library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
DK <- sunrise.set(56.892579,8.525657000000024, "2024/01/01", timezone="MET", num.days=370)
sunrise <- DK$sunrise
sunset <- DK$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
DK["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
DK["ss"] <- as.POSIXct(sunset, format = "%H:%M")
DK["timestamp"] <- align.time(DK$sunrise, 60*10)
DK <- DK[c("timestamp", "sr", "ss")]
locsrss <- ggplot(DK, aes(x=DK$timestamp)) + geom_line(aes(y=DK$sr)) + geom_line(aes(y=DK$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - DK 2024", x = "Datum", y = "Zeit")
pdf("DK_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="DK_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
DK["Sonnenaufgang"] <- strftime(DK$sr, format="%H:%M")
DK["Sonnenuntergang"] <- strftime(DK$ss, format="%H:%M")
write.table(DK, file="DK_SaSu.csv", dec=',', sep=';', row.names=FALSE)