library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Cloppenburg_ <- sunrise.set(52.844198,8.053015800000026, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Cloppenburg_$sunrise
sunset <- Cloppenburg_$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Cloppenburg_["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Cloppenburg_["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Cloppenburg_["timestamp"] <- align.time(Cloppenburg_$sunrise, 60*10)
Cloppenburg_ <- Cloppenburg_[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Cloppenburg_, aes(x=Cloppenburg_$timestamp)) + geom_line(aes(y=Cloppenburg_$sr)) + geom_line(aes(y=Cloppenburg_$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Cloppenburg_ 2024", x = "Datum", y = "Zeit")
pdf("Cloppenburg__SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Cloppenburg__SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Cloppenburg_["Sonnenaufgang"] <- strftime(Cloppenburg_$sr, format="%H:%M")
Cloppenburg_["Sonnenuntergang"] <- strftime(Cloppenburg_$ss, format="%H:%M")
write.table(Cloppenburg_, file="Cloppenburg__SaSu.csv", dec=',', sep=';', row.names=FALSE)