library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
AT_2540 <- sunrise.set(47.9654019,16.1642407, "2023/01/01", timezone="MET", num.days=370)
sunrise <- AT_2540$sunrise
sunset <- AT_2540$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
AT_2540["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
AT_2540["ss"] <- as.POSIXct(sunset, format = "%H:%M")
AT_2540["timestamp"] <- align.time(AT_2540$sunrise, 60*10)
AT_2540 <- AT_2540[c("timestamp", "sr", "ss")]
locsrss <- ggplot(AT_2540, aes(x=AT_2540$timestamp)) + geom_line(aes(y=AT_2540$sr)) + geom_line(aes(y=AT_2540$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - AT_2540 2023", x = "Datum", y = "Zeit")
pdf("AT_2540_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="AT_2540_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
AT_2540["Sonnenaufgang"] <- strftime(AT_2540$sr, format="%H:%M")
AT_2540["Sonnenuntergang"] <- strftime(AT_2540$ss, format="%H:%M")
write.table(AT_2540, file="AT_2540_SaSu.csv", dec=',', sep=';', row.names=FALSE)