library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Arnegg <- sunrise.set(47.4138069,9.257916799999975, "2023/01/01", timezone="MET", num.days=370)
sunrise <- Arnegg$sunrise
sunset <- Arnegg$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Arnegg["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Arnegg["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Arnegg["timestamp"] <- align.time(Arnegg$sunrise, 60*10)
Arnegg <- Arnegg[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Arnegg, aes(x=Arnegg$timestamp)) + geom_line(aes(y=Arnegg$sr)) + geom_line(aes(y=Arnegg$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Arnegg 2023", x = "Datum", y = "Zeit")
pdf("Arnegg_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Arnegg_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Arnegg["Sonnenaufgang"] <- strftime(Arnegg$sr, format="%H:%M")
Arnegg["Sonnenuntergang"] <- strftime(Arnegg$ss, format="%H:%M")
write.table(Arnegg, file="Arnegg_SaSu.csv", dec=',', sep=';', row.names=FALSE)