library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Budjadingen <- sunrise.set(53.5770019,8.3674888, "2022/01/01", timezone="MET", num.days=370)
sunrise <- Budjadingen$sunrise
sunset <- Budjadingen$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Budjadingen["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Budjadingen["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Budjadingen["timestamp"] <- align.time(Budjadingen$sunrise, 60*10)
Budjadingen <- Budjadingen[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Budjadingen, aes(x=Budjadingen$timestamp)) + geom_line(aes(y=Budjadingen$sr)) + geom_line(aes(y=Budjadingen$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Budjadingen 2022", x = "Datum", y = "Zeit")
pdf("Budjadingen_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Budjadingen_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Budjadingen["Sonnenaufgang"] <- strftime(Budjadingen$sr, format="%H:%M")
Budjadingen["Sonnenuntergang"] <- strftime(Budjadingen$ss, format="%H:%M")
write.table(Budjadingen, file="Budjadingen_SaSu.csv", dec=',', sep=';', row.names=FALSE)