berlingerode$sunrise
sunset <- Berlingerode$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Berlingerode["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Berlingerode["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Berlingerode["timestamp"] <- align.time(Berlingerode$sunrise, 60*10)
Berlingerode <- Berlingerode[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Berlingerode, aes(x=Berlingerode$timestamp)) + geom_line(aes(y=Berlingerode$sr)) + geom_line(aes(y=Berlingerode$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Berlingerode 2023", x = "Datum", y = "Zeit")
pdf("Berlingerode_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Berlingerode_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Berlingerode["Sonnenaufgang"] <- strftime(Berlingerode$sr, format="%H:%M")
Berlingerode["Sonnenuntergang"] <- strftime(Berlingerode$ss, format="%H:%M")
write.table(Berlingerode, file="Berlingerode_SaSu.csv", dec=',', sep=';', row.names=FALSE)