library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
Eferding <- sunrise.set(48.30878999999999,14.02022999999997, "2024/01/01", timezone="MET", num.days=370)
sunrise <- Eferding$sunrise
sunset <- Eferding$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
Eferding["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
Eferding["ss"] <- as.POSIXct(sunset, format = "%H:%M")
Eferding["timestamp"] <- align.time(Eferding$sunrise, 60*10)
Eferding <- Eferding[c("timestamp", "sr", "ss")]
locsrss <- ggplot(Eferding, aes(x=Eferding$timestamp)) + geom_line(aes(y=Eferding$sr)) + geom_line(aes(y=Eferding$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - Eferding 2024", x = "Datum", y = "Zeit")
pdf("Eferding_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="Eferding_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
Eferding["Sonnenaufgang"] <- strftime(Eferding$sr, format="%H:%M")
Eferding["Sonnenuntergang"] <- strftime(Eferding$ss, format="%H:%M")
write.table(Eferding, file="Eferding_SaSu.csv", dec=',', sep=';', row.names=FALSE)