library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Arzberg <- sunrise.set(50.0577948,12.1893693, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Arzberg$sunrise
sunset <- Arzberg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Arzberg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Arzberg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Arzberg["timestamp"] <- align.time(Arzberg$sunrise, 60*10)
Arzberg <- Arzberg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Arzberg, aes(x=Arzberg$timestamp)) + geom_line(aes(y=Arzberg$sr)) + geom_line(aes(y=Arzberg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Arzberg 2024", x = "Datum", y = "Zeit")
pdf("Arzberg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Arzberg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Arzberg["Sonnenaufgang"] <- strftime(Arzberg$sr, format="%H:%M")
Arzberg["Sonnenuntergang"] <- strftime(Arzberg$ss, format="%H:%M")
write.table(Arzberg, file="Arzberg_SaSu.csv", dec=',', sep=';', row.names=FALSE)