library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Carolei <- sunrise.set(39.2512388,16.218568799999957, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Carolei$sunrise
sunset <- Carolei$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Carolei["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Carolei["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Carolei["timestamp"] <- align.time(Carolei$sunrise, 60*10)
Carolei <- Carolei[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Carolei, aes(x=Carolei$timestamp)) + geom_line(aes(y=Carolei$sr)) + geom_line(aes(y=Carolei$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Carolei 2024", x = "Datum", y = "Zeit")
pdf("Carolei_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Carolei_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Carolei["Sonnenaufgang"] <- strftime(Carolei$sr, format="%H:%M")
Carolei["Sonnenuntergang"] <- strftime(Carolei$ss, format="%H:%M")
write.table(Carolei, file="Carolei_SaSu.csv", dec=',', sep=';', row.names=FALSE)