library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Blavand <- sunrise.set(55.5629035,8.1802254, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Blavand$sunrise
sunset <- Blavand$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Blavand["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Blavand["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Blavand["timestamp"] <- align.time(Blavand$sunrise, 60*10)
Blavand <- Blavand[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Blavand, aes(x=Blavand$timestamp)) + geom_line(aes(y=Blavand$sr)) + geom_line(aes(y=Blavand$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Blavand 2023", x = "Datum", y = "Zeit")
pdf("Blavand_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Blavand_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Blavand["Sonnenaufgang"] <- strftime(Blavand$sr, format="%H:%M")
Blavand["Sonnenuntergang"] <- strftime(Blavand$ss, format="%H:%M")
write.table(Blavand, file="Blavand_SaSu.csv", dec=',', sep=';', row.names=FALSE)