library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Barnstorf <- sunrise.set(52.7064102,8.497608200000058, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Barnstorf$sunrise
sunset <- Barnstorf$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Barnstorf["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Barnstorf["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Barnstorf["timestamp"] <- align.time(Barnstorf$sunrise, 60*10)
Barnstorf <- Barnstorf[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Barnstorf, aes(x=Barnstorf$timestamp)) + geom_line(aes(y=Barnstorf$sr)) + geom_line(aes(y=Barnstorf$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Barnstorf 2022", x = "Datum", y = "Zeit")
pdf("Barnstorf_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Barnstorf_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Barnstorf["Sonnenaufgang"] <- strftime(Barnstorf$sr, format="%H:%M")
Barnstorf["Sonnenuntergang"] <- strftime(Barnstorf$ss, format="%H:%M")
write.table(Barnstorf, file="Barnstorf_SaSu.csv", dec=',', sep=';', row.names=FALSE)